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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Appendix A
Contributed Manuscripts

A1
THE CASE FOR PATHOGEN-SPECIFIC THERAPY1

Arturo Casadevall2

Albert Einstein College of Medicine


At the beginning of the twenty-first century, the treatment of microbial diseases is increasingly complicated by drug resistance, the emergence of new pathogenic microbes, the relatively inefficacy of antimicrobial therapy in immunocompromised hosts, and the reemergence of older diseases, often with drug-resistant microbes. Some of these problems can be traced to the switch between pathogen-specific antibacterial therapy and the nonspecific antibacterial therapy that followed the transition from serum therapy to modern antimicrobial chemotherapy. The widespread availability of cheap, effective, nontoxic wide-spectrum antibacterial therapy for almost 75 years fostered a culture of therapeutic empiricism that neglected diagnostic technologies. Despite unquestioned lifesaving efficacy for individuals with microbial diseases, the use of broad-spectrum antimicrobials was associated with fungal superinfections and antibiotic-associated

1

Reprinted from Casadevall, A. 2009. The case for pathogen-specific therapy. Expert Opinion in Pharmacotherapy 10(11):1699-1703 with permission from Taylor & Francis Ltd.

2

Affiliation: Arturo Casadevall, Albert Einstein College of Medicine, Division of Infectious Diseases of the Department of Medicine, Department of Microbiology and Immunology, 1300 Morris Park Avenue, Bronx, NY 10461, USATel: +1 781 430 3665; Fax: +1 718 430 8741

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

colitis, helped to catalyze the emergence of resistance, and is now tentatively associated in the pathogenesis of certain chronic diseases, including atopy, asthma and – perhaps – certain forms of cancer. This article briefly reviews these trends and suggests that the current strategy of nonspecific therapy is fundamentally unsound because it damages the microflora and – consequently – the human symbiont. The essay argues for the development of immunotherapy and pathogen-specific therapies, especially with regard to bacterial and fungal diseases, and suggests possible routes to that future.

1.
The Problematic Status Quo

Current antimicrobial therapy is largely pathogen-specific for viral diseases and nonpathogen-specific for bacterial, fungal, and parasitic diseases (Casadevall, 1996). Although some of the latter diseases are sometimes treated with pathogen-specific drugs, such as the use of isoniazid for tuberculosis, the overwhelming majority of compounds targeting bacteria, fungi, and parasitic diseases have activity against multiple microbes. Furthermore, these compounds target both pathogenic and nonpathogenic microbes. This current antimicrobial paradigm is currently in use at a time of significant upheaval in the therapy of microbial diseases, which is the only field of medicine in which one can argue that therapeutic options have declined over time. For example, in the 1950s Jawetz noted that the then currently available antimicrobial drugs were satisfactory for the treatment of bacterial diseases (Jawetz, 1956). However, in recent years the field of infectious diseases has seen dramatic increases in antimicrobial resistance, an increasing prevalence of bacterial and fungal superinfections in treated individuals, a relatively low therapeutic efficacy of antimicrobial therapy in individuals with impaired immunity, the emergence of new infectious diseases, and the reemergence of older microbial diseases, often with highly resistant microbes such as XDR-Tb. Given this status quo, it behooves us to ask the questions: How did we get here? What are the consequences of the choices made then and now? Can we do better and how do we get there?

2.
How Did We Get Here?

Effective antimicrobial therapy can be dated to the introduction of serum therapy in the 1890s, which, for the first time, provided physicians with the ability to intervene and cause a favorable outcome for an infectious disease. Serum therapy was developed against numerous bacterial and viral diseases, including pneumococcal pneumonia, meningococcal meningitis, erysipelas, anthrax, and measles (for reviews, see refs Casadevall and Scharff, 1994; Casadevall and Scharff, 1995; Buchwald and Pirofski, 2003). The heyday of serum therapy was the 1930s, but the modality was rapidly abandoned because serum could not compete with small-molecule antimicrobial therapy, such as sulfonamides and

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

penicillin, with regard to price, stability, ease of use, and (low) toxicity. For some diseases such as meningococcal meningitis, small-molecule antimicrobial therapy was clearly more effective than serum therapy; however, for pneumococcal pneumonia the difference in efficacy was less clear. In addition to serum therapy, the few other therapies available (e.g., quinine for malaria, salvarsan for syphilis, optochin for pneumococcus, and phage therapy) were all pathogen specific. In a prior essay (Casadevall, 2006), I argued that the time of serum therapy and the subsequent era of therapy with small molecules constituted the two first ages of antimicrobial therapy. When viewed through the prism of microbial specificity, the greatest difference in the therapeutic approach between the first and second ages of antimicrobial therapy was a switch from pathogen-specific to nonspecific therapy with regard to antibacterial therapeutics. In this essay, I argue that this change was to have enormous implications, which are root causes for some of the problems we face today.

In evaluating the therapeutic paradigm for microbial diseases, it is worthwhile contrasting it with the therapy of cancer. Like therapy for infectious diseases, the treatment of tumors has relieved [sic] heavily on antibiotics made by microorganisms; adryamicin, actinomycin D, bleomycin etc. are all microbial products. Like antimicrobial antibiotics, these antimetabolite antibiotics are each nonspecific in the sense that they are cytotoxic to multiple tumors. However, unlike most antimicrobial antibiotics, these agents have tremendous toxicity for the host and, consequently, are never used empirically. Hence, oncology practice has placed great emphasis on diagnosis and in exploiting subtle pharmacological differences between these agents to enhance their therapeutic index.

In fairness to infectious diseases, it noteworthy that the temporal kinetics of microbial infections and tumorogenesis favored a more deliberate approach to diagnosis as tumors, which unlike microbes, seldom killed the host rapidly. Nevertheless, the analogy is relevant because it provides an inkling of how the practice of infectious diseases might have developed if early antimicrobials had more significant toxicity, as evidenced by the hesitant empiric use of amphotericin b and Ara-C for fungal and herpetic diseases, respectively, Consistent with this notion, the development of the relatively nontoxic antiherpetic drug acyclovir as a replacement for Ara-C was followed with significantly greater empiric use, especially in neonates and cases of encephalitis. Similarly, the introduction of low-toxicity azoles and echinochandins as replacements for the highly toxic amphotericin b has promoted the empirical use of antifungal therapy. Hence, the advantage of low toxicity has the perverse effect of promoting empirical and inappropriate use.

In comparing the ages of antimicrobial therapy, it is clear that the change in the specificity of therapeutic agents did not affect all types of antimicrobial therapy equally. Serum therapy for viral diseases was specific and current antiviral drugs remain largely pathogen-specific, with the caveat that some drugs like acyclovir have activity against multiple herperviruses [sic]. For mycobacterial

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

diseases, there was no effective therapy in the preantibiotic era and most drugs that were subsequently developed (isoniazid, ethambutol, and others) were used primarily for the therapy of tuberculosis. For fungal diseases, there was no effective therapy prior to the late 1950s when amphotericin B was introduced; a compound active against most fungal pathogens and antifungal therapy has always relied on nonpathogen-specific agents. For bacterial diseases, the change from serum to small-molecule therapeutics was a revolution, as therapeutic specificity was abandoned in favor of agents with increasingly greater spectrum of antimicrobial activity. However, what made the switch from pathogen-specific to non-pathogen-specific therapy so significant with regard to antibacterial therapy is that the human host is a symbiont, with microflora consisting mostly of desired commensal bacteria. By contrast, there are no known desirable commensal viruses and the known fungal flora is limited to a few fungal species where Candida spp predominate. Unlike bacteria, a beneficial function has not been demonstrated for the host-associated fungal microflora. Hence, the use of nonspecific bacterial therapy carried an inherent potentially detrimental effect in damaging the associated bacterial microflora, and thus the human symbiont.

3.
The Consequences of Nonspecific Antimicrobial Therapy

The nonspecificity of antibacterial, and to a lesser extent antifungal, therapies was to have profound consequences on the practice and outcome of infectious diseases that reverberate to current times. The availability of nonspecific antibacterial therapies with broad spectrum and low toxicity allowed physicians to rapidly treat many infectious diseases without a need for a microbial diagnosis. For individuals with bacterial diseases, such therapy was often lifesaving. However, the ability to effectively treat many diseases safely without making a diagnosis deemphasized diagnostic clinical microbiology and fostered a culture of empiricism. For example, the diagnosis of pneumococcal pneumonia with the identification of the offending serotype took approximately 6 – 8 h in the 1930s and used the mouse peritoneal infection assay followed by typing with rabbit type-specific serum. This methodology was developed to rapidly ascertain the presence and serotype of pneumococcus in sputum because the efficacy of serum therapy depended on matching the bacterial serotype with the specificity of the antiserum. Despite the problems in unequivocally diagnosing pneumonia from sputum, this approach was successful for selecting therapeutic sera and supported the use of serum therapy. However, the introduction of penicillin and later antimicrobial drugs made the test much less relevant and it was abandoned as a diagnostic tool. Currently, a definitive diagnosis of pneumococcal pneumonia is possible only when accompanied by bacteremia, information that requires 48 h. For fungal diseases, a full embrace of empiric therapy was checked by the toxicity of amphotericin b, but by the late 1990s, the availability of relatively nontoxic azole and echinocandin-type drugs had ushered greater empiric use. By contrast,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

for conditions that required specific therapy, such as viral and mycobacterial diseases, the practice ethos supported continued emphasis on diagnostic identification of the causative microbe.

For bacterial and later fungal diseases, the availability of relatively nontoxic broad-spectrum therapy contributed to the emergence of resistance among both targeted and nontargeted microbes. Although specific therapy can also elicit resistance, as witnessed by the emergence of isoniazid-resistant Mycobacterium tuberculosis, only nonspecific therapy can elicit resistance among nontargeted microbes such as common inhabitants of the microflora. Furthermore, only non-specific therapy can damage the microflora to create alterations that foster the emergence of usually commensal microbes such as Candida and Enteroccocus spp, first as major pathogenic microbes and then as drug-resistant pathogenic microbes. Consequently, the discipline of infectious diseases may be the only specialty of medicine where previously effective therapeutic options have to be abandoned because of drug resistance creates [sic] obsolescence.

Another consequence of nonspecific antibacterial and antifungal therapy was damage to the human symbiont. There is rapidly accumulating evidence that the human microflora is established early in life through complex steps and that there are individual differences in microbial species composition, a fact that could reflect differences in the timing of acquisition or modulation by the host immune system. The microbial flora is essential for development of the immune system, helps digestion, provides numerous nutrients including vitamins, and protects the human host by niche-denial to more pathogenic microbes. There is conclusive evidence that damage to the microflora by nonspecific antibacterial therapy can translate into antibiotic-associated colitis and fungal diseases such as oral thrush and candidal vaginitis. However, there are ominous signs that nonspecific antimicrobial use might translate into certain chronic diseases such as atopy (Kusel et al., 2008), asthma (Kozyrskyj et al., 2007), and even some types of cancer (Velicer et al., 2004), possibly by altering the development of the immune system in childhood and/or affecting metabolites produced by the microflora. In this regard, it is noteworthy that there is a temporal association between widespread antimicrobial use and the increase in immunoreactive diseases such as allergies and asthma, although it is premature to conclude causality as there may be confounding variables (Wickens et al., 2008). Nevertheless, the available evidence does provide reason for concern.

In summary, the development of effective, nontoxic, nonspecific antibacterial and antifungal therapy has had great consequences, some positive and some negative. Positive consequences include a significantly enhanced capacity to treat bacterial and fungal diseases early and effectively, which has translated to reduced mortality. Furthermore, the ability to treat early, safely, and without knowledge of the causative microbe has created a permissive environment for the development of complex surgeries, aggressive chemotherapy for tumors, and organ transplantation, procedures that would have unacceptable mortality without

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

such drugs. However, the same approach has also created a culture of empiricism that promoted antibiotic use, which in turn selected for resistance in targeted and nontargeted microbes, promoted the phenomenon of superinfection and damaged the symbiont with consequences that are only now beginning to be understood. In this regard, empiricism was a practice largely dictated by clinical findings and historical probability that essentially rejected causality in favor of associations.

4.
Can We Do Better and How to Get There?

Of course we can do better. Even for the short historical time that effective antimicrobial therapy has been available it is clear that the effectiveness of therapy and diagnosis has fluctuated with time. In a previous essay (Casadevall, 2006), I argued that we are in the throes of a major paradigm shift that will usher in the third age of antimicrobial therapy. This age can be envisioned as an equilateral triangle with pathogen-specific therapy, greatly improved diagnostics, and immunotherapy at each apex. Nonspecific therapy will always have a role for the treatment of polymicrobial diseases and to insure proper coverage in individuals with fulminant disease but its use could be limited by the combination of rapid diagnostics and pathogen-specific drugs. Even for such polymicrobial diseases as abdominal sepsis originating from a ruptured viscus there is evidence that damage is caused by only a few microbial species and their identification would permit employment of pathogen-specific drugs. In this age, immunotherapy, whether with large molecules, such as antibodies or small-molecular-weight immuno-modulators, would have co-equal status with therapies designed to directly kill or inhibit the microbe. Although this author believes that third-age therapeutics will arrive in the twenty-first century, significant scientific, economic, and behavioral hurdles must be overcome for the realization of this vision.

On the scientific front, drug discovery would have to move from trying to identify common therapeutic pathways among phylogenetically distant bacteria to exploiting differences in physiology and virulence mechanisms and/or to augmenting host mechanisms that promote microbial clearance, which, interestingly, are nonspecific. This formidable task is made even more difficult by the economics of antimicrobial drug discovery. As for other diseases, the economics of drug development is a function of the prevalence of the disease, which dictates market size. However, in antimicrobial drug discovery this formula is further modified by the fact that the market size is directly proportional to the width of the drug antimicrobial spectrum. Given the cost of drug development, the economics are stacked against pathogen-specific drugs in favor of broad-spectrum drugs. One caveat in this analysis is that drug resistance can disproportionately shorten the useful life of broad-spectrum drugs and that the emergence of resistant microbes can in itself create new market opportunities. For example, the emergence and spread of methicillin-resistant Staphylococcus aureus (MRSA) creates a niche such that a new staphylococcal-specific drug active against methicillin- and

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

possibly vancomycin-resistant isolates would probably be developed clinically if available. The use of pathogen-specific drugs would necessitate advances in diagnostics to provide rapid and accurate information to support their use, and this would require new investments in research and laboratory assays. Finally, physicians would have to change their approach to patients with presumed infectious diseases, emphasizing the need for diagnosis to select appropriate therapy in an echo to the practices of physicians in the age of serum therapy.

Perhaps the hurdles are so high that pathogen-specific therapy is only in the far horizon. If that is the case, there are concrete actions that can be taken in the present to slow the spread of drug resistance and damage to the human microbial flora. For example, educational campaigns aimed at physicians and the general public can promote more prudent use of antimicrobial drugs. At a political level, policy makers should be made aware of the economic and regulatory hurdles that slow the development of rapid diagnostic tests and pathogen-specific drugs. However, perhaps things can change more rapidly that one can anticipate. Certainly, if future research was to associate disturbances in the microflora with such chronic diseases as asthma, atopy, and cancer, this would create tremendous medical and legal disincentives in the use of nonspecific microbial therapy. Another powerful force could be the categorization of such complications of broad-spectrum therapy as C. difficile colitis and candidiasis as medical errors, which would be followed by aversion of third-party payers for hospital and physician reimbursements. At the same time, economic incentives for the development of pathogen-specific therapy by industry could be created by linking the patent protection time of antimicrobial drugs to the width of the antimicrobial spectrum and inclusion of narrow-spectrum drugs as orphan drugs. For example, patent policy could be amended such that narrow-spectrum drugs with small markets enjoy much longer patent protection than broad-spectrum drugs. Although in 2009 a revolution in the antimicrobial therapeutic paradigm seems distant, it is worth noting that only a generation ago smoking was widely permitted and accepted in most public places. For smoking, it was the realization that second-hand smoke was dangerous that catalyzed the creation of smoke-free environments in most public places. Perhaps increased awareness of the consequences of long-term damage to the human flora will have a similar catalytic effect in promoting pathogen-specific antimicrobial therapies.

The re-introduction of pathogen-specific therapy for bacterial diseases, and its extension to fungal diseases, would require a concerted effort and collaboration between intellectual leaders in the field, industry, and government to find mechanisms that would promote and encourage the development of such drugs. There are indications of movement in this direction. A recent report by the Institute of Medicine recommended ‘development of strategies that will selectively target pathogenic organisms while avoiding targeting the host and beneficial or benign organisms’, which in other words is pathogen-specific therapy.3 Several therapies

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

narrow-spectrum are currently in development, for example, the renewed interest in phage therapy, monoclonal antibody therapies, and drugs aimed primarily at targeting highly resistant bacteria. However, the task of refocusing anti-bacterial and antifungal therapy to pathogen specificity is too great for any individual party and cooperation from industry, government, and the medical community will be needed to effect change. There is an acute need for an economic model that would allow the development and use of pathogen-specific drugs. Despite these hurdles, it is clear that pathogen-specific therapy makes sense and, given that the current nonspecific strategies are increasingly bankrupt, it behooves all parties to begin a dialogue on how to get there, and get there sooner than later.

Declaration of Interest

The author states no conflict of interest and has received no payment in preparation of this manuscript.

Bibliography

Buchwald UK, Pirofski L. Immune therapy for infectious diseases at the dawn of the 21st century: the past, present and future role of antibody therapy, therapeutic vaccination and biological response modifiers. Curr Pharm Des 2003;9(12):945-68

Casadevall A. Crisis in Infectious Diseases: Time for a new paradigm? Clin Infect Dis 1996;23:790-4

Casadevall A, Scharff MD. “Serum Therapy” revisited: Animal models of infection and the development of passive antibody therapy. Antimicrob Agents Chemother 1994;38:1695-702

Casadevall A, Scharff MD. Return to the past: the case for antibody-based therapies in infectious diseases. Clin Infect Dis 1995;21:150-61

Casadevall A. The third age of antimicrobial therapy. Clin Infect Dis 2006;42(10):1414-6

Jawetz E. Antimicrobial therapy. Ann Rev Microbiol 1956;10:85-114

Kozyrskyj AL, Ernst P, Becker AB. Increased risk of childhood asthma from antibiotic use in early life. Chest 2007;131(6):1753-9

Kusel MM, de KN, Holt PG, Sly PD. Antibiotic use in the first year of life and risk of atopic disease in early childhood. Clin Exp Allergy 2008;38(12):1921-8

Velicer CM, Heckbert SR, Lampe JW, et al. Antibiotic use in relation to the risk of breast cancer. JAMA 2004;291(7):827-35

Wickens K, Ingham T, Epton M, et al. The association of early life exposure to antibiotics and the development of asthma, eczema and atopy in a birth cohort: confounding or causality? Clin Exp Allergy 2008;38(8):1318-24

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A2
WAVES OF RESISTANCE: STAPHYLOCOCCUS AUREUS IN THE ANTIBIOTIC ERA4

Henry F. Chambers5 and Frank R. DeLeo6

Abstract

Staphylococcus aureus is notorious for its ability to become resistant to antibiotics. Infections that are caused by antibiotic-resistant strains often occur in epidemic waves that are initiated by one or a few successful clones. Methicillin-resistant S. aureus (MRSA) features prominently in these epidemics. Historically associated with hospitals and other health care settings, MRSA has now emerged as a widespread cause of community infections. Community or community-associated MRSA (CA-MRSA) can spread rapidly among healthy individuals. Outbreaks of CA-MRSA infections have been reported worldwide, and CA-MRSA strains are now epidemic in the United States. Here, we review the molecular epidemiology of the epidemic waves of penicillin- and methicillin-resistant strains of S. aureus that have occurred since 1940, with a focus on the clinical and molecular epidemiology of CA-MRSA.


Staphylococcus aureus is naturally susceptible to virtually every antibiotic that has ever been developed. Resistance to antibiotics is often acquired by the horizontal transfer of genes from outside sources, although chromosomal mutation and antibiotic selection are also important. This exquisite susceptibility of S. aureus led to Alexander Fleming’s discovery of penicillin, which ushered in the ‘antibiotic era’. Penicillin was truly a miracle drug: uniformly fatal infections could now be cured. However, by the mid 1940s, only a few years after its introduction into clinical practice, penicillin resistance was encountered in hospitals, and within a decade it had become a notable problem in the community.

A fundamental biological property of S. aureus is its ability to asymptomatically colonize healthy individuals. Approximately 30% of humans are asymptomatic nasal carriers of S. aureus (Kluytmans and Verbaugh, 1997; Gorwitz et al., 2008) such that in these individuals S. aureus is part of the normal flora. S. aureus

4

Reprinted with permission from Nature Reviews Microbiology 7, 629-641 (September 2009).

5

Division of Infectious Diseases, Department of Medicine, San Francisco General Hospital, University of California, San Francisco, California 94110, USA.

6

Laboratory of Human Bacterial Pathogenesis, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, 903 South 4th Street, Hamilton, Montana 59840, USA. Correspondence to H.F.C. e-mail: hchambers@medsfgh.ucsf.edu. doi:10.1038/nrmicro2200.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

carriers are at higher risk of infection and they are presumed to be an important source of the S. aureus strains that spread among individuals. The primary mode of transmission of S. aureus is by direct contact, usually skin-to-skin contact with a colonized or infected individual, although contact with contaminated objects and surfaces might also have a role (Miller and Diep, 2008; Kazakova et al., 2005; Lowy, 1998; Muto et al., 2003). Various host factors can predispose individuals to infection, including the loss of the normal skin barrier, the presence of underlying diseases such as diabetes or AIDS and defects in neutrophil function.

Infections that are caused by antibiotic-resistant strains of S. aureus have reached epidemic proportions globally (Tiemersma, 2006). The overall burden of staphylococcal disease, particularly disease caused by methicillin-resistant S. aureus (MRSA) strains, is increasing in many countries in both health care and community settings (Kaplan et al., 2005; Hersh et al., 2008; Klevens et al., 2007; Hope et al., 2008; Laupland et al., 2008; European Antimicrobial resistance Surveillance System, 2008). In the United States, the emergence of community associated MRSA (CA-MRSA) strains accounts for much of this increase, as it is a major cause of skin and soft-tissue infections (Moran et al., 2006; Fridkin et al., 2005). The rapidity and extent of the spread of CA-MRSA strains has been remarkable. In addition to the United States, CA-MRSA strains have been reported in Canada, Asia, South America and Australia as well as throughout Europe, including in countries that historically have a low prevalence of MRSA, such as Norway, the Netherlands, Denmark and Finland (Laupland et al., 2008; Larsen et al., 2007; Larsen et al., 2008; Wannet et al., 2005; Deurenberg et al., 2009; Vandenesch et al., 2003; Stam-Bolink et al., 2007; Huang et al., 2007; Nimmo and Coombs, 2008; Kanerva et al., 2009; Park et al., 2009; Gardella et al., 2008; Francois et al., 2008; Fang et al., 2008; Conly and Johnston, 2003). Globally, CA-MRSA strains have shown considerable diversity in the number of different clones that have been identified.

In addition to their increasing prevalence and incidence, CA-MRSA strains seem to be particularly virulent. Overwhelming and tissue-destructive infections, such as necrotizing fasciitis and fulminant, necrotizing pneumonia (Francis et al., 2005; Gonzalez et al., 2005; Kallen et al., 2009), were rarely seen before the emergence of CA-MRSA strains. The factor (or factors) that is responsible for this hypervirulent behaviour is not known, but Panton–Valentine leukocidin (PVL), which has been epidemiologically associated with severe skin infections and pneumonia that are caused by methicillin-susceptible S. aureus (MSSA) strains (Lina et al., 1999), is a leading candidate.

Antibiotics arguably constitute the most concentrated selective pressure on S. aureus in its long coevolutionary history with mankind. The consequences of this selective pressure, in conjunction with horizontal and vertical gene transfer, are discussed in this Review. Given their crucial importance as therapeutic agents, we focus on resistance to penicillins and the structurally related β-lactam antibiotics.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Epidemic Waves of Resistance

The emergence of antibiotic resistance in S. aureus can be visualized as a series of waves (Figure A2-1). The first wave began in the mid 1940s as the proportion of infections caused by penicillin-resistant strains of S. aureus increased in hospitals (Kirby, 1944; Barber and Rozwadowska-Dowzenko, 1948). These strains produced a plasmid-encoded penicillinase, which hydrolyses the β-lactam ring of penicillin that is essential for its antimicrobial activity. Penicillin-resistant strains soon began to cause community infections, and by the early 1950s they had become pandemic (Roundtree and Freeman, 1956). These infections, both in hospitals and in the community, were frequently caused by an S. aureus clone known as phage type 80/81 (Roundtree and Freeman, 1956; Blair and Carr, 1960; Bynoe et al., 1956; Roundtree and Beard, 1958). Pandemic phage type 80/81 S. aureus infections largely disappeared after the introduction of methicillin (Jevons and Parker, 1964), but the prevalence of penicillinase-producing strains from other S. aureus lineages has remained high.

The introduction of methicillin marks the onset of the second wave of resistance (Figure A2-1). The first reports of a S. aureus strain that was resistant to methicillin were published in 1961 (Barber, 1961; Jevons, 1961). Although the specific gene responsible for methicillin resistance (mecA, which encodes the low-affinity penicillin-binding protein PbP2a (also known as PbP2′)) was not identified until over 20 years later, it was appreciated early on that the resistance mechanism involved was different from penicillinase-mediated resistance because drug inactivation did not occur. Unlike penicillinase-mediated resistance, which is narrow in its spectrum of activity, methicillin resistance is broad, conferring resistance to the entire β-lactam class of antibiotics, which include penicillins, cephalosporins and carbapenems. Among the earliest MRSA clinical isolates was the archetypal MRSA strain COL, a member of the ‘archaic’ clone of MRSA and perhaps the most studied MRSA strain, which was isolated from a patient in Colindale, UK, in 1960 (Jevons, 1961). COL is a member of the most successful MRSA lineage, which includes both hospital and community-associated strains.

Archaic MRSA strains circulated in hospitals throughout Europe until the 1970s (Crisostomo et al., 2001). There were also isolated reports of MRSA in hospitals in the United States (Barrett et al., 1968; Bran et al., 1972), but the rest of the world was largely unaffected, and these early MRSA strains never gained a foothold in the community. By the 1980s, for reasons that remain unclear, the archaic MRSA clone had largely disappeared from European hospitals, marking the end of the second and the beginning of the third wave of antibiotic resistance. Descendants of the archaic MRSA clone (for example, the Iberian and Rome clones (Mato et al., 2004) and other, highly successful MRSA lineages emerged (Enright et al., 2002; Robinson and Enright, 2003; Deurenberg and Stobberingh, 2008) (Table A2-1). Outbreaks of infections caused by MRSA strains were reported in hospitals in the United States in the late 1970s, and by the mid 1980s

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A2-1 The four waves of antibiotic resistance in Staphylococcus aureus. Wave 1 (indicated above the graph), which continues today, began shortly after the introduction of penicillin into clinical practice in the 1940s. The first pandemic antibiotic-resistant strains, from the lineage known as phage type 80/81, were penicillin-resistant and produced Panton-Valentine leukocidin (PVL). Wave 2 began almost immediately following the introduction of methicillin into clinical practice with the isolation of the first MRSA strain (an archaic clone), which contained staphylococcal chromosome cassette mecl (SCCmecl) (indicated on the graph as MRSA-I); this wave extended into the 1970s in the form of the Iberian clone. Wave 3 began in the mid to late 1970s with the new emergence of MRSA strains that contained the new SCCmec allotypes, SCCmecll and SCCmeclll (MRSA-II and MRSA-III), marking the ongoing worldwide pandemic of MRSA in hospitals and health care facilities. The increase in vancomycin use for the treatment of MRSA infections eventually led to the emergence of vancomycin-intermediate S. auereus (VISA) strains. Wave 4, which began in the mid to late 1990s, marks the emergence of MRSA strains in the community. Community-associated MRSA (CA-MRSA) strains were susceptible to most antibiotics other than β-lactams, were unrelated to hospital strains and contained a new, smaller, more mobile SCCmec allotype, SCCmecIV (MRSA-IV) and various virulence factors, including PVL. Vancomycin-resistant S. aureus (VRSA) strains, ten or so of which have been isolated exclusively in health care settings, were first identified in 2002.

FIGURE A2-1 The four waves of antibiotic resistance in Staphylococcus aureus. Wave 1 (indicated above the graph), which continues today, began shortly after the introduction of penicillin into clinical practice in the 1940s. The first pandemic antibiotic-resistant strains, from the lineage known as phage type 80/81, were penicillin-resistant and produced Panton-Valentine leukocidin (PVL). Wave 2 began almost immediately following the introduction of methicillin into clinical practice with the isolation of the first MRSA strain (an archaic clone), which contained staphylococcal chromosome cassette mecl (SCCmecl) (indicated on the graph as MRSA-I); this wave extended into the 1970s in the form of the Iberian clone. Wave 3 began in the mid to late 1970s with the new emergence of MRSA strains that contained the new SCCmec allotypes, SCCmecll and SCCmeclll (MRSA-II and MRSA-III), marking the ongoing worldwide pandemic of MRSA in hospitals and health care facilities. The increase in vancomycin use for the treatment of MRSA infections eventually led to the emergence of vancomycin-intermediate S. auereus (VISA) strains. Wave 4, which began in the mid to late 1990s, marks the emergence of MRSA strains in the community. Community-associated MRSA (CA-MRSA) strains were susceptible to most antibiotics other than β-lactams, were unrelated to hospital strains and contained a new, smaller, more mobile SCCmec allotype, SCCmecIV (MRSA-IV) and various virulence factors, including PVL. Vancomycin-resistant S. aureus (VRSA) strains, ten or so of which have been isolated exclusively in health care settings, were first identified in 2002.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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TABLE A2-1 Lineages of Common Nosocomial MRSA Strains

Clonal complex

Sequence type

Common name(s)

Comment and SCCmec allotypes

CC5

ST5

USA100, NewYork or Japan clone

The most common health care-associated MRSA strain in the United States; SCCmecII

 

ST5

EMRSA-3

SCCmecI

 

ST5

USA800 or paediatric clone

Prevalent in Argentina, Colombia and the United States; SCCmecIV

 

ST5

HDE288 or paediatric clone (in Portugal)

SCCmecVI

CC8

ST250

Archaic

The first MRSA clone to be identified, includes the COL strain; SCCmecl

 

ST247

Iberian clone or EMRSA-5

A descendant of COL-type strains; SCCmecl

 

ST239

Brazilian or Hungarian clone

SCCmeclll

 

ST239

EMRSA-1

An Eastern Australian epidemic clone of the 1980s; SCCmeclll

 

ST239

AUS-2 and AUS-3

Common Australian multidrug-resistant clones of the early 2000s; SCCmeclll

 

ST8

Irish-1

Common hospital-acquired isolate in the 1990s in Europe and the United States; SCCmecll

 

ST8

USA500, EMRSA-2 or EMRSA-6

SCCmecIV

CC22

ST22

EMRSA-15

An international clone that is prominent in Europe and Australia; SCCmecIV

CC30

ST36

USA200 or EMRSA-16

The single most abundant cause of MRSA infections in UK hospitals and the second most common cause of MRSA infections in US hospitals in 2003; SCCmecll

CC45

ST45

USA600

SCCmecll

 

ST45

Berlin clone

SCCmecIV

CC, clonal complex; MRSA, methicillin-resistant Staphylococcus aureus; SCCmec, staphylococcal chromosome cassette mec, ST, sequence type.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

these strains were endemic (Crossley et al., 1979; Peacock et al., 1980), leading to the worldwide pandemic of MRSA in hospitals that continues to the present time. Although global in its distribution and impact, MRSA was still confined mainly to hospitals and other institutional health care settings, such as long-term care facilities. The ever-increasing burden of MRSA infections in hospitals led to the increased use of vancomycin, the last remaining antibiotic to which MRSA strains were reliably susceptible. This intensive selective pressure resulted in the emergence of vancomycin-intermediate S. aureus (VISA) strains, which are not inhibited in vitro at vancomycin concentrations below 4–8 μg ml–1 (Hiramatsu et al., 1997), and vancomcyin-resistant S. aureus (VRSA) strains, which are inhibited only at concentrations of 16 μg ml–1 or more (Weigel et al., 2003).

The MRSA invasion of the community constitutes the fourth and most recent wave of antibiotic resistance (Figure A2-1). Some of the earliest cases of CA-MRSA infection occurred in indigenous populations in Western Australia in the early 1990s (O’Brien et al., 2004; Coombs et al., 2004; Udo et al., 1993). These MRSA strains were distinguishable from the contemporary clones or genotypes that were circulating in Australian hospitals by their pulsed-field gel electrophoresis patterns and their susceptibility to most antibiotics other than β-lactams, suggesting that they were either remote, ‘feral’ descendants of hospital strains or community strains that had acquired mecA by horizontal gene transfer. In the United States, the first well-documented cases of MRSA infection that were truly community associated occurred in otherwise healthy children from 1997 to 1999 (CDC, 1999). These children had no risk factors for developing MRSA and all died with overwhelming infection, suggesting that these CA-MRSA strains were especially virulent. Like their Australian counterparts, these CA-MRSA isolates were unrelated to hospital associated clones and were susceptible to most antibiotics. The CA-MRSA epidemic in the United States can be traced back to the early 1990s on the basis of retrospective data from 1993 to 1995, which show a dramatic increase in MRSA infections in Chicago among children who lacked risk factors for hospital-associated MRSA exposure (Herold et al., 1998). CA-MRSA has since been reported in numerous populations, including American Indians and Alaskan natives (Baggett et al., 2004), Pacific Islanders (CDC, 2004), athletes (Kazakova et al., 2005), jail and prison inmates (Aiello et al., 2006), men who have sex with men (Diep et al., 2008), contacts of patients with CA-MRSA infection (Johansson et al., 2007), military personnel (Aiello et al., 2006), adult emergency room patients (Moran et al., 2006) and children in day care centres (Adcock et al., 1998). CA-MRSA clones have also gained a foothold in hospitals and are increasingly being identified as a cause of hospital-onset and heath care-associated infections (Klevens et al., 2007; Laupland et al., 2008; Park et al., 2009; Liu et al., 2008; Seybold et al., 2006).

The epidemic wave of CA-MRSA in the United States and Canada (Gilbert et al., 2006; Mulvey et al., 2005) is actually two overlapping epidemics. The USA400 clone, which was isolated from the paediatric cases described above,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

was most prevalent before 2001 (Lowy, 1998; CDC, 1999; Stemper et al., 2004) and remains a common cause of community-onset disease among indigenous populations in Alaska and the Pacific Northwest (David et al., 2008). A second epidemic clone, MRSA strain USA300, which is unrelated to USA400 and has largely displaced it in most other locations, emerged between 1999 and 2001 and now causes most of the CA-MRSA infections in the United States (Lowy, 1998; Kazakova et al., 2005; Pan et al., 2003; Pannaraj et al., 2006; Diep et al., 2004; Chavez-Bueno et al., 2005).

Outbreaks and epidemics of CA-MRSA now occur worldwide and have a similar epidemiology, although the specific clones that have emerged vary with geographical location. CA-MRSA strains are not merely escapees from health care facilities; their genotypes indicate that they are not closely related to endemic hospital clones and they are susceptible to numerous antibiotics to which hospital strains are routinely resistant. Two molecular markers that are not found in typical hospital MRSA strains are strongly associated with the emergence of CA-MRSA regardless of geographical origin: a specific cassette element encoding mecA and genes encoding PVL. These markers are discussed in detail below.

Molecular Epidemiology of S. aureus

S. aureus Clonal Complexes

Robust, sequence-based molecular methods for genotyping strains of S. aureus, and multilocus sequence typing (MLST) (Enright et al., 2000) in particular, have made it possible to study the evolutionary history of this pathogen (Box A2-1). MLST is carried out by sequence analysis of ~450 bp internal fragments of seven housekeeping genes (Figure A2-2). Isolates that have identical sequences at all seven loci are considered to be a clone and are assigned a unique sequence type (ST). STs that differ by single nucleotide polymorphisms (SNPs) at fewer than three loci are thought to be closely related and are grouped into clonal complexes (CCs). This grouping is accomplished by the eBURST algorithm, which uses MLST data to group closely related strains into a CC. It also predicts the probable founding clone, or ST, of each group and the recent evolutionary descent of all other strains in the CC from the founder (Feil et al., 2004; Turner et al., 2007). The analysis can be further refined to identify specific subclones by the addition of other methods, such as spa typing (Shopsin et al., 1999) or pulsed-field gel electrophoresis of genomic DNA (Box A2-1), or by the presence of other genetic markers (for example, toxin genes or specific plasmids).

Studies of MSSA strains, carriage isolates and hospital and community isolates causing disease that were collected worldwide between 1961 and 2004 show that 88% of the collected strains can be assigned to one of 11 clonal complexes (CC1, CC5, CC8, CC9, CC12, CC15, CC22, CC25, CC30, CC45 and CC51/121) (Enright et al., 2002, 2000; Feil et al., 2004, 2003; Tenover et al., 2008; Goering

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

BOX A2-1

Staphylococcus aureus Genotyping

Multilocus sequence typing

Multilocus sequence typing (MLST) is a sequence-based genotyping method based on single nucleotide varioations (each variant is termed an allele) of seven housekeeping genes in Staphylococcus aureus, providing a discriminatory allelic profile known as a sequence type (ST) (Enright et al., 2000) for each bacterial isolate. Because it indexes variations that accumulate slowly over time, MLST can be used to measure long periods of evolution among S. aureus lineages, and the results obtained are highly reproducible. S. aureus isolates that have identity at five or more of the seven housekeeping genes as determined by MLST are known as a clonal complex (CC) (Feil et al., 2004, 2003).


Pulsed-field gel electrophoresis

Pulsed-field gel electrophoresis (PFGE) has a more rapid clock speed than MLST and is suitable for the evaluation of more recent evolution among groups of strains. The method relies on the separation of Smal-digested S. aureus genomic DNA fragments in an agarose gel according to size. Related strains are clustered according to an 80% similarity coefficient (McDougal et al., 2003). The CDC has developed a national PFGE database for S. aureus, which uses the ‘USA’ designation; for example, USA300 refers to an ST8, Panton-Valentine leukocidin-positive community-associated MRSA strain (McDougal et al., 2003).


spa typing

spa typing (Shopsin et al., 1999) is based on the sequence analysis of variable-number tandem repeats in the gene that encodes protein A (spa). spa typing takes into account point mutations in the repeat region as well as the number of repeat variations. This method is suitable for the investigation of local or global S. aureus outbreaks. This sequence-based analysis of a single target locus is an inexpensive way of acquiring robust data that can be used to determine both epidemiological and phylogenetic relationships.

et al., 2008; Hallin et al., 2007; Feng et al., 2008; Feil and Enright, 2004; Lindsay et al., 2006) (Figure A2-3a). For ten of these CCs, the percentage of isolates in each complex ranges from 2% to 9%; CC30 is an outlier, accounting for 21% of isolates.

The CCs for contemporary isolates are almost certainly the same as those of strains that were circulating before 1940. For example, the ST5 lineage (the founder of CC5) is estimated to have existed for over 2,000 years (Nubel et al., 2008). Gomes and colleagues (Gomes et al., 2006) genotyped 22 penicillin-susceptible and 67 penicillin-resistant MSSA blood culture isolates that were collected between 1957 and 1973 by the Statens Serum Institute in Copenhagen, which has collected and maintained every blood culture isolate from patients in Denmark from 1957 to the present. They found that 86% of the isolates fell into

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

seven CCs, the most common being CC8 and CC30, which together accounted for 46% of the isolates (Figure A2-3b). The distributions of penicillin-sensitive and penicillin-resistant isolates were similar. In this analysis, only a few isolates were tested and they all originated from a single country, which probably accounts for the absence of isolates from CC9, CC12, CC15 and CC22.

CC8 and CC30 have given rise to epidemics during each of the four waves of antibiotic resistance. The first well-characterized pandemic of antibiotic-resistant S. aureus that is attributable to a single clone was caused by phage type 80/81 strains, which belong to CC30 (Robinson et al., 2005). Phage type 80/81 strains were originally isolated in Australia in 1953 (Roundtree and Beard, 1958). They are penicillin resistant and have caused both hospital and community outbreaks on a global scale (Robinson et al., 2005). These strains are prevalent in collections that date back to 1927; they were thought to be highly transmissible and particularly virulent and were also among the first to be identified as penicillin resistant (Blair and Carr, 1960). Almost all of the phage type 80/81 isolates in a collection dating to the 1950s and 1960s encode PVL88, which is reminiscent of the association between PVL and resistance to methicillin in the contemporary epidemic CA-MRSA strains. For unknown reasons, phage type 80/81 strains virtually disappeared in the early 1960s, and this coincided with the first use of semisynthetic penicillins, which are resistant to penicillinase. Modern descendents of the CC30 lineage include the PVL-positive southwest Pacific (SWP) clone of CA-MRSA in Australia and the hospital-associated ST36 EMRSA-16 clone, a major cause of nosocomial infections and bacteraemia in both Australia and the United Kingdom (Robinson et al., 2005; Cox et al., 1995; Johnson et al., 2001).

MRSA CCs

The first MRSA clinical isolates, of which COL is an example, were ST250 and members of CC8. ST250 MRSA strains circulated in the United Kingdom and the rest of Europe before the 1970s but did not become established in the United States and had largely disappeared by the 1980s. However, other highly successful clones emerged, including the ST247 Iberian or EMRSA-5 clone, which is closely related to ST250. No fewer than nine other endemic nosocomial clones are descendants of the ST8 founder of this lineage. The CA-MRSA strain USA300 (which is PVL positive) that is prevalent in the United States is also ST8 (McDougal et al., 2003). MRSA strains have generally been found to be members of a subset of S. aureus CCs, including CC1, CC5, CC8, CC22, CC30 and CC45, although CA-MRSA strains have exhibited some diversity (discussed below). These CCs were widespread before the emergence of methicillin resistance (Crisostomo et al., 2001; Gomes et al., 2006), indicating that superior epidemicity preceded the acquisition of drug resistance and that the adaptations and innovations that make S. aureus clones successful can also favour their adaptation to antibiotic selective pressures.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A2-2 An example of a multilocus sequence typing scheme and the designation of clonal complexes. Multilocus sequence typing in Staphylococcus aureus involves PCR amplification and sequencing of approximately 450 nucleotides of seven chromosomal “housekeeping” genes that were selected for their presumed absence of selective pressure and their moderately stable nucleotide sequences (carbamate kinase (arc), shikimate dehydrogenase (aroE), glycerol kinase (glpF), guanylate kinase (gmk), phosphate acetyltransferase (pta), triose phosphate isomerase (tpiA) and acetyl-CoA acetyl-transferase (yqiL)). Each unique sequence within a gene locus is assigned a number. The numbers are concatenated left-to-right in the order shown to provide a seven-integer series of numbers, which is then assigned a sequence type (ST). Strains that are identical at all seven loci are classified as the same ST. Strains differing at one or two loci are related but, as they are not identical, they are assigned different STs. Closely related STs are grouped into a clonal complex (CC). In the example shown, ST1, ST5, and ST8 differ at most loci and so are not closely related; ST250 and ST247 differ from each other at one locus (gmk) and from ST8 at one (yqiL) and two loci (gmk, yqiL), respectively. Therefore, ST8, ST250 and ST247 are closely related and form CC8, so designated because the analysis of sequence identities and differences in a large collection of strains indicates that ST8 is the founder of this CC and the ancestor of both ST247 and ST250, and that ST247 is a descendant of ST250.

FIGURE A2-2 An example of a multilocus sequence typing scheme and the designation of clonal complexes. Multilocus sequence typing in Staphylococcus aureus involves PCR amplification and sequencing of approximately 450 nucleotides of seven chromosomal “housekeeping” genes that were selected for their presumed absence of selective pressure and their moderately stable nucleotide sequences (carbamate kinase (arc), shikimate dehydrogenase (aroE), glycerol kinase (glpF), guanylate kinase (gmk), phosphate acetyltransferase (pta), triose phosphate isomerase (tpiA) and acetyl-CoA acetyl-transferase (yqiL)). Each unique sequence within a gene locus is assigned a number. The numbers are concatenated left-to-right in the order shown to provide a seven-integer series of numbers, which is then assigned a sequence type (ST). Strains that are identical at all seven loci are classified as the same ST. Strains differing at one or two loci are related but, as they are not identical, they are assigned different STs. Closely related STs are grouped into a clonal complex (CC). In the example shown, ST1, ST5, and ST8 differ at most loci and so are not closely related; ST250 and ST247 differ from each other at one locus (gmk) and from ST8 at one (yqiL) and two loci (gmk, yqiL), respectively. Therefore, ST8, ST250 and ST247 are closely related and form CC8, so designated because the analysis of sequence identities and differences in a large collection of strains indicates that ST8 is the founder of this CC and the ancestor of both ST247 and ST250, and that ST247 is a descendant of ST250.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Staphylococcal Chromosome Cassette mec

The discovery by Hiramatsu and colleagues (Ito et al., 2001) that mecA is always found in a mobile cassette element was a great advance for our understanding of the biology of methicillin resistance and provided an additional tool for determining the evolutionary relationships among MRSA strains. Staphylococcal chromosome cassette mec (SCCmec) is integrated into orfX, an S. aureus gene of unknown function (Figure A2-4). To date, eight SCCmec allotypes, designated SCCmecI–SCCmecVIII (Deurenberg and Stobberingh, 2008; Ito et al., 2001; Ma et al., 2002; Oliveira et al., 2006; Higuchi et al., 2008; Zhang et al., 2009), have been described (Table A2-2), along with numerous subtypes, and more will probably be identified as sequence data become available for more MRSA strains (see the SCCmec website for additional descriptions and information). Similar elements are present in coagulase-negative staphylococci, which are commensal organisms that are part of the normal skin flora of humans and other mammals (Ruppe et al., 2009). Two gene complexes, mec and ccr (the recombination and excision locus encoding the gene or genes that mediate the integration and excision of the whole cassette into and out of orfX), are used to classify the SCCmec allotypes (Table A2-2). There are also other differences among the various SCCmec allotypes, particularly in terms of insertion sequences and antimicrobial resistance genes. However, as these are themselves mobile elements, they have not proved useful for the classification of the main allotypes, although they are useful for defining subtypes.

The class A mec gene complex is the prototype complex and is found in SCCmecII (Figure A2-4a), SCCmecIII and SCCmecVIII. It contains mecA, the complete mecR1 and mecI regulatory genes upstream of mecA, and the hypervariable region (HVR) and insertion sequence 431 (IS431) downstream of mecA. The class b mec gene complex is found in SCCmecI, SCCmecIV (Figure A2-4b) and SCCmecVI and is composed of mecA, a truncated mecR1 (resulting from the insertion of IS1272) upstream of mecA, and the HVR and IS431 downstream of mecA. There are two distinct class C mec gene complexes, both of which contain mecA, a truncated mecR1 (resulting from the insertion of IS431) upstream of mecA, and the HVR and IS431 downstream of mecA. In the class C1 mec gene complex, the IS431 elements upstream and downstream of mecA are in the same orientation, whereas in the class C2 mec gene complex, which is found in SCCmecV and SCCmecVII, the orientation of the IS431 upstream of mecA is reversed. C1 and C2 are regarded as different mec gene complexes, as they have probably evolved independently. The mecA, mecR1 and mecI sequences are highly conserved, with >99% nucleotide sequence identity.

The ccr gene complex consists of two adjacent genes, ccrA and ccrB, in SCCmecI–SCCmecIV, SCCmecVI and SCCmecVIII and one gene, ccrC, in SCCmecV and SCCmecVII. MRSA strains that were isolated before 1990, which were all nosocomial isolates, contained predominantly SCCmecI–SCCmecIII.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A2-3 Distribution of antibiotic-susceptible and -resistant Staphylococcus aureus among clonal complexes. a| The distribution of methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant S. aureus (MRSA) among the various clonal complexes. These data were collected from six continents between 1961 and 2004. b| The distribution of penicillin-susceptible S. aureus (PSSA) and penicillinresistant S. aureus (PRSA) among the various clonal conplexes. These data are from a single study of 89 isolates that were collected in Copenhagen from 1957 to 1973. See main text for details.

FIGURE A2-3 Distribution of antibiotic-susceptible and -resistant Staphylococcus aureus among clonal complexes. a| The distribution of methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant S. aureus (MRSA) among the various clonal complexes. These data were collected from six continents between 1961 and 2004. b| The distribution of penicillin-susceptible S. aureus (PSSA) and penicillinresistant S. aureus (PRSA) among the various clonal conplexes. These data are from a single study of 89 isolates that were collected in Copenhagen from 1957 to 1973. See main text for details.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A2-4 Comparison of the methicillin resistance cassettes that are typical of hospital- or community-acquired methicillin-resistant Staphylococcus aureus. Staphylococcal chromosome cassette mecII (SCCmecII) is most abundant in hospitals, whereas SCCmecIV is present in the most abundant community-acquired methicillin-resistant Staphylococcus aureus strains. The mecR1 gene (R1) in SCCmecIV is truncated, whereas the copy in SCCmecII is full-length. Transposon Tn554, which is present in SCCmecII but not in SCCmecIV, encodes resistance to macrolide-lincosomide-streptogramin B antibiotics and spectinmycin. pUB110 is an integrated plasmid that encodes a tobramycin resistance gene. SCCmecII therefore encodes resistance to multiple antibiotics, whereas SCCmecIV encodes resistance to methicillin alone. A, mecA; I mecl; IS431, insertion sequence 431.

FIGURE A2-4 Comparison of the methicillin resistance cassettes that are typical of hospital- or community-acquired methicillin-resistant Staphylococcus aureus. Staphylococcal chromosome cassette mecII (SCCmecII) is most abundant in hospitals, whereas SCCmecIV is present in the most abundant community-acquired methicillin-resistant Staphylococcus aureus strains. The mecR1 gene (R1) in SCCmecIV is truncated, whereas the copy in SCCmecII is full-length. Transposon Tn554, which is present in SCCmecII but not in SCCmecIV, encodes resistance to macrolide-lincosomide-streptogramin B antibiotics and spectinmycin. pUB110 is an integrated plasmid that encodes a tobramycin resistance gene. SCCmecII therefore encodes resistance to multiple antibiotics, whereas SCCmecIV encodes resistance to methicillin alone. A, mecA; I mecl; IS431, insertion sequence 431.

CA-MRSA isolates most frequently contain variants of the SCCmecIV or SCCmecIV allotypes; less commonly, they contain SCCmecV (Francois et al., 2008; Okuma et al., 2002). SCCmecIV is also increasingly identified in contemporary hospital MRSA strains.

The three epidemic waves of MRSA correspond to evolutionary changes in SCCmec. The early MRSA strains (COL and other CC8 strains that circulated in the United Kingdom and Denmark in the early 1960s) all carried SCCmecI. They were replaced in the 1980s by new and arguably more successful lineages that eventually became established in hospitals throughout the world. These clones, which were predominantly CC5 and CC8, carried SCCmecII or SCCmecIII (for example, New York/Japan EMRSA, EMRSA-16 in Australia and the United Kingdom, the Brazilian clone and the Hungarian clone), or the type IA variant of the archaic SCCmecI (the Iberian clone). Why SCCmecII and SCCmecIII were more successful than SCCmecI is not known, but it could be that the recombinase genes, which are defective in SCCmecI but functional in SCCmecII and

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

TABLE A2-2 Comparison of Staphylococcal Chromosome Cassette mec Allotypes

Feature*

SCCmec allotype

I

II

III

IV

V

VI

VII

VIII

Size (kb)

34

53

67

21-24

28

24

41-49

32

mec complex

B

A

A

B

C2

B

C1 or C2

A

ccr complex

A1 and B1

A2 and B2

A3 and B3

A2 and B2

C

A4 and B4

C2 and C8

A4 and B4

IS431(n)

1

2

4

1

2

1

1

1

Tn554(n)

0

1

2

0

0

0

0

1

pUB110

-

+

-

-

-

-

-

-

pT181

-

-

+

-

-

-

-

-

Pl258

-

-

+

-

-

-

-

-

Other resistance genes

None

erm, spc, and tobra

erm, tet, and Hg++

None

None

None

None

erm and spc

*mec complex A has intact regulatory genes, mecR1 and mecl, upstream of mecA; mec complex B has regulatory gene deletions resulting from the insertion sequence 1272 (IS1272) insertion; mec complexes C1 and C2 have regulatory gene deletions resulting from the IS431 insertion; the ccr complex is the recombinase locus; pUB110, pT181 and pl258 are plasmids integrated at insertion sequences. erm, erythromycin resistance gene; Hg++, mercury resistance gene; IS431, insertion sequence 431; n, number of copies; spc, spectinomycin resistance gene, tet, tetracycline resistance gene; Tn554, transposon 554; tobra, tobramycin resistance gene.

SCCmecIII92, limited the potential for horizontal gene transfer of SCCmecI into new genomes.

SCCmecIV, which seems to have evolved from SCCmecI (although it has the ccrA and ccrB genes of SCCmecII (Lina et al., 2006)), gave rise to the most recent worldwide epidemic wave of CA-MRSA. Originally identified in the community-associated USA400 strain, MRSA strain MW2, the first occurrence of SCCmecIV in S. aureus might have been in the ST5 ‘paediatric’ clone that was circulating in hospitals in the late 1980s and the 1990s (Oliveira et al., 2001). The ultimate origins of mecA and SCCmec elements might never be known, but there is good evidence suggesting that coagulase negative staphylococci are the sources (Hanssen et al., 2004; Hanssen and Ericson Sollid, 2006; Wu et al., 1996).

The success of SCCmecIV is borne out by two observations. First, it is the most widely distributed SCCmec among S. aureus isolates. It has been found in nine distinct MRSA CCs or STs, whereas there are only two such lineages for SCCmecI, three for SCCmecII and two for SCCmecIII (Lina et al., 2006). Second, CA-MRSA strains containing SCCmecIV have faster growth rates than hospital MRSA strains carrying other SCCmec allotypes, and these growth rates are no different from MSSA isolates. In a rabbit bacteraemia model the fitness and virulence of USA300, which carries SCCmecIVA, were indistinguishable from those

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

of its isogenic MSSA variant (Diep et al., 2008). Thus, the SCCmecIV seems to confer little or no cost in fitness on the organism.

The Epidemiology of CA-MRSA

As mentioned above, the earliest reported cases of CA-MRSA infection in the United States were caused by a USA400 strain, MW2 (CDC, 1999). MW2 is closely related to the PVL-negative clone WA-1, which is an important CA-MRSA clone in Australia, and to the MSSA476 strain in the United Kingdom (Coombs et al., 2004). USA400 has been supplanted by USA300, which is currently by far the most frequent cause of CA-MRSA infections in the United States (Kennedy et al., 2008). The USA300 clone seems to be well adapted to the community, and there are reports of CA-MRSA infections caused by USA300 or its close relatives in Australia, Denmark and Colombia (Bartels et al., 2007; Gottlieb et al., 2008; Arias et al., 2008). USA300 strains can also cause health care-associated infections (Liu et al., 2008; Seybold et al., 2006; Maree et al., 2007; Gonzalez et al., 2006). Although there is evidence for the international spread of USA300 and USA400 (Wannet et al., 2005; Nimmo and Coombs, 2008; Tristan et al., 2007; Larsen et al., 2009), CA-MRSA strains that are not related to either USA300 or USA400 have been responsible for infections outside of the United States. ST80 is the predominant clone circulating in Europe, ST59 is the main clone in Taiwan and ST30 is the most frequent in Eastern Australia, demonstrating that CA-MRSA strains have evolved in separate geographical regions (Stam-Bolink et al., 2007; Huang et al., 2007; Nimmo and Coombs, 2008). There can also be considerable diversity in CA-MRSA strains from country to country. For example, in Australia 45 distinct clones of CA-MRSA have been identified; many of these are related to well-known MRSA lineages, but others seem to be new. The diversity of CA-MRSA isolates has also been noted by other studies (Wannet et al., 2005; Francois et al., 2008; Bartels et al., 2007; Tristan et al., 2007; Larsen et al., 2009). In the United Kingdom, most CA-MRSA infections are caused by EMRSA-15 (ST22) and EMRSA-16 (ST36), which are also important hospital-acquired clones (Rollason et al., 2008); ST80 is also present, but accounts for only a small proportion of isolates (Holmes et al., 2005). A CA-MRSA strain of swine origin that is transmissible to humans, ST398, has also been described (Huijsdens et al., 2006; Loeffler et al., 2009).

The epidemiology of CA-MRSA is similar regardless of the country of origin. Isolates tend not to be resistant to multiple drugs, SCCmecIV or SCCmecV is typically present, and infections of skin and soft tissue are the most common. The presence of PVL among CA-MRSA isolates is more variable. For example, in Australia and the United Kingdom most CA-MRSA clones do not produce PVL (Nimmo and Coombs, 2008; Rollason et al., 2008), and the prevalence of PVL among the more common CA-MRSA isolates from Denmark ranges from 17%

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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to 100% (Larsen et al., 2009). Conversely, isolates of clones that typically do not carry PVL genes (for example EMRSA-15 and EMRSA-16) have occasionally been found to be PVL-positive.

Nasal carriage of MRSA has increased in parallel with the emergence of MRSA as a community pathogen, which is not unexpected given that approximately 30% of individuals are asymptomatic nasal carriers of S. aureus. Between 2001 and 2004, carriage of MRSA strains in a US population-based study approximately doubled from 0.8% to 1.5% (Gorwitz et al., 2008), and the percentage of CA-MRSA genotypes increased from 7% to 24.2% (Tenover et al., 2008). Although the sites of carriage (for example, nares versus groin versus other sites) and the relationship between the carriage of CA-MRSA strains and disease are not entirely clear, CA-MRSA strains, especially USA300, seem to be more easily transmitted than other strains (Crum et al., 2006), which could account for the increasing carriage rates in the community. Thus, no individual or group can be considered not to be at risk for CA-MRSA infection.

The Virulence of CA-MRSA

CA-MRSA infections have been associated with fulminant and lethal infections and worse clinical outcomes than are seen with infections caused by health care-associated MRSA strains and community MSSA (Francis et al., 2005; Turner et al., 2007; Davis et al., 2007), giving rise to the impression that CA-MRSA strains, especially USA300, are more virulent than other strains. Much of our understanding of the unique virulence properties of CA-MRSA is based on studies of USA300 strains, the most extensively investigated clone. The USA300 core genome (the chromosome, excluding any mobile genetic elements) is similar to that of the early MRSA strain COL (Diep et al., 2006). However, studies in animal models indicate that USA300 is more virulent than COL (Voyich et al., 2005; Li et al., 2009). The expression of virulence factors by USA300 is high, and this and other closely related strains are more lethal than their more distant relatives and cause more extensive disease in animal models of infection (Li et al., 2009; Montgomery et al., 2008; Wang et al., 2007). The main difference between the COL and USA300 genomes is in their mobile genetic elements, which include prophages, plasmids, pathogenicity islands and transposons that have been acquired through horizontal gene transfer. These elements encode factors that can affect transmission, antibiotic resistance and virulence. Prophages ΦSA2 and ΦSA3, which are present in USA300 strains but not in COL, could contribute to the noted differences in virulence between these two lineages. Prophage ΦSA2 contains lukS–PV and lukF–PV, which encode PVL. Prophage ΦSA3 is present in strains other than CA-MRSA and encodes staphylokinase, staphylococcal complement inhibitor (SCIN) and S. aureus chemotaxis inhibitory protein (CHIPS), all of which are modulators of the innate immune system (Rooijakkers et al., 2006; van Wamel et al., 2006). In addition, USA300 contains

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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the pathogenicity island SaPI5, which is similar to the island that is present in COL. SaPI5 encodes two superantigens that are not present in COL, staphylococcal enterotoxin Q (SEQ) and staphylococcal enterotoxin K (SEK), which are also found in other MRSA and MSSA lineages. S. aureus produces many other molecules that promote host colonization, facilitate evasion of the innate immune system and alter immune responses (Wang et al., 2007; Deleo et al., 2009; Li et al., 2007) (see Supplementary information S1 [Table A2-S1]). Most of these molecules are not unique to CA-MRSA. The virulence factors that are found more commonly in CA-MRSA than in other strains, that are linked by epidemiology to CA-MRSA infections or that have been studied in animal models of CA-MRSA infection are discussed below.

PVL

PVL has been studied extensively since its discovery by Panton and Valentine 70 years ago (Wright, 1936). The role of PVL in the marked epidemicity and enhanced virulence of CA-MRSA is a subject of debate. PVL is composed of two subunits, LukS-PV and LukF-PV (Woodin, 1960), which are encoded by the horizontally acquired prophage ΦSA2 (Kaneko et al., 1998) and are secreted by the bacterium. These subunits bind to specific membrane receptors, which have yet to be identified, and associate to form pores in the membrane of host leukocytes (Meyer et al., 2009; Colin et al., 1994). At high concentrations (for example, 200 nM) PVL causes lytic cell death, but at sublytic concentrations (for example, 5 nM) it seems to partially activate neutrophils in a phenomenon known as priming, as they secrete potent mediators of inflammation, such as leukotriene b4 and interleukin 8, and also cause the release of neutrophil granule contents through exocytosis (Konig et al., 1995; Woodin and Wieneke, 1964; Genestier et al., 2005). In addition, PVL primes neutrophils for the enhanced production of reactive oxygen species on stimulation with the widely used neutrophil agonist fMLP (N-formyl-methionylleucyl-phenylalanine) (Colin and Monteil, 2003). Therefore, PVL could contribute to pathogenesis by causing an exaggerated inflammatory response and injury to the host. Several lines of evidence that are largely circumstantial indicate that PVL is associated with severe skin infections and severe necrotic haemorrhagic pneumonia (Lima et al., 1999; Gillet et al., 2002, 2007). Both USA300, which is now the leading cause of skin and soft tissue infections in the United States and a cause of extremely severe infections, and the penicillin-resistant phage type 80/81 strains that were associated with numerous outbreaks and severe disease in the 1950s produce PVL. The epidemiological association between PVL and the emergence of genetically unrelated CA-MRSA strains (that is, different and unrelated STs) that are geographically dispersed is striking.

There are other observations that call into question the presumption that PVL is driving the CA-MRSA epidemic. First, PVL is found infrequently in

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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other common, successful community strains. For example, the genes encoding PVL are present in only ~1–10% of MSSA clinical isolates (Goering et al., 2008; Kuehnert et al., 2006; Ellington et al., 2007). Second, although both USA300 and USA400 express PVL, USA300 has become the predominant CA-MRSA clone in the United States. This suggests that factors other than PVL are important for the recent emergence of CA-MRSA.

The experimental evidence does not provide a clear picture either. Voyich et al. (2006) found that USA300 and USA400 wild-type and isogenic PVL-deficient (∆pvl) strains caused virtually identical courses of infection in mouse abscess and sepsis models. Furthermore, there was no difference in neutrophil phagocytosis or lysis after uptake of the bacteria. However, because these experiments were carried out using culture supernatants, the results could reflect the action of multiple lytic factors. Similar results from a rat pneumonia model were reported by Montgomery and Daum (2009). Bubeck Wardenburg et al. (2007, 2008) also showed that USA300 and USA400 wild-type and isogenic ∆pvl strains were equally virulent in mouse abscess and pneumonia models. Diep et al. (2008) used two rabbit bacteraemia models to compare the haematogenous dissemination of wild-type and ∆pvl CA-MRSA strains to major organs: although PVL did not promote seeding of lungs, spleen or blood by USA300, there was a modest, transient contribution of PVL to colonization of the kidneys. In a series of experiments that used the same USA300 wild-type and mutant (∆pvl) strain pair as Voyich et al. (2006), Brown et al. (2008) found that the parent strain was more virulent than the ∆pvl mutant in mouse pneumonia and abscess models and that the disease caused by the wild-type strain was attenuated by immunization with recombinant LukF-PV or LukS-PV. In addition, Labandeira-Rey et al. (2007) found evidence to suggest that PVL might have a role in disease development in a mouse model of staphylococcal pneumonia: direct instillation of high doses of purified toxin provoked an inflammatory response in the lung and reduced survival. The authors used a laboratory strain of S. aureus that had been transduced with PVL-encoding bacteriophage to establish infection, and reported more severe disease in mice infected with this PVL-producing variant than in those infected with the PVL-negative parent. However, in addition to the presence of PVL, this transduced laboratory strain has substantial alterations in global gene expression that confounded the interpretation of the data. As PVL has no impact on protein or gene expression in USA300 or USA400 (Diep et al., 2008), it is possible that factors other than PVL accounted for the experimental results. Taken together, the data suggest that the contribution of PVL to CA-MRSA pathogenesis could be minor or perhaps dependent on an as-yet-unidentified bacterial factor or host susceptibility component.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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α-Haemolysin

The pore-forming toxin α-haemolysin (also known as Hla or α-toxin) causes the destruction of a wide range of host cells, including epithelial cells, erythrocytes, fibroblasts and monocytes, and is lethal in animal models when injected in purified form (Bhakdi and Tranum-Jensen, 1991). α-haemolysin is ubiquitous among clinical isolates, although some strains lack an active α-toxin. Recent studies by Bubeck Wardenburg et al. (2007) showed that α-haemolysin is essential for USA300 and USA400 to cause lethal pneumonia in a mouse model of the disease. The amount of this toxin that is produced by these strains in vitro correlates with the severity of the resultant lung disease (Montgomery et al., 2008; Bubeck Wardenburg et al., 2007; Burlak et al., 2007).

α-Type Phenol-Soluble Modulins

α-type phenol-soluble modulins (PSMαs) are a newly discovered group of peptides in S. aureus that are similar to the PSMs of Staphylococcus epidermidis (Wang et al., 2007). High expression of PSMαs might contribute to the enhanced virulence of CA-MRSA; PSMs are produced at higher levels in vitro by prominent CA-MRSA strains, including USA300 and USA400, than by hospital-acquired MRSA strains (Wang et al., 2007). PSMα peptides recruit, activate and ultimately lyse human neutrophils, thereby promoting S. aureus pathogenesis, and greatly contribute to the virulence of USA300 and USA400 in mouse abscess and sepsis models. The study by Wang et al. (2007) was the first to identify molecules from CA-MRSA that could account at least in part for the enhanced virulence of USA300 and USA400.

Arginine Catabolic Mobile Element

The arginine catabolic mobile element (ACME) is a 30.9 kb segment of DNA that seems to be unique to USA300 (Diep et al., 2008). This element is adjacent to SCCmecIV and is mobilized by the recombinases that are encoded by SCCmec. It contains two potential virulence factors, a cluster of arginine catabolism (arc) genes that encode an arginine deiminase pathway and opp3, which encodes an oligopeptide permease (Coulter et al., 1998; Degnan et al., 1998). Deletion of ACME but not SCCmec has been shown to decrease the fitness of USA300 in a rabbit bacteraemia model (Diep et al., 2008). Therefore, ACME might contribute to the fitness and epidemic spread of USA300.

Although mobile genetic elements such as ACME are likely to play a part in the transmission of CA-MRSA, there are differences in virulence potential and human disease manifestation even among similar USA300 isolates. For example, Kennedy et al. (2008) used comparative whole-genome sequencing to determine whether USA300 arose by convergent evolution towards a

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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hypervirulent phenotype or from a recent common ancestor of high virulence potential. Ten USA300 isolates, including some from a wide range of clinical syndromes and from different geographical locations in the United States, were examined. The strains differed from the USA300 reference strain FPR3757 genome by only a few SNPs, ranging from 11 to 408 in number. Phylogenetic analysis indicated that 8 of the strains, differing on average by 32 SNPs from the reference strain and 50 SNPs from each other, clustered with the reference strain and had descended from a recent common ancestor. These nine closely related isolates constitute the epidemic USA300 clone. Eight of the nine strains were ACME positive and all nine contained the same SCCmecIVA subtype. The two other strains were outliers, both lacking ACME and carrying a different SCCmec subtype, type IVB. Unexpectedly, the virulence of the more closely related isolates was variable in animal infection models. Some of these isolates had caused dramatically different disease syndromes in humans (for example, necrotizing pneumonia versus abscesses were caused by isolates that differed by only 23 SNPs), which serves to highlight the importance of host factors in disease presentation and severity.

Treatment in the Era of CA-MRSA

CA-MRSA has had a marked impact on empirical therapy of suspected staphylococcal infection. Most β-lactam antibiotics, including all orally available agents, can no longer be assumed to be effective for a range of common staphylococcal infections, in particular for skin and soft-tissue infections. In regions where CA-MRSA is prevalent, antimicrobial therapy should be active against MRSA strains. However, there are few clinical data to support the use of agents other than vancomycin, daptomycin or linezolid. Despite a lack of rigorous clinical studies, the oral agents that are recommended for the treatment of CA-MRSA skin and soft-tissue infections include clindamycin, long-acting tetracyclines (doxycycline and minocycline) and trimethoprim–sulphamethoxazole, as well as rifampin and fusidic acid as adjunctive agents to be used in combination (Gorwitz et al., 2006; Barton et al., 2006; Nathwani et al., 2008).

Surgical incision and drainage is the treatment of choice for cutaneous abscesses; adjunctive antimicrobial therapy is of little or no benefit in most of these cases (Moran et al., 2006; Fridkin et al., 2005; Llera and Levy, 1985; Lee et al., 2004). Antibiotic therapy after drainage of CA-MRSA abscesses is not routinely recommended unless the patient has severe or extensive disease, has rapid progression in the presence of associated cellulitis, has symptoms of systemic illness, is very old or very young, has another illness or immune suppression (for example, type I diabetes, HIV infection or neoplastic disease), has an abscess in an area that is difficult to drain or has an abscess that is associated with septic phlebitis (Gorwitz et al., 2006).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Vancomycin is still the preferred drug for the treatment of serious MRSA infections. However, its effectiveness is limited by prolonged, persistent or recurrent bacteraemia during therapy (Khatib et al., 2009; Hawkins et al., 2007), high rates of microbiological and clinical failures (Dombrowski and Winston, 2008), nephrotoxicity (Lodise et al., 2008) and the increasing prevalence of non-susceptible strains (Steimkraus et al., 2007; Wang et al., 2006). Randomized clinical trials of alternative agents, such as linezolid and daptomycin, show that they are comparable or, more precisely, neither inferior nor superior to standard therapy (Arbeit et al., 2004; Shorr et al., 2005; Wunderink et al., 2003; Weigelt et al., 2005; Kaplan et al., 2003; Fowler et al., 2006). Resistance and drug toxicity will remain concerns regardless of the choice of agent.

One or more new compounds that are currently being developed are likely to become available for the treatment of MRSA infections in the near future (Lentino et al., 2008; Pan et al., 2008). Telavancin, dalbavancin and oritavancin are vancomycin derivatives that rapidly kill S. aureus in a concentration-dependent manner in vitro. Whether more rapid killing will translate into an improved efficacy over vancomycin for more serious infections, such as endocarditis or bacteraemia, remains to be determined. Carbapenems and cephalosporins that bind PBP2a, the penicillin-binding protein that mediates methicillin resistance, with much higher affinity than the currently available β-lactams have been developed (Koga et al., 2005). Two cephalosporins, ceftobiprole and ceftaroline, were shown to be clinically effective for the treatment of MRSA skin and soft-tissue infections (Parish and Scheinfeld, 2008; Anderson and Gums, 2008). One drawback with these and the other anti-MRSA β-lactams under development is that they are broad-spectrum antibiotics and are therefore not narrowly targeted treatments of MRSA infection. Further studies are needed to define their eventual role in the therapy of MRSA infections. Moreover, the vancomycin derivatives and anti-MRSA β-lactams, which can only be administered intravenously, do not address the need for orally administered agents. Orally bioavailable oxazolidinones that are active against MRSA are in the early stages of development (Shaw et al., 2008).

Several non-traditional approaches to the treatment and prevention of MRSA infections have been or are still being investigated. These include lysostaphin (Dajcs et al., 2001), antimicrobial peptides (Lawton et al., 2007) and other natural products (for example, tea tree oil) (Stapleton et al., 2007), as well as anti-staphylococcal vaccines (Bubeck Wardenburg and Schneewind, 2008). There are considerable challenges to be faced in the development of these agents, including prohibitively expensive costs, the potential for patient hypersensitivity (caused by the repeated administration of protein products), the short half-lives that are associated with systemic administration and the short-lived or only partially protective immunity that is gained from vaccines, as was the case with an anti-capsular vaccine that proved to be ineffective (Shinefield et al., 2002). These approaches are years away from being available in the clinic, if they make it at all. Prudent

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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use of the agents that are now available is essential to avoid further erosion of the antimicrobial armamentarium.

Concluding Remarks

S. aureus is an extraordinarily adaptable pathogen with a proven ability to develop resistance. The steady erosion of the effectiveness of β-lactam antibiotics since their first use only 60 years ago is particularly worrying. As we have described, there have been four waves of resistance over the past 60 years. Although the details vary, the basic themes of each successive wave of antibiotic resistance are similar. Often occurring as a consequence of horizontal gene transfer, resistance is initially encountered in hospitals and health care institutions, where the selective pressures for resistance are greatest. Resistant strains are temporarily contained in hospitals but eventually, through a series of modifications and adjustments, they find their way into or arise from within the community to emerge as fully fit and virulent pathogens. Our understanding of the forces that direct the evolution of virulent and drug-resistant organisms is not perfect, but the overuse and misuse of antibiotics is clearly a contributing factor. The discovery and development of new antimicrobials, although necessary, is unlikely to solve the problem of drug resistance for long. New technologies that lead to improved and more rapid diagnostics, a better understanding of the pathogenesis of staphylococcal disease and non-antimicrobial approaches to the prevention and treatment of infection will also be needed to forestall the coming of the post-antibiotic era.

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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Acknowledgments

F.R.D. is supported by the Intramural Research Program of the National Institute of Allergy and Infectious Disease (NIAID) and the National Institutes of Health (NIH) and H.F.C. is supported by the NIH, NIAID grant number R01 AI070289.

Supplementary Information

TABLE A2-S1 Virulence Factors of Staphylococcus aureus

Target cell, host factor or response

Gene(s)

Protein or molecule

Putative function or effect on immune system

Factors that interfere with bacterial killing

Antimicrobial peptides

aur

Zinc metalloproteinase aureolysin, Aur

Degrades LL-37

 

dlt operon

Dlt operon, DltABCD

Promotes resistance to cationic antimicrobial peptides and group IIA phospholipase A2

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Target cell, host factor or response

Gene(s)

Protein or molecule

Putative function or effect on immune system

 

icaA, icaD, icaB, icaC, icaR

Polysaccharide intercellular adhesion, PIA

Resistance to cationic antimicrobial peptides

 

isdA, isdB

Iron-regulated surface determinants of S. aureus, IsdA and IsdB

Resistance to antimicrobial peptides, skin fatty acids, and neutrophil reactive oxygen species

 

mprF

Multiple peptide resistance factor, MprF

Promotes resistance to cationic antimicrobial peptides

 

sak

Staphylokinase

Inhibits host α-defensins

Oxygen-mediating bacterial killing

ahpC, ahpF

Alkylhydroperoxide reductase subunits C and F, AhpC and AhpF

Promotes resistance to ROS

 

crtM, crtN

Carotenoid pigment, staphyloxanthin (S. aureus golden pigment)

Promotes resistance to reactive oxygen species

 

isdA, isdB

Iron-regulated surface determinants of S. aureus, IsdA and IsdB

Resistance to neutrophil reactive oxygen species

 

sodA, sodM

Superoxide dismutase, SodA, SodM

Promotes resistance to reactive oxygen species

Hemolysins and anti-platelet factors

Erythrocytes

hla, hly

Alpha-hemolysin (α-hemolysin), Hla

Causes cell lysis (also affect epithelial cells, fibroblasts, and monocytes)

 

hld

Delta-hemolysin, Hld

Causes cell lysis

 

hlgA, hlgB, hlgC

Gamma-hemolysin subunits A, B, and C; HlgA, HlgB, HlgC; two-component leukocidin

Causes cell lysis

Platelets

clfA

Clumping factor A ClfA

Causes platelet activation

 

fnbA, fnbB

Fibronectin-binding proteins A and B, FnbA and FnbB

Causes platelet activation

 

katA

Catalase, KatA

Detoxifies hydrogen peroxide

 

sodA, sodM

Superoxide dismutase, SodA, SodM

Promotes resistance to reactive oxygen species

Leucocidins and anti-phagocytic factors

Polymorphonuclear leukocytes

cap5 or cap8 genes

Capsular polysaccharide

Inhibits phagocytosis

 

clfA

Clumping factor A, ClfA

Inhibits phagocytosis

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Target cell, host factor or response

Gene(s)

Protein or molecule

Putative function or effect on immune system

 

eap

Extracellular adherence protein, Eap

Inhibits leukocyte adhesion

 

hlgA, hlgB, hlgC

Gamma-hemolysin subunits A, B, and C; HlgA, HlgB; HlgC; two-component leukocidin

Causes cell lysis

 

lukD, lukE

Leukocidin D and E; LukD and LukE; two-component leukocidins

Causes leukocyte lysis

 

lukS-PV, lukF-PV

Leukocidin S-PV and F-PV subunits; two-component leukocidin, PVL

Causes leukocyte lysis

 

psm

Phenol-soluble modulin-like peptides, PSMs

Cause leukocyte lysis

 

sbi

IgG-binding protein, Sbi

Sequesters host IgG

 

scn

Staphylococcal inhibitor of complement, SCIN

Inhibits complement

 

ssl5

Staphylococcal superantigen-like 5, SSL5

Binds P-selectin glycoprotein ligand-1 and inhibits neutrophil rolling

Chemotaxis

chp

Chemotaxis inhibitory protein of S. aureus, CHIPS

Inhibits chemotaxis

 

ecb

Extracellular complement-binding protein, Ecb

Inhibits C5a generation

 

efb

Extracellular fibrinogen-binding protein, Efb

Inhibits C5a generation

 

sbi

IgG-binding protein, Sbi

Sequesters host IgG

 

scn

Staphylococcal inhibitor of complement, SCIN

Inhibits complement

 

ssl7

Staphylococcal superantigen-like 7, SSL7

Binds to C5a and IgA

Superantigens

T-cells

sea, seb, secn, sed, see, seg, she, sei, sej, sek, sel, sep

Staphylococcal enterotoxins; SEA, SEB, SECn, SED, SEE, SEG, SEH, SEI, SEJ, SEK, SEL, and SEP

Activate T-cells (superantigen)

 

tst

Toxic shock syndrome toxin-1, TSST-1

Activate T-cells (superantigen)

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

A3
SUBLETHAL ANTIBIOTIC TREATMENT LEADS TO MULTIDRUG RESISTANCE VIA RADICAL-INDUCED MUTAGENESIS7

Michael A. Kohanski,8,9,10,11,12 Mark A. DePristo,9,10,11,13 and James J. Collins8,9,10,11,12,14,*

Summary

Antibiotic resistance arises through mechanisms such as selection of naturally occurring resistant mutants and horizontal gene transfer. Recently, oxidative stress has been implicated as one of the mechanisms whereby bactericidal antibiotics kill bacteria. Here, we show that sublethal levels of bactericidal antibiotics induce mutagenesis, resulting in heterogeneous increases in the minimum inhibitory concentration for a range of antibiotics, irrespective of the drug target. This increase in mutagenesis correlates with an increase in ROS and is prevented by the ROS scavenger thiourea and by anaerobic conditions, indicating that sublethal concentrations of antibiotics induce mutagenesis by stimulating the production of ROS. We demonstrate that these effects can lead to mutant strains that are sensitive to the applied antibiotic but resistant to other antibiotics. This work establishes a radical-based molecular mechanism whereby sublethal levels of antibiotics can lead to multidrug resistance, which has important implications for the widespread use and misuse of antibiotics.

Introduction

There are a number of mechanisms whereby bacteria can develop antibiotic resistance (Dwyer et al., 2009; Hegreness et al., 2008; Livermore, 2003; McKenzie and Rosenberg, 2001), including horizontal transfer of resistance genes (Davies, 1994), drug-specific selection of naturally occurring resistant

7

Reprinted from Molecular Cell 37(3), Kohanski, M. A., M. A. DePristo, and J. J. Collins, Sublethal antibiotic treatment leads to multidrug resistance via radical-induced mutagenesis, pages 311-320, with permission from Elsevier. Copyright (2010).

8

Howard Hughes Medical Institute.

9

Department of Biomedical Engineering.

10

Center for BioDynamics.

11

Center for Advanced Biotechnology Boston University, Boston, MA 02215, USA.

12

Boston University School of Medicine, Boston, MA 02118, USA.

13

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.

14

Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.

*

Correspondence: jcollins@bu.edu.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

variants within a population, and increased mutagenesis in hypermutator strains (Andersson, 2003; Chopra et al., 2003). Quinolones, which are DNA-damaging antibiotics, can stimulate the emergence of drug resistance via SOS-independent recombination (López et al., 2007) and through the induction of RecA-mediated processes, including homologous recombination (Drlica and Zhao, 1997) and SOS-regulated error-prone polymerases (Cirz et al., 2005). β-lactams can also induce the SOS response via RecA (Kohanski et al., 2007) and the DpiAB two-component system (Miller et al., 2004), and these drugs have been shown to induce DinB in an SOS-independent fashion, resulting in increased frameshift mutations (Pérez-Capilla et al., 2005).

Antibiotic treatment can also result in multidrug resistance (Cohen et al., 1989), which has been associated with mutations in multidrug efflux pumps, such as AcrAB (Ma et al., 1993). These drug efflux pumps can be regulated by a number of transcription factors, including the superoxide-responsive SoxRS system (Greenberg et al., 1990). In addition, there is evidence that low level antibiotic treatment can lead to mutations that cause resistance (Girgis et al., 2009); however, the mechanisms underlying this effect are not well understood.

Bactericidal antibiotics, including β-lactams, quinolones, and aminoglycosides, can stimulate bacteria to produce reactive oxygen species (ROS) (Dwyer et al., 2007; Kohanski et al., 2007, 2008), which are highly deleterious molecules that can interfere with the normal functions of oxygen-respiring organisms (Brumaghim et al., 2003; Fridovich, 1978; Imlay, 2006). Certain ROS, such as hydroxyl radicals, can directly damage DNA and lead to an accumulation of mutations (Demple and Harrison, 1994; Friedberg et al., 2006; Imlay et al., 1988). Oxidative DNA damage also activates the error-prone SOS response (Carlsson and Carpenter, 1980; Imlay and Linn, 1986, 1987) and error-correcting repair systems such as the “GO” repair system (Michaels and Miller, 1992; Miller, 1996). In this study, we hypothesized that ROS formation due to treatment with low levels of bactericidal antibiotics leads to an increase in mutation rates, which can result in the emergence of multidrug resistance. We thus consider a possible molecular mechanism whereby bactericidal antibiotics act as active, reactive mutagens.

Results

To test the above hypothesis, we examined mutation rates in E. coli strain MG1655 following treatment with low levels of the bactericidal antibiotics norfloxacin (quinolone), ampicillin (β-lactam), and kanamycin (aminoglycoside), respectively. Mutation rates were determined by plating aliquots of treated cultures onto rifampicin plates, counting rifampicin-resistant colonies, and using the MSS maximum likelihood method (Rosche and Foster, 2000) to estimate the number of mutation events per culture (see Experimental Procedures for additional details). The mutation rate for untreated wild-type E. coli was approximately 1.5 × 10−8 mutations/cell/generation.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Treatment with 1 μg/ml ampicillin, 3 μg/ml kanamycin, 15 ng/ml norfloxacin, or 50 ng/ml norfloxacin resulted in significant increases in the mutation rate relative to an untreated control (Figure A3-1). Treatment with 1 μg/ml kanamycin resulted in a modest increase in mutation rate (Figure A3-1). The largest increases in mutation rate were seen following treatment with ampicillin or 50 ng/ml norfloxacin (Figure A3-1A). These changes were on par with the increase in mutation rate observed following treatment with 1mM hydrogen peroxide (Figure A3-1A), a concentration of hydrogen peroxide known to induce hydroxyl radical formation via Fenton chemistry (Imlay et al., 1988). To determine if there is a correlation between these changes in mutation rate and ROS formation, we examined radical levels using the radical-sensitive dye 3′-(p-hydroxyphenyl) fluorescein (HPF) (Setsukinai et al., 2003) (see Experimental Procedures for more details). We found a significant correlation (R2 = 0.8455) between the fold change in mutation rate and peak HPF signal for the treatments described above (Figure A3-1B).

The strong correlation between ROS formation and fold change in mutation rate following treatment with bactericidal antibiotics suggests that ROS actively contribute to bactericidal drug-induced mutagenesis. To test if this is indeed the case, we added 100 mM thiourea to wild-type E. coli treated with antibiotics or hydrogen peroxide at the concentrations noted above (Figure A3-1C). Thiourea is a potent hydroxyl radical scavenger that mitigates the effects of hydroxyl radical damage in both prokaryotes and eukaryotes (Novogrodsky et al., 1982; Repine et al., 1981; Touati et al., 1995). We have previously shown that thiourea reduces hydroxyl radical formation and cell killing following treatment with bactericidal antibiotics (Kohanski et al., 2007).

The addition of thiourea significantly reduced the mutation rate to near untreated levels following the addition of 1 mM hydrogen peroxide, norfloxacin, or ampicillin (Figure A3-1). Interestingly, we were unable to detect any rifampicin-resistant colonies after plating up to 109 cells following treatment with both 3 μg/ml kanamycin and thiourea (Figure A3-1C). However, we were able to detect rifampicin-resistant colonies after scaling up the system to 1 L flasks and plating up to 1010 cells following treatment with both 3 μg/ml kanamycin and thiourea (data not shown). These results suggest a role for kanamycin-mediated interference with ribosome function and translation, in the absence of oxidative stress, on significantly lowering mutation rate.

To further demonstrate that antibiotic-mediated ROS formation has a mutagenic component, we examined mutation rates under anaerobic growth conditions (see Experimental Procedures for additional details) following treatment of wild-type E. coli with antibiotics or hydrogen peroxide as described above (Figure A3-1D). We observed mutation rates near untreated levels for all antibiotic treatments tested (Figure A3-1D). Treatment with 1 mM hydrogen peroxide, which results in direct addition of an oxidant, led to an increase in mutation rate relative to the no drug control under anaerobic growth conditions (Figure A3-1D), but

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A3-1 Low levels of bactericidal antibiotics increase mutation rate due to reactive oxygen species formation. (A) Fold change in mutation rate (mean ±95% confidence interval [CI]) relative to an untreated control (no drug) for wild-type E. coli (MG1655) following an overnight treatment with 1 μg/ml ampicillin, 1 μg/ml kanamycin, 3 μg/ml kanamycin, 15 ng/ml norfloxacin, 50 ng/ml norfloxacin, or 1 mM hydrogen peroxide (H2O2). (B) Correlation between oxidative stress levels (HPF fluorescence) and fold change in mutation rate for wild-type E. coli for the treatments described in (A). (C and D) Fold change in mutation rate (mean ±95% CI) relative to an untreated control (no drug) for wild-type E. coli following an overnight treatment with 100 mM thiourea and no drug, 1 μg/ml ampicillin, 1 μg/ml kanamycin, 3 μg/ml kanamycin, 15 ng/ml norfloxacin, 50 ng/ml norfloxacin, or 1 mM hydrogen peroxide (H2O2) under aerobic growth conditions with 100 mM thiourea (C) or anaerobic growth conditions (D). See also Figure A3-S2.

FIGURE A3-1 Low levels of bactericidal antibiotics increase mutation rate due to reactive oxygen species formation. (A) Fold change in mutation rate (mean ±95% confidence interval [CI]) relative to an untreated control (no drug) for wild-type E. coli (MG1655) following an overnight treatment with 1 μg/ml ampicillin, 1 μg/ml kanamycin, 3 μg/ml kanamycin, 15 ng/ml norfloxacin, 50 ng/ml norfloxacin, or 1 mM hydrogen peroxide (H2O2). (B) Correlation between oxidative stress levels (HPF fluorescence) and fold change in mutation rate for wild-type E. coli for the treatments described in (A). (C and D) Fold change in mutation rate (mean ±95% CI) relative to an untreated control (no drug) for wild-type E. coli following an overnight treatment with 100 mM thiourea and no drug, 1 μg/ml ampicillin, 1 μg/ml kanamycin, 3 μg/ml kanamycin, 15 ng/ml norfloxacin, 50 ng/ml norfloxacin, or 1 mM hydrogen peroxide (H2O2) under aerobic growth conditions with 100 mM thiourea (C) or anaerobic growth conditions (D). See also Figure A3-S2.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

this increase was considerably smaller than that exhibited under aerobic growth conditions (Figure A3-1A).

Antibiotic-resistant strains can arise via drug-mediated selection of preexisting antibiotic-resistant variants that occur naturally within a population (Livermore, 2003). Antibiotic-induced oxidative stress may be an additional mechanism that allows for the accumulation of mutations that increase resistance to drugs, irrespective of the drug target of the applied antibiotic. To test this, we measured changes in the minimum inhibitory concentration (MIC) of wild-type E. coli over a period of 5 days of selective growth for the following antibiotics: norfloxacin, kanamycin, ampicillin, tetracycline, and chloramphenicol. During the growth period, the cultures were exposed to no drug, norfloxacin, ampicillin, or kanamycin (see Experimental Procedures for more details). In all cases, growth in the absence of antibiotics did not change the MIC for any of the drugs tested (data not shown).

Treatment with 25 ng/ml norfloxacin led to an increase in the MIC for norfloxacin and kanamycin (Figure A3-S1A). The observed increases in MIC following treatment with norfloxacin were concentration dependent (see Supplemental Information for more details). Treatment of wild-type E. coli with 3 μg/ml kanamycin led to an increase in the MIC for kanamycin and minimal increases in the MIC for norfloxacin and ampicillin, respectively (Figure A3-S1C). The MIC for tetracycline and chloramphenicol did not change (Figure A3-S1C), indicating that kanamycin treatment may not lead to mutants resistant to other classes of ribosome inhibitors.

Treatment of wild-type E. coli with 1 μg/ml ampicillin for 5 days led to an increase in the MIC to different levels for ampicillin, norfloxacin, kanamycin, tetracycline, and chloramphenicol (Figure A3-2A). These results show that treatment with a β-lactam can stimulate formation of mutants that are potentially resistant to a wide range of antibiotics. Cultures that had been grown for 5 days in the presence of low levels of ampicillin were shifted to a drug-free environment and grown without any ampicillin for 2 additional days. The MICs, which were increased after 5 days of ampicillin treatment (Figure A3-2A), remained elevated and did not change significantly following 2 days of growth in the absence of ampicillin (Figure A3-S1D). These findings demonstrate that the observed increases in MIC are stable and not due to a transient adaptation to growth in the presence of ampicillin.

To determine if the observed increases in MIC were related to antibiotic-mediated ROS formation, we measured the MIC for ampicillin, norfloxacin, kanamycin, tetracycline, and chloramphenicol, respectively, following treatment with no drug or 1 μg/ml ampicillin under anaerobic growth conditions. Untreated anaerobic growth had no effect on MIC relative to untreated aerobic growth (data not shown). Following treatment with 1 μg/ml ampicillin under anaerobic conditions, we observed almost no increase in MIC for ampicillin, kanamycin, tetracycline, or chloramphenicol (Figure A3-2B). The MIC for norfloxacin exhib-

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A3-2 Low levels of bactericidal antibiotics can lead to broad-spectrum increases in MIC due to ROS-mediated mutagenesis. (A and B) Fold change in MIC relative to an aerobic no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline, and chloramphenicol, following 5 days of growth in the presence of 1 μg/ml ampicillin under aerobic (A) or anaerobic (B) growth conditions. See also Figure A3-S1.

FIGURE A3-2 Low levels of bactericidal antibiotics can lead to broad-spectrum increases in MIC due to ROS-mediated mutagenesis. (A and B) Fold change in MIC relative to an aerobic no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline, and chloramphenicol, following 5 days of growth in the presence of 1 μg/ml ampicillin under aerobic (A) or anaerobic (B) growth conditions. See also Figure A3-S1.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

ited a small increase by day 5 (Figure A3-2B); however, this change in MIC was much smaller than the increase in MIC for norfloxacin following ampicillin treatment under aerobic growth conditions (Figure A3-2A). These results suggest that ROS formation due to treatment with low levels of bactericidal antibiotics can lead to mutagenesis and the emergence of bacteria resistant to a wide range of antibiotics.

Drug resistance may not always be uniform throughout a population. Some cells within a population may remain susceptible to the antibiotic, whereas other cells display varying degrees of drug resistance (de Lencastre et al., 1993), a phenomenon referred to as heteroresistance. Antibiotic-stimulated, ROS mediated mutagenesis could be a mechanism that stimulates the formation of a range of mutations that result in varying MICs within a population of cells. We sought to determine if the observed increases in population-level MIC for ampicillin following 5 days of treatment with 1 μg/ml ampicillin (Figure A3-2A) exhibited heterogeneity in MIC at the single-colony level.

We isolated individual colonies following ampicillin treatment and measured the MIC of each clone to ampicillin. We found that these isolates exhibited a range of resistance to ampicillin (>2.5–12.5 μg/ml), with some isolates remaining completely susceptible (≤2.5 μg/ml) to treatment with this drug (Figure A3-3A). We also found that the MICs for these isolates to norfloxacin ranged from <100 ng/ml (completely susceptible) to ≥1000 ng/ml (Figure A3-3B). Although levels of resistance from clinical isolates are typically quite high (with MICs in the range of 10–1000 μg/ml for norfloxacin [Becnel Boyd et al., 2009]), the upper ranges of the MICs for ampicillin or norfloxacin observed here (Figure A3-3) are near the peak serum concentrations for these drugs (Bryskier, 2005), indicating that these MICs might be near the limit for the amount of drug a human can tolerate. These data show that heterogeneous increases in MIC to ampicillin arise in E. coli following treatment with low levels of ampicillin, and treatment with one drug class can lead to heterogeneous increases in MIC against other classes of antibiotics.

Resistance to multiple antibiotics has been linked to mutations in drug-efflux systems such as the AcrAB multidrug (MDR) efflux pump (George and Levy, 1983; Ma et al., 1993) as well as mutations in transcription factors controlling these systems, such as MarA (Alekshun and Levy, 1997), Rob (Ariza et al., 1995), and SoxS (Greenberg et al., 1990). Our results suggest that ROS-mediated DNA damage induced by low levels of bactericidal antibiotics can result in mutations in a wider range of genes, potentially in some unrelated to the applied antibiotic and drug efflux systems. This implies that treatment with ampicillin, for example, may generate mutants that are not ampicillin resistant but are resistant to other antibiotics.

To determine if these types of resistant strains arise, we examined multidrug resistance following 5 days of treatment with 1 μg/ml ampicillin or no treatment. Mutants from ampicillin treated or untreated cultures were selected on plates

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A3-3 Ampicillin treatment of E. coli results in heterogeneous increases in MIC for ampicillin and norfloxacin. (A and B) Shown are the distributions of ampicillin (A) or norfloxacin (B) MICs for 44 ampicillin-treated isolates. The maximum growth-inhibitory concentration tested for norfloxacin was 1000 ng/ml, and the MICs for these isolates may be ≥1000 ng/ml.

FIGURE A3-3 Ampicillin treatment of E. coli results in heterogeneous increases in MIC for ampicillin and norfloxacin. (A and B) Shown are the distributions of ampicillin (A) or norfloxacin (B) MICs for 44 ampicillin-treated isolates. The maximum growth-inhibitory concentration tested for norfloxacin was 1000 ng/ml, and the MICs for these isolates may be ≥1000 ng/ml.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

containing norfloxacin, ampicillin, kanamycin, tetracycline, and chloramphenicol, respectively. From this primary selection, we determined cross-resistance to the other four antibiotics via replica plating (see Experimental Procedures for additional details). We found substantially more primary resistant colonies and higher rates of cross-resistance following ampicillin treatment as compared to no treatment (Table A3-1). Ampicillin-selected mutants displayed a range of cross-resistance to the other classes of antibiotics and showed a strong correlation (89% cross-resistance) with norfloxacin resistance (Table A3-1). We also found that ampicillin-treated cells selected originally on the basis of norfloxacin or kanamycin resistance were only 75% and 63% cross-resistant to ampicillin, respectively (Table A3-1). Interestingly, primary resistance selection with the static drugs tetracycline and chloramphenicol yielded isolates that were always

TABLE A3-1 Cross-Resistance Following Ampicillin Treatment and Primary Resistance Selection with Five Different Classes of Antibiotics

E. coli Control Strain

Percent Cross-Resistant Following Ampicillin Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Tetracycline

Chloramphenicol

Primary Selection

 

 

 

 

 

Norfloxacin

100% (40/40)

75% (30/40)

25% (10/40)

23% (9/40)

23% (9/40)

Ampicillin

89% (77/87)

100% (87/87)

20% (17/87)

54% (47/87)

21% (18/87)

Kanamycin

20% (17/83)

63% (52/83)

100% (83/83)

7% (6/83)

0% (0/83)

Tetracycline

79% (63/80)

100% (80/80)

14% (11/80)

100% (80/80)

78% (62/80)

Chloramphenicol

87% (67/77)

100% (77/77)

35% (27/77)

100% (77/77)

100% (77/77)

 

Percent Cross-Resistant Following No-Drug Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Tetracycline

Chloramphenicol

Primary Selection

 

 

 

 

 

Norfloxacin

100% (10/10)

0% (0/10)

0% (0/10)

0% (0/10)

0% (0/10)

Ampicillin

0% (0/10)

100% (10/10)

0% (0/10)

0% (0/10)

0% (0/10)

Kanamycin

0% (0/15)

0% (0/15)

100% (15/15)

0% (0/15)

0% (0/15)

Tetracycline

100% (1/1)

0% (0/1)

0% (0/1)

100% (1/1)

0% (0/1)

Chloramphenicol

100% (1/1)

0% (0/1)

0% (0/1)

0% (0/1)

100% (1/1)

Wild-type E. coli were treated with 1 mg/ml ampicillin or no drug for 5 days. These ampicillin-treated or untreated cells were spread on plates containing norfloxacin, ampicillin, kanamycin, tetracycline, or chloramphenicol, and mutants resistant to the individual drugs were isolated. Resistance to the other four classes of antibiotics was determined by replica plating of the primary-selected strains onto plates containing the respective antibiotic. Shown is percent resistance (resistant colonies/total primary resistant colonies). Note: Double the volume of no-drug control cells were plated for primary resistance selection for E. coli as compared to the ampicillin-treated cells.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

(100%) cross-resistant to ampicillin (Table A3-1); this effect deserves further study. Also of note, ampicillin-treated, kanamycin-resistant strains were found to have very low cross-resistance to tetracycline (7%) and no cross-resistance with chloramphenicol (Table A3-1). This is consistent with previous work showing a lack of cross-resistance to tetracycline or chloramphenicol following selective treatment with aminoglycosides (Grassi, 1979). While the majority of these multidrug cross-resistant strains exhibit resistance against the treatment drug, ampicillin, our results demonstrate that treatment with ampicillin can also generate mutants that are not resistant to ampicillin yet are resistant to other classes of antibiotics.

We sought to determine if some of the ampicillin-treated, cross-resistant isolates had acquired mutations in specific antibiotic targets or in genes making up the common oxidative damage cell death pathway induced by bactericidal antibiotics (Kohanski et al., 2007, 2008), or if the observed cross-resistance (Table A3-1) was solely a function of altered drug efflux. We examined six norfloxacin-resistant isolates, six kanamycin-resistant isolates, and the untreated control strain. We sequenced the following genes where mutations could potentially lead to an increase in drug resistance: gyrA, gyrB, rpsL, ampC, icdA, arcA, cpxA, sdhB, iscR, tolC, marRA and its promoter region, and acrA and its promoter region. gyrA and gyrB code for the subunits of DNA Gyrase; the known target of quinolones, rpsL, encodes a component of the 30S subunit of the ribosome and has been associated with aminoglycoside resistance; ampC has been associated with ampicillin resistance; icdA, arcA, cpxA, sdhB, and iscR are genes involved in the common mechanism of cell death; and tolC, marRA and its promoter region, and acrA and its promoter region are involved in multidrug efflux.

We found that 3 of the 6 norfloxacin-resistant isolates contained point mutations in gyrA that resulted in a substitution of glycine for aspartic acid at amino acid 82 in one isolate and a substitution of tyrosine for aspartic acid at amino acid 87 in two other isolates (Figure A3-4A). We also found that 1 of these 6 norfloxacin-resistant isolates, which did not have a mutation in gyrA, had a point mutation resulting in the conversion of serine to phenylalanine at residue 464 of GyrB (Figure A3-4B). Interestingly, the point mutations we found in gyrA and gyrB are all in the quinolone resistance-determining regions of GyrA and GyrB, respectively, and these mutations have been observed in clinical isolates of Bacteroides fragilis (Oh et al., 2001), Salmonella enterica (Weill et al., 2006), and Pseudomonas aeruginosa (Mouneimné et al., 1999).

As noted above, mutations in rpsL have been associated with aminoglycoside resistance. We found that 2 of the 6 kanamycin-resistant isolates had point mutations in rpsL. These mutations led to a frameshift and truncated form of RpsL in both isolates (Figure A3-4D). It is possible that these mutations contribute to kanamycin resistance in these isolates.

Among the ampicillin-treated, drug-resistant mutants, we did not find any mutations in ampC (data not shown), a gene associated with ampicillin resistance.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A3-4 Ampicillin treatment leads to the formation of norfloxacin-resistant isolates with mutations in gyrA, gyrB, or the acrAB promoter (PacrAB) and kanamycin-resistant isolates with mutations in rpsL or arcA. (A and B) Isolates with point mutation resulting in a D82G or D87Y substitution in GyrA (A) or a S464F substitution in GyrB (B). (C) T-to-A DNA base pair mutation in the AcrR/EnvR binding site of the -35 region of PacrAB. PacrAB is partially annotated to show the -10 and -35 regions (bold), the transcription start site (capitalized A), and the AcrR/EnvR binding site (underlined). (D) Isolates with insertion between base pair 92 and 93 (K58) and between base pair 78 and 79 (K62) resulting in truncation of RpsL. (E) Isolate with a single base pair insertion between base pair 211 and 212 resulting in a truncated ArcA protein missing the majority of the helix-turn-helix (HTH) DNA binding domain. See also Table A3-S1.

FIGURE A3-4 Ampicillin treatment leads to the formation of norfloxacin-resistant isolates with mutations in gyrA, gyrB, or the acrAB promoter (PacrAB) and kanamycin-resistant isolates with mutations in rpsL or arcA. (A and B) Isolates with point mutation resulting in a D82G or D87Y substitution in GyrA (A) or a S464F substitution in GyrB (B). (C) T-to-A DNA base pair mutation in the AcrR/EnvR binding site of the -35 region of PacrAB. PacrAB is partially annotated to show the -10 and -35 regions (bold), the transcription start site (capitalized A), and the AcrR/EnvR binding site (underlined). (D) Isolates with insertion between base pair 92 and 93 (K58) and between base pair 78 and 79 (K62) resulting in truncation of RpsL. (E) Isolate with a single base pair insertion between base pair 211 and 212 resulting in a truncated ArcA protein missing the majority of the helix-turn-helix (HTH) DNA binding domain. See also Table A3-S1.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

We also did not find any mutations in icdA, cpxA, sdhB, or iscR (data not shown). Interestingly, we did find a single insertion mutation in arcA in one of the drug-resistant isolates. ArcA is a two-component system transcription factor containing a sensor domain and a DNA-binding domain, and the mutation we found results in a truncated ArcA protein that is missing the DNA-binding element of the protein (Figure A3-4E). We have previously shown that two-component systems are important elements in the common mechanism of cell death, and a knockout of arcA is more tolerant to treatment with ampicillin and kanamycin compared to norfloxacin (Kohanski et al., 2008). This isolate is resistant to ampicillin and kanamycin, but not to norfloxacin. This result suggests that mutations leading to low-level antibiotic resistance can occur in genes that are involved in the common mechanism of cell death.

We did not find any mutations in tolC, marRA, the marRA promoter, or acrA (data not shown); however, we did find a T-to-A conversion in the promoter upstream of acrA (Figure A3-4C) in one of the norfloxacin-resistant isolates that also had a mutation in gyrA (Figure A3-4A). This promoter mutation occurs within the annotated -35 site of the promoter and the binding site for the repressor transcription factors AcrR and EnvR (Keseler et al., 2005; Miller et al., 2002). The observed mutations could reduce the ability of these repressors to bind to the acrAB promoter which would result in increased pump expression and drug resistance. These sequencing results demonstrate that ampicillin treatment can lead to the formation of norfloxacin-resistant strains with mutations in DNA Gyrase and/or mutations that can affect drug efflux pump activity, which likely contribute to the emergence of multidrug resistance.

To demonstrate that sublethal levels of bactericidal antibiotics can lead to an increase in multidrug cross-resistance in Gram-positive as well as Gram-negative bacteria, we also examined multidrug cross-resistance in Staphylococcus aureus following treatment with low levels of ampicillin (35 ng/ml) for 5 days. Previously, we demonstrated antibiotic-mediated ROS formation in S. aureus (Kohanski et al., 2007). In the present study, we found substantially more primary resistant S. aureus colonies and higher rates of cross-resistance following ampicillin treatment as compared to no treatment (Table A3-2). Interestingly, we were unable to enrich for tetracycline- or chloramphenicol-resistant S. aureus isolates following treatment with low-level ampicillin as compared with the no-drug treatment. This may be due to the lower level of ROS formation we have observed with S. aureus (Kohanski et al., 2007).

To demonstrate that these effects are not limited to lab strains, we considered a clinical isolate of E. coli from a patient with diarrhea (NCDC C771). We examined multidrug cross-resistance in the clinical isolate following treatment with 1 μg/ml ampicillin (see Experimental Procedures for more details). As with the wild-type strains, we found substantially more primary resistant colonies and higher rates of cross-resistance in the clinical isolates following ampicillin treatment as compared to no treatment. We also found that ampicillin-treated cells

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

TABLE A3-2 Cross-Resistance for S. aureus Following Ampicillin Treatment and Primary Resistance Selection with Five Different Classes of Antibiotics

S. aureus

Percent Cross-Resistant Following Ampicillin Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Tetracycline

Chloramphenicol

Primary Selection

 

 

 

 

 

Norfloxacin

100% (59/59)

64% (38/59)

56% (33/59)

36% (21/59)

19% (11/59)

Ampicillin

41% (29/71)

100% (71/71)

18% (13/71)

25% (13/71)

14% (10/71)

Kanamycin

13% (9/68)

60% (41/68)

100% (68/68)

18% (12/68)

15% (10/68)

Tetracycline

0% (0/2)

100% (2/2)

0% (0/2)

100% (2/2)

0% (0/2)

Chloramphenicol

0/0

0/0

0/0

0/0

0/0

 

Percent Cross-Resistant Following No-Drug Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Tetracycline

Chloramphenicol

Primary Selection

 

 

 

 

 

Norfloxacin

100% (19/19)

5% (1/19)

26% (5/19)

0% (0/19)

5% (1/19)

Ampicillin

0% (0/13)

100% (13/13)

0% (0/13)

8% (1/13)

0% (0/13)

Kanamycin

2.6% (1/38)

2.6% (1/38)

100% (38/38)

0% (0/38)

8% (3/38)

Tetracycline

0/0

0/0

0/0

0/0

0/0

Chloramphenicol

0/0

0/0

0/0

0/0

0/0

Wild-type S. aureus were treated with 35 ng/ml ampicillin or no drug for 5 days. These ampicillin-treated or untreated cells were spread on plates containing norfloxacin, ampicillin, kanamycin, tetracycline, or chloramphenicol, and mutants resistant to the individual drugs were isolated. Resistance to the other four classes of antibiotics was determined by replica plating of the primary selected strains onto plates containing the respective antibiotic. Shown is percent resistance (resistant colonies/total primary resistant colonies).

selected originally on the basis of norfloxacin or kanamycin resistance were only 11.5% and 21.5% cross-resistant to ampicillin, respectively (Table A3-3). This further affirms that treatment with ampicillin can generate mutants that are not resistant to ampicillin yet are resistant to other classes of antibiotics.

Discussion

Here, we establish a radical-based molecular mechanism whereby sublethal levels of antibiotics can lead to multidrug resistance. This occurs via bactericidal antibiotic-mediated radical formation that results in the formation of mutations, some of which confer antibiotic resistance. Low-level resistance likely provides a first step toward clinically significant resistance (Goldstein, 2007), and the mechanism we propose and validate here establishes an antibiotic-stimulated mutagenic effect that likely works in conjunction with SOS-induced mutagenesis in the emergence of mutations that confer drug resistance.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

TABLE A3-3 Cross-Resistance for E. coli Clinical Isolate NCDC C771 Following Ampicillin Treatment and Primary Resistance Selection with Four Different Classes of Antibiotics

E. coli Clinical Isolate

Percent Cross-Resistant Following Ampicillin Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Chloramphenicol

Primary Selection

 

 

 

 

Norfloxacin

100% (78/78)

11.5% (9/78)

1.3% (1/78)

10.3% (8/78)

Ampicillin

13.2% (5/38)

100% (38/38)

2.6% (1/38)

23.9% (9/38)

Kanamycin

15.2% (12/79)

21.5% (17/79)

100% (79/79)

7.6% (6/79)

Chloramphenicol

41.4% (29/70)

45.7% (32/70)

22.9% (16/70)

100% (70/70)

 

Percent Cross-Resistant Following No-Drug Treatment

 

Norfloxacin

Ampicillin

Kanamycin

Chloramphenicol

Primary Selection

 

 

 

 

Norfloxacin

0/0

0/0

0/0

0/0

Ampicillin

0/0

0/0

0/0

0/0

Kanamycin

2.8% (1/36)

11.1% (4/36)

100% (36/36)

2.8% (1/36)

Chloramphenicol

0/3

0/3

0/3

100% (3/3)

E. coli strain NCDC C771 was treated with 1 μg/ml ampicillin or no drug for 5 days. These ampicillin-treated or untreated cells were spread on plates containing norfloxacin, ampicillin, kanamycin, or chloramphenicol, and mutants resistant to the individual drugs were isolated. Resistance to the other three classes of antibiotics was determined by replica plating of the primary-selected strains onto plates containing the respective antibiotic. Shown is percent resistance (resistant colonies/total primary resistant colonies). Tetracycline cross-resistance was not quantified for NCDC C771, as this strain is resistant to tetracycline (MIC > 35 μg/ml).

Clinical situations where bacteria are exposed to low levels of antibiotics can occur with incomplete treatment of an infection, noncompliance with antibiotic treatment (e.g., a missed pill), and reduced or limited drug accessibility to certain tissues (e.g., bone or cerebrospinal fluid [Bryskier, 2005]). It is possible that mutations arising via antibiotic-mediated oxidative stress could be maintained in the normal bacterial flora of the body and transferred to virulent bacteria via horizontal gene transfer, a mechanism that can be induced by DNA damage (Beaber et al., 2004). Novel therapeutics targeting ROS-forming systems or error-prone DNA damage repair systems may help reduce and contain the spread of new antibiotic-resistant bacteria.

Experimental Procedures

Strains, Media, and Antibiotics

All experiments were performed with wild-type E. coli strain MG1655 (ATCC 700926) in Luria-Bertani (LB) medium (Fisher Scientific; Waltham, MA). For all treatment conditions, we used 1 mM hydrogen peroxide (VWR;

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

West Chester, PA) and the following bactericidal antibiotics: norfloxacin (Sigma; St. Louis), ampicillin, and kanamycin (Fisher Scientific). Bactericidal antibiotics were used at concentrations of 15 ng/ml norfloxacin, 50 ng/ml norfloxacin, 1 μg/ml ampicillin, 1 μg/ml kanamycin, or 3 μg/ml kanamycin. Tetracycline (MP Biomedical; Solon, OH) and chloramphenicol (Fluka; St. Louis) were used for MIC assays, rifampicin (Sigma) for determination of antibiotic resistant rates, and thiourea (Fluka) for radical-quenching experiments. Anaerobic media was made by heating LB in 17 ml Bellco glass hungate tubes (FisherScientific) under anaerobic conditions in a Coy anaerobic chamber (Coy Laboratory Products Inc.; Grass Lake, MI) to drive out dissolved oxygen (Norris and Ribbons, 1969). Resazurin (10 mM) (Sigma), which turns clear in the absence of oxygen, was used as an indicator for anaerobic conditions. Multidrug resistance was also determined in wild-type S. aureus (ATCC 25923) and the E. coli clinical isolate NCDC C771 (ATCC 23985).

Determination of Mutation Rate

Mutation rates were examined following 24 hr of growth in the presence of a bactericidal antibiotic. Drug levels were chosen such that there was an observable effect on growth or survival within the first 6 hr after drug addition (Figure A3-S2), followed by “recovery” of the culture to near untreated colony density 24 hr after treatment. All treatment conditions exhibited recovery to near untreated colony density levels, with the exception of 50 ng/ml norfloxacin. This allowed us to compare mutation frequencies for cultures of similar densities following treatment with an antibiotic.

Mutation rates were determined using a rifampicin-based selection method (Giraud et al., 2001). Briefly, an overnight culture of E. coli was diluted 1:10,000 into 50 ml LB in a 250 ml baffled flask and grown for 3.5 hr at 37°C and 300 rpm. Cultures were grown at high shaking speeds and in baffled flasks to maximize aeration and ROS formation. The culture was diluted 1:3 into fresh LB containing no drug, an antibiotic, or hydrogen peroxide at the concentrations described above. For experiments with thiourea, thiourea in solid form was added to each diluted culture for a final concentration of 100 mM. Aliquots (1 ml; ten replicates) of these diluted cultures were grown in 14 ml tubes for 24 hr at 37°C and 300 rpm. Aliquots of each treatment were serially diluted and plated on LB-agar plates for colony forming unit per milliliter (cfu/ml) determination. Aliquots of each treatment were also plated on LB-agar plates containing 100 μg/ml rifampicin and grown for 48 hr at 37°C. Colonies were counted at 24 and 48 hr, and the colony count from the 48 hr time point was used to estimate mutation rates. For experiments in anaerobic conditions, cells were diluted 1:10,000 into 15 ml anaerobic LB in sealed hungate tubes to minimize exposure to oxygen. Antibiotic treatments, growth temperature, shaking speed, and sample collection were as described above for the aerobic growth conditions.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

The colony counts from the ten replicates were then used in the MSS maximum-likelihood method (Rosche and Foster, 2000; Sarkar et al., 1992) to estimate the number of mutational events per culture. The MSS maximum likelihood method is a recursive algorithm based on the Lea-Coulson function for solving the Luria-Delbruck distribution for a given number of mutational events (Sarkar et al., 1992); its utility has been demonstrated in vitro (Rosche and Foster, 2000). The mutation rate was determined by dividing the number of mutational events per culture by the total number of bacteria plated on the rifampicin plates (Rosche and Foster, 2000). Fold change in mutation rate was determined for all treatments and conditions relative to an untreated MG1655 control. Three biological replicates were run for each treatment condition, and the averages are shown in Figure A3-1.

ROS Detection Using HPF

To detect ROS formation, we used the fluorescent reporter dye HPF (Invitrogen; Carlsbad, CA) and flow cytometry as previously described (Kohanski et al., 2007). Average fluorescence was determined at 0 (baseline), 1, 3, and 6 hr (normalized to a no-dye control) following antibiotic treatment at the concentrations described above, and peak fluorescence levels were used to determine the change in mean fluorescence relative to baseline (Figure A3-1B).

Determination of MIC

For wild-type E. coli, MICs for norfloxacin, ampicillin, kanamycin, tetracycline, and chloramphenicol were measured over 5 days of treatment with no drug, 25 ng/ml norfloxacin, 50 ng/ml norfloxacin, 1 μg/ml ampicillin, or 3 μg/ml kanamycin. Briefly, an overnight culture of E. coli was diluted 1:10,000 into 50 ml LB in a 250 ml baffled flask and grown for 3.5 hr at 37°C and 300 rpm. The culture was diluted 1:3 into fresh LB containing no drug or antibiotics at the above concentrations. Aliquots (1 ml) of these diluted cultures were grown in 14 ml tubes for 24 hr at 37°C and 300 rpm. Each day thereafter for 5 days, in order to avoid mutations arising due to evolution during stationary phase (GASP mutants) (Zinser and Kolter, 2004), cells were diluted 1:1000 into 1 ml LB in a 14 ml tube containing the respective antibiotic and grown for 24 hr at 37°C and 300 rpm.

MICs were also measured for anaerobically grown E. coli over 5 days of treatment with no drug or 1 μg/ml ampicillin. Briefly, an overnight culture of E. coli was diluted 1:1000 into 15 ml anaerobic LB in sealed hungate tubes containing no drug or 1 μg/ml ampicillin. These cultures were grown in the sealed hungate tubes for 24 hr at 37°C and 300 rpm. Each day thereafter for 5 days, cells were diluted 1:1000 into 15 ml anaerobic LB in a sealed hungate tube containing the respective antibiotic and grown for 24 hr at 37°C and 300 rpm.

To determine the MIC on each day, an aliquot of cells from each treatment condition was diluted 1:10,000 into LB and dispensed into 96-well plates (100 μl

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

total volume per well) containing various concentrations (ten replicates per drug concentration) of norfloxacin, ampicillin, kanamycin, tetracycline, or chloramphenicol. Plates were incubated at 37°C and 300 rpm for 24 hr, after which time the optical density at 600 nm (OD600) was measured using a SPECTRAFluor Plus (Tecan; Männedorf, Switzerland). The median OD600 was calculated for each drug concentration, and the MIC was determined as the concentration that inhibited 90% of growth based on OD600. Fold change in MIC was determined by dividing the treated MIC on each day by its respective MIC from day 0.

Determination of MIC Variability and Multidrug Resistance

Wild-type E. coli were grown for 5 days in the presence of 1 μg/ml ampicillin or no drug (untreated) as described above. These long-term-treated cultures were diluted 1:1000 into 25 ml LB in 250 ml flasks and grown for 3 hr at 37°C and 300 rpm. Aliquots (1 ml) were plated onto LB-agar plates containing 300 ng/ml norfloxacin, 7.5 μg/ml ampicillin, 15 μg/ml kanamycin, 8 μg/ml tetracycline, and 25 μg/ml chloramphenicol, respectively, and grown for 24 hr at 37°C. Approximately 100 ampicillin-treated colonies from each primary drug selection were purified by streaking them onto LB-agar plates containing the same selective antibiotic. Double the volume of untreated control cells were plated for primary resistance selection as compared to the ampicillin-treated cells, and these untreated colonies were also purified as described above. Plates were placed at 37°C for 24 hr; these strains were then transferred via replica plating onto LB-agar plates containing norfloxacin, ampicillin, kanamycin, tetracycline, or chloramphenicol. Cross-resistance for each primary antibiotic selection following the 5 day ampicillin treatment or the no-drug treatment was determined after 24 hr of growth at 37°C by counting the colonies that displayed growth on the various drug-containing replicated plates.

The MIC of 44 of the above isolates and the MG1655 control strain were determined for ampicillin and norfloxacin, respectively. Overnight cultures of each strain were diluted 1:10,000 into 100 μl LB plus varying concentration of antibiotic (four replicates per strain per drug concentration) in 96-well plates. Plates were incubated at 37°C and 300 rpm for 24 hr, after which time the OD600 was measured using a SPECTRAFluor Plus (Tecan). The median OD600 was calculated for each drug concentration, and the MIC was determined as the concentration that inhibited 90% of growth based on OD600.

Wild-type S. aureus were grown for 5 days in the presence of 35 ng/ml ampicillin or no drug (untreated) as described above. E. coli clinical isolate NCDC C771 was grown for 5 days in the presence of 1 mg/ml ampicillin or no drug (untreated) as described above. These long-term-treated cultures were diluted 1:1000 into 25 ml LB in 250 ml flasks and grown for 3 hr at 37°C and 300 rpm. For S. aureus, 1 ml aliquots were plated onto LB-agar plates containing 3 μg/ml

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

norfloxacin, 7.5 μg/ml ampicillin, 15 μg/ml kanamycin, 8 μg/ml tetracycline, and 25 μg/ml chloramphenicol, respectively, and grown for 24 hr at 37°C. For NCDC C771, 1 ml aliquots were plated onto LB-agar plates containing 400 ng/ml norfloxacin, 8.5 μg/ml ampicillin, 20 μg/ml kanamycin, and 15 μg/ml chloramphenicol. Tetracycline cross-resistance was not quantified for NCDC C771, as this strain is resistant to tetracycline (MIC >35 μg/ml). Approximately 100 ampicillin-treated colonies from each primary drug selection were purified by streaking them onto LB-agar plates containing the same selective antibiotic. An equal volume of untreated S. aureus or the E. coli clinical isolate cells were plated for primary resistance selection as compared to the ampicillin-treated cells, and these untreated colonies were also purified as described above. The remainder of the cell growth and cross-resistance determination was performed as described above for wild-type E. coli.

Sequencing of Ampicillin-Treated, Norfloxacin-Resistant, or Kanamycin-Resistant Mutants

Six ampicillin-treated, norfloxacin-resistant isolates and six ampicillin-treated, kanamycin-resistant isolates from the cross-resistance experiment described above, as well as the untreated MG1655 control strain, were grown to a cell density of approximately 109 cfu/ml. Genomic DNA was extracted from each sample using a QIAGEN genomic DNA extraction kit according to the manufacturer’s instructions. Primers from IDT (Coralville, IA) (Table A3-S1) were utilized to PCR amplify, using Phusion DNA Polymerase (Finnzyme; Espoo, Finland), the regions surrounding gyrA, gyrB, tolC, acrA, marRA, ampC, rpsL, icdA, iscR, sdhB, arcA, and cpxR. These samples were sequenced by Agencourt Bioscience Corporation (Beverly, MA) using primers from IDT (Table A3-S1). Sequences were analyzed using Clone Manager 7 (Scientific & Educational Software; Cary, NC) and Sequence Scanner v1.0 (Applied Biosystems; Foster City, CA).

Supplemental Information

Supplemental Information includes Supplemental Results, Supplemental References, two figures, and one table and can be found with this article online at doi:10.1016/j.molcel.2010.01.003.

Acknowledgments

We thank D. Dwyer, B. Davies, and K. Allison for helpful discussions during the course of this work. We thank Q. Beg for help running the anaerobic chamber. This work was supported by the National Institutes of Health through

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

the NIH Director’s Pioneer Award Program, grant number DP1 OD003644, and the Howard Hughes Medical Institute.


Received: June 15, 2009

Revised: October 18, 2009

Accepted: November 12, 2009

Published: February 11, 2010

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Miller, C., Thomsen, L.E., Gaggero, C., Mosseri, R., Ingmer, H., and Cohen, S.N. (2004). SOS response induction by beta-lactams and bacterial defense against antibiotic lethality. Science 305, 1629–1631.

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Supplemental Information

Molecular Cell, Volume 37

Sublethal Antibiotic Treatment Leads to Multidrug Resistance via Radical-Induced Mutagenesis

Michael A. Kohanski, Mark A. DePristo and James J. Collins

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Supplemental Results

Bactericidal Antibiotics Lead to Low-Level Increases in MIC for a Range of Antibiotics

Treatment with 25 ng/ml norfloxacin led to significant increases in the MIC for norfloxacin and kanamycin as well as modest, low-level increases in the MIC for ampicillin, tetracycline and chloramphenicol (Figure A3-S1A). This increase in MIC for norfloxacin was concentration dependent. Treatment with 50 ng/ml norfloxacin led to a 6-fold increase in the MIC for norfloxacin (Figure A3-S1B); however, we were unable to observe an increase in the MIC for ampicillin, kanamycin, tetracycline, or chloramphenicol following treatment

FIGURE A3-S1 Bactericidal antibiotics can lead to broad-spectrum increases in MIC. (A-C) Fold change in MIC relative to a no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline and chloramphenicol, following 5 days of growth in the presence of (A) 25 ng/ml norfloxacin, (B) 50 ng/ml norfloxacin, or (C) 1 μg/ml kanamycin. (D) Ampicillin-mediated increases in MIC are stable. Fold change in MIC relative to a no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline and chloramphenicol, following 5 days of growth in the presence of 1 μg/ml ampicillin and an additional 2 days of growth in the absence of drug.

FIGURE A3-S1 Bactericidal antibiotics can lead to broad-spectrum increases in MIC. (A-C) Fold change in MIC relative to a no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline and chloramphenicol, following 5 days of growth in the presence of (A) 25 ng/ml norfloxacin, (B) 50 ng/ml norfloxacin, or (C) 1 μg/ml kanamycin. (D) Ampicillin-mediated increases in MIC are stable. Fold change in MIC relative to a no-drug control for ampicillin, norfloxacin, kanamycin, tetracycline and chloramphenicol, following 5 days of growth in the presence of 1 μg/ml ampicillin and an additional 2 days of growth in the absence of drug.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A3-S2 Survival of E. coli following treatment with near-MIC levels of antibiotics. (A) Survival of MG1655 following treatment with no drug (filled squares), 1 μg/ml ampicillin (amp, open circles), 1 μg/ml kanamycin (kan, open triangles), and 15 ng/ml norfloxacin (nor, filled diamonds), respectively. (B) Survival of MG1655 following treatment with no drug (filled squares), 3μg/ml kanamycin (filled triangles), 1 mM hydrogen peroxide (H2O2, open squares), and 50 ng/ml norfloxacin (filled diamonds), respectively.

FIGURE A3-S2 Survival of E. coli following treatment with near-MIC levels of antibiotics. (A) Survival of MG1655 following treatment with no drug (filled squares), 1 μg/ml ampicillin (amp, open circles), 1 μg/ml kanamycin (kan, open triangles), and 15 ng/ml norfloxacin (nor, filled diamonds), respectively. (B) Survival of MG1655 following treatment with no drug (filled squares), 3μg/ml kanamycin (filled triangles), 1 mM hydrogen peroxide (H2O2, open squares), and 50 ng/ml norfloxacin (filled diamonds), respectively.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

TABLE A3-S1 PCR Primers and Sequencing Primers

PCR Primers

Primer Name

Sequence (5′-3′)

gyrA-F

CCA GAC TTT GCA GCC TGG ACT T

gyrA-R

AAC TCA CCT TCC AGA TCC CAC CA

gyrB-F

TGA ACG CCT TAT CCG GCC TAC AA

gyrB-R

CTC TGA GCT TGA TGA TGA GCG TCG

tolC-F

TGA CTG CCG TTT GAG CAG TCA TGT G

tolC-R

TTA CGT TGC CTT ACG TTC AGA CGG

marRA-F

TAG CTA ACG GCA GCA ACA CCA C

MarRA-R

CAA TGT ATT TGG CTT GCG GTG GC

acrAB-F

TCG TAT GAG ATC CTG AGT TGG TGG TTC

acrAB-R

AAT GCC AGT AGA TTG CAC CGC

acrAB-F2

ACT TAT TAC TAC GCG ATC GCC TGC T

acrAB-R2

GCA GTG AAC CAG AAT AGC AAC GAC GA

sdhB-F

CTG CCA ACT TCC GTA CCG AAA G

sdhB-R

AGC TCT TGT CTA CGT AGT GGC TC

icdA-F

CTG GTA GAA CGT TGC GAG CT

icdA-R

GAC TAG TAG TAG AAC TAC CAC CTG ACC G

iscR-F

GTT ACC AAA GGT TCC GTC CAT CGT

iscR-R

CGT CTT ATC AGG CCT ACA GTG TAC AG

cpxR-F

CGA CAT GCT GCT CAA TCA TCA GC

cpxR-R

GCT TAA TGA ACT GAC TGC CAG CGT TGA

arcA-F

GAC TGC TCA ACT CTG CCG ATA G

arcA-R

TGC TGT TAA AAT GGT TAG GAT GAC AGC CGT

ampC-F

AGG CAA CGA CCA GAA ATG CAG CT

ampC-R

TAT GCA CCA CGC GAT GCA CGA T

Sequencing Primers

Primer Name

Sequence (5′-3′)

gyrA1

CAG GCA TTG GAT GTG AAT AAA GCG TAT AGG

gyrA2

ATC ATT AAC GGT CGT CGC GGT ATT G

gyrA3

TGC GTG ATG GTC TGT ACT ACC TGA

gyrA4

TCC TCA CCG AGT TCA ACC GTC T

gyrB1

TCA GTG CTG AAC ACG TTA TAG ACA TGT CGG

gyrB2

GAC GGC AAA GAA GAC CAC TTA CAC T

gyrB3

AAG CGC GCT TCG ATA GA TGC T

gyrB4

GTT TGA TGT TCA CAC CAA TGC TGA GC

tolC1

TAT GGC ACG TAA CGC CAA CCT

tolC2

TAA CCT TGA TAA CGC GGT AGA GCA GC

tolC3

GCT CAA GCG TGC CTG TAA CA

marRA1

AGC TAG CCT TGC ATC GCA TTG A

marRA2

CGG ACG AAG TGG CAA CAC TTG AGT AT

marRA-M1

AGG TAT GAC GAT GTC CAG ACG CA

marRA-M2

TGC GTC TGG ACA TCG TCA TAC CT

acrA1

CAG CTG CTT TTG CAA TCT CGC

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Sequencing Primers

Primer

Name Sequence (5′-3′)

acrA2

CTG CTC GGT ACT CAG TAC ATC AGT AAG C

acrA3

TGC AGA AAG TGC GTC CTG GTG T

acrA4

ATT ACC GCC ATC AAA GCG CAG

acrA8

CTC CAT CAA TAA TCG ACG CCG TTC T

acrA9

TGT AAG CCA GAT TGA TCC GCG CA

acrA-M1

GTT CTG TAC CAA TGC GCC TTC CGT

acrA-M2

ACG GAA GGC GCA TTG GTA CAG AAC

icdA1

TAG CCT AAT AAC GCG CAT CTT TCA TGA CG

icdA2

ATT CGC TTC CCG GAA CAT TGT GGT A

icdA3

CTA CCC CAA AAC TAC CGA GGG GTT

icdA4

CCA GTC TTT AAA CGC TCC TTC GGT

icdA-R5

GGA GCG TTA CGC TCC CGT TAA TA

icdA-M1

GGT ATC GAA TGG AAA GCA GAC TCT GC

sdhB1

TCG ACT TCC CGG ATC GTG ATG ATG A

sdhB2

TCC TTT GTT ACG CCT GAT GCG CT

iscR1

TGG GTT GCG GAG TAG TCG AGA TAA

iscR2

ATA TGG CGT TCA CGC CGC AT

cpxR1

ACG ATG TTC GCT ATC CAG AAG CTC

cpxR2

GCA GCG GTA ACT ATG CGC ATC ATT

arcA1

GTG ACC CGT ATT ATC GAC TGG TAT GC

arcA2

GTA CCC ACG ACC AAG CTA ATG ATG

ampC1

TGG CTG CTA TCC TGA CAG TTG TCA

ampC2

GTC TGT ATG CCA ACT CCA GTA TCG GT

with 50 ng/ml norfloxacin for 5 days (Figure A3-S1B). Interestingly, selection of drug-resistant mutants following quinolone treatment is concentration dependent, with higher concentrations of quinolone selecting only quinolone-resistant strains and lower levels of quinolone selecting broadly for drugresistant mutants with mutations in a wide array of targets in E. coli (Drlica, 2003) and Mycobacterium tuberculosis (Zhou et al., 2000). It is possible that treatment with 50 ng/ml norfloxacin selects for naturally occurring quinolone-resistant mutants before the drug-induced mutagenesis has a chance to create mutants resistant to other drugs.

Supplemental References

Drlica, K. (2003). The mutant selection window and antimicrobial resistance. J Antimicrob Chemother 52, 11-17.

Zhou, J., Dong, Y., Zhao, X., Lee, S., Amin, A., Ramaswamy, S., Domagala, J., Musser, J.M., and Drlica, K. (2000). Selection of antibiotic-resistant bacterial mutants: allelic diversity among fluoroquinolone-resistant mutations. J Infect Dis 182, 517-525.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

A4
ANTIBIOTIC-INDUCED RESISTANCE FLOW

Patrice Courvalin

Institut Pasteur, Unité des Agents Antibactériens, Paris, France

Introduction

The evolution of bacteria toward antibiotic resistance is unavoidable since it represents a particular aspect of the general evolution of bacteria. It results from two independent steps, emergence and dissemination; however, as we consider, the mechanism of the first one can largely influence the success of the second one. Resistance to antibiotics in bacteria is secondary to mutations in resident (housekeeping) structural or regulatory genes or to horizontal acquisition of foreign genetic information (Perichon and Courvalin, 2009). In this review, we consider the relationship between low levels of antibiotics and dissemination of resistance.

The emergence of resistance, an event that occurs by pure chance, can be a rare, even transient, event if it does not provide a selective advantage against a molecule present in the environment of the bacterium. Resistance potentially exists in nature, not only before the clinical use but also before the discovery, or even the design, of a new antibiotic. This is obvious for natural antibiotics, because the producing microorganisms must protect themselves against suicide by the products of their secondary metabolism, but it also holds true for semisynthetic (e.g., amikacin) or entirely synthetic (e.g., fluoroquinolone) antibiotics.

The bacterial genome is composed of the chromosome and of accessory genetic elements, self-transferable or mobilizable plasmids, integrative conjugative elements (ICEs), transposons, insertion sequences, and bacteriophages. The chromosome contains all the genetic information required for the life cycle of the bacterium, whereas, as their name indicates, accessory genetic elements carry genes that are dispensable, although under certain circumstances, they can provide major advantages for the survival of the host, such as antibiotic resistance. The chromosome is inherited vertically by the progeny of the cell and is not transferable horizontally, whereas accessory genetic elements can also be transmitted to other bacteria. As a result, resistance can thus be endogenous or exogenous. Endogenous resistance results from chromosomal mutations and is generally not infectious from bacteria to bacteria. In contrast, exogenous resistance is due to horizontal (lateral) transfer of DNA among bacteria, resulting in acquisition of mobile genetic elements.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

The Classical View

Endogenous Resistance

The occurrence of chromosomal mutations is an efficient pathway to resistance. Mutations are considered rare because they occur at low frequency, generally between 10−7 and 1010 and were considered errors that occurred during DNA replication. However, this limitation is easily overcome because, during infections in humans, bacterial populations are often very large. Mutations in chromosomal genes clearly represent the only mechanism of antibiotic resistance in genera such as Mycobacterium or strictly intracellular pathogens (such as Chlamydia, Rickettsia, Coxiella, Ehrlichia), which are not known to exchange DNA under natural conditions.

Exogenous Resistance

Dissemination of resistance has, in numerous instances, been shown to be closely associated with antibiotic use (Malhotra-Kumar et al., 2007), which stresses the importance of the prudent use of these molecules. In addition, resistance is, if at all, slowly reversible (Andersson, 2003). There are three levels of resistance dissemination, depending upon the vector: bacteria (clonal spread), replicons (plasmid epidemics), or genes (conjugative transposon [ICE] epidemics). These various levels of dissemination, which coexist in nature and thus account for the extraordinary rise in antibiotic resistance among bacteria, are not only infectious but also exponential because each is associated with DNA duplication. Clonal dissemination is associated with chromosome replication, plasmid conjugation with replicative transfer, and gene migration with replicative transposition.

It also turns out that conjugation has a very broad host range—plasmids and ICEs can transfer efficiently between phylogenetically remote bacterial genera—and that there are limited barriers to heterologous gene expression (Courvalin, 1994); that is, resistance genes can be expressed in very diverse hosts.

These observations led to the notion of a bacterial gene pool, in particular with respect to resistance, which means that genes are loosely bound to their hosts and can easily disseminate under natural conditions. This concept has many practical consequences, for example, in the case of the use of antibiotics as animal feed additives. Rather than discussing endlessly (and often in a biased fashion) whether the enterococci from animals and humans are similar (Phillips, 1999) (i.e., whether vancomycin-resistant enterococci from animals can stably colonize the human gut), the true question should rather be the following: Are the resistance genes (to glycopeptides, in this example) the same among bacteria of these two ecosystems? Along this line, studies published long ago that examined the biochemistry and genetics of aminoglycoside resistance, as well

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

as molecular study of the bacterial hosts (with the techniques available at that time), elucidated how the exclusive use of apramycin in animals could select gentamicin-resistant bacteria that were later found in humans (Chaslus-Dancla et al., 1986a, 1986b, 1991). This notion has since been largely documented, using more powerful techniques, for resistance to other drug classes (Stobberingh and van den Bogaard, 2000).

The Modern View

Endogenous Resistance

It was shown recently that bactericidal antibiotics kill bacteria by inducing the formation of highly deleterious hydroxyl radicals, reactive oxygen species, which can damage DNA (Kohanski et al., 2007). This oxidative stress leads to a significant increase in mutation rate either directly or indirectly by activation of the SOS DNA damage response pathway (Kohanski et al., 2010) as well as an increase in recombination (Figure A4-1). Thus, certain classes of antibiotics may behave as mutagens, in particular at low concentrations, and may select for resistance to other drug classes, whereas the mutant derivatives remain susceptible to the applied antibiotic (Kohanski et al., 2010).

The major human pathogen Streptococcus pneumoniae may represent a particular case of this mechanism. Evidence has been recently provided that the stress caused by low concentrations of certain antibiotics induces genetic transformability in pneumococci (Prudhomme et al., 2006). Transformation is a process inherent in this bacterial species that allows the transient uptake and integration of exogenous DNA in the recipient genome as well as the capability to kill noncompetent cells, a phenomenon referred to as fratricide. Low concentrations of bactericidal antibiotics, such as quinolones and aminoglycosides, induce full competence for genetic transformation, thereby increasing the rate of genetic exchange in S. pneumoniae and making chromosomal mutations horizontally transferable (Figure A4-2). Competence appears thus as a general stress response, playing a role similar to that of the SOS response in Escherichia coli that lacks in S. pneumoniae (Claverys and Havarstein, 2002). Fratricide is the killing of cells from the same species and can be considered a mechanism that is used by competent bacteria to acquire DNA from noncompetent pneumococci (Claverys et al., 2007). Considering the high incidence of asymptomatic carriage of and co-colonization by this human pathogen, inappropriate antibiotic use could accelerate the emergence of resistant clones, promote evolution toward virulence, and enrich in capsular types that are not included in the current vaccines. The latter observation represents an additional argument for not prescribing fluoroquinolones to children.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A4-1 Antibiotic induced increase mutation rate in S. pneumoniae. Subinhibitory concentrations of bactericidal antibiotics promote production of reactive oxygen species (ROS) by bacteria via the stress response. This leads to DNA damage which i) increases recombination frequency and ii) induces a competence state resulting in transformation which both cause mutations.

FIGURE A4-1 Antibiotic induced increase mutation rate in S. pneumoniae. Subinhibitory concentrations of bactericidal antibiotics promote production of reactive oxygen species (ROS) by bacteria via the stress response. This leads to DNA damage which i) increases recombination frequency and ii) induces a competence state resulting in transformation which both cause mutations.

Exogenous Resistance

Antibiotics can enhance gene transfer: they provide selective pressure for resistant bacteria to maintain and disseminate, but they can also induce the transfer of resistance genes. For example, it has been reported that (1) the use of subinhibitory concentrations of penicillins increased the conjugal transfer of plasmid DNA from Escherichia coli to Staphylococcus aureus and Listeria monocytogenes (Trieu-Cuot et al., 1993), (2) oxacillin increased the frequency of in vitro transfer of Tn916, an enterococcal ICE, from Enterococcus faecalis to Bacillus anthracis (Ivins et al., 1988), (3) the transfer frequency of conjugative transposons belonging to the Tn916/Tn1545 family (Figure A4-3), which contain a tetracycline resistance determinant, was increased 10- to 100-fold in vitro and in vivo in the presence of low concentrations of tetracycline (Doucet-Populaire et al., 1991), and (4) tetracycline also increased dramatically the transfer of a

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A4-2 Antibiotic promotes evolution of resistance in S. pneumoniae. The presence of an antibiotic generates a bacterial stress responsible for competence. The competence state induces transformation and fratricidy in which both can lead to antibiotic resistance and capsular switch.

FIGURE A4-2 Antibiotic promotes evolution of resistance in S. pneumoniae. The presence of an antibiotic generates a bacterial stress responsible for competence. The competence state induces transformation and fratricidy in which both can lead to antibiotic resistance and capsular switch.

Bacteroides conjugative transposon (Li et al., 1995). In the two latter cases, the antibiotic has a triple activity: as an antibacterial agent, as an inducer of resistance to itself, and as an inducer of the dissemination of resistance determinants. It thus appears that several antibiotics can behave like pheromones: they are synthesized by specific cells (such as the Actinobacteria), and they act on another cell, at low concentrations, on very specific targets to promote DNA exchange.

It was also shown that mitomycin C and ciprofloxaxin de-repressed the expression of genes necessary for transfer of an ICE in Vibrio cholerae (Beaber et al., 2004). This resulted in an unpredictable horizontal dissemination of the genetic element which confers resistance to chloramphenicol, trimethoprim, sulphonamides, and streptomycin.

Another example of increased resistance gene mobility by antibiotics is represented by the integrons (Mazel, 2006). These compact structures act as genetic systems for in vivo capture and expression of genes in the form of circular cassettes. These genes are the most tightly linked because they are not only adjacent but coexpressed from the same promoter. Integrons are thus typically responsible for coresistance: the stable association in the same cell of various resistance determinants, each conferring resistance to a drug class. Similarly to cross-resistance, which results in cross-selection, coresistance implies coselection: the use of any antibiotic that is substrate for a mechanism encoded by the integron will coselect for the other resistances. This genetic organization renders the consequences of

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×
FIGURE A4-3 Transfer of an integrative conjugative element (ICE). ICEs are mobile genetic elements that carry one or several resistance genes. They excise by site-specific recombination between their flanking attachment sites, attR and attL, leading to the formation of an episomal ICE carrying an attI site and an empty attB site in the chromosome. They replicate during their transfer by conjugation and integrate in the chromosome of the recipient. Dissemination of resistance by ICEs is thus infectious and exponential.

FIGURE A4-3 Transfer of an integrative conjugative element (ICE). ICEs are mobile genetic elements that carry one or several resistance genes. They excise by site-specific recombination between their flanking attachment sites, attR and attL, leading to the formation of an episomal ICE carrying an attI site and an empty attB site in the chromosome. They replicate during their transfer by conjugation and integrate in the chromosome of the recipient. Dissemination of resistance by ICEs is thus infectious and exponential.

the use of a single drug unpredictable. Because there is transcriptional attenuation along the operons in integrons (Collis and Hall, 1995), the use of an antibiotic selects not only for the neighboring resistance determinants but for a higher level of resistance to itself as well. This is achieved by the movement (excision, circularization, and re-integration) of the corresponding cassette that ends up downstream from the strong common promoter. Integrons, therefore, allow quantitative (self) and qualitative (nonself) alteration of resistance. Most interestingly, it has been shown recently that certain antibiotics such as mitomycin C, trimethroprim, the quinolones, and the β-lactams stimulate the intracellular mobility of the gene cassettes (Guerin et al., 2009).

Limitations to Dissemination

Genes from Gram-positive cocci can be transferred by conjugation (of plasmids or ICE) not only among these microorganisms but also to Gram-negative bacteria (Courvalin, 1994). The reverse is not true because of limitations in heterologous gene expression. This is due to the fact that the −35 and −10 sequences

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

and their spacing that constitute the promoters for expression of the genes, as well as the ribosome binding site, are conserved and are close to the consensus in Gram-positives; they are thus also functional in Gram-negatives. In contrast, these motifs are much more degenerate in Gram-negatives and cannot be accommodated by Gram-positives. Similarly, the promoters from Bacteroides fragilis and from E. coli are dissimilar, resulting in lack of gene expression from E. coli promoters (even strong promoters) in B. fragilis and the inactivity of B. fragilis promoters in other bacterial species (E. coli, Bacillus subtilis, and Clostridium perfringens) (Bayley et al., 2000; Smith et al., 1992). One can thus confidently predict that strains of B. fragilis will not, or will extremely inefficiently, act as intermediates in resistance gene transfer or represent a pool of origin of these genes for human pathogens.

Acquisition of resistance by bacteria corresponds to a gain of function and is, thus, generally associated with a biological cost. In other words, resistant derivatives have a lower degree of fitness than the parental strain lacking the resistance genes; that is, daughter cells are less competitive for growth in a given ecosystem and in the absence of antibiotic, than the mother cell. The proportion of resistant strains in a bacterial population depends on several factors, such as the concentration and type of antibiotic used, the biological cost of resistance to that antibiotic, and the ability of bacteria to compensate for the fitness cost of the resistance mechanism. Acquisition of antibiotic resistance is often associated with a biological cost because (1) bacteria acquire a new gene (or set of genes) responsible for new functions, (2) the resistance mutations occur in genes with essential functions, or (3) additional energy is required for replication and maintenance of plasmids that bear the resistance genes. The biological cost determines the stability and potential reversibility of resistance.

A compensatory evolution could occur to reduce the biological cost leading to stabilization of the resistant bacteria in a natural population. This process allows resistant strains to regain competitivity relative to their susceptible counterparts in an antibiotic-free environment (Hughes and Andersson, 2001).

However, it has been recently demonstrated that inducibility of resistance is a compensatory mechanism (Foucault et al., 2010). This accounts for the observation that the majority of horizontally acquired antibiotic resistance mechanisms is tightly regulated and that resistance evolves to become selectively neutral in the absence of antibiotics.

Conclusion

Regardless of the mechanism of action of a drug class, it must be realized that resistance already occurs in nature or will inevitably emerge. This is, perhaps, obvious for natural antibiotics, because the producing organisms must avoid self-destruction, but it also holds true for nonnatural drugs. It is thus clear that bacteria are able to resist every antibiotic, naturally or in an acquired

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

fashion, and selection of resistant bacteria can be regarded as the ultimate criterion for activity of an antibiotic. In addition, and by the mechanisms we have considered, resistance, either by mutation or after acquisition of foreign genetic information, can be drastically enhanced by low concentrations of antibiotics in the environment of the bacteria. Because dissemination of resistance is closely linked to the magnitude of the selective pressure, the only hope is to delay this dissemination. This leaves us with a single recommendation: antibiotics should be used cautiously.

References

Andersson, D. I. 2003. Persistence of antibiotic resistant bacteria. Curr. Opin. Microbiol. 6:452–6.

Bayley, D. P., E. R. Rocha, and C. J. Smith. 2000. Analysis of cepA and other Bacteroides fragilis genes reveals a unique promoter structure. FEMS Microbiol. Lett. 193:149–54.

Beaber, J. W., B. Hochhut, and M. K. Waldor. 2004. SOS response promotes horizontal dissemination of antibiotic resistance genes. Nature 427:72–4.

Chaslus-Dancla, E., G. Gerbaud, J. P. Lafont, J. L. Martel, and P. Courvalin. 1986a. Nucleic acid hybridization with a probe specific for 3-aminoglycoside acetyltransferase type IV: A survey of resistance to apramycin and gentamicin in animal strains of Escherichia coli. FEMS Microbiol. Lett. 34:265–8.

Chaslus-Dancla, E., J. L. Martel, C. Carlier, J. P. Lafont, and P. Courvalin. 1986b. Emergence of 3-aminoglycoside acetyltransferase IV in Escherichia coli and Salmonella typhimurium from animal in France. Antimicrob. Agents Chemother. 29:239–43.

Chaslus-Dancla, E., P. Pohl, M. Meurisse, M. Marin, and J. L. Lafont. 1991. High genetic homology between plasmids of human and animal origins conferring resistance to the aminoglycosides gentamicin and apramycin. Antimicrob. Agents Chemother. 35:590–3.

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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A5
ACTINOBACTERIA: THE GOOD, THE BAD, AND THE UGLY15,16

Vivan Miao and Julian Davies17

Abstract

The actinobacteria are arguably the richest source of small molecule diversity on the planet. These compounds have an incredible variety of chemical structures and biological activities (in nature and in the laboratory). Their potential for the development of therapeutic applications cannot be underestimated. It is suggested that an improved understanding of the biological roles of low molecular weight compounds in nature will lead to

15

Reprinted with kind permission from Springer Science + Business Media: Miao and Davies (2010).

16

Keywords: Antibiotics · Bioactive molecules · Chemical diversity · Genomics · Molecular evolution · Natural products · Signaling · Therapeutics

17

V. Miao and J. Davies (email) Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada email: jed@interchange.ubc.ca.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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the discovery an inexhaustible supply of novel therapeutic agents in the next decade. To support this objective, a functional marriage of biochemistry, genomics, genetics, microbiology, and modern natural product chemistry will be essential.


The phylum actinobacteria, one of the largest groups in the domain Bacteria (Figure A5-1), largely consists of environmental bacteria and the denizens of many varied habitats: soils, the rhizosphere, marine and extreme arid environments. A number live in close association with higher organisms; for example, as components of different microbiomes they constitute more than a third of the healthy human microbiota. Members of the genus Frankia, on the other hand, can form symbiotic nodules in certain species of trees and shrubs, and fix atmospheric nitrogen to allow their hosts to survive in nutrient-limiting environments. Actinobacteria typically have elevated guanosine-cytosine contents (65-75% G + C) and their genome sizes range from the 2.5-Mb skin commensal Micrococcus luteus to the 9.7-Mb environmental strain Rhodococcus jostii. Since the discovery of antibiotics in the 1940s, the actinomycetes have received a great deal of attention, and Streptomyces species in particular have become renowned as the principal sources of therapeutic pharmaceuticals. There have been several good reviews on actinobacteria of late, notably that by Ventura et al. (2007) on evolutionary and genomic aspects, as well as occasional articles focusing on specific genera. Interest in the phylum in recent years is evidenced by the increasing number of citations; streptomycetes lead, of course, with the mycobacteria not far behind! However, other genera, including Rhodococcus, are beginning to excite more interest (Larkin et al., 2005, Kitagawa and Tamura, 2008) and who knows, Streptomyces may command less attention in the future.

Streptomycetes are demonstrably a rich source of compounds, but no more so than other members of the actinobacteria, also the Bacilli and bacterial genera such as the myxobacteria (Wenzel and Muller, 2009) and pseudomonads (Gross and Loper, 2009). Among the eukaryotes, fungal genomes are replete with biosynthetic gene clusters for encoding small molecule production. The ability to make bioactive small molecules is not exclusive to microbes. Plants are rich sources of a great variety of compounds that have been used as pharmaceuticals for millennia; this resource remains poorly understood and still largely untapped.

There is a global crisis in the treatment of infectious diseases; people are dying of infections that were previously treatable. Microbes are the source and the solution for the crisis, and for this reason it is imperative that the search for novel therapeutic agents be intensified. The constant moan of the pharmaceutical industry, that the natural reservoir of molecules with antibiotic activity is close to being exhausted and that they can no longer find useful bioactive compounds, is due in part to Waksman’s focus (see below) on the streptomycetes. It can also be explained by the inability to detect bioactive compounds when they are present only in low concentrations; the industry has found all the easily accessible

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A5-1 Phylogenetic tree of actinobacteria based on 1,500 nucleotides of 16S rRNA. Scale bar, 5 nucleotides. Families containing members subjected to complete genome sequencing at the time of this writing are depicted in bold. Orders are indicated.

FIGURE A5-1 Phylogenetic tree of actinobacteria based on 1,500 nucleotides of 16S rRNA. Scale bar, 5 nucleotides. Families containing members subjected to complete genome sequencing at the time of this writing are depicted in bold. Orders are indicated.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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bioactives, the so-called “low hanging fruit” (Baltz, 2006). Presumably it was not considered essential to develop the technology to find compounds that were missed. In addition, actinobacteria as a whole have been ignored, even though they too possess the capacity to produce a huge number of bioactive small molecules; to date, only a small proportion have been examined for therapeutic purposes. We are now in the “genomic era” and in the case of streptomycetes, exciting new information coming from complete genome sequencing efforts reveals that most of these bacteria have the genetic capacity to produce many more structurally different bioactive compounds than suspected. As such, they represent an inexhaustible collection of hidden chemical and biochemical diversity. Moreover, creative techniques for generating some of these compounds are being developed and exploited (Baltz, 2008; Challis, 2008). We have no excuse for being short of compounds to screen (assuming that reliable screens are in place)! In this short article we present the case for a more extensive survey of the biology, properties and uses of natural molecules, especially those from other members of the actinobacteria. Now that we know the ubiquity and diversity of bioactive small molecules, the most important questions remain: “How do we find them?” and “What are their roles in nature?” When we have the answers to these questions, we will be far better equipped to harvest and exploit this vast chemical and biological wealth.

The “GOOD”

This characteristic refers mainly to the discovery and production of microbial small molecules with antibiotic activity that began with Waksman’s work on actinomycetes in the early 1940s. These seminal studies, together with the discovery of the fungal product penicillin by Fleming and co-workers and its characterization around the same time, were responsible for momentous and radical changes in medicine. A representative, but grossly incomplete, list is presented in Table A5-1; for more information see the review by Demain and Sanchez (2009). The availability of antimicrobial agents made possible, for the first time, the successful treatment of most types of infectious diseases. The discovery of antibiotics also presaged many other uses for microbial compounds in human and animal therapy and in agriculture. Recently these microbial sources have provided treatments for many non-infectious diseases including cancer and heart disease. Another role, often overlooked, is their use in prophylaxis and in immunosuppression prior to invasive surgery, which has been one of the most important factors in the development and success of organ transplantation. Hundreds of millions of dollars have been invested by pharmaceutical companies in saving the lives of millions of people—with profits of many billions of dollars! In addition, many actinobacterial strains have been developed for industrial applications such as bioremediation, the destruction of toxic xenobiotics, vitamins, fine chemical transformation and production and, more recently, for the development

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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TABLE A5-1 Some Beneficial Actinobacteria

Producing organism

Compound

Application

Streptomyces aureofaciens

Tetracycline

Antibacterial

Streptomyces griceus

Streptomycin

Antibacterial

Streptomyces kanamycetius

Kanamycin

Antibacterial

Streptomyces lactamdurans

Cefotoxin

Antibacterial

Streptomyces mediterranei

Rifamycin

Antibacterial

Streptomyces pristinaspiraelis

Pristinamycin

Antibacterial

Streptomyces roseosporus

Daptomycin

Antibacterial

Streptomyces spheroids

Novobiocin

Antibacterial

Streptomyces venezuelae

Chloramphenicol

Antibacterial

Amycolatopsis orientalis

Vancomycin

Antibacterial

Micromonospora purpurea

Gentamicin

Antibacterial

Saccharopolyspora erythraea

Erythromycin

Antibacterial

Streptomyces avermitilis

Ivermectin

Antihelminthic

Streptomyces clavuligerus

Clavulanic acid

β-Lactamase inhibitor

Streptomyces hygroscopicus

Bialophos

Herbicide

Streptomyces hygroscopicus

Rapamycin

Immunosuppressive

Streptomyces noursei

Nystatin

Antifungal

Streptomyces verticillus

Bleomycin

Anticancer

of biofuel conversions. Novel uses of the extensive biosynthetic capacities of the Rhodococci are being discovered and one can predict their increasing importance as industrial microorganisms (Martinkova et al., 2009).

In spite of the numerous benefits accruing from these seemingly inexhaustible sources, the ecology and biology of actinobacteria and their roles in environmental communities are poorly understood and the functions of their myriad low-molecular-weight products in the environment are even less well studied. The development of these products as antibiotics led to the assumption that their primary (and only) function in nature was for use as molecular weaponry by their producers. The field was driven by the concept of antagonism: during the past half-century, their discovery and the proof of their biological activity relied solely on tests of their inhibition of the growth of other microbes under laboratory conditions. Given the number of bacterial genera and the inestimable number of compounds involved, this implies that the microbial world is nothing less than a constant theatre of war (Hibbing et al., 2009). There is very little sound evidence for this extreme concept and such an anthropocentric viewpoint needs to be discarded.

As with all biologically active compounds, the properties of bacterial products depend on the concentrations at which they are tested, immediately creating a dilemma: what exists and happens in nature is often quite distinct from what is found in a laboratory. Recent studies using sensitive promoter-reporter libraries or RNA microarrays have shown that at sub-inhibitory concentrations many microbial compounds modulate transcription patterns in a variety of bacterial and eukaryotic cells (Yim et al., 2006). Do the transcriptional effects provide the mechanistic basis for their wide range of biological activities? We believe so and have proposed that bioactive compounds act by binding to receptors in cells,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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triggering cellular responses that are many and various; in other words they are cell-cell signaling agents (Davies et al., 2006; Fajardo and Martinez, 2008). In the past, studies of mechanisms of antibiotic activity in bacteria led to the identification of specific targets/receptor molecules and macromolecules. These include components of the cell wall, ribosomes, ribosomal RNA, DNA replication, RNA synthesis, as well as numerous enzymatic reactions, such as those involved in the synthesis of fatty acids. There is substantial genetic validation for these interactions and for the roles of single, specific targets in the cell.

Detailed studies with eukaryotic organisms are sparse, but recent results in studies of the different microbial populations that make up the human microbiome indicate that bioactive compounds play important roles in many aspects of human physiology that impact health and disease (Kaper and Sperandio, 2005). It can be predicted that studies of bacterial-mucosal and bacterial-tissue interactions and the role of bioactive small molecules in these processes will be pursued actively in the coming years. The native bacterial communities of humans and other organisms presumably use inter-cellular signaling mechanisms to modulate and control the activities of bacterial consortia and the essential interactions with their host. These interactions have significant implications on related issues such as the activity of probiotics and their roles in regulating immune responses. Similarly, the roles of small-molecule mediation in the operation of distributed metabolic networks in natural microbial communities is another topic that demands scrutiny in the future (Vallino, 2003). Will the next decade be the age of bioactive small molecules?

The evolutionary origins of the great diversity of bacterial products are poorly understood. How old are the actinomycetes? The photosynthetic cyanobacteria are associated with the appearance of oxygen in the earth’s atmosphere, and evidence of bacterial cells in fossilized stromatolites suggests that bacteria are as old as 2.7 Gya; the domain Bacteria includes the most ancient living organisms in the biosphere (Oren, 2004). Detection of hopanoids in ancient shales and also as cell membrane components that play a role in the structure of aerial hyphae in streptomycetes is another clue to the pathway of bacterial evolution (Taylor, 1984). Many actinomycetes, including streptomycetes and the Rhodococci, possess putative genes for gas vesicle production associated with the ability to survive in aqueous environments (as might be found under primordial conditions) (van Keulen et al., 2005).

Both the wide variety of amino acid derivatives found in meteorites and the seminal “primordial soup” experiments by visionaries such as Miller and Urey (Miller et al., 1976) provide chemical evidence for the presence of many types of non-protein amino acid derivatives in the prebiotic world. This leads to the probability that molecules similar to modern nonribosomal peptides are among the oldest bioactive molecules, as is borne out by their extant biological functions and their production by many types of microbes and plants. Their presence defined the evolutionary direction of the earliest forms of life. The evolution of

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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the biosynthetic pathways for nonribosomal peptides and other natural products such as the polyketides remains unclear, although tangible models for their being have been proposed (Nett et al., 2009; Ridley et al., 2008). The widespread use of similar classes of bioactive compounds in microbial and plant life, their coevolution and coexistence, are clearly of related interest.

From an historical point of view the first useful antibiotics to be discovered and used as such came not from actinomycetes but from members of the Bacilli! The peptide gramicidin was reported by Rene Dubos in 1938, and is still employed. (Check your local pharmacy if you don’t believe this.) There is every reason to believe that all bacteria have the capacity to make similar types of compounds; confirmation comes from the discovery of hybrid NRP-PK toxins produced by certain strains of E. coli (Putze et al., 2009). Recently, a novel non-ribosomal peptide derivative has been isolated from a strain of Staphylococcus (Magarvey, personal communication). This leads to the conclusion that the number of bioactive microbial compounds is, at a minimal estimate, equal to the number of microbial species; therefore, in terms of production of bioactives, all microbes are “good”. So much for suggestions that the supply is close to exhaustion!

We live in an occult universe of low-molecular-weight compounds. Suffice it to say, the antiquity of bioactive small molecules and their huge range of chemical space explains their ubiquity and enormous range of functions in cell biology. Paraphrasing the words of Douglas Adams, the author of The Hitchhikers Guide to the Galaxy: “Microbial chemical space is big. You just won’t believe how vastly, hugely, mind-bogglingly big it is!” As has been suggested on several occasions, the many roles of low-molecular-weight natural products justify their place as elements of the “central dogma” along with DNA, RNA, and protein (Schreiber, 2005). More focused efforts on their biology will reap many intellectual advances along with increasing medical and industrial applications.

However, a major stumbling block is the isolation and characterization of the organic compounds in this vast repertoire. Methods for the chemical identification of microbial products have improved significantly in recent years; however, it still requires an enormous effort to isolate, purify and determine the structures of natural products. Even with the most advanced instrumentation (nuclear magnetic resonance, mass spectroscopy, etc. and various combinations thereof), unraveling the structures of natural compounds remains a slow and highly specialized process. The throughput of current platforms does not in any way meet the needs for identifying thousands of diverse bioactive molecules with multiple biological roles. Until there is a revolutionary advancement in the structure determination process (akin to the effect of pyro-sequencing on genomics) studies of the world of small molecules will lag behind other fields. It is imperative that we decipher the language of small molecules in nature. This major undertaking would provide huge benefits, not the least, novel medicines and the identification of other bioactive molecules with applications in many areas of human and animal health and industry.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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It is worth noting that an inventory of bioactive molecules will be only the prelude to developing the methodology required to systematically determine their functions, thereby effecting the metamorphosis of structural data into results and ultimately into molecular understanding. Precious little is known at present about the natural functions of these compounds.

One can identify antibiotics, siderophores, redox-active agents, transcription factors, transporters, and cell signals, etc. (Dietrich et al., 2008), but what are they actually doing in microbial population dynamics? The possibilities are many and the proposed functions must be confirmed under natural conditions (possibly using modern in situ imaging techniques). There is no doubt that working with well-characterized compounds will permit more sophisticated biochemical and genetic studies in target organisms, with the subsequent identification of unsuspected receptors and functions. If macromolecules such as the bacterial ribosome possess dozens of different receptor sites (Yassin and Mankin 2007) this will be a significant enterprise!

The “BAD”

We refer of course to parasitic strains that cause disease in other living organisms. From an evolutionary point of view any synergistic relationship can potentially lead to negative interactions; synergy with one partner or host can easily be translated into pathogenic interactions with another. The total number of known human and animal microbial pathogens is currently limited to a few thousand or so (including viruses); this is but a small percentage of the Bacteriaceae (Taylor et al., 2001). One can predict that the number may be much larger for plant pathogens.

We hear much about emerging pathogens in clinical studies: there are two broad classes: those organisms to which humans are newly exposed as a result of anthropogenic activities (reclaiming land, forest destruction, or social practices) and those dedicated pathogens that have recently acquired antibiotic resistance by mutation or horizontal gene transfer and thereby overcome/bypass the prevailing therapeutic options. Relatively few actinobacteria fall into the category of professional pathogens (that we know of) (Table A5-2).

Historically, M. tuberculosis is the most important pathogen and remains the most widely disseminated; there is evidence of human infection for 9,000 years (Hershkovitz et al., 2008). The total number of human deaths due to TB throughout history is not known, but it is estimated that M. tuberculosis caused at least 200 million deaths in the twentieth century (Kaufman and Van Helden, 2008). The first streptomycete-derived antibiotic and the most successful, streptomycin, was developed for the purpose of combating TB, the “White Plague”. At the present time, it is difficult to appreciate the incredible importance of the discovery of streptomycin; we have become nonchalant about the control of infectious diseases. Other critical drug discovery events in the 1940s built the reputation of

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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TABLE A5-2 Some Actinobacterial Pathogens (human, animal, and plant)

Mycobacterium avium

Actinomyces bovis

Mycobacterium avium complex

Actinomyces israelii

Mycobacterium bovis

Clavibacter michiganensis

Mycobacterium chelonae

Corynebacterium diphtheria

Mycobacterium fortuitum

Leisonia xyli

Mycobacterium leprae

Nocardia asteroids complex

Mycobacterium marinum

Nocardia farcinia

Mycobacterium tuberculosis

Rhodococcus equi

Mycobacterium ulcerans

Streptomyces scabies

Propionibacterium acnes

Tropheryma whipplei

Streptomyces somaliensis

 

Streptomyces sudanensis

 

the actinomycetes and established the bias towards this family of soil bacteria as producers of antibiotics. Although penicillin and several antibiotics from Bacillus spp. predated streptomycin in therapeutic use, they did not cure TB!

Other pathogenic mycobacteria are of significance, such as M. leprae (leprosy) and M. ulcerans (buruli ulcers). Among the actinomycetes, Rhodococcus equi has been recently identified as an equine infection that is an opportunistic pathogen for humans. Interestingly, the disease-causing actinomycetes evolved primarily by extensive genome reduction compared to their environmental precursors, rather than by the horizontal gene transfer of myriad pathogenicity islands associated with the Gram-negative pathogens such as E. coli, etc. M. tuberculosis is a notoriously difficult organism to work with due to its virulence, slow growth, and, until recently, lack of facile genetic manipulation; thus comparative studies of close relatives among the actinomycetes have provided important information on novel aspects of mycobacterial metabolism and mechanisms of virulence. For example, there is the important question of how M. tuberculosis survives in human macrophages. This has been revealed by comparative genomic analyses with the genome sequence of Rhodococcus jostii RHA1 that identified a gene cluster encoding a possible cholesterol degradation pathway (McLeod et al., 2006). The observation that this matched a closely related sequence in M. tuberculosis led to studies that have shown that the pathogen does indeed use cholesterol as a carbon source, providing critical information on its intracellular survival mechanisms and the possibility of novel targets for TB drug development (Van der Geize et al., 2007).

The “UGLY”

There are no ugly actinomycetes. However, for every silver lining there is a cloud, and this family is no different. It has been demonstrated that most of the common antibiotic resistance genes or their progenitors have their origins in environmental bacteria, and evidence suggests strongly that actinobacteria may be one of the main natural sources of clinically significant antibiotic resistance genes (Wright, 2007). On the other hand, the actinomycetes produce the

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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clavulanate-derived inhibitors of β-lactamases and also enzymes that degrade the acylhomoserine lactones, signal molecules that are responsible for the induction of virulence functions in a number of common pathogens. If we had been smart enough to recognize this fact earlier, it might have been possible to devise inhibitors of these resistance mechanisms and so defuse the pathogens prior to years of unrestricted antimicrobial therapy.

Afterthoughts

We have mentioned the “occult universe of small molecules” and will conclude with a few additional comments on this theme. The existence and the roles of low-molecular-weight organic compounds in biology have been all but ignored. Despite a century of studies of the chemistry, physiology, and critical roles of vitamins, neurotransmitters, pheromones, alkaloids, and other useful products of plants and animals, the chemical store of the microbial world remains a great mystery. Recent studies of the phenomenon of quorum sensing communication have taught microbiologists and chemists that small can be beautiful and meaningful (Atkinson and Williams, 2009; Winans and Bassler, 2008). However, quorum-sensing activities, like antibiotic effects, are still largely studied as laboratory phenomena that do not necessarily represent the environmental roles of organic compounds; it remains difficult to assess concentrations of the signaling compounds in the wild. What is needed is more science and much less anthropocentricity; the latter provides the substance of exciting movies but is bad science. (Admittedly, for convenience we have slipped into anthropomorphic mode by using the descriptors “good”, “bad” and “ugly”; this is almost as lamentable as saying that bacteria “decide”, or “make lifestyle choices”, phrases seen in many publications!)

Finally, the diversity and ubiquity of bioactive small molecules, their multitudinous sources, and their potential and critical roles in the functioning and interactions of all living things lead us to propose that there should be significant, targeted funding initiatives (and perhaps even institutes) devoted to their study: chemical (structural and synthetic), genetic, biological, physical, imaging, etc. Surely, the increasing interest in systems biology will benefit from a full understanding of small-molecule biology? We can do no better than to quote the proverb “from small beginnings come great things”.

Acknowledgments

We are grateful to Dorothy Davies for her patient editing assistance and Dr. Marco Ventura for permission to reproduce Figure A5-1. Funding has been provided by the National Science and Engineering Research Council, the Canadian Institutes for Health Research, Merck Research Laboratories, and the Tally Fund.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A6
ANTIBIOTICS FOR EMERGING PATHOGENS18

Michael A. Fischbach19 and Christopher T. Walsh20,21


Antibiotic-resistant strains of pathogenic bacteria are increasingly prevalent in hospitals and the community. New antibiotics are needed to combat these bacterial pathogens, but progress in developing them has been slow. Historically, most antibiotics have come from a small set of molecular

18

Reprinted from Fischbach, M. A., and C. T. Walsh (2009). Antibiotics for emerging pathogens. Science 325(5944):1089-1093 with permission from AAAS.

19

Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA. E-mail: fischbach@fischbachgroup.org.

20

Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. E-mail: christopher_walsh@hms.harvard.edu.

21

Research in the authors’ laboratories is supported by the Department of Molecular Biology and the Center for Computational and Integrative Biology at Massachusetts General Hospital (M.A.F.) and by NIH grants GM20011 and GM49338 (C.T.W.). C.T.W. is a member of the board of directors of Achaogen (South San Francisco, CA).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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scaffolds whose functional lifetimes have been extended by generations of synthetic tailoring. The emergence of multidrug resistance among the latest generation of pathogens suggests that the discovery of new scaffolds should be a priority. Promising approaches to scaffold discovery are emerging; they include mining underexplored microbial niches for natural products, designing screens that avoid rediscovering old scaffolds, and repurposing libraries of synthetic molecules for use as antibiotics.


There is a perpetual need for new antibiotics: Whereas most drugs will be just as effective in the future as they are today, the inevitable rise of resistance will erode the utility of today’s antibiotics (Walsh, 2003). Two factors exacerbate this supply problem by creating unique disincentives for antibiotic development (Nathan et al., 2005). First, antibiotics are used in smaller quantities than other drugs. Prescriptions for chronic illnesses can last years or decades, whereas a standard course of antibiotics lasts only weeks; therefore, antibiotics yield lower revenues than most drugs. Second, whereas most newly approved drugs can be prescribed to all who would benefit, the use of a newly approved antibiotic may be restricted to the treatment of serious bacterial infections. The result is a quandary: Resistance is on the rise while antibiotic discovery and development are on the decline (Nathan, 2004; von Nussbaum et al., 2006).

The unfavorable economics of antibiotic development have had a chilling effect on industrial discovery programs, and policy-based efforts to reverse this decline deserve attention (Nathan, 2004). This perspective focuses on a different, yet no less formidable, challenge: finding new classes of antibiotics.

On the face of it, antibiotic discovery would seem to be straightforward. The goal is to kill an organism that is only distantly related to humans; unique, essential targets should be abundant, and novel antibiotics with low toxicity should be easy to find. Yet, the history of antibiotic development suggests otherwise. Since the early 1960s, only four new classes of antibiotics have been introduced, and none of these has made a major impact yet; the ~$30 billion global antibiotics market is still dominated by antibiotic classes discovered half a century ago. Since then, most “new” antibiotics have been chemically tailored derivatives of these well-worn scaffolds. In this review, we argue that the rise of resistant pathogens should redouble our focus on discovering not just new antibiotics, but new classes of antibiotics. We then highlight some promising approaches to scaffold discovery: mining under explored microbial niches for natural products, designing screens that avoid rediscovering old scaffolds, and repurposing libraries of synthetic molecules for use as antibiotics.

A New Generation of Resistant Pathogens

Three classes of antibiotic-resistant pathogens are emerging as major threats to public health (Figure A6-1). First, methicillin-resistant Staphylococcus aureus

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A6-1 Multidrug-resistant strains of these bacterial pathogens are on the rise.

FIGURE A6-1 Multidrug-resistant strains of these bacterial pathogens are on the rise.

SOURCE: Copyright Dennis Kunkel Microscopy, Inc.

(MRSA) is estimated to cause ~19,000 deaths per year in the United States (Klevens et al., 2007). Apart from their high mortality rate, MRSA infections lead to an estimated $3 billion to $4 billion of additional health care costs per year. Furthermore, the rising prevalence of MRSA increases the likelihood that vancomycin-resistant S. aureus (VRSA) (Weigel et al., 2003)—just as deadly as MRSA but more challenging to treat—will become a new scourge in hospitals.

Pathogens from the second class, multidrug-resistant (MDR) and pandrug-resistant (PDR) Gram-negative bacteria, are less prevalent than MRSA, but they pose the grave threat of infections that are truly untreatable (Falages et al., 2005). These strains of Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa are resistant to some (MDR) or all (PDR) of the antibiotic classes commonly used to treat Gram-negative bacteria: penicillins, cephalosporins, carbapenems, monobactams, quinolones, aminoglycosides, tetracyclines, and polymyxins (Falages et al., 2005). Prospects for finding new antibiotics for Gram-negative pathogens are especially poor: Their outer membrane blocks the entry of some antibiotics, and efflux pumps expel many of the remainder.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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The third class comprises MDR and extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis (MDR-TB and XDR-TB), which are a rising threat in the developing world (Dorman and Chaisson, 2007). MDR-TB treatment requires a 2-year course of antibiotics with serious side effects; XDR-TB is even more difficult to cure and often fatal (Kim et al., 2008). Cases of MDR-TB and XDR-TB have been reported in the United States and other developed countries.

In spite of the rise of resistant pathogens, the rate of new antibiotic approvals is dropping. Where will new antibiotics come from? In the past, this question has mostly been answered through synthetic tailoring of a small group of “scaffolds.”

Few Scaffolds, Many Generations of Tailoring

Members of each antibiotic class share a common core structure, or scaffold. For example, the cephalosporins share a β-lactam embedded in a fused 4,6-ring system (Figure A6-2). Most chemical scaffolds from which today’s antibiotics are derived were introduced between the mid-1930s and the early 1960s (Figure A6-3). Aside from the introduction of carbapenems in 1985, all antibiotics approved for clinical use between the early 1960s and 2000 were synthetic derivatives of existing scaffolds. Just four such scaffolds—cephalosporins, penicillins, quinolones, and macrolides—account for 73% of the antibacterial new chemical entities filed between 1981 and 2005 (Newman and Cragg, 2007).

During synthetic tailoring (Figure A6-2), the core of the antibiotic is left intact, preserving its activity, but the chemical groups at its periphery are modified to improve the drug’s properties. New generations are often designed to be active against pathogens that have become resistant to the previous generation. For example, second- (Neu and Fu, 1978) and third-generation (Dunn, 1982) cephalosporins like cefaclor and ceftazidime are more resistant to destruction by the resistance enzyme β-lactamase, and they can penetrate the Gram-negative outer membrane more effectively. When new β-lactamases emerged that can cleave third-generation cephalosporins, pharmaceutical companies developed fourth-generation molecules, like cefepime, that are less susceptible to cleavage by these enzymes (Garau et al., 1997). Cephalosporins and other semisynthetic antibiotics account for 64% of the new chemical entities filed between 1981 and 2005 (Newman and Cragg, 2007), suggesting that incremental synthetic tailoring of natural scaffolds has become the predominant mode of antibiotic discovery. The most useful scaffolds have therefore been those that are easy for medicinal chemists to tailor; this allows many derivatives to be synthesized and tested for improved properties.

Organic synthesis plays two other key roles in antibiotic discovery. First, scaffolds like the quinolones and oxazolidinones are derived entirely from chemical synthesis; these fully synthetic scaffolds account for an additional 25% of the

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A6-2 Synthetic tailoring is widely used to create successive generations of antibiotic classes. Scaffolds are colored black; peripheral chemical modifications are colored red. The quinolone scaffold is synthetic, whereas the other scaffolds are neutral products.

FIGURE A6-2 Synthetic tailoring is widely used to create successive generations of antibiotic classes. Scaffolds are colored black; peripheral chemical modifications are colored red. The quinolone scaffold is synthetic, whereas the other scaffolds are neutral products.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A6-3 Between 1962 and 2000, no major classes of antibiotics were introduced.

FIGURE A6-3 Between 1962 and 2000, no major classes of antibiotics were introduced.

antibiotic new chemical entities. Second, some natural scaffolds like carbapenems can now be produced entirely by organic synthesis, expanding the scope of accessible scaffold modifications.

The interplay between semisynthesis and total synthesis—and the ability of synthetic modifications to unlock the therapeutic potential of a scaffold—are exemplified by the tetracyclines. Resistance to this class of 30S-targeting antibiotics is mediated in part by a widely distributed gene encoding an efflux pump. Semisynthetic modifications to the tetracycline scaffold yielded the glycylcycline tigecycline (Figure A6-4) (Noskin, 2005). This third generation molecule (Figure A6-2) is no longer a substrate for the efflux pump, restoring its activity against tetracycline-resistant pathogens. A fully synthetic route to the tetracyclines (Charest et al., 2005) makes it possible to modify scaffold positions that are difficult to modify semisynthetically, further broadening the range of accessible derivatives.

Making incremental improvements to existing scaffolds is a good short-term strategy for refilling the antibiotic pipeline, but a presumably more sustainable way to combat resistance is to discover new scaffolds. Their utility will depend on three criteria: spectrum of activity against Gram-positive and Gram-negative pathogens, lack of cross-resistance to existing drugs, and amenability to generations of synthetic tailoring.

Next-Generation Scaffolds: Natural Products

More than two-thirds of clinically used antibiotics are natural products or their semisynthetic derivatives (Newman and Cragg, 2007). It is therefore troubling that natural product discovery efforts have waned in recent years (Li and

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A6-4 Surmounting resistance with scaffold alterations. Two ways of overcoming resistance are shown, using tetracycline (center) as an example. First, the tetracycline scaffold can be chemically modified, creating a tetracycline derivative like tigecycline that is no longer a substrate for the efflux pump (left). Second, a new scaffold like retapamulin, which is not a substrate for efflux and binds to a different site in the ribosome, can be used instead of tetracycline (right).

FIGURE A6-4 Surmounting resistance with scaffold alterations. Two ways of overcoming resistance are shown, using tetracycline (center) as an example. First, the tetracycline scaffold can be chemically modified, creating a tetracycline derivative like tigecycline that is no longer a substrate for the efflux pump (left). Second, a new scaffold like retapamulin, which is not a substrate for efflux and binds to a different site in the ribosome, can be used instead of tetracycline (right).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Vedesas, 2009); this decline is due in part to a rising rate of scaffold rediscovery (Baltz, 2006) and the accompanying difficulty in finding new antibiotics. Recent efforts to search new modalities—underexplored ecological niches, unmined bacterial taxa, and the genomes of even well-studied bacteria—have yielded novel molecules, whereas new screening strategies have begun to circumvent the time-consuming problem of rediscovery (Clardy et al., 2006).

New Places to Look

Most natural product antibiotics have come from soil actinomycetes, reflecting the historical bias of pharmaceutical screening programs toward these easily collected and cultured bacteria (Walsh, 2003). Searches of underexplored ecological niches and bacterial taxa have revealed new molecules. Marine niches are particularly promising; for example, a deep-sea sediment sample yielded an actinomycete that produces the abyssomicins (Bister et al., 2004), a new antifolate scaffold (Figure A6-5). Terrestrial and marine symbioses are also promising ecological niches; recent efforts to study bacterial symbionts of insects, ascidians, and fungi have yielded many new natural products (Donia et al., 2008; Partida-Martinez and Hertweck, 2005; Piel, 2009; Scott et al., 2008). Among underexplored bacterial taxa, myxobacteria are particularly prolific natural product producers, and their continued mining holds much promise for the discovery of new antibiotic scaffolds (Wenzel and Muller, 2009).

The genome sequences of a handful of actinomycetes and myxobacteria have revealed that these bacteria generally harbor >25 gene clusters encoding secondary metabolites. Given that only one to four natural products are known from a typical bacterium under various culture conditions, researchers may as yet have discovered only 10% of natural products from screened strains and just 1% of molecules from the global consortium of microbial producers (Watve et al., 2001). Taking this lesson to heart, several industrial and academic groups have carried out bioinformatics-based efforts to mine bacterial genomes for new natural products (Challis, 2008; McAlpine, 2009). Ecopia Biosciences (now Thallion Pharmaceuticals) has had particular success with their genome-scanning approach, including the discovery of ECO-0501, a new antibiotic scaffold (Banskota et al., 2006) (Figure A6-5). If the throughput of these genomics-based approaches to natural product discovery can be scaled up efficiently, their contribution to antibiotic discovery will be increasingly important.

Lastly, some promising candidate scaffolds for development may already be known. The founding members of the three most recently introduced antibiotic classes—mutilins, lipopeptides, and oxazolidinones—were each discovered at least 2 decades before they were introduced. Old patent literature seems a good place to start; on the basis of a 1985 patent from Eli Lilly, a group from Bayer recently isolated a series of acyldepsipeptide antibiotics that activate the bacterial chambered protease ClpP, leading to uncontrolled proteolysis and cell death

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A6-5 The chemical structures of new and underexplored antibiotic scaffolds mentioned throughout the text are organized by type into three categories: synthetic, semisynthetic, and natural product. For synthetic and semisynthetic scaffolds, core scaffolds are shown in black and variable positions are shown in red.

FIGURE A6-5 The chemical structures of new and underexplored antibiotic scaffolds mentioned throughout the text are organized by type into three categories: synthetic, semisynthetic, and natural product. For synthetic and semisynthetic scaffolds, core scaffolds are shown in black and variable positions are shown in red.

(Brotz-Oesterhelt et al., 2005) (Figure A6-5). Focusing development efforts on known but underexplored scaffolds can mitigate the risk of a costly and time-consuming de novo discovery program.

Combating Rediscovery

Out of 1000 randomly selected actinomycetes, about 10 will produce streptomycin, and 4 will produce tetracycline (Baltz, 2005). If extracts from these strains are screened against an indicator organism, most hits from the screen will be unhelpful rediscoveries. Two new screening strategies are beginning to

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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circumvent the problem of rediscovery. First, researchers at Cubist have developed a strain of E. coli that harbors resistance genes for the 15 most commonly rediscovered antibiotics (Gullo et al., 2006). Hits from their screening efforts are therefore preselected to be members of novel classes.

Second, a group at Merck has reported a bacterial antisense technology that allows them to knock down the expression of a given S. aureus gene, decreasing the amount of the encoded protein to the point that, in principle, it is present in growth-limiting quantities (Singh et al., 2007). Using this approach, they discovered platensimycin, the founding member of a new class of fatty acid biosynthesis inhibitors (Wang et al., 2006) (Figure A6-5), as well as several new protein synthesis inhibitory scaffolds.

Next-Generation Scaffolds: Synthetic Molecules

Fully synthetic molecules are a crucial component of the current antibiotic arsenal: The quinolones are highly effective broad-spectrum antibiotics, and the oxazolidinones are of increasing importance in the treatment of Gram-positive pathogens, including MRSA. However, recent efforts—based largely on high-throughput screens of novel targets identified by bacterial genomics—to discover and develop new synthetic scaffolds have not yet been successful (Payne et al., 2007).

Historically, synthetic scaffolds have originated outside of antibiotic discovery programs. The first drug in the sulfa class of antibiotics, Prontosil, was originally developed as a dye at Bayer, and the first quinolone was nalidixic acid, an intermediate in the synthesis of chloroquine. The oxazolidinones were discovered at DuPont as antibacterials but were originally developed to treat foliage diseases of plants.

Since the late 1990s, the rise of bacterial genomics held the promise of rejuvenating the discovery of synthetic antibiotics (Rosamond and Allsop, 2000). The genome sequences of pathogens like Haemophilus influenzae, S. aureus, Streptococcus pneumoniae, and E. coli made it possible to identify conserved enzymes that are essential for bacterial growth. These novel targets served as the basis for high-throughput screens of synthetic compound libraries, an approach that has been fruitful in other therapeutic areas. Genomics-based technologies have accelerated the process of identifying targets of existing drugs (Freiberg et al., 2005); however, they have not yet yielded new antibiotics (Payne et al., 2007; Mills, 2006).

Use External Libraries and a Whole-Cell Screen

The success of repurposing synthetic molecules from other development programs (Bogusli et al., 2009) and the failure of other approaches hold two important lessons for developing new synthetic antibiotics. First, look outside

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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antibacterial development programs for synthetic libraries to screen. Most pharmaceutical companies have invested considerable resources in synthesizing small molecule libraries for other therapeutic areas. Given the current level of uncertainty about which targets are relevant in an infected host (Brinster et al., 2009) and how antibiotics get into bacterial cells (Nikaido, 2003), libraries developed for other therapeutic areas may be just as likely to harbor hits as compound libraries developed for antibacterial screening.

Second, unbiased whole-cell screens have fewer pitfalls than other assays. The advantages of target-based screening—knowledge of the target and ease of optimization using a biochemical screen—are outweighed by the disadvantage of having to engineer cell permeability into a scaffold at a subsequent stage of the development process. Technologies like genome-wide expression profiling (Freiberg et al., 2005) and whole-genome resequencing of resistant mutants (Andries et al., 2004) have accelerated the bacterial infection, such as the hypoxia and oxidative stress that M. tuberculosis experiences in a host (Cho et al., 2007). A recent report has cast doubt on whether lipid synthesis is a viable target for Gram-positive pathogens; its authors argue that most models of infection fail to account for the fact that lipids in human serum can circumvent the inhibition of fatty acids synthesis (Brinster et al., 2009). Although future experiments will help resolve whether lipid synthesis inhibitors will be useful as drugs for Staphylococcus and Streptococcus, the mycolic acid pathway is already a well-validated target for M. tuberculosis. Any identified fatty acid synthesis inhibitors should therefore be tested against TB rather than being shelved for lack of efficacy against other Gram-positive pathogens.

A Recent Example of Success

A recent report from Pfizer demonstrates the utility of repurposing external compound libraries by screening them in a whole-cell antibacterial assay (Boguski et al., 2009). Miller and co-workers screened a one-million-compound library developed for eukaryotic protein kinase inhibition in an assay of E. coli killing, predicting that the low molecular weight ATP-mimetic molecules in the library might inhibit an essential bacterial enzyme and therefore exhibit antibacterial activity. They identified a set of pyridopyrimidines (Figure A6-5) that are subnanomolar inhibitors of the biotin carboxylase subunit of acetyl–coenzymeA (CoA) carboxylase (ACC), acting as competitive inhibitors of ATP binding. These molecules are selective for bacterial ACC over eukaryotic protein kinases and have potent activity against Gram-negative bacteria in vitro and in vivo. Similar efforts using other existing libraries could uncover new targets and scaffolds.

Is There Still a Role for Target-Based Antibiotic Discovery?

The failure of bacterial genomics to validate novel targets or yield new antibiotics has cast doubt on the utility of target-based discovery programs (Payne et

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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al., 2007; Mills, 2006). Nevertheless, retooled target-based strategies can play an important role in discovery. Examples include developing novel scaffolds for old targets and grouping new targets by inhibitor class.

A New Look at Old Targets

Most clinically used antibiotics inhibit enzymes from pathways that have been known for decades: peptidoglycan synthesis, ribosomal protein synthesis, folate synthesis, and nucleic acid synthesis and topoisomerization. Future generations of existing scaffolds should continue to have success in the clinic, and these classical targets will thus remain useful. However, a complementary and perhaps more promising strategy is to develop new scaffolds for these targets, thereby avoiding cross-resistance with existing drugs.

For example, the recently introduced mutilin retapamulin (Figures A6-4 and A6-5) targets the 50S subunit of the bacterial ribosome but is unaffected by resistance to other 50S-targeting classes like macrolides (Davidovich et al., 2007). Another target that deserves renewed focus is Lipid II; the success of glycopeptide antibiotics like vancomycin bodes well for other Lipid II–binding molecules like the mannopeptimycins (Figure A6-5) and lantibiotics (Breukink and de Kruijff, 2006).

Grouping Targets by Inhibitor Scaffold

To identify new targets, candidates are often grouped by a functional criterion, such as membership in a validated pathway or essentiality for growth in the laboratory. The attendant dangers of single-target bias (Payne et al., 2007) argue in favor of a strategy that begins with a wider funnel at its early stages.

A different way of grouping targets—by a common inhibitor scaffold rather than by pathway—may not only reveal new targets but also clues about how to inhibit them. For example, ATP binding enzymes are a group of targets that can be inhibited by ATP-mimetic scaffolds, and they deserve particular attention for two reasons.

First, bacterial genomes encode hundreds of ATP-binding proteins. They include well-validated targets like DNA gyrase, the target of the quinolones, and a host of new or underexplored targets: the chambered protease ClpP (Brotz-Oesterhelt et al., 2005), ATP synthase (Andries et al., 2004), aminoacyl-tRNA synthetases, and acyl-CoA carboxylase. The sensor kinase PhoQ is essential for the virulence of Salmonella (Bader et al., 2005), and several widely conserved essential genes encode proteins of unknown function that are predicted to bind ATP (Gerdes et al., 2003), suggesting that this class might include a particularly broad range of relevant targets. Insights from outside the antibiotic arena are also important for antibiotics; the observation that Zn-dependent hydrolases are efficiently inhibited by small molecules with Zn-chelating groups has led to the

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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development of inhibitors for a broad range of enzymes, including angiotensin-converting enzyme, histone deacetylases, and matrix metalloproteases. Indeed, semisynthetic derivatives of actinonin—a Zn-chelating natural product that inhibits the Zn-dependent bacterial enzyme peptide deformylase—have been considered as antibiotic candidates (Chen et al., 2000) (Figure A6-5).

Second, Miller and co-workers have demonstrated the feasibility of finding molecules from libraries of ATP-mimetic molecules that are selective for bacterial targets over human targets (Miller et al., 2009). Screening these libraries in whole-cell assays could simultaneously identify new targets and new lead compounds with scaffolds that can be optimized synthetically.

A More Inclusionary Approach?

In the heyday of antibiotic discovery, the pool of lead compounds was large enough for pharmaceutical companies to focus on broad-spectrum antibiotics for use as single-agent therapies and shelve compounds that failed these high therapeutic barriers. Today’s greater need for new antibiotics may encourage the development of lead molecules with characteristics that, until recently, have been seen as liabilities: narrow activity spectra and high intrinsic resistance rates.

The rule for antibacterial activity spectrum has been “broader is better.” However, the challenge of finding new broad-spectrum antibiotics and the rising threat from specific pathogens like MRSA have led to the development and approval of more agents with a narrower spectrum of activity, particularly those that kill Gram-positive but not Gram-negative bacteria. Extending this trend to near its logical limit, two groups recently reported Staphylococcus-selective antibiotics: One group used a repurposed series of eukaryotic cholesterol synthesis inhibitors to block the production of the gold pigment staphyloxanthin (Liu et al., 2008), from which the species name aureus is derived; the other group identified inhibitors of the tubulinlike protein FtsZ to block cell division (Haydon et al., 2008). It remains to be seen whether compounds with a spectrum this narrow find a therapeutic niche; one prerequisite for their use would be the availability of rapid diagnostics to identify the etiological agent of infection (Bootsma et al., 2006). Such genus-selective agents may have the benefit of sparing more of the endogenous microflora than conventional antibiotics, thereby avoiding complications like secondary Clostridium difficile infections.

Most bacterial infections are treated with a single antibiotic, ruling out the use of molecules with high intrinsic resistance rates. However, pairing these compounds into additive or synergistic combinations could rescue candidates formerly thought to be untenable for development. Although development of combination therapies carries the risk of unforeseen toxicity, precedents like amoxicillin-clavulanate and isoniazid-rifampicin-pyrazinamide-ethambutol all argue that antibacterial combination therapies can be quite successful, especially in suppressing the development of resistance. Whether natural or synthetic,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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broad-spectrum or narrow, single agents or combinations, new scaffolds will be an essential component of a sustainable plan for combating resistance.

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A7
AVERTING A POTENTIAL POST-ANTIBIOTIC ERA

Shelley Hearne22

The Pew Charitable Trusts

Introduction

Antibiotics save untold numbers of human lives every day. Modern medicine depends on our ability to treat and prevent infections. Yet a global crisis looms. Drug-resistant bacteria are spreading in our hospitals, our communities, and on our farms. Resistance is fueled by injudicious use of existing drugs and compounded by a failure to invest adequately in the development of new ones.

Dr. Thomas Frieden, director of the Centers for Disease Control and Prevention (CDC), has warned that we may be on the brink of “a post-antibiotic era” (Frieden, 2010). To prevent this warning from becoming an accurate prediction, we need to embrace what we already know from the science and heed the decades-long call to action by our leading health authorities and institutions, including the Institute of Medicine (IOM) and the World Health Organization (WHO). Several piecemeal legislative proposals exist that could address portions of the problem. But only a comprehensive policy framework designed to both preserve the efficacy of existing antibiotics and spur innovation of new drugs will provide a sustainable solution.

Antibiotic Resistance: An Inevitable and Growing Health Threat

Infections caused by bacteria can strike and kill anyone, including the young and the old, and the healthy and the chronically ill, but when antibiotics were discovered and developed beginning some 70 years ago, humanity turned a corner in

22

Managing Director, Pew Health Group.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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its ability to fight pathogens. Antibiotics quickly became the treatment of choice for staving off infections and saving lives.

But exposure to antibiotics inherently creates resistance among microorganisms (Levy, 2002; Wilkins, 1996). Their short generation time and the efficiency with which they develop and share resistance genes mean that no antibiotic remains effective forever (American Academy of Microbiology, 2009).

Resistance has increased rapidly among the major causes of bacterial illness in the United States, including Escherichia coli (Lewis et al., 2007), Salmonella (Winokur et. al., 2000), Campylobacter (Boucher et al., 2009), Enterococcus (McDonald, 2006), Streptococcus (Albrich et al., 2004), Staphylococcus (Klevens et al., 2007), and others (Rice, 2008).

One of the most widely known superbugs is methicillin-resistant Staphylococcus aureus (MRSA), which was once confined to already-vulnerable patients in hospitals and nursing homes. Now a community-acquired strain is also spreading among young, healthy individuals in everyday locations, among them schools, daycare centers, and locker rooms. Since 1998, the incidence of MRSA infections in children’s hospitals in the United States has increased 10-fold (see Figure A7-1) (Herigon et al., 2010). Researchers estimate that MRSA

FIGURE A7-1 Shifting balance. The number of hospital admissions with Staphylococcus aureus infections that remains sensitive (MSSA) to methicillin treatment has kept steady while that of resistant infections (MRSA) has been increasing.

FIGURE A7-1 Shifting balance. The number of hospital admissions with Staphylococcus aureus infections that remains sensitive (MSSA) to methicillin treatment has kept steady while that of resistant infections (MRSA) has been increasing.

SOURCE: Herigon et al. (2010). Reprinted with permission from Pediatrics, 125(6), pages e1294-e1300. Copyright © 2010 by the AAP.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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alone causes almost 100,000 serious infections and 18,000 deaths every year in the United States (Klevens et al., 2007), and it costs $3 billion to $4 billion each year to treat (Fischbach and Walsh, 2009). Infections with resistant bacteria also result in longer and more costly hospital stays. Overall, antibiotic resistance was responsible for an estimated $16.6 billion to $26 billion per year in extra costs to the U.S. healthcare system (Roberts et al., 2009).

Other resistant infections are also on the rise and may pose even more serious challenges in the long term. The frequency of multidrug-resistant Acinetobacter baumannii infections, for example, is increasingly significant (Falagas et al., 2006; Munoz-Price and Weinstein, 2008) among U.S. military personnel returning from duty in Iraq and Afghanistan. Ordinarily, A. baumannii causes a variety of conditions, ranging from pneumonia to serious blood or wound infections, but in soldiers it also causes devastating prostheses infections and catheter-related sepsis (Crane et al., 2009). The bacterium is now spreading among patients in non-military U.S. hospitals and intensive care units (Perez et al., 2008). Some strains of A. baumannii are resistant to all known antibiotics, and estimates of death rates from resistant Acinetobacter infections range from 30 to 40 percent. A strain of the tuberculosis bacterium, extensively drug-resistant tuberculosis (TB), which has not yet become prevalent in the United States, is resistant to all currently available TB drugs, and is virtually untreatable (Shah et al., 2007). WHO warns that widespread multidrug resistance is making gonorrhea increasingly hard to treat (Tapsall, 2009).

A Dearth of Innovation Just When It Is Needed

Increasing the likelihood of a post-antibiotic future is an innovation slow-down: the pipeline of drugs to replace ineffective antibiotics has dwindled to a trickle (Boucher et al., 2009; Spellberg et al., 2004). Many major pharmaceutical companies have abandoned the antibiotics business in favor of medicines promising greater profits. Companies that remain engaged face both scientific and regulatory barriers that are compounded by limited return on investment.

Development of a new pharmaceutical costs hundreds of millions of dollars for basic and clinical research, including the investments related to drug candidates that fail. For antibiotics, revenue is limited by the fact the drugs tend to be short-course therapies that are completed in days, weeks, or at most months. Compared to revenues generated from sales of high blood pressure or cholesterol medications that patients take for many years or a lifetime, returns from antibiotics are low. Even an effective new treatment for MRSA, such as daptomycin (Cubicin®), is estimated to generate annual revenues of more than $500 million—which is not insubstantial—this is far below, for example, estimated revenues for a mid-market antipsychotic drug (Cubist Pharmaceuticals, 2010).

Another problem derives from a paradox of sorts. In an effort to preserve the effectiveness of a good new drug, clinicians will often use it only infrequently. In

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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this way, they aim to stave off the emergence of resistance to the new antibiotic, at least until the usefulness of older drugs is exhausted. This is an appropriate and prudent antibiotic-preserving practice, but it further diminishes the flow of at least near-term revenue that an antibiotic developer might expect from rolling out a new product.

An additional economic barrier to antibiotic development is the cost of regulatory approval, which has increased in recent years due to revisions and more stringent standards for clinical trials instituted by the Food and Drug Administration (FDA). Pharmaceutical companies argue that their inability to predict changes in FDA’s requirements prevents them from effectively planning for approval time and costs and further deters them from development of new antibiotics. The Pew Health Group has interviewed companies small and large, and the discussions suggest that this lack of clarity from the FDA about the standard of evidence required for approval discourages companies from pursuing innovative approaches to new antibiotics.

Growing Resistance from Injudicious Use

Overuse of antibiotics by doctors and their patients has long been a major threat to antibiotic efficacy. The medical community has known for decades that some practices, among them the repeated and inappropriate use of antibiotics in clinical settings, are a primary factor in the accelerated rise of antibiotic-resistant bacteria (Costelloe et al., 2010). Numerous international programs are successfully reducing antibiotics use and resistance through public and physician education and improved vaccination guidance (Anonymous, 2008; Goosens et al., 2008). In the United States, efforts to promote more judicious use of antibiotics in children with acute respiratory tract infections appear also to be having positive outcomes (Finkelstein et al., 2003; Grijaldi et al., 2009). That is a start, but countless people with viral infections (such as colds and influenza) incorrectly believe that an antibiotic will help, and they lobby their physicians for these treatments. Additionally, the medical community has underemphasized the strategy of preventing infectious disease as a way of reducing antibiotic use and thereby prolonging the drugs’ efficacy.

One critical but less appreciated and understood part of the microbial resistance dynamic is the long-term and unnecessary use of antibiotics in food animal production (Cohen and Tauxe, 1986; Sarmah et al., 2006). In the United States, it is common for growers of swine, poultry, and, to a lesser degree, cattle to administer low, sub-therapeutic doses of antibiotics to healthy food animals in their feed or water to encourage faster growth and as a prophylactic measure to hedge against overcrowding and other unsanitary and disease-friendly conditions. In addition, in contrast to Europe, most of the antibiotics used on industrial farms in the United States are obtained and administered without the consultation of a veterinarian.

Precise data about antimicrobial use in food animal production in the United

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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States is not publicly available, but analysts say existing data suggest U.S. consumption of antibiotics for these purposes greatly outpaces that of European countries (Aarestrup et al., 2010). Estimates indicate that the non-therapeutic use of antibiotics accounts for anywhere from 35 to 70 percent of all antibiotics sold in the United States (American Health Institute; Mellon et al., 2001)23. In terms of annual quantities, the mass of antibiotics used in animals amounts to between 100 and 1,000 times that used in humans (Feinmen, 1998; Levy, 1998; Witte, 1998). This makes the United States one of the biggest users of antibiotics in food animal production on a pound-per-pound basis in the world (see Figure A7-2) (Aarestrup, 2009; DANMAP, 2008).

Here in the United States, food animal producers use many antibiotics that are similar or even identical to those used in human medicine, among them penicillins, tetracyclines, macrolides, and sulfonamides (Chee-Sanford et al., 2009). This practice encourages the proliferation of resistance to the very drugs that doctors now rely on to save their patients’ lives (Ho et al., 2010). Administering human drugs to animals at sub-therapeutic dosages is like giving evolutionary intelligence away to pathogens so that they will be able to more quickly counter the drugs that might otherwise kill them off in a patient’s body.

Over the last four decades, researchers have demonstrated that feeding antibiotics to healthy food animals over a long period of time promotes the development of dangerous strains of drug-resistant bacteria that can spread to humans (Angulo et al., 2004; McDonald et al., 2001). Here are some of the seminal findings:

  • In 1969, a ground-breaking report from the United Kingdom concluded that the use of antimicrobials in food animal production, especially when used for growth promotion, was of great concern and should be limited and in some cases excluded from animal use altogether (Swann et al., 1969). Since then, a growing body of research has continually strengthened that conclusion.

  • In the 1970s, researchers gave chickens a diet that included tetracycline-supplemented feed. After 6 months, the scientists found that both the chickens and the farm workers were colonized with tetracycline-resistant bacteria (Levy et al., 1976).

  • Studies in the 1980s linked multidrug-resistant Salmonella infections in humans with exposure to cattle on dairy farms (O’Brien et al., 1982). Further studies and molecular subtyping revealed widespread emergence of resistance in Salmonella infections in humans in the United States, which researchers concluded were likely from food animals (GAO, 2004).

  • During the late 1990s and early 2000s, contemporaneous food and hospi-

23

The lower figure is from a calculation by Mellon et al. (2001, p. 57), based on data on antimicrobial use in livestock gathered in 1998 by the American Health Institute.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A7-2 Total antimicrobial use in food animal production.

FIGURE A7-2 Total antimicrobial use in food animal production.

SOURCE: Based on data in DANMAP (2008), p. 31; Aarestrup (2009). Reprinted with permission from Aarestrup (2009).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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tal surveillance linked the introduction of fluoroquinolones to U.S. broiler production with the emergence of resistant Campylobacter infections in humans (GAO, 2004). Although the use of fluoroquinolones in poultry was banned in the United States in 2005, this class of antibiotics is still approved for therapeutic use in cattle and swine and thus continues to exert a selective pressure for the emergence of fluoroquinolone-resistant bacteria that can be transferred to humans. Likewise, a broad collection of antibiotics beyond the fluoroquinolones continues to be approved for use in U.S. broiler production.

Recent data from North America also point to the public health benefits of reducing antibiotics in food production. In 2009, for instance, researchers in Canada found that removing third-generation cephalosporins from broiler hen production resulted in significant reductions in contamination of retail poultry products with ceftiofur-resistant Salmonella enterica and E. coli as well as commensurate reductions in third-generation cephalosporin-resistant Salmonella enterica infections in humans (Dutil et al., 2010).

Buying Time by Using Antibiotics More Judiciously

Some countries have been enacting laws and implementing agricultural practices that help protect the efficacy of antibiotics as well as the interests of food animal producers. In 2006, the European Union banned the use of antibiotics and related drugs for growth promotion purposes in livestock. Beginning in the late 1990s, Denmark became the leader in scaling back the routine use of antibiotics in industrial farming when it instituted a series of policy strategies for preventing antibiotic resistance in humans and animals. Since then, the country has experienced tremendous productivity growth in its swine production, little economic impact, and evidence of lower resistance rates in human and animal pathogens. Denmark is one of the world’s largest pork exporters, accounting for 17 percent of the global export market for pork as well as 22 percent of the world’s exports of bacon and ham (Hamann, 2006). Today, the Danish business interests and farmers are supportive of the actions to limit antimicrobial use in agriculture.

The Danish law ensured that antibiotics remained available to veterinarians for treating sick animals. To prevent misuse, the law stipulated that antibiotics for use in food animals must be accompanied by a prescription from a veterinarian acquired through a valid veterinarian-client-patient relationship and never used for growth promotion.

A key Danish provision prohibited veterinarians from selling antibiotics. In the United States, physicians have long been barred from selling pharmaceuticals to patients because this would constitute a conflict of interest. This restriction also serves as a critical means of avoiding overprescribing. In the United States, veterinarians generate much of their revenue in the sale of pharmaceuticals. This too

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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poses a conflict of interest and an incentive to use antimicrobials. Although this practice of serving simultaneously as both the animals’ doctor and the animals’ pharmacist should be eliminated, policy makers should address veterinarians’ potential loss of income with stricter requirements for actual animal veterinarian visits for prescribing and other incentives.

With pressure growing for the United States to adopt similar antibiotic restrictions, agribusiness opposition has also begun to mount. The American Veterinary Medical Association, for example, claims that the European antibiotic phase-out has caused increased animal deaths and economic hardship on livestock and poultry producers (American Veterinary Medical Association, accessed August 13, 2010).

Research by Danish scientists reveals that antibiotic consumption per kilogram of swine production on industrial farms dropped by more than half between 1992 and 2008, while production increased by 47 percent, from 18.4 million hogs in 1992 to 27.1 million in 2008 (Figure A7-3) (Aarestrup et al., 2010). At the same time, antibiotic-resistant bacteria in food animals have become less prevalent.

The WHO concurs that the antibiotics ban in Denmark has reduced the risks to human health without making a significant financial impact (WHO, 2002). Data from industry and from the Danish government reveal that livestock and poultry production has increased since the ban while antibiotic resistance on farms and in meat has declined (Hammerum et al., 2007; Letter from Dr. Jan Mousing, Chief Veterinary Officer of Denmark, to Congress, August 12, 2009). U.S. industry has expressed alarm over increased treatment of diarrhea and a rise in mortality in weaner pigs in the few years immediately after the ban. The WHO found that diarrhea in young pigs did increase following the ban, creating a short-term need to increase therapeutic antibiotic use. However, levels of diarrhea treatment began to decline after 7 months and were back to the pre-ban levels after 1 year. Weaner mortality has improved considerably in recent years (WHO, 2003).

The Danish Integrated Antimicrobial Resistance Monitoring and Research Programme (DANMAP) confirms that, in general, the numbers of antibiotic-resistant microbes in food animals rise and fall with changes in antibiotic usage (DANMAP, 2000 and 2008). For example, data reported by DANMAP in 2008 indicated that decreases in neomycin, spectinomycin, and macrolide use in pig farming correlated with declines in neomycin, spectinomycin, and erythromycin (a macrolide antibiotic) resistance in bacterial isolates from the pigs. Likewise, elimination of avoparcin (related to vancomycin) and virginiamycin (related to Synercid) as growth promoters resulted in significant reductions in bacteria resistant to these two critical antibiotics among poultry and swine. Similarly, a 24 percent increase in apramycin use in swine feed between 2006 and 2008 correlated with an increase in apramycin/gentamicin cross-resistance among S. typhimurium isolates from pigs (Jensen et al., 2006). And an increase in the use of tetracycline in pigs corresponded with an increase in tetracycline resistance

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A7-3 Danish laws limiting antimicrobial use in swine production resulted in a dramatic decline in non-therapeutic (NTA) use of these agents (dark gray) as well as an overall decline in antibiotic use per kilogram of meat produced.

FIGURE A7-3 Danish laws limiting antimicrobial use in swine production resulted in a dramatic decline in non-therapeutic (NTA) use of these agents (dark gray) as well as an overall decline in antibiotic use per kilogram of meat produced.

SOURCE: Adapted from Aarestrup et al. (2010; 71(7): 726, Fig 2, p 730), with permission of the AVMA.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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among S. typhimurium isolates from pigs and among human bacterial infections (DANMAP, 2000).

Surveillance data from the U.S. National Antibiotic Resistance Monitoring System reveals that resistance rates to some of the most commonly used antibiotics are high among bacteria from food animals. For example, retail meat and poultry surveys indicate that well above 50 percent of the Enterococcus isolates that contaminate these products are resistant to the streptogramins, tetracyclines, and lincosamides routinely used in poultry production. Likewise, aminoglycoside and tetracycline resistance is common among E. coli isolates from these same products. Reducing non-therapeutic antibiotic use will likely decrease resistance and increase the utility of these drugs for disease therapy.

Industry groups have argued that a ban on using human drugs as growth promoters on farms would lead to higher food prices for consumers. A study by the National Research Council indicates that a ban would have a negligible effect, increasing the price of meat by an estimated 0.013 to 0.06 dollars per pound. For consumers, this translates to $4.84 to $9.72 per person each year (National Research Council, 1999). In Denmark, consumers have not had price increases related to antimicrobial restrictions.

The Denmark example shows that it is possible to raise food animals profitably even while reducing the presence of antibiotic-resistant bacteria by eliminating unnecessary antibiotic use (Aarestrup et al., 2001). Pork producers initially opposed the ban but now acknowledge its successful implementation.

Owing to poor regulations and lack of oversight of drug use in food animal production, U.S. consumers do not know what their food is treated with or how often. Nor is there an adequate system in place to test meat and poultry for dangerous antibiotic-resistant bacteria. Government, industry, and professional leaders need to monitor and regulate the use of antibiotic drugs in poultry and livestock more carefully in order to limit the development of resistant bacteria in food animals and the unnecessary threat it poses to people. Any comprehensive antimicrobial preservation and discovery bill would have to make provisions for these functions.

The Way Forward

The rising tide of resistant infections demands a comprehensive policy response (Laxminarayan and Malini, 2007). The failure of the market to deliver effective new treatments must be addressed (Gilbert et al., 2010). But with the pipeline nearly empty, policy makers also must act to preserve the waning effectiveness of existing drugs. That requires a multipronged response to improve infection control and reduce injudicious use of antibiotics in both humans and animals (IOM, 1998). None of these elements can be effective in isolation.

Under the leadership of its co-chairs, the late Nobel Laureate Joshua Lederberg, and Margaret Hamburg, now Commissioner of the FDA, the IOM produced a consensus blueprint on how to best address the global crisis of reemerging microbial infections. That report, Microbial Threats to Health: Emergence,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Detection, and Response, included a series of commonsense policy strategies for addressing antibiotic resistance and the need for new antimicrobial drugs (IOM, 2003):

  1. Limit antimicrobial use to medical situations in which their use will yield results. This means ending the practice of prescribing antibiotics to merely appease patients or because it has become the normal thing to do.

  2. Discourage misuse, such as poor compliance by patients or low-dose regimens that only accelerate the rise of resistance bacteria. Specifically, the IOM urged the FDA to ban any classes of antibiotics used in human medicine from being used as growth promoters in the livestock and poultry.

  3. Reduce the need for antibiotic treatment by reducing the rates of infection through better hygiene, vaccines, and other disease-prevention measures.

  4. Develop and enact policies and incentives to spur innovation in new antibiotics and other tactics for treating infections.

These fundamental consensus points can provide the basic building blocks for comprehensive legislation that could preserve the medical value of antibiotics while fueling the next generation of therapies for microbial infection. Such a bill would recognize that antibiotics are a vital, shared public resource. Only a comprehensive policy framework designed to both preserve the efficacy of existing antibiotics and spur innovation of new drugs will provide a sustainable solution.

Currently, numerous specific legislative proposals exist that link to different components of the IOM framework:

  • The Strategies to Address Antimicrobial Resistance (STAAR) Act, backed by the Infectious Diseases Society of America (IDSA), would bolster existing surveillance, data collection, and research. It would strengthen the public health infrastructure essential to the long-term management of antibiotic-resistant diseases in such settings as hospitals, clinics, veterinarians’ offices, and animal production operations.

  • The Preservation of Antibiotics for Medical Treatment Act (PAMTA) of 2009 would phase out the routine use of seven classes of medically important antibiotics (penicillins, tetracyclines, macrolides, lincosamides, streptogramins, aminoglycosides, and sulfonamides) in healthy food animals unless manufacturers can prove reasonable certainty of no danger to public health from resistance. New drugs are required to meet the same standard. PAMTA critically shifts the burden of proof to the drug manufacturers to ensure antibiotics used in farm animal production have no human health impacts.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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In addition to provisions like those in STAAR and PAMTA to curtail and manage antimicrobial resistance, a comprehensive antimicrobial preservations and discovery bill must include a set of powerful incentives to spur innovation by scientists and pharmaceutical companies to develop new antibiotics, better diagnostics for use at the “point of care,” and vaccines to prevent bacterial infections.

Public policy has long played a role in antibiotics innovation, beginning with the public-private partnership that led to the large-scale introduction of penicillin in 1944. Congress has taken a number of approaches to encourage pharmaceutical investment. The Orphan Drugs Act, passed in 1983, stimulates the development of drugs for rare but serious disorders, using a mix of pre-market, or “push,” incentives, such as research and development (R&D) tax credits and help with the cost of clinical trials, as well as post-market “pull” incentives, including longer periods of exclusivity during which the drug does not face generic competition. Similarly, the Best Pharmaceuticals for Children Act provides companies with extended exclusivity in exchange for conducting pediatric research on their products. And in 2006, Congress moved to create the Biomedical Advanced Research and Development Authority to facilitate the public- and private-sector R&D of antimicrobials and other emergency countermeasures to respond to potential bioterrorist, pandemic, or other urgent medical threats.

Any successful policy-driven effort to stimulate antibiotic development will have to recognize that new drug candidates may originate and move through a variety of pathways, including large pharmaceutical companies, small and mid-sized companies, or academic laboratories. Each enterprise will have distinct needs and may respond to different types of incentives. Therefore, the legislation will need to include a range of mechanisms. In addition to the specific measures mentioned above, possible innovation incentives include funding to defray cost of clinical development or approvals; grants or partnerships to facilitate transitional research; technical assistance, particularly for small companies that would benefit from help in navigating the federal agencies that facilitate drug development and approval; and advance market commitments, by which the sales volume of a product is guaranteed in advance.

It also is essential that the FDA provide clarity on the standards for approval of new antibiotics, which have been repeatedly revised in recent years. Approval standards must remain rigorous and scientifically appropriate in order to protect patients, but pharmaceutical companies must feel confident that they can embark on drug development with some predictable understanding of the scale and cost of the required trials.

Besides enacting antibiotics-preserving policy, better professional practices and behavior regarding antibiotic use is a must. In this regard, the FDA, the CDC, and professional health organizations, academia, agribusiness, and the pharmaceutical industry should increase their efforts to reduce the inappropriate use of antimicrobials in human and animal medicine. Important tactics here include

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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renewed efforts in outreach and improved education of healthcare professionals and the public about the dangers resulting from the misuse and overuse of antibiotics. These organizations also should encourage the development and routine use of rapid diagnostic tests to determine the specific viral or microbial causes of infections and ensure appropriate treatments are applied.

As Joshua Lederberg said repeatedly: “In the race against microbial genes, our best weapon is our wits, not natural selection on our genes” (Lederberg, 1997).

Scientists, physicians, and public health experts agree. The WHO, the American Academy of Pediatrics, the American Nursing Association, the American Society of Microbiology, IDSA, and the American Medical Association all echo the IOM recommendations and have repeatedly called for a policy response to the crisis of antimicrobial resistance. Yet, as a nation, we have failed to take action.

Donald Kennedy, president emeritus of Stanford University who served as commissioner of the FDA from 1977 to 1979, proposed eliminating the use of penicillin and tetracycline as growth promoters in food animals more than 30 years ago. Kennedy and Stanley Falkow, one of the nation’s leading microbiologists, later described the antibiotic debate as a “struggle between good science and strong politics” (Kennedy and Falkow, 2001). Agribusiness proponents of this application won that policy decision by pressuring Congress to shelve the FDA proposal to limit the practice. Kennedy and Falkow concluded that “science lost.”

With the impending threat to our crown jewel in medicine—antibiotics—we cannot afford to let science lose. Now, more than ever, we need to ensure that science effectively informs and drives our antibiotic policy strategies, not politics. In 1863, with the approval of President Abraham Lincoln, the U.S. Congress chartered the National Academy of Sciences for this very purpose: to advise the federal government on scientific and technological matters. As such, the nation needs the IOM to play a more prominent role in translating science for policy makers and advancing their existing recommendations. If the IOM does not lend a voice to its findings, not only will science lose again, but we may be sped along to Frieden’s dire predictions of a post-antibiotic era.

Acknowledgments

This manuscript was prepared with valuable assistance from Merry Buckley, Lance Price, and Pew Health Group staff members Allan Coukell, Laura Rogers, Gail Hansen, and Ivan Amato.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A8
ANTIBIOTIC EFFECTIVENESS: NEW CHALLENGES IN NATURAL RESOURCE MANAGEMENT24

Markus Herrmann25 and Ramanan Laxminarayan26,27,28

Abstract

Problems of optimal natural resource extraction that were first addressed by economists in the contexts of fisheries and forests have reemerged in the context of a newly recognized resource: antibiotic effectiveness. This review

24

Reprinted with permission from Annual Reviews, posted online 20 April 2010.

25

CRÉA-GREEN and CIRPÉE, Department of Economics, Université Laval, Québec, Québec G1V 0A6, Canada; email: markus.herrmann@ecn.ulaval.ca.

26

Resources for the Future, Washington, DC 20036; email: ramanan@rff.org.

27

Princeton Environmental Institute, Princeton University, Princeton, New Jersey 08544.

28

Corresponding author.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

introduces economists to the growing literature on optimal use, innovation, and regulation of antibiotic effectiveness. Along the way, we draw links and parallels to similar problems in the management of other resources with which economists may be more familiar, and we address new questions that have arisen in the context of antibiotic effectiveness but that are also relevant to other resources.

1.
Antibiotic Effectiveness as a Natural Resource

Although humans may have known of antibiotics for centuries, the formal discovery of antibiotics occurred in 1929.29 Improvements in public health and medicine and a decline in infectious disease mortality preceded the widespread use of penicillin, but since the introduction of antibiotics in 1942, they have made possible further reductions in deaths and disability from infectious disease. Perhaps equally important, they have facilitated the vast expansion of other medical interventions, such as kidney and heart transplants, by allowing clinicians to prevent surgical site infections and to suppress the immunity of organ recipients.

Resistance to penicillin emerged soon after its introduction and was linked to patient deaths in the early 1950s (Abboud and Waisbren, 1959). Since then, bacteria have grown increasingly resistant to available antibiotics. In recent years, pan–drug resistance has emerged: Bacteria are resistant to nearly all antibiotics that were earlier active against them. The prevalence of high-level penicillin resistance in Streptococcus pneumoniae in the United States rose from 0.02% in 1987 to nearly 20% in 2004 (Laxminarayan et al., 2007). Over roughly the same period, the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) in hospitals climbed from roughly 2% to more than 50% in many U.S. hospitals. Although the United States is among the heaviest users of antibiotics in the world on a per capita basis, the situation is even worse in some other countries, where infections spread more rapidly because of a lack of infection control in hospitals and inadequate water and sanitation in the community. For instance, in Vietnam, gram-negative organisms like Acinetobacter and Klebsiella are resistant to all antibiotics approved for human medicine; in addition, resistant organisms are commonly found in the environment (Duong et al., 2008).

Most antibiotics are derived from natural organisms like fungi, which use these compounds as weapons against bacteria. Resistance to antibiotics has always existed in bacteria, albeit at a very low frequency (perhaps one in a million or less), and predates the use of antibiotics as a treatment for infectious disease

29

Tetracycline has been identified in the bones of Nubians buried between 350 and 550 A.D. in what is now the Sudan (Bassett et al., 1980). That the Nubians were aware of this antibiotic is supported by two other bits of evidence: A bacterium from which many antibiotics are derived, streptomycetes, is common in the Nubian Sudanese desert, and infectious disease rates among this Nubian population were apparently low.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

(Levy, 1992). Human use of antibiotics has vastly tilted the balance of survival in favor of bacteria that evade antibiotics. In the changed environment with large quantities of antibiotic use, forces of natural selection favor resistant strains.30 However, carrying resistance genes is costly from an evolutionary standpoint and can be disadvantageous in an antibiotics-free environment. Some studies have demonstrated that resistant strains face an evolutionary disadvantage in an antibiotics-free environment. Biologists call this the fitness cost of resistance and have found it to be significant for some combinations of bacteria and antibiotics (Musher et al., 1977; Bennett and Linton, 1986; Bouma and Lenski, 1988), but not for others (Schrag et al., 1997; Björkman et al., 1998).

The problem of resistance is common in other efforts to control organisms that are harmful to humans and human enterprise. Resistance is observed in bacteria (to antibiotics), malarial parasites (to antimalarial drugs), viruses (to antivirals), and pests (to pesticides). In each case, application of control measures increases the likelihood that they will be less effective when used in the future. The effectiveness of the control agents can therefore be modeled as a natural resource in much the same way as are fish, trees, oil, or other resources. As with other resources, the optimal management of antibiotic effectiveness is determined by the biological dynamics of bacterial evolution of resistance, the spread of infection, and the demand for antibiotic treatment.

This review of the current literature on the economics of managing antibiotic effectiveness is organized as follows. In Section 2, we discuss the literature on the optimal use of antibiotics. Section 3 presents models in which antibiotic effectiveness is renewable. In Section 4, we address the impact of market structure on antibiotic use. Section 5 covers problems of managing antibiotic effectiveness as a global public good. In Section 6, we cover optimal investment in research and development (R&D) of new antibiotics. Section 7 discusses the economic costs of resistance. Section 8 concludes the paper and suggests future avenues for research.

2.
Optimal Use of Antibiotic Effectiveness

Brown & Layton (1996) discuss resistance as a dynamic externality.31 Laxminarayan & Brown (2001) were the first to use a dynamic disease framework to model antibiotics as a natural resource. In their formulation of an optimal con-

30

Natural selection is not the only mechanism for the emergence and spread of resistance. Bacteria can directly transfer resistance genes between each other on packets known as plasmids. This method is responsible for the geographical spread of resistance. Plasmid transfer is expensive, from a biological standpoint, and is encouraged by the use of antibiotics.

31

In the literature on the optimal use of pesticides, Hueth & Regev (1974) model pest susceptibility (to pesticides) as a stock of nonrenewable natural resource that is costless to use in the short run but extremely expensive to replace in the long run. Comins (1977, 1979) treats pest susceptibility as an exhaustible resource and determines that the cost of resistance is analytically equivalent to an increase in the cost of the pesticide.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

trol problem combining an economic, intertemporal objective with a deterministic compartment model of disease transmission derived from epidemiology, the relative proportion of individuals infected by antibiotic-susceptible bacteria to the overall infected population represents a measure for the treatment effectiveness of the antibiotic drug, the evolution of which depends on the use of antibiotics.

Antibiotic treatment implies social benefits and costs that are external to the person receiving treatment. Benefits include the treatment of sick patients, which also has the dynamic effect of reducing infections in the future. The cost of antibiotic use is not just the treatment cost that is borne by the patient or the insurance provider; it is also the shadow cost associated with the decline in its effectiveness. At the optimum, an antibiotic should be used when the full marginal benefits equal the full marginal costs.

Laxminarayan & Brown (2001) find that, depending on the relative production cost and the speed at which effectiveness declines, an initial phase may exist during which it is optimal to use only one antibiotic. For instance, when antibiotics have the same production cost but differ with respect to their level of effectiveness, the more effective drug should be used in the first phase because it procures at the margin a higher number of effective treatments and avoided future infections. This phase continues until the two antibiotics have equal effectiveness. It then becomes optimal to use them in a proportion that is inversely related to the speed at which their effectiveness declines.

The basic intuition underlying this conclusion parallels that of the optimal extraction of different ore qualities, when production costs depend on current extraction rates and remaining stocks (Weitzman 1976). As with resource pools with declining quality, there are three conditions under which simultaneous extraction from more than one resource pool is optimal. First, the marginal costs of extraction from the multiple pools may be identical, implying that it is optimal to engage in simultaneous extraction.

The other two reasons are unique to antibiotics. One is that the likelihood of resistance is a nonlinear function of antibiotic use. In most other resource problems, the stock of the resource decreases linearly with the use of the resource. With antibiotics, the marginal impact on effectiveness of antibiotic use is increasing. Therefore, simultaneously deploying two antibiotics reduces the likelihood that resistance to either of them will develop. The other reason is that, even if an infection is resistant to one antibiotic, it is treatable with a second antibiotic. So simultaneously treating the population with two antibiotics may lower resistance because effectiveness is regained when bacteria resistant to one antibiotic are treated with a different antibiotic.

Those considerations alter the standard prescription that resources should be used strictly in order of increasing marginal cost (Weitzman, 1976) and imply that when resistance arises as a consequence of antibiotic use, it may be shortsighted to use a single antibiotic on all patients just because that antibiotic appears to be the most cost-effective option (Laxminarayan and Weitzman, 2002). The

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

trade-off between economic costs and epidemiological advantage is described by Laxminarayan & Weitzman, who show that it may be optimal, from society’s point of view, to use different drugs on different but observationally identical patients and include on this menu of drugs some that may not be cost-effective from the individual patient’s perspective. The notion of treatment heterogeneity—the simultaneous use of different types of antibiotics—is consistent with the finding in Laxminarayan & Brown (2001) but addresses a different question: which antibiotics are optimal to include on a menu for simultaneous use at a population level. Other studies confirm the economic value of treatment heterogeneity (Bonhoeffer et al., 1997; Boni et al., 2008).

Thus far, we discuss models in which antibiotic effectiveness can be interpreted as a nonrenewable resource and in which more than one antibiotic is available to fight an infection. For antibiotics, the criterion of the most cost-effective treatment does not hold; instead, the overall social costs and benefits of using antibiotics must be considered. In the next section, we address models in which antibiotic effectiveness is renewable.

3.
Antibiotic Effectiveness as a Renewable Resource

Wilen & Msangi (2003) extend earlier models by assuming that the effectiveness of antibiotic efficacy represents a renewable resource. Such a modeling is appropriate when the drug-resistant bacterial strain incurs a positive fitness cost, in which case a low-enough treatment rate allows the population of bacteria to reach a sustainable equilibrium for the effectiveness of the drug. Whereas in the fishery case, multiple sustainable equilibria are attainable and depend on the regeneration rate of the remaining stock of fish in the sea, the regeneration of antibiotic effectiveness is independent of the stock of infection. In the model by Wilen & Msangi, the independence of the stock of infection occurs because the overall population is constant. When the economic objective is to minimize the discounted cost associated with infection, the authors show, the typical optimal solution combines an initially extreme treatment with subsequent intermediate controls. The extreme control corresponds to treating the overall infected population. This comes at the cost of decreasing the effectiveness of the drug but at the benefit of lowering, at least temporarily, the level of infection considerably below its steady state. The extreme control remains optimal as long as the marginal benefit of treating the infected population outweighs the marginal shadow cost of lowering antibiotic effectiveness. Once the two are in balance, an intermediate fraction of the infected population should get antibiotic treatment. This fraction eventually converges to the critical value at which the selection of the susceptible strain is exactly compensated by the selection of the resistant one.

In contrast, Rowthorn & Brown (2003) model two infections, each of which can be fought with a particular antibiotic only. At the time of treatment, the physician may be unaware of the specific bacterial strain that he or she is treating

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

and chooses the best possible treatment, knowing that a successful treatment may cure the patient but may also increase the likelihood of resistance in the future. The authors find that it makes sense to treat all patients with the antibiotic that is effective against the more prevalent strain, even if that antibiotic is relatively more expensive. Although one may not necessarily encounter the problem of two drugs used to treat two mutually exclusive diseases in a clinical setting, the model developed here offers a framework and provides a point of departure for more realistic variations of the problem.

Herrmann & Gaudet (2009) build on the model of renewable effectiveness by Wilen & Msangi (2003) and compare the optimal use of antibiotics with a market outcome in which drug producers have open access to a common pool of antibiotic effectiveness. As in the open-access fishery, economic rents are dissipated such that the price of the resource equals its average production cost and no producer accounts for the future evolution of the resource. The demand for the antibiotic plays a crucial role in the model dynamics: Demand shifts downward (upward) as the level of effectiveness decreases (increases). In equilibrium, this movement of the demand function makes the fraction of individuals buying the antibiotic adjust to the current level of antibiotic effectiveness and allows the latter to reach a sustainable level in the long run. This level may be higher or lower than the one that would be reached in the social optimum. Notably, when the average production cost is high, so is the price of the antibiotic, and a relatively small fraction of individuals buy the antibiotic over time. This comes, however, at the social cost of relatively high infection levels when out of steady state. To treat a higher fraction of the infected population, a lower-than-average price, which is lower than the average cost, may be optimal, implying that the production or the consumption of the antibiotic should be subsidized to make the market outcome coincide with the social optimum.

Finally, an important question of optimal use that has been discussed widely in the medical literature involves cycling. The optimality of treatment heterogeneity, discussed above, implies that cycling antibiotics may not be the best strategy, even though it has received much attention in the medical profession as a way to address the growing resistance of bacteria to antibiotics in hospitals (McGowan, 1986; Niederman, 1997; Bergstrom et al., 2000; John and Rice, 2000). Cycling hinges on the notion of the fitness cost of resistance: the evolutionary disadvantage placed on resistant strains in an antibiotics-free environment. If the fitness cost associated with bacterial resistance to antibiotics is high, the argument goes, then one can periodically remove an antibiotic from active use until it recovers its effectiveness. In contrast, if fitness cost is insignificant, then antibiotic effectiveness always declines, and it makes no sense to cycle antibiotics.

In this case, introducing economics can alter the conclusions reached by purely epidemiological models, as well as enrich their applicability to the real world, where economic costs play an important role. Cycling is suboptimal only

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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when antibiotic treatment costs are convex32 (Laxminarayan and Brown, 2001). This may not be the case in a hospital setting, where maintaining a drug on the hospital formulary entails a fixed cost, for shelf space, plus any cost associated with returning unused or expired products to the wholesaler. Furthermore, some drug companies offer volume discounts and even special prices if their products are put on the formulary and substitutes are excluded.33 Such factors introduce nonconvexities into the cost function and may make cycling of two antibiotics economically efficient. Switching from one antibiotic to another also entails its own costs, such as the administrative effort of taking one drug off the formulary and adding another one and the cost associated with educating physicians and nurse practitioners about a new drug. In the absence of these nonconvexities, there may be no economic rationale to cycle antibiotics.

4.
Market Structure and Antibiotic Use

The foregoing market equilibrium of open access represents a benchmark analysis for a generic industry selling an antibiotic once its patent has expired. Before that occurs, a single firm sells the antibiotic and thus controls at least to some extent the evolution of antibiotic effectiveness. More particularly, to what extent the evolution of antibiotic effectiveness can be controlled depends on whether the effectiveness of the antibiotic is linked to other antibiotics via a common resource pool of effectiveness.

Mechoulan (2007) and Herrmann (2009) consider the case in which the effectiveness of an antibiotic can be managed perfectly by a monopolist and the costs related to innovation can be considered sunk. Mechoulan (2007) shows that, although it may be socially optimal to eradicate a disease, a monopolist does not do so because the disease represents market size to the firm. With nonrenewable antibiotic effectiveness being added (in an ad hoc manner) into this model, the author shows that a reactivation of the patent after its initial expiration can be welfare improving. This occurs when the price charged by the monopolist is closer to the socially optimal price than to the price charged by the generic industry.

Herrmann (2009) characterizes the pricing policy and its impact on renewable antibiotic effectiveness and infection in a combined epidemiological-economic framework, as explained above. As the end of the patent approaches, the monopolist’s pricing policy bears greater resemblance to the myopic monopolist’s policy,

32

Typically, in economic analysis, marginal costs are assumed to be convex—that is, they increase with use and at an increasing rate. However, when the cost associated with use is fixed, the marginal cost of using the first unit is much greater than the marginal cost of each additional unit.

33

For example, hospitals would be quoted the lowest price for levofloxacin from Ortho-McNeil if ciprofloxacin (an antibiotic made by a rival firm) were not on the formulary. This discount is offered, regardless of how much levofloxacin is used. Therefore, having ciprofloxacin on the formulary is costly in terms of increasing the price of levofloxacin to the hospital (personal communication from D. Black, Dept. Pharm., Univ. Washington, January 30, 2000).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

as less value is attached to the quality and market size of the antibiotic. This decreases the monopolist’s opportunity cost of selling the antibiotic, such that the amount of antibiotics sold increases, and decreases future levels of antibiotic efficiency and infection. This result depends crucially on the hypothesis that no profits are to be made in a generic industry—that is, there is open access to the pool of effectiveness. Whether a prolongation of the patent is socially desirable hinges on the relative values of antibiotic effectiveness and infection. Clearly, monopolistic pricing benefits the evolution of effectiveness more than the open-access outcome via lower treatment rates. However, this benefit comes at the cost of higher levels of infection because it represents a valuable asset to the monopolist. Thus, a prolongation of the patent is socially desirable only when infection is not an issue—when infection levels are relatively low compared with the level of antibiotic efficacy.

An important characteristic of an antibiotic is that it may have multiple end uses, implying multiple markets to which it can be sold. For instance, consider an antibiotic that can be used to treat humans and is also a growth-enhancing product for livestock. These two markets are likely to differ in size and in quantity responses to price changes. In such a context, Fischer & Laxminarayan (2004) show that a monopolist will extract the pool of antibiotic effectiveness faster than what is socially optimal, even if the demand in each market has a constant, but differing, price elasticity. Because there is only one resource pool with a unique shadow cost of extraction, it would be socially optimal to sell the antibiotic at identical prices in both markets. However, the monopolist discriminates between markets, lowering the drug’s price in the market characterized by the higher demand elasticity while increasing it in the other market compared with the social optimum. The combined effect of the price discrimination in both markets is such that antibiotic effectiveness is extracted at a higher rate over all periods.34

5.
Transboundary and Externality Problems

An early insight into the nature of antibiotic resistance was provided by Salant (2003), who likened resistance to a congestion problem. A key feature of the congestion problem is that enclosure of some resources but not others could lead to resource use that is suboptimal from a societal perspective (de Meza and Gould, 1992). For instance, efforts to reduce overgrazing and environmental degradation have focused on encouraging pastoralists to confine their animals to fenced enclosures, on the basis of the argument that overgrazing is more

34

The authors show that the faster pace of extraction by the monopolist would persist, even if arbitrage between markets were possible. Although a monopolist is then constrained to sell the antibiotic at identical prices, Fischer & Laxminarayan (2004) show that the price elasticity of the aggregated demand decreases over time, implying that the price rises at a rate higher than the interest rate. Any speculation would constrain the monopolist’s price path even further.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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likely to be avoided if pastoralists “own” the land. However, the effect of private enclosures on the remaining grazing lands that remain open access has often not been recognized. A possible regulatory response to the cross-resource spillover problem may be to impose a levy per animal to ensure against overgrazing. Alternatively, one could impose a quota restriction on the number of cattle allowed to graze on a common pasture.

Congestion spillovers across resources are also relevant in the case of antibiotic effectiveness. Patents permit enclosure of the effectiveness of new antibiotics but also confer monopoly rights. Other antibiotics have long been in use and are no longer under patent; they are in an open-access regime. Although patents may give a single firm the incentive to care about resistance to a drug, the patentee is likely to ignore the effect of her pricing decision on exacerbating resistance to antibiotics that may be in the generic domain, and she may overprice or under-use her antibiotic relative to the socially optimal level. Fischer & Laxminarayan (2009) analyze the optimality of price and quantity instruments in regulating resource use when there is uncertainty about congestion costs and show that taxes on antibiotics are preferable to quotas on antibiotic use, and strictly so when demand for antibiotic treatment is less than perfectly elastic.

The explanation arises from the fact that the tax still allows both markets—particularly, the enclosed market—to adjust to the cost shock, whereas the quota does not. This result differs from the well-known Weitzman result, in which the overall level of the pollution externality does not affect the marginal abatement cost curve and the relative slopes drive the preference for a tax or quota (Weitzman, 1974). Here, because the congestion externality for the open-access supply is defined by the difference between marginal and average costs, a shock shifts that market supply (average cost) curve in the same direction as the social marginal cost curve. Thus, whereas in the Weitzman case the tax fixes the price signal for producers, here the tax is not the price; rather, it influences the price, as do the cost shocks. A quota, in contrast, makes supply invariant to shocks, as in the Weitzman case. As a result, the relative trade-off is not between a too-rigid price and a too-rigid quantity but between a flexible, suboptimal price and a too-rigid quantity. Without the spillovers from partial enclosure, however, taxes are equally preferred to quotas.

Congestion spillovers across resources (antibiotics) are one challenge; spill-over of infection across one hospital, one health care institution, or one country is another. Smith et al. (2005) explore incentives for hospitals to invest in control of antibiotic-resistant bacteria when patients coming from other facilities are colonized (and therefore potentially infectious). In a result that is no surprise to economists, Smith et al. find that incentives to control drug resistance are greatest when there is only one hospital and decline as there are more hospitals. However, in a result that demonstrates the value added by disease models, these researchers find that investments in infection control initially increase in response to the growth in the influx rate of patients carrying resistant infections and then drop

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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to a minimum. This finding implies that efforts to manage antibiotic effectiveness in any single country or hospital has implications for incentives to manage elsewhere and that disease dynamics play a strong role in determining when such efforts are strategic substitutes across countries or institutions and when they are strategic complements.

Efforts to manage resistance across national borders would have to rely on international agreements and regulations (Walker et al., 2009) or on tax or subsidy instruments (Arrow et al., 2004). In the absence of such agreements and regulation, countries are unable to commit themselves to an optimal use of antibiotics, which would be in all countries’ interest. As a consequence, a country makes a too-intensive use of antibiotics as an input into its production at a macroeconomic level (Cornes et al., 2001). A supranational authority would have to consider both the externality benefits of antibiotic use, in terms of reducing infections, and the costs, in terms of resistance (Rudholm, 2002). Whether antibiotic consumption should be taxed or subsidized to reach the first-best outcome then depends on the relative magnitude of the externalities.

A relatively new class of antimalarial drugs, called artemisinins, requires a different way of thinking about optimal subsidies to manage resistance. When chloroquine, a once powerful antimalarial drug, became obsolete, the public health world was left with the challenge of using the last remaining effective drug class, artemisinins, in an effective manner. The World Health Organization (WHO, 2001) has recommended that artemisinin be used in combination with a partner drug that is unrelated in its mechanism of action and genetic bases of resistance, so that a single mutation cannot encode resistance to both components. Artemisinin combination treatments (ACTs), if used instead of monotherapies of either artemisinin or the partner drug, should slow down the emergence of anti-malarial resistance. However, the WHO guidelines are routinely flouted because monotherapies are much less expensive than ACTs. In response to this problem, an Institute of Medicine report (Arrow et al., 2004) recommended establishing an international fund to buy ACTs at producer cost and to resell them at a small fraction of that cost.

On economic efficiency grounds, there is a second-best case for subsidizing ACTs because the ideal policy of taxing monotherapies and other antimalarials according to the marginal external cost from the elevated risk of resistance evolution is infeasible, given the widespread use of these therapies in the informal sector. The efficiency argument is further strengthened by the positive externality to the extent that effective treatment of one individual reduces the risk of infection transmission to other individuals. Laxminarayan et al. (2007) show that it is possible to determine the optimal subsidy in a dynamic-disease-modeling framework. Bioeconomic analysis has been helpful for determining whether the social benefit from the subsidy, in terms of delayed resistance and saved lives, exceeds the social cost of resistance because of increased use of ACTs (Laxminarayan et al., 2006). Such analysis was also instrumental in turning an idea into the

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Affordable Medicines Facility for malaria, a global financing system launched in early 2009.

6.
Antibiotic Innovation

In recent years, growing resistance levels have given rise to fears that antibiotic innovation cannot keep pace. Ellison & Hellerstein (1999) argue that a society that underevaluates antibiotic diversity’s contribution to addressing the problem of bacterial resistance also tends to value insufficiently the innovation of new antibiotics. They hypothesize that this effect is reinforced in the context of a competitive industry. Laxminarayan et al. (2007) argue that the private demand for new antibiotics may be considerably lower than what would be socially optimal, because private demand tends to be shortsighted. Consequently, if the current market supply of new antibiotics responds to the private demand, it may also be suboptimal.

As for any type of product innovation, a determining factor is patent protection. The patenting of new antibiotics has allowed firms to recover their previous spending on R&D.35 However, because of the particularly long regulatory control process (as exercised by the U.S. Food and Drug Administration) intended to ensure the safety of any new drug for human use, the nominal 20-year period of patent protection is considerably reduced, making the innovation of new antibiotics less profitable. A report by the Office of Technology Assessment (OTA, 1995) notes that the regulatory process shortens patent life by effectively seven to ten years. This clearly reduces the incentive for pharmaceutical firms to innovate.

A patent conveys an exclusive property right to sell a given antibiotic drug. Whether this incentive is sufficient for the patentee to incur the considerable R&D cost and, at the same time, to account for the intertemporal evolution of antibiotic effectiveness of its drug depends crucially on the corroboration of cross-resistance of the patented antibiotic with respect to other antibiotics. The OTA (1995) report advances the idea of increasing incentives for innovation by prolonging the duration of antibiotic length in exchange for restrictions on its use to fight a particular infection. Laxminarayan (2002) discusses the optimal breadth of a patent when there is a common pool of effectiveness related to antibiotic use in humans and livestock. The analysis shows that a narrower patent breadth is

35

Because antibiotics are derived from fungi naturally present in the environment, it was initially questionable whether they could be patented, because their invention process lacked the researcher’s “flash of creative genius,” which was necessary in the United States for obtaining a patent in the first half of the twentieth century. Kingston (2000) discusses this and presents historical notes on the invention and innovation of penicillin and streptomycin in particular. In fact, the invention of antibiotics results from having a portfolio of research topics in which thousands of combinations of bacteria are actually tested (penicillin is an exception). The particularity of this invention process was accounted for in the U.S. Patent Act of 1952, in which the initial criterion of a “flash of creative genius” was replaced by a requirement for an “inventive step” and by a “nonobvious test.”

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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associated with a more rapid exhaustion of antibiotic effectiveness by the patent-holding firm. The optimal patent breadth then brings into balance the deadweight loss, which results from the greater market power of a firm that holds a broader patent, and the social benefits of increasing a firm’s incentives to conserve antibiotic effectiveness. Broader patents may discourage marginal innovations, such as new drugs that are closely related to existing antibiotics, and instead encourage nonmarginal innovations of new classes of antibiotics and increase incentives to conserve their effectiveness.

Laxminarayan et al. (2007) suggest a sui generis right for antibiotic drugs whose patents have expired. In particular, the rights associated with drugs in the same pool of antibiotic effectiveness should be assigned to the same company or individual to permit better control of antibiotic effectiveness and to provide better incentives for further innovations. This type of right would be a surrogate for the physical territory and related property rights in the case of other natural resources.

A thorough modeling of the many aspects related to the innovation of antibiotics is still missing. Fischer & Laxminarayan (2005) provide a first sketch of how a single firm exploits successive pools of effectiveness and how this compares with the social optimum. Modeling antibiotic effectiveness as a nonrenewable resource and abstracting from issues related to cross-resistance, the authors address the sequential development and exploitation of a series of resource pools on behalf of a monopolist and compare the extraction path to the social optimum. The process of antibiotic innovation is captured by a fixed setup cost, which has to be incurred to access a subsequent resource pool. Whether the depletion of effectiveness, and thus the process of innovation, is faster under monopoly than in the social optimum depends principally on the demand schedule and the number of remaining resource pools. The opportunity cost of postponing the switch to the next resource pool depends on the current and future values of the monopolist’s and social planner’s optimization problem, as well as the speed at which an existing resource pool is extracted if no new pools are developed. In particular, the authors show that for a constant elasticity demand and zero extraction cost, the opportunity cost of waiting is higher for the monopolist than for the social planner when there are many resource pools left in the line, such that the monopolist extracts the resource relatively faster. The result is reversed when there are only a few resource pools left.

Cairns & Davis (2007) embed the former result in a more general setting, in which the setup cost may vary over time and in which the social surplus as well as the profits derived from the exploitation of the resource may be nonstationary. The formulation of the problem of when to invest, at a fixed cost, in a new resource pool leads to a reinterpretation of Hotelling’s r-percent rule. The rule applies not to the evolution of the scarcity rent of a resource unit when there are “lumpy” setup costs but rather to the rate of change in the net present value (also called forward value in finance) at the optimal investment date of the particular

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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resource project under consideration. When investment occurs at the optimal time, the current market value of the overall project rises at the rate of interest. When one is dealing with the sequential exploitation of multiple resource pools, it may be optimal not to extract the resource for a period of time, notably if the setup cost is high or the benefits derived from the use of the resource pool are low (because of the nonstationary nature of the problem). In particular, as long as the forward value of a yet-to-be-developed resource pool rises faster than the rate of interest, it is optimal to wait.

7.
Empirical Work

Two parameters drive optimal use of antibiotics: first, the relationship between antibiotic use and resistance and second, the magnitude of the biological fitness cost of resistance.

Antibiotic resistance is often positively correlated with antibiotic use. However, the direction of causality is unclear because, although antibiotic selection pressure contributes to resistance, higher resistance also necessitates greater antibiotic use. Moreover, the influence of antibiotic use on the level of infection complicates a direct estimation of the relationship. Comprehensive data sets are only now being assembled to estimate this function. Phelps (1989) calculates the resistance response for gentamicin and amikacin use and finds that a 1% increase in the use of each drug leads to a 0.15% increase and a 1.1% increase in resistance, respectively. Most other studies are unable to control for the effect of antibiotic resistance on use. For instance, Kaier & Frank (2008) document the use of fluoroquinolones and the incidence of hospital-acquired MRSA, finding a 0.55% increase in resistance in Geneva and a 0.32% increase in Belfast, but there is no evidence that fluoroquinolone use has any effect on MRSA. Considering not only antibiotic consumption but also a preventive measure, an alcohol-based hand sanitizer, on the incidence levels of MRSA and Clostridium difficile, Vernaz et al. (2008) can explain up to 57% and 17% of the variation in the level of infection, respectively. No particular policy related to antibiotic use was in place during their time series analysis. The consumption of antibiotics belonging to the fluoroquinolone and cephalosporin classes had a lagged effect of one month and four to five months, respectively, on MRSA; C. difficile was influenced only by broad-spectrum cephalosporins (with a one-month time lag).

The analysis by Aldeyab et al. (2008) also considers MRSA infections and generally confirms the aforementioned results. Their time series model explains up to 78% of the variation in hospital-acquired MRSA and accounts also for the influx of positively tested MRSA patients into the hospital and the number of patients tested for MRSA when in the hospital.

The second critical parameter is the fitness cost of resistance, which tells us how rapidly antibiotic effectiveness recovers when antibiotic selection pressure is removed. Studies in the medical literature have observed a decrease in

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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resistance after a period of sustained decrease in antibiotic use. In one Finnish study, a reduction in the overall use of macrolide antibiotics in the community was followed by a decrease in erythromycin-resistant Streptococcus pyogenes (Seppala et al. 1997). A similar study observed a decrease in penicillin-resistant S. pneumoniae following a decrease in use of antibiotics in children (Kristinsson, 1997). Sundqvist et al. (2007) find a significant but small estimated fitness cost of 1–2% of Escherichia coli resistant to trimethoprim. However, in vitro, no fitness cost is observed. This finding dampens the hope that a reduction in antibiotic consumption may reverse the rising trend of antibiotic resistance. Indeed, the authors find that a two year decrease of trimethoprim consumption to 15% of the former consumption level effectively halted the rise of resistance but led to only a slight reversal in resistance rates.

Another estimation challenge is the economic cost associated with bacterial resistance. In hospital settings, the challenge has been disentangling two effects: The longer the hospital stay, the greater is the likelihood of being infected with a resistant pathogen, and in turn, a hospital acquired infection with a resistant pathogen lengthens the hospital stay. In community settings, the challenge has been correctly estimating both the benefits and the costs of antibiotic use. Resistance-related costs alone are an insufficient reason to recommend that fewer antibiotics be used, because antibiotics bring benefits as well as costs. To date, there has been no reliable benefit-cost estimate of antibiotic use in either setting.

8.
Conclusions and Avenues for Further Research

The literature on the economics of antibiotic effectiveness as a natural resource has grown considerably in the past decade. Many of the problems faced in the management of antibiotic effectiveness bear resemblance to problems in both renewable and nonrenewable natural resources. For antibiotic effectiveness, as for optimal oil and mineral extraction, the effect of market structure on extraction rates, optimal investment in development of new resource pools, and the impact of taxation on antibiotic resistance are salient questions. And just as for fisheries or biodiversity conservation, problems in antibiotic effectiveness require understanding of biological and metapopulation dynamics, and the solutions involve management of open-access resources. However, those researching problems in antibiotic effectiveness face some unique challenges.

The first challenge is the realities of the health care system and pharmaceutical industry. Resource economists must learn the institutional details that will inform their models and assumptions. Second, the demand for antibiotics can be modified by reducing the need for antibiotics through better hospital infection control and vaccinations. Although antibiotic effectiveness is a scarce resource, its value depends on the number of individuals infected. Therefore, under some conditions it is optimal to use more antibiotics if that reduces the stock of infected individuals, although antibiotic effectiveness is somewhat decreased. Although

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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demand for energy or fish can also be modified, the dynamics of doing so are not tied closely to the problem of resource management, as is the case with antibiotics. This potential for a trade-off between smaller stocks of infected individuals in the present and a high level of antibiotic effectiveness in the future stems from discounting future infection costs. Additional insight should be gained by using other than utilitarian welfare functions. Third, qualitative conclusions reached by resource economists should be robust to assumptions about the size of the biological fitness cost of resistance. Although earlier papers have described a problem with either zero or high fitness costs, reality may not be so clear-cut. Therefore, deriving comparative statics with respect to the fitness cost of resistance would be valuable for policy.

Disclosure Statement

The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

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Weitzman M. 1976. The optimal development of resource pools. J. Econ. Theor. 12(3):351–64

Weitzman ML. 1974. Prices vs. quantities. Rev. Econ. Stud. 61(4):477–91

Wilen J, Msangi S. 2003. Dynamics of antibiotic use: ecological versus interventionist strategies to manage resistance to antibiotics. In Laxminarayan 2003, pp. 17–41

World Health Organ. (WHO). 2001. The use of antimalarial drugs. Report of a WHO informal consultation. WHO Geneva

A9
THE ROLE OF HEALTH CARE FACILITIES36

Ramanan Laxminarayan


Rapid improvements in medical technology have made possible lifesaving interventions that keep hospitalized patients alive for longer. However, the downside of these interventions is that patients tend to be sicker, spend longer periods of time in the hospital, and are more in need of intensive medical care than before, leading to an increased prevalence of many noso-

36

Reprinted from Laxminarayan and Malani (2007). Extending the cure: Policy responses to the growing threat of antibiotic resistance. Chapter 4: The role of health care facilities. © Resources for the Future 2007. All rights reserved. www.extendingthecure.com.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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comial infections.37 Also known as a hospital-acquired infection (HAI), a nosocomial infection is acquired in a hospital by a patient who was admitted for a reason other than that infection. Moreover, protracted illness and time on life support for these patients, many of whom are immuno-compromised, have increased reliance on antibiotics to help stave off infection, which in turn has resulted in increasing drug resistance among common, previously treatable HAIs.


According to the Centers for Disease Control and Prevention (CDC), HAIs account for an estimated 2 million infections and 90,000 deaths each year. Common HAIs include infections of surgical wounds, urinary tract infections, and lower respiratory tract infections. Infections acquired in health care institutions are among the top 10 causes of death in the United States: they are the primary cause of 1 percent of all deaths and are major contributors to an additional 2 percent of all deaths (Harrison and Lederberg, 1998). Many of the endemic bacteria causing these infections are resistant to one or more classes of antibiotics’ pose a major challenge to inpatient health, and significantly increase the costs of hospital stays. In fact, the United States has among the highest rates of drug-resistant hospital infections in the world, as described in Chapter 1. Vancomycin-resistant enterococci (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) are among the most important HAIs because they now account for a large fraction of nosocomial infections, but they are not the only problematic pathogens: increasingly, resistant Gram-negative bacteria such as Pseudomonas aeruginosa and Klebsiella pneumoniae are causing serious infections in hospital patients. Hospitals and long-term care facilities like nursing homes and hospice care tend to use large quantities of antibiotics and are consequently significant reservoirs of resistant pathogens. The ability of these pathogens to persist may be due to multiple interacting factors, including excessive antibiotic use, poor hygiene by health care workers, high susceptibility of patients, establishment in long-term care facilities (as well as in prisons and in the community), and colonization of hospital staff or the hospital environment. Each of these factors contributes to the emergence and establishment of endemicity within a clinical setting. In addition to the impact of endemic antibiotic-resistant bacteria on their own patients, hospitals are significant reservoirs of resistant pathogens that can be transported to other facilities.

Strategies for lowering the resistance levels in hospitals fall into three categories.38 First is lowering antibiotic use by requiring preapproval for certain antibiotic prescriptions. Second is using creative antibiotic restriction strategies,

37

Many of the procedures commonly performed on the seriously ill today, such as central venous catheterization and mechanical ventilation, predispose the patient to colonization with hospital-associated bacteria and an enhanced susceptibility to invasive infection with these agents.

38

There are others, such as physician education, that are discussed in Chapter 3.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

such as cycling and treatment heterogeneity. Third is better infection control, which is applicable not just to resistant pathogens, but to all HAIs. Studies suggest that the economic and health benefits of many common interventions to lower the prevalence of HAIs exceed the costs. In this chapter we explore the incentives for hospitals39 to invest in hospital infection control (HIC) and other measures to lower the prevalence of resistant bacteria in their facilities, as well as potential regulatory solutions to encourage greater reporting and improved infection control.

Economic Costs and Benefits

HAIs cost between $17 billion and $29 billion each year, and older studies have shown that a third of this burden can be lowered by adequate infection control programs (Haley et al., 1985). Numerous studies show that HAIs, especially resistant infections, cause longer hospital stays, greater risk of death, and much higher rates of hospitalization. There is also strong evidence that the overall economic benefits of infection control programs exceed costs by a wide margin and that “an effective infection control programme is one of the most cost-beneficial medical interventions available in modern public health” (Wenzel, 1995). However, there is considerable disagreement over who bears the principal economic burden of these infections, and this influences incentives for health care facilities to engage in better infection control. In this section, we review existing evidence on the economic benefits of hospital infection control and incentives for hospitals to engage in it.

Cost of Hospital-Acquired Infections

Numerous studies have documented the increased costs of nosocomial blood-stream infections, stretching back into the 1970s and 1980s. Pittet, Tarara et al. (1994) and Pittet and Wenzel (1995) found that during the 1980s, the incidence and risk of death from nosocomial bloodstream infections had risen markedly and that a patient with a nosocomial bloodstream infection was 35 percent more likely to die; for a patient who survived, extra costs attributable to the infection were approximately $40,000, and extra hospital costs, $6,000. Haley (1986) looked at all nosocomial infection costs and found that the average cost was about $1,800 per infection, with a maximum cost of about $42,000.

It is important to recognize the significant economic costs that nosocomial infections impose on both the hospital and the patient. The congressional Office of Technology Assessment has estimated the minimal hospital cost associated

39

Although the problem of MRSA (and other HAIs) in nursing homes and prisons is not addressed in this chapter, a number of the recommendations made here are applicable to those situations as well.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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with nosocomial infections caused by antibiotic-resistant bacteria to be $1.3 billion per year (in 1992) (OTA, 1995). This does not include the increased cost to patients, both monetarily and through the indirect and long-term morbidity and mortality consequences of resistant infections. In addition, most published studies have shown increased mortality risk on the order of 1.3 to 2 times, which may also have significant effects on indirect costs, such as long-term lost productivity. It is also important to understand that antibiotic resistance has an effect on many patients who do not become infected: they have to use stronger drugs, which may be more expensive, have more dangerous side effects, or be more toxic or possibly less effective than older or mainline drugs.

Those indirect costs aside, the cost of an antibiotic-resistant infection is still significant. According to Cosgrove, Qi et al. (2005), a nosocomial MRSA bacteremia significantly increases the length of hospital stays, the charges per patient, and hospital costs per case. They estimate that the excess cost of an MRSA bacteremia is $26,424 in patient charges and $14,655 in excess hospitals costs (total, $41,079 in excess charges) versus a control population. They also calculated costs for patients with methicillin-sensitive Staphylococcus infection (MSSA); these averaged $19,212 in excess patient charges and $10,655 in excess hospital costs (total, $29,867). McHugh and Riley (2004), similarly, estimated total per patient costs (as opposed to excess costs) of $9,699 for an MSSA infection versus $45,920 for an MRSA infection (an excess cost of $36,221).

Another important problem is surgical site infections, which are responsible for increased morbidity and mortality and cost hospitals more than $1.6 billion in extra charges each year (Martone and Nichols, 2001). Engemann, Carmeli et al. (2003) studied MRSA in surgical site infections in a large cohort at the Duke University Medical Center. MRSA in a surgical wound was found to result in more than a 12-fold increase in mortality versus non-infected patients and more than a 3-fold increase versus patients infected with MSSA. MRSA infections also cost patients about $40,000 more than an MSSA infection and about $84,000 more than an uninfected patient.

Vancomycin-resistant enterococci (VRE) are also associated with higher morbidity, mortality, and costs. Carmeli, Eliopoulos et al. (2002) found that a VRE infection led to longer hospital stays, a 2-fold increase in the rate of mortality, increased odds that a patient would require major surgery or be placed in the intensive care unit, and a 1.4-fold increase in hospital costs, which over the length of the study translated to excess costs of $2,974,478 (233 patients at an excess cost of $12,766 each). In addition, the authors found an increase in the likelihood that a patient would end up being discharged to a long-term care facility, meaning that the additional costs of a VRE infection are significantly understated in the study and that they continue for many patients. These estimates are lower than in another study (Stosoret al., 1998), which found that VRE bacteremia was associated with $27,190 in excess costs; yet another study (Song et al., 2003) found mean excess costs of VRE to be $81,208.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

According to the Pennsylvania Health Care Cost Containment Council (PHC4) (PHC4, 2005), the average charge for Pennsylvania Medicare patients with HAIs was about $160,000, five times the $32,000 average charge for Medicare patients who did not contract infections. Among Medicaid patients, the average charge was approximately $391,000 for patients who contracted infections while hospitalized, compared with an average of $29,700 when infections did not occur. Private commercial insurers of businesses and labor unions that provide health insurance were billed for almost 23 percent, or 2,633, of the reported hospital-acquired infections, which added $604 million in extra hospital charges. The average charge for a hospital admission in which a commercially insured patient contracted an infection was almost $258,000, compared with an average of $28,000 for admissions when infections did not occur. The average charge for stays in which uninsured patients contracted infections reached almost $230,000, compared with $21,000 for an uninsured patient without an infection.

Benefits of Hospital Infection Control

There has been relatively little evaluation of the impact of programs to lower antibiotic use within hospitals, but greater attention has been paid to the benefits and costs of infection control programs. For example, a program of intensive surveillance and interventions targeted at reducing the risk of hospital-acquired ventilator-associated pneumonia at the University of Massachusetts Medical Center in 1997–1998 lowered the incidence of this pneumonia and resulted in a cost savings greater than $350,000 (Lai et al., 2003).

Similarly, a 1994 VRE outbreak at the University of Virginia Hospital prompted an active surveillance program and contact isolation of colonized patients. The costs of the program, including time spent collecting samples, additional length of hospital stays in isolation, and laboratory fees, were estimated at $253,099 during the two-year study, during which time only one primary VRE bacteremia occurred (Muto et al., 2002). At a control hospital, where no such program was in place, there were 29 cases of VRE bacteremia during the corresponding period, and these resulted in an estimated cost of $761,320, based on an estimate of excess costs of $27,190 per case of VRE (Stosor et al., 1998). Other per-case VRE cost estimates would value the program benefits at $357,448 (Carmeli et al., 2002) to $2,273,824 (Song et al., 2003), but even the lower end of these benefits far exceeded the costs of the program.

Two Charleston, S.C., hospitals implemented an active surveillance program and a contact isolation protocol as recommended by the Society for Health care Epidemiology of America (SHEA). Based on prior rates of nosocomial infections, the new programs and protocols prevented an estimated 13 MRSA bacteremias and 9 surgical site infections for a cost savings of about $596,960 for the prevented bacteremias ($45,920 per case, based on McHugh and Riley 2004) and $756,000 for the prevented surgical site infections ($84,000 in excess costs per

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

case, based on Engemann, Carmeli et al. 2003). The cost of implementing the program was $113,955, comprising $54,381 for surveillance and $59,574 for contact isolation (West et al., 2006).

Quality Control in U.S. Hospitals

This section provides an overview of how hospital quality, in general, and in particular with respect to infections, is currently measured and how hospitals are currently regulated or accredited.

Accreditation Process

Hospital accreditation organizations such as the Joint Commission on Accreditation of Health care Organizations (JCAHO) currently do not require standards for antibiotic use, resistance, or nosocomial infections.40 Hospitals are required to report only whether they follow a certain set of best practices for infection control, and not infection prevalence rates or resistance levels. JCAHO uses an onsite evaluation as the basis of accreditation. No long-term reporting is required for continued accreditation. Standards alone may not be able to solve the problem; a change in attitudes about hospital infections would come from a combination of education about the benefits of infection control and stronger incentives for hospitals to invest in control programs. Moreover, JCAHO clears more than 99 percent of all hospitals it inspects, which suggests that the current system is set up more to catch egregious violators of medical practices than to address pervasive problems like hospital-acquired infections and resistance (Gaul, 2005).41

Health Care Quality Organizations

The Leapfrog Consortium and other organizations that represent the interests of large purchasers of health care (such as automobile manufacturers) work with hospitals to encourage public reporting of health care quality and outcomes. They use a carrot-and-stick approach by rewarding hospitals that perform well and by leveraging consumer and health care purchaser choice to improve poor performers. Information on hospital infection control practices—including safety measures, hand washing, and vaccination of health care staff—is collected using self-reported surveys by hospitals. However, like JCAHO, Leapfrog may be better at separating good institutions from bad ones than at discerning finer indicators of performance, such as the prevalence of hospital acquired infection.

40

Based on a conversation with Dennis O’Leary, vice president, JCAHO, November 28, 2005.

41

In fact, concerns have been raised about the rigor of JCAHO’s hospital surveys and its ability to catch even gross violations that have seriously compromised patient health.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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In general, hospital-acquired infections and resistance are not a focus for existing organizations like JCAHO and Leapfrog. Although drug resistance can be seen as a quality issue, the current system for determining hospital quality may not work well to improve reporting or compliance with better infection control practices.

HICPAC and SHEA Guidelines

Existing initiatives to improve hospital infection control—such as by CDC’s Health care Infection Control Practices Advisory Committee (HICPAC) (McKibbe et al., 2005) and SHEA (Muto et al., 2003)—provide guidance to hospitals to engage in greater infection control and thereby help prevent the spread of resistance. Both sets of guidelines are based on clinical evidence that the vast majority of MRSA and VRE infections are the result of transmission from patient to patient and not from de novo mutations, and thus they suggest that stringent infection control practices are probably the most important factor in limiting the spread of MRSA and VRE.

However, they differ in some important respects. In the context of MRSA and VRE, the SHEA guidelines call for active surveillance cultures to identify colonized patients, with barrier precautions for patients colonized or infected with MRSA and VRE. CDC guidelines, on the other hand, reject the need for active surveillance cultures on the grounds that they may impose unnecessary costs on hospitals. Nevertheless, the voluntary nature of these guidelines indicates that many hospitals are not likely to apply them unless they have a strong financial motivation for doing so.42

Reporting of Infections and Resistance in Hospitals

Since 1970, data on hospital infections and prevalence of MRSA and VRE (based on passive surveillance) have been voluntarily reported confidentially by hospitals participating in CDC’s National Nosocomial Infection Surveillance (NNIS) program. These hospitals provide general medical-surgical inpatient services to adults or children requiring acute care. With a few exceptions, most current understanding of the extent of HAIs and drug resistance comes from the NNIS surveillance. However, there are important problems with this system that restrict its usefulness in delivering a comprehensive, nationwide picture of hospital infections and resistance. First, the nearly 300 hospitals that participate in the program are self-selected and represent only about 2 percent of hospitals, mainly academic centers—raising strong concerns about selection bias. Second, reporting within hospitals can change significantly. For instance, hospitals do not necessarily report data from the same intensive care unit each year, making comparisons across years problematic. Third, NNIS data are generally not available

42

And, some hospitals do have such an incentive, as seen in studies reviewed earlier in this chapter.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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to researchers outside CDC because of confidentiality agreements signed with hospitals. This has restricted wider use of these data.

In recent years, under strong pressure from consumer advocates, some states have moved to require public reporting of hospital infections. In 2006, Consumers Union reported that six states (Illinois, Pennsylvania, Missouri, Florida, Virginia, and New York) had hospital infection disclosure laws, and 30 states had introduced similar legislation requiring hospitals to report their infection levels to state monitoring bodies (CU, 2006). By providing more transparency to consumers, better reporting of infection and resistance levels may give hospitals greater incentives to engage in infection control.

Incentives and Disincentives to Control Resistant HAIs

Hospital Incentives

Despite some awareness of the problem and new measures to tackle the growing threat, the overall trend of infections, both susceptible and resistant, appears to be upward, as seen in Chapter 1. Antibiotic restrictions and better infection control are the two main tools available to hospitals. Currently, antibiotic restrictions are the main strategy reported by hospitals. Cost containment had been the original reason for implementing these restrictions (to divert physicians from expensive antibiotics to cheaper generics), but these reasons have been reborn in the form of concerns about drug resistance.

Programs intended to control antibiotic-resistant infections associated with health care have been around for a long time; however, implementation of these programs has been highly variable across facilities. Moreover, the guidelines have mostly focused on contact precautions that require staff hand washing, staff cohorting,43 and use of protective equipment to prevent the spread of infection from patients identified as carrying an infection. Guidelines issued by SHEA in 2003, focused mainly on the spread of MRSA and VRE within the hospital setting, called existing measures insufficient and recommended active surveillance cultures to identify patients colonized but not infected with resistant pathogens (Muto et al., 2003).

Next we consider important reasons why hospitals may not invest heavily in infection control programs on their own.

Hospital Disincentives

The extent to which hospitals bear the cost of resistant HAIs is a subject of disagreement, as is the extent to which these costs are passed on to Medicare,

43

This refers to assigning hospital staff to a limited number of patients rather than allowing for unlimited contact between health care workers and patients, which increases the likelihood of infection spread.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

Medicaid, and private insurers. If reimbursement to the facility is tied to the number of days of hospitalization rather than by diagnosis-related group or episode of illness, the hospital may not bear any of the financial burden of extended hospital stays and may have few financial incentives for investing in HAIs even if the overall benefits of such investments exceed the costs.

A 1987 study that looked at charges associated with 9,423 nosocomial infections identified in 169,526 admissions, selected randomly from adult admissions to a random sample of U.S. hospitals, found that at least 95 percent of the cost savings obtained from preventing nosocomial infections represented financial gains to the hospital (Haley et al. 1987).

However, a series of recent reports from PHC4 find that Medicare and Medicaid bear the greatest burden of the additional cost of HAIs.44 Pennsylvania hospitals billed the federal Medicare program and Pennsylvania’s Medicaid program for 76 percent of the 11,668 hospital-acquired infections in 2004, with Medicare taking up much of the burden. The economic burden on government resources imposed by the additional hospital charges was estimated at $1 billion for Medicare and $372 million for Medicaid. Extrapolating from the figures in Pennsylvania to the entire country, PHC4 estimated that at least $20 billion was charged to Medicare to pay for HAIs during 2004. These figures indicate that hospitals may actually benefit by extending the length of stay and may have fewer incentives to control infection levels within the hospital.

Medicare is currently in the process of revising its rules on reimbursing for hospital-acquired infections, and these changes could have a significant impact on hospital incentives to invest in infection control. Some payers, such as Blue Cross–Blue Shield, have already made some payments contingent on lower rates of certain HAIs, and anecdotal evidence suggests that this has lowered the prevalence of those HAIs.

Impact of Lawsuits

Some hospitals have faced lawsuits from individual patients for HAIs, based on plaintiffs’ claims that defendants (hospitals) failed to adhere to the standard of care for infection control.45 A study from Philadelphia found that 72 percent of HAI malpractice cases in Philadelphia were either withdrawn or settled; when brought to trial, the plaintiff was more likely to prevail (Guinan et al., 2005). MRSA infections were the most common reason for lawsuits. Moreover, MRSA in class I surgical sites were more likely to result in a victory for plaintiffs because national data show lower rates of infection for these surgeries, with the

44

The PHC4 reports were based on a state law that required hospitals to submit data on some categories of HAIs to PHC4 starting January 2004. Starting January 1, 2006, nearly all hospital-acquired infections are reportable to PHC4 (PHC4 2006).

45

Media reports of MRSA-related lawsuits are growing. In one recent example, the families of two women who died from MRSA infections while incarcerated at the jail in Allegheny County, Pennsylvania, sued the warden and other county officials for failing to provide medical care.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

implication that these infections were preventable. The impact of lawsuits on infection control is unclear, but they may have made hospitals wary of reporting infection and resistance rates.

Short-Term Financial Considerations

Even if most of the costs of HAIs can be passed on to payers, hospitals and long-term care facilities may bear at least some of the burden associated with the high cost of treating resistant infections. However, even for these limited costs, short-term cost considerations may trump the long-term gains of lower levels of resistance and infection for facilities in financial trouble. Are financially troubled institutions more likely to cut back on infection control? Do hospitals and long-term care facilities really behave optimally, or do they tend to be myopic because they fail to recognize the effect of resistance management and infection control on future costs? Also, to what extent are hospitals prompted by the threat of lawsuits to do a better job of controlling nosocomial infections and resistant pathogens? Answering these questions is pivotal to making policy decisions on how best to incentivize hospitals to invest in stronger infection control programs.

Issues of Agency

Although the hospital as a whole may have an incentive to restrict the use of antibiotics and drug resistance, individual clinicians may not share the same incentives. Also, many physicians are not employees but consultants of hospitals and may therefore have a smaller incentive to care about costs imposed by resistance on hospitals. Conversely, the problem of resistance may be evident to infection control committees and clinicians, but they may not be able to convince senior management of the long-term financial benefits of lower levels of resistance. Management and operational structures of hospitals have implications both for investment in infection control and for implementation of control measures, but little is currently known about the influence of organizational culture and structure on infection and resistance levels.46

Incentives to Free-Ride

Hospital infection control is expensive and becomes more difficult and less effective when patients enter the hospital already carrying the resistant pathogens. Recent research on incentives for hospitals to control HAIs suggests that the large

46

Hospital objectives may be multifaceted. Many participants at our consultations agreed that although hospital managers care about reducing infection-related mortality, they are less adept at seeing the long-term health and economic benefits of infection control. Some of the shortsightedness is reflected in compensation of infectious disease clinicians and nurses: an infection control nurse typically earns less than a bedside nurse and consequently there is a shortage in supply.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
×

spillovers of antibiotic-resistant bacteria among medical care facilities may be one factor that explains the lack of response (Smith et al., 2005). When institutions share patients, a person colonized in one facility may be responsible for introducing or increasing the prevalence of resistance in another facility.

Since any single hospital (especially in the current era of cost cutting and short-term financial pressures) may not see the benefits of its HIC program outside its own walls, hospitals may not benefit from decreasing the overall level of resistance in the catchment area when those patients are admitted later to other hospitals. Instead, hospitals may prefer to free-ride on the infection control investments of other hospitals. This results in an overall higher level of resistance.

Modeling shows that the selfishly “optimal” level of HIC that any hospital would undertake is lower the greater the number of hospitals that share a catchment area. In fact, it is in the interests of the hospital to spend less and free-ride on the efforts of other hospitals. When everyone free-rides, all hospitals will spend less on HIC, leading to epidemics that develop earlier and faster. A much better outcome can be achieved through regulation and the resulting coordination between facilities.

A good example comes from the Siouxland experience. An epidemic of VRE in the Siouxland region of Iowa, Nebraska, and South Dakota was first detected in late 1996. Within a short time, VRE had quickly spread to nearly half of the health care facilities in the region. In response, a VRE task force was constituted with representatives from acute care and long-term care facilities and public health departments in the region (Ostrowsky et al., 2001). Following a comprehensive two-year intervention (including aggressive culturing to identify VRE-colonized patients, isolation of patients, improved antibiotic use, sterile device measures, improved staff hand hygiene, and sharing of information among institutions), VRE was eliminated from all acute care facilities and significantly reduced in long-term care facilities in the region. This could not have happened without coordination. When hospitals are unwilling to coordinate on their own, regulation will ensure that no single hospital free-rides on the efforts of others. Regulations that require portability of patient records (which could show which patients are colonized) could help hospitals in identifying high-risk carriers of resistant pathogens.

The similarly successful experience of Dutch hospitals in lowering the prevalence of MRSA is described in Box A9-1.

Incentives to Report Infection Levels

Hospitals have a clear incentive to downplay infection levels in their facilities, since accurate reporting could decrease demand for their services. “Report cards” that provide patients with information on hospital quality, including nosocomial infection rates, may encourage hospitals to discriminate against sicker patients or those coming from long-term care facilities because they might be

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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BOX A9-1

The Dutch Experience with Controlling MRSA

MRSA incidence rates in the Netherlands are among the lowest in the world—1.1 percent—in contrast to more than 25 percent in France, Spain, and Belgium and 43.5 percent in the United Kingdom (The National Institute for Public Health and the Environment (RIVM)) (see Figure 1.4). This extremely low rate is attributable to a decade-old national “search and destroy” policy to limit the spread of MRSA. The implementing guidelines are based on the premise that the best way to fight MRSA is to identify it as early as possible and to isolate infected or possibly infected patients. Patients and health care workers are categorized according to risk and screened regularly based on those risk assessments. For example, all patients treated in a foreign hospital are considered at high risk of being MRSA carriers and thus are isolated until cultures prove negative (Dutch Workingparty Infection Prevention, 2005). Most importantly, the policy requires the cooperation of all health care facilities and is enforced by the Dutch government.

The policy has not been cheap to implement. Over the course of 10 years, the MRSA policy resulted in more than 2,265 lost hospitalization days (Vriens et al., 2002). Wards had to be closed 48 times, 29 health care workers had to temporarily discontinue working, and 78,000 additional cultures had to be performed. However, it is estimated that the 6 million euros realized as benefits of the campaign in terms of averted MRSA infections and increased vancomycin resistance in other bacteria (S. aureus and VRE) far outweighed the cost (2.8 million euros) of hospital infection control in the Netherlands during the period.

A new strain of MRSA appeared in 1999 but was not immediately recognized as such because of the limited sensitivity of the tests at the time. Within weeks this new strain, still unrecognized, had spread to several health care facilities. By increasing the sensitivity of the tests and maintaining intensive screening of both patients and health care workers, by the end of 2003, the new strain of MRSA was under control (Vos et al., 2005). Controlling the spreading epidemic was possible only because of the national strategy: if any hospital had lapsed, MRSA would spread to all the other institutions fairly quickly.

more likely to carry a resistant pathogen.47 To address this problem, Florida and some other states that publicly report outcome indicators by hospital risk adjust the data to account for the fact that some hospitals admit more patients who are sicker and require more resources than the average patient. An alternative strategy would be to monitor and subsidize inputs for hospital infection control rather than monitoring the outputs—that is, infection levels. Educational efforts to get

47

A related study in the context of cardiac surgery found that the use of hospital report cards in New York and Pennsylvania led to improved matching of patients with hospitals, but also gave doctors and hospitals an incentive to turn away severely ill patients who were more difficult to treat. This resulted in higher levels of resource use and worse health outcomes, particularly for sicker patients (Dranove et al., 2002).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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hospitals to recognize the long-term gains of infection control may also be part of the solution.

Hospital report cards also should be issued by an independent agency that is less susceptible to political pressure. These reports, if issued by government agencies, can be influenced or quashed by interference from the governor or state senators, who in turn are influenced by campaign contributions from wealthy doctors. Governmental policy can also influence the timing of the release of reports.

Some degree of enforcement is required, via periodic external surveillance cultures, withdrawal of approval for state Medicare reimbursement, or fines. Because reporting requirements can create perverse incentives—for example, hospitals that suspect high levels of resistance may cut back on surveillance expenditures—any reporting program needs to be designed to take these factors into consideration.

Recommendations

Hospitals are an important reservoir for resistant pathogens, and the problem of resistant infections is emblematic of broader problems with ensuring health care quality. The issue is not knowing how to address resistant infections in hospitals48—good examples exist, from both the United States and abroad, of how to maintain low levels of resistance in health care settings—but rather, understanding why some facilities have an incentive to invest in these programs while others do not.

Regulatory agencies play two important roles in the antibiotic resistance problem. One is to enable cooperative outcomes better than those attained if hospitals behave in their own self-interest. Regional coordination in infection control efforts may be one of several solutions to this dilemma (Kaye et al., 2006). Another is to make public the data on resistance and infection levels so that hospitals have an incentive to invest in addressing the problem. Here we propose ways to encourage reporting and control of resistant infections and improve surveillance, and we also recommend additional research.

Conclusions

  1. Hospital reimbursement policies for HAIs could be linked to levels of infection and drug resistance. Tying Medicare and private insurance payments to a hospital to its levels of infection control may be one approach.

  2. Subsidizing inputs for infection control and surveillance programs would

48

Although much of the problem with drug resistance in hospitals is related to lack of sufficient infection control rather than to excessive antibiotic use, hospitals have tended to focus on the antibiotic use issue to a greater extent. Some hospitals have pursued cycling and other antibiotic restriction policies even though ecologists have questioned the soundness of these strategies (Bergstrom et al., 2004).

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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provide a greater incentive for hospitals to invest in them. Chapter 6, on health insurance and Medicare, describes such a program.

  1. State requirements for reporting of hospital infections should adjust the data for risk so that hospitals that admit sicker patients are not penalized for having higher levels of antibiotic use and infection.

  2. The national hospital infection and resistance surveillance system should be more comprehensive. Ideally, it would be separate from JCAHO and other accreditation groups and would take the approach used by several states: it would collect nationwide data not just on outcomes (infections and resistance) but also on inputs, such as antibiotic use, number of infection control nurses, and physical inputs for HIC. Given the incentive problems with reporting outcomes, independent monitoring and reporting of infections should be complemented with reports on infection control inputs.

  3. Legal avenues for responding to resistance should be examined, perhaps involving a combination of workplace safety and labor laws (e.g., penalizing hospitals for a failure to protect nursing staff if they are at risk). Studies indicate that nurses are at-risk for infections caused by C. difficile and E. coli, however this risk is believed to be low (Sepkowitz, 1996a; 1996b).

  4. Research needs to address the important policy-relevant questions. Little is known about the institutional characteristics (ownership structure,49 proximity to other hospitals and facilities) that predict resistance. We also know little about the costs of surveillance and infection control for a typical hospital and how these compare with other hospital expenses. Additional data will help determine the burden of infection control on hospital budgets and inform the design of taxes and subsidies for specific inputs for infection control.

  5. A policy research program is needed to explore how to create incentives for hospitals to conduct surveillance and reporting, not just of infections but also of other important health care quality measures.

References

Bergstrom, C. T., M. Lo, et al. (2004). “Ecological Theory Suggests that Antimicrobial Cycling Will Not Reduce Antimicrobial Resistance in Hospitals.” Proceedings of the National Academy of Sciences of the United States of America 101(36): 13285-90.

Carmeli, Y., G. Eliopoulos, et al. (2002). “Health and Economic Outcomes of Vancomycin-Resistant Enterococci.” Archives of Internal Medicine 162(19): 2223-2228.

49

Categories include government hospitals, for-profit hospitals, nonprofit teaching hospitals, and nonprofit nonacademic hospitals.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Cosgrove, S. E., Y. Qi, et al. (2005). “The Impact of Methicillin Resistance in Staphylococcus aureus Bacteremia on Patient Outcomes: Mortality, Length of Stay, and Hospital Charges.” Infection Control and Hospital Epidemiology 26: 166-174.

CU. (2006). http://www.consumersunion.org (accessed October 18, 2006). Consumers Union.

Dranove, D., D. P. Kessler, et al. (2002). “Is More Information Better? The Effects of ‘Report Cards’ on Health Care Providers.” Working paper bW8697. Cambridge, MA: NBER (National Bureau of Economic Research).

Engemann, J. J., Y. Carmeli, et al. (2003). “Adverse Clinical and Economic Outcomes Attributable to Methicillin Resistance among Patients with Staphylococcus aureus Surgical Site Infection.” Clinical Infectious Diseases 36: 592-598.

Gaul, G. M. (2005). “Accreditors Blamed for Overlooking Problems: Conflict of Interest Cited Between Health Facilities, Group That Assesses Conditions.” Washington Post. Washington, DC, July 25, A01.

Guinan, J. L., M. McGuckin, et al. (2005). “A Descriptive Review of Malpractice Claims for Health Care-Acquired Infections in Philadelphia.” American Journal of Infection Control 33(5): 310-2.

Haley, R. W. (1986). Managing Hospital Infection Control for Cost Effectiveness: A Strategy for Reducing Infectious Complications. Chicago: American Hospital Publishing, Inc.

Haley, R. W., D. H. Culver, et al. (1985). “The Efficacy of Infection Surveillance and Control Programs in Preventing Nosocomial Infections in US Hospitals.” American Journal of Epidemiology 121(2): 182-205.

Haley, R. W., J. W. White, et al. (1987). “The Financial Incentive for Hospitals to Prevent Nosocomial Infections under the Prospective Payment System. An Empirical Determination from a Nationally Representative Sample.” JAMA 257(12): 1611-4.

Harrison, P. F. and J. Lederberg (eds.). (1998). Antimicrobial Resistance: Issues and Options, Workshop Report. Forum on Emerging Infections. Washington, DC: Institute of Medicine.

Jevons, M. (1961). “Celbenin-Resistant Staphylococci.” BMJ 1: 124-5.

Kaye, K. S., J. J. Engemann, et al. (2006). “Favorable Impact of an Infection Control Network on Nosocomial Infection Rates in Community Hospitals.” Infection Control and Hospital Epidemiology 27(3): 228-32.

Lai, K. K., S. P. Baker, et al. (2003). “Impact of a Program of Intensive Surveillance and Interventions Targeting Ventilated Patients in the Reduction of Ventilator-Associated Pneumonia and Its Cost-Effectiveness.” Infection Control and Hospital Epidemiology 24(11): 859-863.

Laxminarayan, R., D. L. Smith, et al. (2005). “On the Importance of Incentives in Hospital Infection Control Spending.” Discovery Medicine 5(27): 303-308.

Martone, W. J. and R. L. Nichols. (2001). “Recognition, Prevention, Surveillance, and Management of Surgical Site Infections: Introduction to the Problem and Symposium Overview.” Clinical Infectious Diseases 33: S67-S68.

McHugh, C. G. and L. W. Riley. (2004). “Risk Factors and Costs Associated With Methicillin-Resistant Staphylococcus aureus Bloodstream Infections.” Infection Control and Hospital Epidemiology 25(5): 425-430.

McKibben, L., T. Horan, et al. (2005). “Guidance on Public Reporting of Health care-Associated Infections: Recommendations of the Health care Infection Control Practices Advisory Committee.” American Journal of Infection Control 33(4): 217-26.

Muto, C. A., E. T. Giannetta, et al. (2002). “Cost-Effectiveness of Perirectal Surveillance Cultures for Controlling Vancomycin-Resistant Enterococcus.” Infection Control and Hospital Epidemiology 23(8): 429-435.

Muto, C. A., J. A. Jernigan, et al. (2003). “SHEA Guideline for Preventing Nosocomial Transmission of Multidrug-Resistant Strains of Staphylococcus aureus and Enterococcus.” Infection Control and Hospital Epidemiology 24(5): 362-386.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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Ostrowsky, B. E., W. E. Trick, et al. (2001). “Control of Vancomycin- Resistant Enterococcus in Health Care Facilities in a Region.” The New England Journal of Medicine 344(19): 1427-1433.

OTA. (1995). Impact of Antibiotic-Resistant Bacteria: A Report to the U.S. Congress. Washington, DC: Government Printing Office. Office of Technology Assessment.

PHC4. (2005). “Reducing Hospital-Acquired Infections: The Business Case.” Research Brief No. 8. http://www.phc4.org/reports/researchbriefs/111705/docs/researchbrief2005report_hospacq-infections_bizcase.pdf (accessed March 5, 2007). Pennsylvania Health Care Cost Containment Council.

PHC4. (2006). Hospital-acquired Infections in Pennsylvania 2005. http://www.phc4.org/reports/hai/05/default.htm (accessed December 11, 2006). Pennsylvania Health Care Cost Containment Council.

Pittet, D., D. Tarara, et al. (1994). “Nosocomial Bloodstream Infection in Critically Ill Patients. Excess Length of Stay, Extra Costs, and Attributable Mortality.” JAMA 271(20): 1598-1601.

Pittet, D. and R. P. Wenzel. (1995). “Nosocomial Bloodstream Infections. Secular Trends in Rates, Mortality, and Contribution to Total Hospital Deaths.” Archives of Internal Medicine 155(11): 1177-1184.

RIVM. (2005). “European Antimicrobial Resistance Surveillance System (EARSS).” http://www.rivm.nl/earss/ (accessed on January 18, 2005). The National Institute for Public Health and the Environment.

Sepkowitz, K. A. (1996a). “Occupationally Acquired Infections in Health Care Workers: Part I.” Annals of Internal Medicine 125(10): 826-834.

Sepkowitz, K. A. (1996b). “Occupationally Acquired Infections in Health Care Workers: Part II.” Annals of Internal Medicine 125(11): 917-928.

Smith, D. L., S. A. Levin, et al. (2005). “Strategic Interactions in Multi- Institutional Epidemics of Antibiotic Resistance.” Proceedings of the National Academy of Sciences of the United States of America 102(8): 3153-8.

Sohn, A. H., B. E. Ostrowsky, et al. (2001). “Evaluation of a Successful Vancomycin-Resistant Enterococcus Prevention Intervention in a Community of Health Care Facilities.” American Journal of Infection Control 29(1): 53-57.

Song, X., A. Srinivasan, et al. (2003). “Effect of Nosocomial Vancomycin-Resistant Enterococcal Bacteremia on Mortality, Length of Stay, and Costs.” Infection Control and Hospital Epidemiology 24(4): 251-256.

Stosor, V., L. R. Peterson, et al. (1998). “Enterococcus faecium Bacteremia: Does Vancomycin Resistance Make a Difference?” Archives of Internal Medicine 158(5): 522-527.

Vos, M. C., A. Ott, et al. (2005). “Successful Search-and-Destroy Policy for Methicillin-Resistant Staphylococcus aureus in The Netherlands.” Journal of Clinical Microbiology 43(4): 2034-2035.

Vriens, M., H. Blok, et al. (2002). “Costs Associated with a Strict Policy to Eradicate Methicillin-Resistant Staphylococcus aureus in a Dutch University Medical Center: A 10-Year Survey.” European Journal of Clinical Microbiology and Infectious Diseases 21(11): 782-786.

Wagenvoort, J. H. (2000). “Dutch Measures to Control MRSA and the Expanding European Union.” Euro Surveillance 5(3): 26-28.

Wenzel, R. P. (1995). “The Lowbury Lecture. The Economics of Nosocomial Infections.” The Journal of Hospital Infection 31(2): 79-87.

West, T. E., C. Guerry, et al. (2006). “Effect of Targeted Surveillance for Control of Methicillin-Resistant Staphylococcus aureus in a Community Hospital System.” Infection Control and Hospital Epidemiology 27(3): 233-238.

WIP. (2005). Policy for Methicillian-resistant Staphylococcus aureus. http://www.wip.nl (accessed May 31, 2006). Dutch Workingparty Infection Prevention.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A10
RESPONDING TO THE GLOBAL ANTIBIOTIC RESISTANCE CRISIS: THE APUA CHAPTER NETWORK

Stuart B. Levy50

Tufts University School of Medicine, Alliance for the Prudent Use of Antibiotics51

The Alliance for the Prudent Use of Antibiotics

The Alliance for the Prudent Use of Antibiotics (APUA) emerged in 1981 following a meeting on plasmids and drug resistance in the Dominican Republic (Levy et al., 1981). This was one of the first meetings to which scientists from the developing world, supported by the conference organizers, were invited to discuss the molecular basis for antibiotic resistance with representatives from industrialized countries. Many of the participants had sent novel resistant organisms to scientists in the industrialized world for study, but had never met face-to-face. The meeting forged new scientific relationships and collaborations. APUA, which began as a two-person part-time operation with about 30 members, has grown to several thousand members in over 100 countries with chapters in more than 60 countries on all continents (Figure A10-1).

The mission of APUA was then, and still is today, to “preserve the power of antibiotics.” This endeavor aims to control infectious diseases worldwide through appropriate access to these valuable therapeutics, as well as containment of antimicrobial resistance. The approach is to build local capacity through recruitment of individual APUA champions and building of APUA national chapters worldwide. The latter form strategic partnerships with other APUA chapters and individuals as well as public health organizations, such as the World Health Organization (WHO) and the Pan American Health Organization. The broad goals are to synthesize and disseminate the latest scientific information on antimicrobial resistance in each country and to conduct studies and activities to maintain and restore the efficacy of antibiotics.

More than half of the chapters are located in the developing world. Support for these chapters comes in the form of correspondence, meetings, lectures, and small grants. The small grants consist of several-thousand-dollar awards to undertake local projects (Figure A10-2). The findings from several of these projects have been published, one of which performed an inventory of antibiotics in home medicine cabinets in Russia (Stratchounski et al., 2003).

In Buenos Aires, Argentina, a training program on antibiotics and antibiotic

50

I thank A. Sosa and B. Marshall for their thoughtful comments, help, and advice.

51

Boston, MA 02111.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-1 APUA global chapter network.

FIGURE A10-1 APUA global chapter network.

SOURCE: A. Sosa, Alliance for the Prudent Use of Antibiotics (personal communication, August 1, 2010).

resistance was initiated. Venezuela declared antibiotic resistance a public health issue and enacted a law that restricted the sale and dispensing of several antibiotic classes: macrolides, fluoroquinolones, third-generation cephalosporins, and rifampin (Figure A10-3). These activities are initiated locally, in large part through the members of the different country chapters. The rationale is to generate local interest and help the chapters devote attention to some local factor that affects antibiotic access and resistance in their own country.

In Chile, pharmacies are now required to obtain prescriptions before selling antibiotics. In just one year, that law translated into a dramatic drop in the sale of antibiotics (Figure A10-4). The lessons learned there can now be tested in other parts of South and Latin America to see if it is appropriate and feasible to limit the access to antibiotics without prescription.

Through journal articles, printed documents, and its website (www.apua.org), APUA gets its message out. One group targeted with information is journalists, for whom a training guide has been written (Figure A10-5). The first training was held in Addis Ababa, Ethiopa, in November 2007 with support from the U.S. Agency for International Development. Their initiatives and ability to

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-2 APUA Small Grants Program.

FIGURE A10-2 APUA Small Grants Program.

SOURCE: A. Sosa, Alliance for the Prudent Use of Antibiotics (personal communication, 2003).

reach diverse readers help deliver an understanding of the concept of antibiotic resistance to lay people.

In 2001, David Heymann invited me to chair a press conference accompanying the release of the WHO Global Strategy for Containment of Antimicrobial Resistance report. I had helped work on the document, but David was its champion, along with Rosamond Williams. Unfortunately, the press conference, scheduled in Washington, DC, on September 11, 2001, never happened because of the events which occurred that day.

Accompanying the report was an APUA-organized examination of 25 previous reports and recommendations from different organizations and countries throughout the world on the problem of antibiotic resistance (Levy and APUA, 2001). The document includes summary tables and text revealing a similarity in their conclusions and recommendations on the means to contain and reduce antibiotic resistance. The APUA report emphasizes that resistance is not a new problem but is an increasing threat and a public health priority. Moreover, each group argued that improper antibiotic use is the pivotal issue leading to resistance. Education of providers and patients on the problem and the factors affecting anti-

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-3 Venezuela declaration of public health threat by antimicrobial resistance (AMR).

FIGURE A10-3 Venezuela declaration of public health threat by antimicrobial resistance (AMR).

SOURCES: Gaceta Oficial, Republica Bolivariana de Venezuela, 2002, and A. Sosa, Alliance for the Prudent Use of Antibiotics (personal communication, August 1, 2010).

biotic resistance is critical. The APUA document urged “action now,” citing the conclusions of the previous reports on the history and extent of the problem.

When APUA was established, we used the term “antibiotic” because bacteria were the major bearers of resistance in the form of transposons and plasmids. Today APUA looks at resistance as a general phenomenon in all microbes—bacteria, viruses, parasites, and fungi.

In 2005, APUA examined resistance globally, not just in bacteria but in viruses and parasites as well. The document, published as a supplement in Clinical Infectious Diseases, looked at resistance in HIV and other viruses, malaria, as well as many different bacteria (Levy and O’Brien, 2005). The situation was deemed epidemic, appropriately seen as “the shadow epidemic,” which clouded and interfered with effective therapy for all microbial diseases (Figure A10-6). APUA’s initial attention was, and continues to be, on developing countries, where resistance has its greatest impact.

We learned the following from work in these countries (A. Sosa, personal communication):

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-4 Effect of the need for a prescription on the sale of antibiotics in Chile.

FIGURE A10-4 Effect of the need for a prescription on the sale of antibiotics in Chile.

SOURCE: Organizacion Panamericana de la Salud (2000). Printed with permissions from Dr. Luis Bavestrello, originally published in Spanish on Rev. méd. Chile v.130 n.11 Santiago Nov. 2002.

  • The government expenditure on health care is rarely 2 to 5 percent of the total budget.

  • There is serious concern about substandard drugs and counterfeits. We are examining this problem now through a situation analysis and needs assessment study under a Gates Foundation grant in Zambia and Uganda.

  • Sale and dispensing of antibiotics is often available without a prescription.

  • Child mortality from acute respiratory infections and diarrheal diseases of bacterial origin is high but is often overshadowed or even misdiagnosed as malaria, tuberculosis (TB), or AIDS. In fact, there are more deaths in children from bacteria than there are from the other microbial disease agents (Wardlaw et al., 2006).

  • There is often a “divorce” between the government and professional organizations.

  • Recognized key opinion leaders in these countries are often interested in

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-5 Training journalists.

FIGURE A10-5 Training journalists.

SOURCE: http://www.tufts.edu/med/apua/Chapters/tripreport_new%20delhi.pdf.

leading efforts to institute change that will improve antibiotic access and prudent use. These individuals are key to forming APUA chapters.

  • The chapters often seek the involvement of WHO country offices, but usually in a cooperative partnership, not monetarily. The ongoing technical assistance is absolutely critical, as is continued communication with the chapters.

The short- and long-term goals are important because they aim to make sure that the chapter network and the chapters are able to do something useful, not only for themselves but also for other countries nearby. We have generated and supported regional meetings and activities.

We need to make resistance a public health issue that garners government ownership and financial support. Legislators and the media should be engaged to support and publicize efforts to educate the public. Activities should involve nongovernmental organizations, corporate entities, faith-based entities, and consumer protection agencies for advocacy mobilization. Local changes should draw a national picture of antimicrobial resistance priority issues, design a funding strategy to begin to sustain the efforts, and design a work plan with attainable

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A10-6 The APUA GAARD project reports a “shadow epidemic.” The 2005 Report of the Global Advisory on Antibiotic Resistance Data (GAARD), a project and publication of the Alliance for the Prudent Use of Antibiotics (www.apua.org).

FIGURE A10-6 The APUA GAARD project reports a “shadow epidemic.” The 2005 Report of the Global Advisory on Antibiotic Resistance Data (GAARD), a project and publication of the Alliance for the Prudent Use of Antibiotics (www.apua.org).

SOURCE: www.apua.org.

goals. Efforts should seek cooperation with neighboring countries—something we are encouraging in Africa and in South America. A goal with very positive consequences is to publicize the findings and achievements, no matter how small. The critical issue in these countries is to get the message out and increase awareness with the public but also to stimulate interest and recognition of local leaders that something is happening on this issue. Important, as well, is getting WHO country offices to join APUA in this effort.

Antibiotics Are “Societal Drugs”

Country- and microbe-wide, there are key common concepts that can aid in the education about, and management of, resistance. Antibiotics and antimicrobials are unique therapeutic drugs. Unlike any other therapeutics in which only the individual is affected by therapy, antibiotics are truly “societal” drugs. Each individual use bears the potential for both narrow- and wide-ranging impacts

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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through the selection and propagation of resistant bacteria, the very target of the therapy.

This concept, which I first mentioned at the 25th anniversary of the Institute of Medicine in 1995, distinguishes these kinds of drugs from any other. Individual usage, by shedding of both the antibiotic and the bacteria and their resistance genes, affects the family unit, the community, and the larger society (Levy and Marshall, 2004).

There are a number of studies that illustrate this point. One by Bill Cunliffe’s group in England looked at the effect of antibiotic treatment of individuals for acne on other individuals living in the same home. Homes with acne-treated patients were compared with a cohort of similar age- and gender-matched homes without treatment (cotrimoxazole, erythromycin, tetracycline). As might be expected, the treated acne patients showed greatly increased carriage of resistant bacteria on their skin. Of note, after 7 to 10 days, the people sharing the household with an individual taking medication for acne began to carry high levels of resistant bacteria, mainly Staphylococcus, on their skin, though they were not taking the antibiotic. The control group remained unchanged during this experimental period. There was clearly a societal effect from the use of antibiotics for the acne patients (Cunliffe et al., 1996).

Antibiotics Have an Ecological Impact

By inference from studies among people (see above), antibiotics affect the environment, but their effect may not stay confined to one geographic location. When animals receive antibiotics—whether it be for therapy, prophylaxis, or growth promotion—that use affects farm workers and dwellers in that environment. For instance, the use of antibiotics on farms produces a broad spectrum of drug-resistant bacteria in both the animals and the farm dwellers (Levy et al., 1976). A more far-reaching effect comes through meats sold for food, fecal runoff into groundwater and streams, and manure being spread onto fruits and vegetables. Wildlife, such as birds and flies, have been shown to pick up resistant bacteria from feces and waste and move them to distant sites (Marshall et al., 1990). There is clearly a large environmental impact of antibiotic use.

The Amount of Resistance Reflects Selection Density

Another concept that is important when analyzing antibiotic use and resistance is the number of individuals getting the drug in that particular environment. If you give 100 grams of an antibiotic to one animal, that animal is the one that is going to be the “factory” producing antibiotic-resistant bacteria. If you take the same 100 grams and give it to 100 animals, you are going to have 100 times more animals producing resistant bacteria. I refer to this as “selection density” (Levy and Marshall, 2004). Thus, in order to understand the impact on nature, one has to

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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know how the antibiotic is being distributed. This information is somewhat more transparent in human medicine by the calculated defined daily dose per 1,000 individuals. This figure provides not merely the total quantity of antibiotic but also how much drug is used for how many people. Moreover, when total antibiotic use goes up or down, one should know how many individuals are involved in order to calculate the number of “producers” of resistant bacteria. Thus, the quantity of antibiotic used in one place does not produce a complete picture of the impact in terms of selection and propagation of resistant bacteria.

APUA supported a study in Nepal where a medical student, Judd Walson, looked at antibiotic resistance of fecal E. coli in three groups of people: those in Kathmandu, those 6 hours’ journey from Kathmandu, and those 3 days’ journey from Kathmandu (Walson et al., 2001). The total amount of antibiotics taken by individuals in the three different locations was the same. Drug sellers get to these distant areas. However, the amount of antibiotic resistance in the gut flora of the separate populations was dramatically different. The highest frequency was found in the group living in Kathmandu. This difference was linked to the presence of multiple health centers and a high density of people taking antibiotics there as compared to individuals in the two more distant areas. Although receiving the same amount of antibiotic, the more remote areas were much less densely populated and not subject to the selective force of antibiotics taken by others or to the spread of resistant bacteria.

Antibiotic “Life” After Treatment

Another factor potentially affecting resistance is the fate of the antibiotic after use. Antibiotics from hospitals, communities, and animals go into the environment. We see reports of antibiotics found in municipal waters downstream of a farm (Campagnolo et al., 2002). Resistant bacteria are isolated from vegetables (Levy, 1984). Also important, antibiotics are dispersed environmentally from our own use and leech into the wastewater from hospitals and homes.

One may ask, therefore: What is the biggest contributor to antibiotic resistance? Is it the treated individual getting the drug or the massive amounts of drug introduced into the environment? There are many more bacteria exposed to low-dose antibiotics released into the environment than confronted by drugs used therapeutically. This is particularly evident in veterinary medicine and agriculture.

Reservoirs of Antibiotic Resistance: The ROAR Project

The vast majority of bacteria sharing the environment do not cause disease; they are the commensal bacteria. Over the past decade, there has been an emphasis on the commensal flora as Reservoirs of Antibiotic Resistance (ROAR) (Marshall et al., 2009). Through a 5-year National Institutes of Health grant,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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APUA, collaborating institutions, and individual scientists addressed this concept with sponsored research projects directed at this hypothesis: Do nonclinical strains bear resistance determinants found in clinical strains? The answer was a resounding “yes.”

An APUA project looked at what bacteria are affected by the dispersal of antibiotic. The ROAR project funded 12 different studies, all of which demonstrated the high levels of resistance carried by bacteria that were not causing disease but were in environments where antibiotics were available and spread was easy (www.apua.org).

We are currently engaged in a project sponsored by the National Biodefense Analysis and Countermeasures Center to examine reservoirs of antibiotic-resistant bacteria unassociated with disease in countries on different continents. Animal and environmental isolates are being sent from colleagues in individual APUA country chapter locations: India, South Korea, Turkey, South Africa, Georgia, Uganda, Vietnam, and Bangladesh. We are searching for trends and/or changes over time in antibiotic resistance and the genetic determinants found in one locale versus another. We may identify new resistance genes by analyzing isolates from soil, water, and healthy animals. The project aims to look at whether there are particular commensal and resistance determinants which are prominent in commensals of certain countries.

Antibiotics Warrant a Separate Drug Category

Should there be a separate drug class for antimicrobials? Antimicrobials are different. If they are placed in a separate drug category, then they would be regarded apart from other pharmaceuticals and dealt with as a unique class. For one thing, each individual use affects society. That should be enough; no other drug class can make that claim. Second, antibiotics have limited lifespans, because resistance that emerges in the microbes limits their long-term utility. We do not see that with other drugs.

Placing antimicrobials in a separate drug class:

  • recognizes that antibiotics are not like any other prescription drug;

  • emphasizes the consequences that the individual misuse has on society at large, which is not true of other drugs; and

  • allows special considerations for these drugs in terms of incentives that will allow industry to reenter the discovery field, which it has abandoned, and to develop new drugs.

The workshop explored wonderful new ideas for new antibiotics, but what is missing is who will fund the work and who will make the new drug?

There can be different incentives to enter or return to antimicrobial discovery, such as extended patent life, postmarketing surveillance to curb resistance,

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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tax reliefs, and preservation of antibiotic efficacy through combined efforts from producers and consumers. I am an optimist; I think we can find new drugs, but I also believe we have to learn how to use our current drugs more appropriately. The fewer individuals that are confronted by antibiotics, the less effect the drugs will have on wider society and the environment, as well as the other bacteria that are sharing that environment.

References

Campagnolo, E.R., K. R. Johnson, A. Karpati, C. S. Rubin, D. W. Kolpin, M. T. Meyer, J. E. Esteban, R. W. Currier, K. Smith, K. M. Thu, and M. McGeehin. 2002. Antimicrobial residues in animal waste and water resources proximal to large-scale swine and poultry feeding operations. The Science of the Total Environment 299(1–3):89–95.

Cunliffe, W. J., Y. W. Miller, E. A. Eady, R. W. Lacey, J. H. Cove, and D. N. Joanes. 1996. Sequential antibiotic therapy for acne promotes the carriage of resistant staphylococci on the skin of contacts. Journal of Antimicrobial Chemotherapy 38:829–37.

Levy, S. B. 1984. Antibiotic resistant bacteria in food of man and animals. In Antimicrobials and Agriculture, edited by M. Woodbine. London, United Kingdom: Butterworths, pp. 525-31.

Levy, S. B., and APUA (Alliance for Prudent Use of Antibiotics) (eds.). 2001. Antibiotic resistance: Synthesis of recommendations by expert policy groups. Geneva, Switzerland: World Health Organization.

Levy, S. B., and B. Marshall. 2004. Antibacterial resistance worldwide: Causes, challenges and responses. Nature Medicine 10:S122–9.

Levy, S. B., and T. O’Brien. 2005. Global antimicrobial resistance alerts and implications. Clinical Infectious Diseases 41(Suppl. 4):S219–88.

Levy, S. B., G. B. Fitzgerald, and A. B. Macone. 1976. Changes in intestinal flora of farm personnel after introduction of tetracycline-supplemented feed on a farm. New England Journal of Medicine 295:583–8.

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Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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A11
CHALLENGES AND OPPORTUNITIES IN ANTIBIOTIC DISCOVERY

Kim Lewis

Antimicrobial Discovery Center and the Department of Biology, Northeastern University52

The Nature of the Threat

It is a given that new antibiotics are needed to combat drug-resistant pathogens. However, this is only part of the need; we actually never had antibiotics capable of eradicating an infection. Currently used antibiotics have been developed against rapidly growing bacteria, most of them have no activity against stationary state organisms, and none are effective against dormant persister cells. The relative effectiveness of antibiotics in treating disease is largely a result of a cooperation with the immune system, which mops up after antibiotics eliminate the bulk of a growing population. But the deficiency of existing antibiotics against supposedly drug-susceptible pathogens is becoming increasingly apparent with the rise of immunocompromised patients (HIV infected, undergoing chemotherapy) and the wide use of indwelling devices (catheters, prostheses, heart valves), where the pathogen forms biofilms protecting cells from the components of the immune system. The ineffectiveness of the immune system leads to chronic diseases, which make up approximately half of all infectious disease cases in the developed world. The main culprit responsible for tolerance of pathogens to antibiotics are specialized survivors, persister cells (Lewis, 2007, 2010), which we examine in the following section.

Persisters

Persisters represent a small subpopulation of cells that spontaneously go into a dormant, nondividing state. When a population is treated with a bactericidal antibiotic, regular cells die, while persisters survive (Figure A11-1). In order to kill, antibiotics require active targets, which explains the tolerance of persisters. Taking samples and plating them for colony counts over time from a culture treated with antibiotic produces a biphasic pattern, with a distinct plateau of surviving persisters. By contrast, resistance mechanisms prevent antibiotics from binding to their targets (Figure A11-2).

Infectious disease is often untreatable, even when caused by a pathogen that is not resistant to antibiotics. This is the essential paradox of chronic infec-

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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FIGURE A11-1 Dose-dependent killing with a bactericidal antibiotic reveals a small subpopulation of tolerant cells, persisters.

FIGURE A11-1 Dose-dependent killing with a bactericidal antibiotic reveals a small subpopulation of tolerant cells, persisters.

tions. In most cases, chronic infections are accompanied by the formation of biofilms, which seems to point to the source of the problem (Costerton et al., 1999; Del Pozo and Patel, 2007). Biofilms have been linked to dental disease, endocarditis, cystitis, urinary tract infection, deep-seated infections, indwelling device and catheter infections, and the incurable disease of cystic fibrosis. In the case of indwelling devices, such as prostheses and heart valves, reoperation is the method of choice for treating the infection. Biofilms do not generally restrict penetration of antibiotics (Walters et al., 2003), but they do form a barrier for the larger components of the immune system (Jesaitis et al., 2003; Leid et al., 2002; Vuong et al., 2004). The presence of biofilm-specific resistance mechanisms was suggested to account for the recalcitrance of infectious diseases (Stewart and Costerton, 2001). However, the bulk of cells in the biofilm are actually highly

FIGURE A11-2 Resistance and tolerance. Bactericidal antibiotics kill cells by forcing the active target to produce corrupted products. Persister proteins act by blocking the target, so no corrupted product can be produced. By contrast, all resistance mechanisms prevent the antibiotic from binding to the target. MIC, minimal inhibitory concentration.

FIGURE A11-2 Resistance and tolerance. Bactericidal antibiotics kill cells by forcing the active target to produce corrupted products. Persister proteins act by blocking the target, so no corrupted product can be produced. By contrast, all resistance mechanisms prevent the antibiotic from binding to the target. MIC, minimal inhibitory concentration.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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susceptible to killing by antibiotics; only a small fraction of persisters remains alive (Spoering and Lewis, 2001). Based on these findings, we proposed a simple model of a relapsing chronic infection: antibiotics kill the majority of cells, and the immune system eliminates both regular cells and persisters from the blood-stream (Lewis, 2001) (Figure A11-3). The only remaining live cells are then persisters in the biofilm. Once the level of antibiotic drops, persisters repopulate the biofilm, and the infection relapses. While this is a plausible model, it is not the only one. A simpler possibility is that antibiotics fail to effectively reach at least some cells in vivo, resulting in a relapsing infection.

Establishing potential causality between persisters and therapy failure is not trivial, because these cells form a small subpopulation with a temporary phenotype, which precludes introducing them into an animal model of infection. We reasoned that causality can be tested based on what we know about selection for high persister (hip) mutants in vitro. Periodic application of high doses of bactericidal antibiotics leads to the selection of strains that produce increased levels of persisters (Moyed and Bertrand, 1983; Wolfson et al., 1990). This is precisely what happens in the course of treating chronic infections: the patient is periodically exposed to high doses of antibiotics, which may select for hip mutants. But hip mutants would only gain advantage if the drugs effectively reach, and kill, the regular cells of the pathogen.

Patients with cystic fibrosis (CF) are treated for decades for an incurable P. aeruginosa infection to which they eventually succumb (Gibson et al., 2003).

FIGURE A11-3 A model of a relapsing biofilm infection. Regular cells (red) and persisters (blue) form in the biofilm and are shed off into surrounding tissue and bloodstream. Antibiotics kill regular cells, and the immune system eliminates escaping persisters. The matrix protects persisters from the immune system, and when the concentration of the antibiotic drops, they repopulate the biofilm, causing a relapse.

FIGURE A11-3 A model of a relapsing biofilm infection. Regular cells (red) and persisters (blue) form in the biofilm and are shed off into surrounding tissue and bloodstream. Antibiotics kill regular cells, and the immune system eliminates escaping persisters. The matrix protects persisters from the immune system, and when the concentration of the antibiotic drops, they repopulate the biofilm, causing a relapse.

Suggested Citation:"Appendix A: Contributed Manuscripts." Institute of Medicine. 2010. Antibiotic Resistance: Implications for Global Health and Novel Intervention Strategies: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12925.
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The periodic application of high doses of antibiotics provides some relief by decreasing the pathogen burden, but it does not clear the infection. If hip strains of pathogens were selected in vivo, they would most likely be present in a CF patient. We took advantage of a set of longitudinal P. aeruginosa isolates from a single patient collected over the course of many years (Smith et al., 2006). Testing persister levels by monitoring survival after challenge with a high dose of ofloxacin showed a dramatic, 100-fold increase in surviving cells in the last 4 isolates (Mulcahy et al., 2010). Testing paired strains from additional patients showed that in most cases there was a considerable increase in persister levels in the late isolate from a patient. Interestingly, most of the hip isolates had no increase in minimal inhibitory concentration (MIC) compared to their clonal parent strain to ofloxacin, carbenicillin, and tobramycin, suggesting that classical acquired resistance plays little to no role in the recalcitrance of CF infection. These experiments directly link persisters to the clinical manifestation of the disease and suggest that persisters are responsible for the therapy failure of chronic CF infection. But why have the hip mutants with their striking survival phenotype evaded detection for such a long time?

The main focus of research in antimicrobials has been on drug resistance, and the basic starting experiment is to test a clinical isolate for its ability to grow in the presence of elevated levels of different antibiotics and to record any increases in the MIC. This is also the standard test employed by clinical microbiology laboratories. hip mutants are of course missed by this test, which explains why they had remained undetected in spite of a major effort aimed at understanding pathogen survival of antimicrobial chemotherapy. Given that hip mutants are the likely main culprit responsible for morbidity and mortality of the CF infection, it makes sense to test for