5

Influence of Diet and Dietary Components on the Microbiome

As the workshop progressed, speakers explored in greater depth the impact of diet on the microbiome, how dietary influences on the microbiome contribute to human health and disease, and ways to modulate the microbiome to build and maintain health through the use of prebiotics and probiotics in food products. This chapter summarizes that discussion.

HUMAN BREAST MILK1

Through evolutionary experimentation, mammals have spent the last 120 million years successfully developing “the most efficient, effective and adaptable means of postnatal nutrient provision that has ever arisen among vertebrates: lactation.” —Blackburn (1993)

That a majority of people suffer from diet-dependent diseases raises the question, Is it possible to prevent disease through diet? In his exploration of the preventive potential of the human diet, Bruce German focuses his research on the one food that evolved to be preventive: human breast milk. The cost–benefit trade-off associated with human milk is key to understanding milk’s preventive potential, German explained. Everything in human milk costs the mother. “The mother is literally dissolving her tissues to make milk,” he said. Yet the third most abundant component in milk, the oligosaccharides, are undigestible by the infant. How can this be? How

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1 This section summarizes the presentation of Bruce German.



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5 Influence of Diet and Dietary Components on the Microbiome A s the workshop progressed, speakers explored in greater depth the impact of diet on the microbiome, how dietary influences on the microbiome contribute to human health and disease, and ways to modulate the microbiome to build and maintain health through the use of prebiotics and probiotics in food products. This chapter summarizes that discussion. HUMAN BREAST MILK1 Through evolutionary experimentation, mammals have spent the last 120 million years successfully developing “the most efficient, effective and adaptable means of postnatal nutrient provision that has ever arisen among vertebrates: lactation.” —Blackburn (1993) That a majority of people suffer from diet-dependent diseases raises the question, Is it possible to prevent disease through diet? In his explora- tion of the preventive potential of the human diet, Bruce German focuses his research on the one food that evolved to be preventive: human breast milk. The cost–benefit trade-off associated with human milk is key to under­ tanding milk’s preventive potential, German explained. Everything in s human milk costs the mother. “The mother is literally dissolving her tissues to make milk,” he said. Yet the third most abundant component in milk, the oligosaccharides, are undigestible by the infant. How can this be? How 1  This section summarizes the presentation of Bruce German. 81

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82 THE HUMAN MICROBIOME, DIET, AND HEALTH can such an abundant material of such a costly phenotype be undigestible by the individual for whom it is intended, that is, the infant? What Are Human Milk Oligosaccharides (HMOs), and What Health Benefit Do They Provide the Infant? Glycobiology2 is “disastrously, catastrophically complex,” German said. According to German, the number of possible glycans, or oligosac- charides, in a biological system is in the billions, based on the number of ways that sugars (the basic structural units of glycans) and linkages (the bonds between sugars) can be combined. This makes sense given that oligo- saccharides on cell surfaces are the basis of a recognition system across all life forms. Carlito Lebrilla developed a methodology for analyzing glycan complexity in human milk, based on innovative separation technologies and very high-efficiency, high-accuracy mass spectrometry (Ninonuevo et al., 2006). His research team has constructed an annotated database of the nearly 200 highly variable structural compositions of HMO (Wu et al., 2010, 2011). David Mills was among the first to address the question, What do HMOs do? He hypothesized that HMOs serve as a food source for the infant microbiome. However when he and his colleagues tested bacterial growth on HMO as a sole food source, none but Bifidobacterium infantis grew (Ward et al., 2007). “Perhaps we shouldn’t be surprised,” German said, given that B. infantis is a dominant member of the breast-fed-infant microbiome. Moreover, Mills and his group have discovered that only very specific strains of B. infantis grow on HMO medium. Even bacteria that grow very well on a variety of other sugar media are unable to grow on HMO medium (Marcobal et al., 2010; Ward et al., 2006). (The only other genus that appears to be able to grow on HMO medium is Bacteroides. However, as both German and, later during the question-and-answer pe- riod, Mills explained, B. infantis readily outcompetes Bacteroides when the two are grown together.) “What we are discovering about this remarkable interaction between milk oligosaccharides and this particular bacterium is remarkable,” German said. “Mothers are literally recruiting another life form to babysit their babies and using the oligosaccharides to direct the microbiome.” How does the system work? For example, if oligosaccharides are serv- ing as a food source for B. infantis, which oligosaccharides are being consumed? Mills and his group have discovered that unlike other bifido­ bacteria, B. infantis selectively cleaves and eliminates sialic acid–­ ontaining c 2  Glycobiology is the study of the structure, biosynthesis, and biology of glycans, also called oligosaccharides (i.e., sugar chains).

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INFLUENCE OF DIET AND DIETARY COMPONENTS 83 oligosaccharides (LoCascio et al., 2007; Ward et al., 2007). Only an es- timated 4 to 38 percent of HMOs are sialyated; a higher proportion are fucosylated (40 to 70 percent) (Ninonuevo et al., 2006). Moreover, Mills’s team has also identified which B. infantis genes cleave what HMO linkages (Sela et al., 2011). Interestingly, in German’s opinion, the expression of the bacterial enzyme that actually cleaves the sialyated oligosaccharides is regulated by the abundance of HMOs in the growth medium. There is other evidence indicating that human milk sugars interact with the microbiome in ways that increase the value of the microbiome to the infant. For example, German mentioned the research of Helen Raybould’s group on B. infantis and its role in endocrine signaling in the infant intestine (Chichlowski et al., 2012). The real question, in German’s opinion, is whether the association between HMOs and B. infantis persists as a phenotype in “real life.” That is, “does is really influence the bacteria in living babies?” Data on micro- biome development through the first 12 weeks of an infant’s life show that initially Bifidobacterium is not present in the microbiome (manuscript in preparation), but by week 12 it emerges as a dominant member of the microbiome. Evidence from fecal sampling indicates that HMOs are not being digested during the first weeks of life, presumably because there are no bifidobacteria to digest them, but they begin to disappear from the infant feces at the same time Bifidobacterium begins to dominate the microbiome (manuscript in preparation). Thus, the association between HMOs and B. infantis is a “true symbiotic relationship,” German said. “It’s as impor- tant to feed the bacteria in the baby as the baby.” German suggested that knowledge of human milk–microbiome sym- biosis could be translated into practice in several ways. For example, he mentioned Mark Underwood’s research on the effects of administering a combination of B. infantis and HMOs to premature infants (manuscript in preparation). HOST-MICROBE INTERACTIONS IN THE PERINATAL PERIOD3 There are very few data on the development of the gut microbiota in healthy infants, let alone how diet impacts that microbiota. Yet, there is a plethora of clinical and epidemiological data suggesting that breast-feeding promotes mucosal immune development and protects against many diseases. These data, combined with the fact that human milk contains a variety of bioactive proteins, carbohydrates, and lipids not present in infant formula, raise questions about whether and how the infant gut microbiota differs between breast-fed and formula-fed infants. Sharon Donovan’s long-term 3  This section summarizes the presentation of Sharon Donovan.

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84 THE HUMAN MICROBIOME, DIET, AND HEALTH research goal is to use noninvasive approaches to define how early nutri- tion shapes host-microbe interactions and influences intestinal development in breast-fed versus formula-fed infants. She hopes that the knowledge gained can be used to identify selective additives, such as bioactive proteins, p ­ rebiotics (including HMO), and probiotics that can be added to infant formula to provide some of the health benefits afforded by breast-feeding. Differential Expression of Microbial Genes in Breast-Fed Versus Formula-Fed Infants In what Donovan described as a “proof-of-concept” study, she and colleagues used a method developed by Robert Chapkin (Davidson et al., 1995) for isolating exfoliated epithelial cells from stool to identify genes differentially expressed in breast-fed versus formula-fed infants (Chapkin et al., 2010). Specifically, they analyzed stool samples collected at 3 months of age from vaginally delivered term infants who were medically certified as healthy and who were either exclusively breast-fed (N = 12) or formula- fed (N = 10) (Chapkin et al., 2010). The researchers gained institutional review board (IRB) approval to train the mothers themselves to collect the samples at home. The initial messenger RNA (mRNA) expression microar- ray analysis yielded 4,250 genes that were expressed in all infants. Of those, about 1,200 were significantly differentially expressed between breast-fed and formula-fed infants. Due to the small sample size and thus greater potential for false discovery, the scientists compared these 1,200 genes to a list of 546 that they had predicted could be differentially expressed based on their known roles in intestinal biology. This yielded 146 differentially expressed genes, to which researchers applied a linear discriminant analysis and coefficient of determination analyses developed by Edward Dougherty and colleagues (Dougherty et al., 2009; Kim et al., 2000) to identify the genes that best classified breast-fed versus formula-fed infants and those that were master regulators, respectively. The strongest classifier was EPAS1, which encodes a protein involved in cellular response to hypoxia. Given that necrotizing enterocolitis (NEC) is associated with tissue hypoxia and that human milk has been shown to protect preterm infants from NEC, Donovan speculated that upregulation of EPAS1 in breast-fed infants might be helping those babies’ guts to toler- ate hypoxic episodes. Other genes that qualified as good classifiers are summarized in Table 5-1. The linear discriminant analysis methodology used allowed in- vestigators to identify not just single genes that could be considered good classifiers of breast-fed versus formula-fed infants, but also two- and three- gene combinations (Chapkin et al., 2010). Donovan speculated that these gene expression differences might ex-

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INFLUENCE OF DIET AND DIETARY COMPONENTS 85 TABLE 5-1  Exfoliated Epithelial Cell Genes Identified as Good Classifiers of Breast-Fed (BF) Versus Formula-Fed (FF) Infants, Based on a Linear Discriminant Analysis of Genetic Material Collected from Stool Samples Fold change Gene Name Function (BF/FF) EPAS1 Transcription factor (TF); cellular response to hypoxia 3.3 NR5A2 TF, encodes liver receptor homologue-1 (LRH-1); 2.8 development NR3C1 Encodes glucocorticoid receptor 5.5 PCDH7 Encodes protocadherin-7; membrane protein 3.9 ITGB2 Encodes integrin beta-2 (CD18); ICAM-1 receptor 2.5 FGF5 Encodes fibroblast growth factor 5; mitogenesis and cell 2.0 survival TJP1 Encodes ZO-1; intercellular tight junctions 2.2 MYB TF, transcriptional transactivation; proto-oncogene 2.8 EPIM Syntaxin 2/epimorphin; epithelial cell morphogenesis 2.5 BAD BCL2-associated agonist of apoptosis 4.0 SOURCE: Chapkin et al., 2010. plain some of the clinical and epidemiological evidence that has accumu- lated over the years showing that breast-fed babies’ guts develop differently and are less leaky than those of formula-fed babies. For example, the ex- pression of TJPI, which encodes ZO-1, an intercellular protein that plays an important role in regulating tight junctions, was also upregulated in the cells from breast-fed babies. Additionally, expression of NR3C1, which encodes a glucocorticoid receptor that plays a role in gut differentiation, was fivefold higher in breast-fed than in formula-fed infants. Using MetaCore, a bioinformatics tool that provides information about function, researchers found that some of the strongest signals were with combinations of genes that encode signaling pathways involved in funda- mental pathways of intestinal stem cell proliferation and differentiation, such as WNT and NOTCH. Donovan suggested that these various gene and gene network classifiers could serve as potential biomarkers for differentiating between breast-fed and formula-fed infants. Also, it would be interesting to see if addition of any of these to infant formula, in the form of a prebiotic or probiotic, would shift the gut microbiota toward the direction of breast-fed infants. Next, Donovan and her team tested the hypothesis that the integra- tion of infant (host) epithelial cell transcriptome and functionally profiled microbiome can be used to suggest important regulatory pathways of the microbiome affecting intestinal development in the first few months of life (Schwartz et al., 2012). Community-wide microbial gene expression in stool

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86 THE HUMAN MICROBIOME, DIET, AND HEALTH from the same breast-fed (N = 6) and formula-fed (N = 6) infants from their earlier work (Chapkin et al., 2010) using established protocols (Poroyko et al., 2010) was evaluated using 454 pyrosequencing of DNA libraries cre- ated from stool samples. Taxonomic composition of the metagenome was analyzed with the metagenomics analysis server MG-RAST using similarity to a large nonredundant protein database. Using the same database, the sequence alignments for known microbial metabolic functions were tested against the SEED subsystems.4 At the phyla level, all formula-fed infants shared the same distinct signature, whereas breast-fed infants were more variable. Three of the breast-fed infants had similar profiles, but the other three “were sort of going to the beat of their own drummer,” said ­ onovan. D She noted that all of the formula-fed infants were receiving the same for- mula but that breast milk composition can be highly variable. Using established protocols for evaluating community-wide microbial gene expression in stool samples, the team observed a greater total percent- age (i.e., percentage of total 16S ribosomal RNA [rRNA]) of Actinobacte- ria, Proteobacteria, and Bacteroidetes in breast-fed piglets as a group and a greater total percentage of Firmicutes and no Bacteroidetes in formula- fed infants as a group (see Figure 5-1) (Donovan et al., 2012). Donovan remarked that these findings warrant follow-up, given Peter Turnbaugh and colleagues’ observation that obesity in mice is associated with a higher Firmicutes:Bacteroidetes ratio. In addition, epidemiological studies have demonstrated that breast-feeding protects against the development of child- hood obesity. Which Human Genes Respond to Bacterial Signals? An overarching theme of the workshop discussion was the importance and growing interest in understanding not just what bacteria are present in the microbiome, but how those bacteria are signaling in a way that impacts the human host biology. For example, Donovan expressed curiosity about whether differences in microbial gene expression between breast-fed and formula-fed infants impact host gene expression. A comparison of the func- tional SEED categories of the stool metagenome of breast-fed and formula- fed infants demonstrated a significantly higher proportion of virulence genes in the breast-fed infants. Next, the scientists applied a systematic and statisti- cally rigorous analytic framework for the simultaneous examination of both host and microbial responses to dietary or environmental components in the early neonatal period. Specifically, using canonical correlation analysis, 4  SEED is an open-source software platform that seeks to curate microbial genomic data into subsystems-based functional annotation (e.g., amino acid metabolism). More information is available online: www.theseed.org (accessed August 28, 2012).

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INFLUENCE OF DIET AND DIETARY COMPONENTS 87 Breast-fed (BF) Formula-fed (FF) Verrucomicrobia Un_sub_classified Un_sub_classified Firmicutes 3.2% 3.3% 7.0% 9.8% Proteo- bacteria 11.1% Firmicutes Bacteroidetes 35.1% 19.6% Actinobacteria Proteobacteria 37.1% Actinobacteria 26.4% 46.4% • BF had more total Proteobacteria and Bacteriodetes • FF had more Firmicutes and no Bacteriodetes FIGURE 5-1  Results from a study on breast-fed versus formula-fed human infants showing variation in gut microbial composition. SOURCE: Donovan et al., 2012. Figure 5-1 Donovan and her team identified associations between the microbiome viru- lence genes and 11 host immunity defense genes (TACR1, VAV2, ALOX5, NDST, REL, BPILI, AOC3, KLRF1, DUOX2, IL1A, and SP2) (Schwartz et al., 2012). Donovan speculated on the potential biomarker usefulness of microbial sequencing, in this case as a way to predict host defense mecha- nisms. These findings suggest that simultaneously examining the multivariate structure underlying the microbiome and gut transcriptome leverages richer and fuller information content compared to analyses focusing on single data­ sets (e.g., only host transcriptome data or only microbiome data) and only single variables (e.g., gene-by-gene differential expression testing). The use of canonical correlation analysis can support the formulation of hypothesis- based studies by accurately identifying those genes active in commensal microbiome and host activities (Schwartz et al., 2012). What Components in the Infant Diet Affect the Intestinal Microbiota? Nutrients and bioactive components in human milk directly influence the development of the infant’s immune system, actively protect the infant from pathogenic infection, and facilitate establishment of the microbiota, the last of which is required to activate the mucosal immune system. Recent data suggest that HMOs contribute to many of these activities (Donovan et al., 2012). Oligosaccharides are the third most predominant component

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88 THE HUMAN MICROBIOME, DIET, AND HEALTH of milk, after lactose and fat, and up to 200 different structural forms have been identified in human milk (Wu et al., 2010, 2011). Since HMOs are resistant to digestion by the infant and pass into the colon, Donovan described them as the fiber of human milk, a fact that she said hasn’t really been appreciated until recently. In the colon, they potentially function in a variety of ways, including as substrates for fermentation and the production of short-chain fatty acids. They can also serve as prebiotics for beneficial bacteria. Donovan referred to David Mills’s very elegant data showing that Bifidobacterium infantis metabolizes specific HMOs (see the previous sec- tion for a more detailed description of work conducted in the Mills labora- tory and by Bruce German). HMO composition is influenced partly by secretor status of the mother and whether she has the 2-fucosyltransferase gene; non-secretor mothers do not produce 2'-fucosyllactose (2'-FL), which is one of the primary HMOs in the milk of secretor mothers. Therefore, Donovan and others are exploring potential predictive associations between HMO composition and infant gut microbiota. Systematic evaluation of the impact of HMO on infant devel- opment, however, has been limited by the lack of sufficient quantities of pure HMOs to conduct animal or human feeding studies. However, in the near future, this limitation will be overcome through improved synthetic approaches, opening avenues of investigation into the biology of HMOs. Additionally, the availability of noninvasive methods of assessing outcomes in human infants (Chapkin et al., 2010; Schwartz et al., 2012) and high- throughput methods for measuring HMOs (Wu et al., 2010, 2011) and the infant microbiome (Schwartz et al., 2012) will facilitate our understanding of the role of HMOs in host-microbe interactions in the developing infant (Donovan et al., 2012). THE RESISTOME AS A DRIVER OF THE MICROBIOME5 Food is not the only major driver of the microbiome. So too is the way we raise food, Ellen Silbergeld stated. Most food animals are grown very intensively, including through the use of animal feeds that contain antibiot- ics. Food and Drug Administration (FDA) data indicate that 80 percent of total antimicrobial production in the United States in 2009 was for use in animal feed.6 Silbergeld stressed that the use of antibiotics in animal feed is not for veterinary medical purposes; rather, antibiotics are added to feed 5  Thissection summarizes the presentation of Ellen Silbergeld. 6  These values were calculated by the Center for a Livable Future based on data pro- vided by the Food and Drug Administration. For more information, read the posting on its website: http://www.livablefutureblog.com/2010/12/new-fda-numbers-reveal-food-animals- consume-lion%E2%80%99s-share-of-antibiotics (accessed September 19, 2012).

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INFLUENCE OF DIET AND DIETARY COMPONENTS 89 as growth promotants. This is a new phenomenon in the history of antimi- crobials and one with significant implications for what Silbergeld referred to as the “resistome.” The Resistome The term “resistome” was introduced by Wright (2007), who defined it as the collection of all the antibiotic resistance genes and their precursors in the entire microbial community of both pathogenic and nonpathogenic bacteria. Genes within the resistome encode molecular changes that confer phenotypic resistance to both general and specific antibiotic molecules. They are often clustered in cassettes and are transferable by plasmids, creat- ing a pleiotropic efficacy. Multigene cassettes can encode other phenotypes, not just resistance. An important feature of the resistome is that resistance genes are read- ily transferred from one bacterial cell to another via horizontal, or lateral, gene transfer (usually via plasmid-mediated transfers but also by conjuga- tion). The classic model of antibiotic resistance describes a population of diverse organisms encountering antibiotic pressure, with some organisms being susceptible and some resistant and with the susceptible organisms dying and the resistant organisms persisting (Sommer and Dantas, 2011). However, that model does not account for the dynamic nature of horizontal gene transfer and the fact that a population of initially susceptible bacteria can accumulate expressible resistance genes over time. Even after a stressor is withdrawn, this system can be permanently altered by the experience. In a study of humans exposed to ciprofloxacin, Dethlefsen and Relman (2011) showed that resistant phenotypes persisted even after exposure ended. Increasingly, horizontal gene transfer involves not just the sharing of single genes, but also the sharing of cassettes of multiple genes. Silbergeld explained how the extensive use of antimicrobials exerts multiple and repeated pressures on bacterial populations, resulting in sequential acquisi- tion of resistance genes and buildup of multigene cassettes (Canton and Ruiz-Garbajosa, 2011). As empirical evidence of the buildup of transferable multigene cassettes, Silbergeld mentioned U.S. Department of Agriculture (USDA) data showing growth over time of extended multidrug resistance phenotypes of Escherichia coli in domestic animals (i.e., chicken, swine, cat, dog, dairy cattle) (Lindsey et al., 2011). Not only is the resistome accruing more resistance genes, either singly or bundled in multigene cassettes, it also appears to be accumulating net- works of preferential horizontal gene transfers, or “cliques” (Skippington and Ragan, 2011). Again, extensive antimicrobial use is exerting selective pressure, in this case for more active networks of horizontal gene transfer.

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90 THE HUMAN MICROBIOME, DIET, AND HEALTH The bacteria involved in any given network, or clique, are not necessarily in close proximity and may not even share the same ecology. Silbergeld described the resistome as being analogous to cloud com- puting, because it is a resource that can be externalized and accessed by various groups of bacteria and because the transfer of resistance genes via horizontal gene transfer is like transferring downloaded bytes of data. She stressed the importance of recognizing that the resistome encompasses both pathogenic and nonpathogenic bacteria and may include most of the bacteria in a specific microbiome. From the Modern Livestock Farm to Humans: Implications for the Resistome Selective pressures exerted by extensive antibiotic use abound in the modern livestock farm, which Silbergeld described as an “impressive labo- ratory for driving microbial evolution.” Danzeisen et al. (2011) sampled the microbiomes of chicken ceca after feeding chickens either control feed, feed with monensin (an antibiotic), or feed with virginiamycin (another antibiotic) and detected significant differences in microbiome content (e.g., percentage of total microbes represented by Lachnospiraceae versus Ru- minococaceae). However, it is not just the flora that is changing in the face of increased antimicrobial pressure. Researchers are also reporting an increased prevalence of antibiotic-resistant phenotypes in food animals fed antibiotic-containing diets (Looft et al., 2012) (see Figure 5-2). Importantly, the increased prevalence of resistant phenotypes being ob- served in the guts of farm animals persists not just in their microbiome but in the resistome at large, mainly because of the practice of land disposal of animal wastes without required pretreatment. For example, Nandi et al. (2004) traced the movement of resistance genes from poultry litter into the soil environment where poultry waste was deposited. Eventually, humans can potentially become exposed to those same resistance genes via several routes. One way to represent the resistome and the way it transcends, or ex- tends across, all of these different microbiomes, from farm animals to soil bacteria to the human gastrointestinal (GI) tract, is as a nested system of increasing complexity, where components occupy different spaces in the ecosystem and events that occur can eventually impact the human micro- biome (Davis et al., 2011). Silbergeld’s research group is conducting an ongoing study of the historical ecology of the Chesapeake Bay to see if the appearance of resistance genes in sediment correlates with the introduction of intensive poultry production and the use of antibiotics in poultry feed. Some experts consider antibiotic-resistant genes to be environ­ ental m pollutants that bioaccumulate over time (Martinez, 2009). Although a ­ ntibiotics are generally not very persistent in the environment, if humans

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INFLUENCE OF DIET AND DIETARY COMPONENTS 91 10000 Normalized number of 16S 8000 sequences 6000 Desulfovibrio Campylobacter 4000 Escherichia/Shigella Succinivibrio 2000 0 Nonmed Med Nonmed Med day 0 day 0 day 14 day 14 150 145 Escherichia Number of reads 20 Shigella Oxalobacter 15 Desulfovibrio Prevotella 10 Parabacteroides Chitinophaga 5 Bacteroides Other 0 Nonmed Med Nonmed Med day 0 day 0 day 14 day 14 NonMed Day 0 Med Day 0 10-3 NonMed Days 3-21 Med Days 3-21 ab a (ARG / 16S rRNA) copy numbers a ab a a a ab a ab 10-4 ab ab ab b b 10-5 ab b b b b b b 10-6 b b 10-7 Class A Beta Tetracycline Sulfonamide Aminoglycoside Resistance- Major Facilitator Lactamase Efflux Pump Resistance O-phospho- Superfamily transferase Division Transporter Transporter FIGURE 5-2  Results from a study showing a shift in gut microbiota (top figures) and an increased prevalence of antibiotic-resistant phenotypes (bottom figure) in food animals fed antibiotic-containing diets (“GPA feeds”). NOTES: ARG = antibiotic-resistant gene; med = antibiotic-containing diet; nonmed = control. Columns with the same letter are not statistically significant (p > 0.05) within each resistance type. SOURCE: Looft et al., 2012.

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110 THE HUMAN MICROBIOME, DIET, AND HEALTH leverage this science on the microbiome to develop products that maintain or improve health? Establishing causal relationship allows for microbes to be targeted, and the next step is to identify specific active ingredients and components that target these microbes and their impact on host health. Or, as van Hylckama Vlieg expressed, “Science provides increased rationale for functional food concepts using pre- and probiotics that bring a clear health benefit to consumers.” Leveraging the Microbiome for Health In fact, humans have been leveraging the microbiome for a long time, initially through animal husbandry and consumption of fermented foods and moving toward science-based evidence for dietary intake. Fermented foods are important constituents of the human diet worldwide, and use of these foods dates back approximately 10,000 years (Evershed et al., 2008). These fermentations are often carried out with lactic acid bacteria. As van Hylckama Vlieg explained, lactic acid bacteria are also natural inhabitants of the human GI tract, so foods fermented by lactic acid bacteria are effec- tively supplementing the indigenous microbiota. In fact, lactic acid bacteria could be considered “domesticated” microbes. By substituting “microbe” for “animal” or “plant,” they fit the Webster’s dictionary definition of domesticated: “to adapt (an animal or plant) to life in intimate association with and to the advantage of humans.”16 As an example of how Danone has leveraged the microbiome for health, van Hylckama Vlieg highlighted work on a fermented food product containing Bifidobacterium animalis subsp. lactis strain CNCM I-2494. The impact of FMP on the gut microbiome and host health was explored using a specific mouse model (T-bet-/- and Rag2-/- knockout mice, also known as TRUC mice) that spontaneously develops gut inflammation resembling hu- man ulcerative colitis (Garrett et al., 2007). Garrett et al. (2007) reported that antibiotics reverse inflammation in TRUC mice, indicating a microbial etiology. Plus, when they co-housed TRUC and wild-type mice, they ob- served colitis in the wild-type mice as well, indicating the communicability of whatever gut microbes were associated with inflammation in the TRUC mice. While a population of individuals with ulcerative colitis is far removed from Danone’s target population, using that sort of extreme model can pro- vide cleaner data and reveal mechanisms more readily than would be possi- ble using other methods. Using the TRUC mouse model, Veiga et al. (2010) analyzed the TRUC gut microbiota by 16S rDNA sequencing and observed low levels of Bifidobacterium in the colon compared to non-inflamed (wild- 16  See http://www.merriam-webster.com/dictionary/domesticate.

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INFLUENCE OF DIET AND DIETARY COMPONENTS 111 type) mice. They observed that feeding the TRUC mice 100 milligrams of FMP per day decreased intestinal inflammation (<0.0001 compared to TRUC mice fed the same amount of nonfermented food product) and in- creased levels of short-chain fatty acids (acetic acid, propionic acid, butyric acid). They also observed increased levels of lactate-consuming bacteria in the FMP-fed TRUC mice. The researchers showed “very elegantly,” accord- ing to van Hylckama Vlieg, that the newly altered intestinal environment in FMP-fed mice inhibits growth of colitogenic bacteria. Research on the impact of FMPs on TRUC mouse microbiome and host health is ongoing. Meanwhile, another study with the same FMP product on the gut mi- crobiomes of healthy twin pairs and gnotobiotic mice demonstrated that FMPs do not cause any major perturbation of the dominant microbiota of healthy human subjects. However, this product does trigger distinct re- sponses in the activity of the microbiome detected through transcriptomics (McNulty et al., 2011). Also, in both the mouse model and human samples, the metabolic activity of gut Bifidobacterium animalis subsp. lactis is dra- matically altered. B. animalis subsp. lactis harvests and grows on the xylo- oligosaccharides derived from dietary components, which demonstrates that strain is becoming an active member in the gut microbial community. Microbiome Biomarkers: Implications for Personalized Nutrition In addition to research on mouse models and human samples, Danone is a partner of the MetaHIT Consortium. Acknowledging controversy about the biological relevance as expressed during the meeting regarding the existence of enterotypes, van Hylckama Vlieg remarked that regardless, “the observation is there” (Arumugam et al., 2011). The question is, What are the implications for the food industry? Do observations of enterotypes or any other clusters of markers in the microbiome indicate that people have specific nutritional needs, perhaps specific probiotic needs, depending on their microbiota compositions? It may be possible that these issues will lead to the emergence of personalized, or categorized, nutrition in coming years. In preparation for these coming years, Danone is building and main- taining a culture collection of more than 3,000 microbes, mainly lactic acid bacteria. The collection includes strains isolated from multiple geographic areas (i.e., from various countries), ecoystems (i.e., from dairy products, cereals, plants, and stools), and time periods (i.e., from the 1960s through the present) and contains more than 80 species. They have sequenced nearly 100 genomes in the collection. “It is a very powerful platform for discovery,” van Hylckama Vlieg said. Much of its power stems from its focus on strain diversity. In a comparative genome hybridization study of 42 strains of Lacto­bacillus plantarum, Siezen and colleagues (2010) found

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112 THE HUMAN MICROBIOME, DIET, AND HEALTH that while about 70 percent of the genome of L. plantarum is shared among all strains, there are many genes not shared by all strains and many strain- specific genes. Strain individuality raises the key question: What is the correlation with functional diversity? Currently, Danone investigators have been exploring the “pangenome” of multiple strains of two species, L. rhamnosus and L. paracasei, for gene-function correlations. Researchers are building a ge- nome diversity database and coupling that with an extensive phenotyping program. Such studies will help to identify both common activities shared by many strains and specific features that can only be delivered by a few strains. According to van Hylckama Vlieg, Danone scientists are looking at phenotypes related to carbohydrate utilization and short-chain fatty acid production, antimicrobial activity, and immune modulation. As an example of the type of results they are collecting, a sequencing analysis of 12 strains of L. rhamnosus and 30 strains of L. paracasei indicated that about 30 to 40 percent of the genome is “core,” that is, shared among all strains. However, up to 25 percent of genes are strain-specific, with different strains having different immune function effects (i.e., based on an NF-kappa B-type screen on HT29 cells). DISCUSSION Most of the discussion during the question-and-answer period at the end of this session revolved around three major issues: (1) functional con- sequences of modulating the microbiome through food, (2) whether there are any known adverse effects of prebiotic and probiotic interventions, and (3) experimental design and study size. Focus on Function A recurring theme of the workshop was the importance of functional, not just compositional, changes to the microbiome as a result of dietary (or antibiotic) intervention. For example, as summarized in this chapter, Johan van Hylckama Vlieg mentioned research results demonstrating that Activia does not cause any major perturbation of the microbiota but does trigger distinct transcriptomic responses related to the metabolic activity of Bifidobacterium animalis. Also, George Fahey commented on the results of a study showing several positive metabolic outcomes associated with oligo- fructose consumption in mice. Finally, James Versalovic elaborated on the many ways that probiotics can impact host immunity. An audience member asked whether, given that food products appear to impact the microbiome not by recolonizing (so not by changing the taxonomic makeup of the mi-

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INFLUENCE OF DIET AND DIETARY COMPONENTS 113 crobiome), by rather through signaling (changing the way the microbiome is functioning), does it matter whether the food product in question is a live organism (i.e., a probiotic) or an inert substance (i.e., a prebiotic)? In other words, is the differentiation between probiotic and prebiotic a false dichotomy? Are the conceptual barriers between probiotic and prebiotic artificial? Versalovic agreed that as the field moves forward, hopefully the dia- logue will move beyond definitions and focus more on how food is impact- ing health via its effect on the microbiome. The value of the discovery of histamine as a microbially produced molecule that impacts host immunity isn’t the histamine itself. Rather, its value is that “it has pointed us in a whole new direction—to look at amino acid conversions.” Are other amino acids being converted by microbes? What other enzymatic machinery is the microbiome providing for the biochemical conversion of dietary informa- tion into biological signals? Versalovic said, “We’re on entirely new trails in the wilderness.” His research group is also studying another microbially catalyzed bioconversion of a host dietary substance into a biological signal, that is, glutamate into gamma-aminobutyric acid (GABA). He speculated on the potential regulatory role of the gut microbiome with respect to how much dietary information is actually being converted in vivo. “What’s re- ally intriguing here,” he said, “is that that may be how the microbiome is really contributing to health and physiology … providing the enzymatic machinery, the metabolic pathways, at a particular location. It could be the GI tract. It could be the airways. It could be the oral cavity … providing that machinery that then allows [for the conversion of] the dietary content into [a] signal for the body.” Adverse Effects? An audience member asked whether there were any known adverse e ­ ffects of prebiotic or probiotic interventions. Mary Ellen Sanders replied that the National Institutes of Health (NIH) recently commissioned a review on probiotic safety that covered hundreds of prevention and treatment-of- disease studies of a variety of microbes (Hempel et al., 2011). The review concluded that most studies have not been adequately designed to address safety. Sanders speculated that the lack of safety data is likely due to the fact that probiotics have always been viewed as a food. They have not been viewed as drugs or as something that potentially could cause problems, at least not when administered to healthy people. So in the past, most re- searchers jumped right into efficacy studies, bypassing what would be the equivalent of a phase I drug study. Today, more researchers are designing their studies with safety factors in mind. Meanwhile, to Sanders’s knowl- edge, at least for the most commonly researched microbes there is no or

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114 THE HUMAN MICROBIOME, DIET, AND HEALTH very little association of use in a normal population with any adverse effects of real concern. There are some notable exceptions, she said. For example, Besselink et al. (2008) reported increased mortality after administration of probiotics to patients with severe pancreatitis. Sanders cautioned that not only do different microorganisms have different safety patterns, but that the health status of the host also influences safety. Dan Levy emphasized the need to examine strain-specific safety effects. He said, “The tendency has been to say, well, we’re exposed to all of these lactic acid bacteria with no adverse effects.” But not all lactic acid bacte- ria are the same. While some strains may cause no adverse effects, that is not necessarily the case for all strains. This is especially worrisome when a strain is chosen for a unique property, that very uniqueness suggesting that the strain does not behave like others, particularly when selecting for strains intended to have specific and perhaps novel physiological effects on the consumer. “You have to stop lumping all lactic acid bacteria together,” Levy said. “We’re looking at specific physiological mechanisms associated with specific strains, and we have to study the good, the bad, and the ugly.” Experimental Design and Study Size The discussion of microbiome markers of health and disease prompted a couple of comments on experimental design. Ellen Silbergeld expressed concern that too many studies on the microbiome are “almost entirely underpowered,” raising serious questions about the value of the informa- tion being provided by those studies. If a study is too underpowered to provide any evidence of an effect, then what is the value of that study? “If you really want to move this field forward,” she said, “you really have to start considering your study design.” In response, Johan van Hylckama Vlieg remarked that many small studies, such as the twin study that he mentioned, are intended to be exploratory and hypothesis-generating. They are not intended to yield the same type of results that large-scale clinical trials provide. Silbergeld then wondered whether any of the larger stud- ies actually meet the criteria of a clinical trial. It is not clear that any do. Versalovic questioned whether large-scale clinical trials are even appropri- ate for microbiome studies. Given such extreme individual-level variation in microbiome composition and function, he said, “I don’t know that we can do trials the same way anymore,” indicating the need for further discussion on issues of study design.

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