(Maroo and Lamont, 2006). “So there is something wrong,” Young said. The question is, What?
Young and his research team have collected data demonstrating that individuals who have recurrent disease have lower diversity of their indigenous gut microbiota compared to individuals who do not and to healthy individuals. Specifically, Chang and colleagues (2008) examined the diversity of the gut microbiota using culture-independent methods that involve retrieving 16S ribosomal RNA (rRNA)-encoding gene data to distinguish different bacteria. The analysis of these data was accomplished by constructing what are known as rarefaction curves6 for gut microbiota in three groups of patients: (1) individuals successfully treated for C. difficile with a single round of metronidazole or vancomycin, (2) individuals with recurrent disease, and (3) controls. The rarefaction curves showed that individuals with recurrent disease had the least amount of gut microbial diversity. Although the gut microbiome diversity in individuals who were successfully treated for C. difficile was not markedly different from that of the controls, it was at the lower end of what would be considered “normal.” However, intestinal microbial diversity in patients with recurrence was much lower than in the other two groups.
This new knowledge that refractory C. difficile disease is associated with lower gut microbiome diversity helps explain the efficacy of an “alternative” treatment for C. difficile, which has been known of for years but has had a recent resurgence given the increasing burden of C. difficile infection. Instead of administering repeated courses of antibiotics in an attempt to kill the “bad” bug that keeps reappearing, physicians try to treat recurrent C. difficile with what is known as microbiota transplantation. By administering a new microbiota (in the form of the administration of fecal material from a healthy individual), the intention is to restore microbiota diversity and therefore colonization resistance. Despite the obvious “ick factor” of this treatment, it has become an option for patients with multiple recurrences with a greater than 95 percent success rate, according to Young (Gough et al., 2011).
6 Young explained that rarefaction analysis is a tool from classical ecology that provides a general sense of the abundance of different species or, in the case of 16S microbiome data, operational taxonomic units (i.e., bacterial types defined by similar 16S-encoding gene sequences). Rarefaction curves are created by repeatedly sampling the data and plotting the number of unique observations as a function of sampling effort. As the number of samples increases, the number of unique observations decreases. An exhaustive sampling of a community yields a flat curve, indicating that no new species should be identified no matter how many additional samples are taken. When comparing two rarefaction curves derived by sampling two communities, the curve that lies below the other at a given level of sampling indicates that the community from which the curve was derived is less diverse.