Gnotobiotic animals have long been used to highlight major functions of the intestinal microbiota such as its contribution to trophic development of gut tissues, immune maturation, direct protection from colonization/proliferation of pathogens (the barrier effect) and more recently its implication in metabolism and fat storage. Yet gnotobiology had never been used in a systematic way as a screening tool. This is what JJ Faith and colleagues are presenting in their paper published Jan 22, 2014 in J. J. Faith, P. P. Ahern, V. K. Ridaura, J. Cheng, J. I. Gordon, Identifying gut microbe–host phenotype relationships using combinatorial communities in gnotobiotic mice. Sci. Transl. Med. 6, 220ra11 (2014).
The approach used calls for the isolation by culture of bacterial members of the dominant intestinal microbiota of a few individuals and the use of these isolates in a combinatorial approach expected to allow pinpointing small cocktails of bacteria that may be active in concert towards signal metabolites output, obesity (fat storage) of Treg immune modulation.
This has been used in numerous conditions in the past, noticeably in the context of a key function of the microbiota, i.e. the ‘barrier effect’, or colonization prevention against pathogens (Fons et al. ; Rambaud JC.).
In the present work, the foreseen originality is the fairly high throughput never reached before. Yet limitations are bound to be the same as in the past:
1) There is yet no possibility to demonstrate that a given bioactive cocktail of culturable strains is actually the major actor in vivo in the initial complex ecosystem from which it derives
2) The control condition used in the present work to qualify a bioactivity is the germ free animal for which it is acknowledged that physiology and immunology are abnormally developed. Induction of a T-regulatory response for example may not be greater than what the complex microbiota will consistently induce.
Beyond these intrinsic limitations, the expectations were to pinpoint bioactive cocktails, and the striking result is that single strains or pairs are sufficient to recapitulate the effect of the ecosystem reduced to 15 culturable candidates.
Links with bacterial signal-metabolites are interesting, but they should be predictable from sequence mining of the annotated genomes or at least validated a posteriori on that basis, when they are not known from the taxonomix description of the strains.
Links with induced adiposity were only explored in mono-associations (single strains). This supports the concept that specific bacteria may act quite differently on the immune tone for example, or Fiaf or PPAR gamma modulation.
Links with T-regulatory response indicated that single strains or pairs might be sufficient to induce the modulation obtained by the 15-strains complex that recapitulates the impact of the complex ecosystem.
Finaly, as discussed by the authors, the identification of bioactive strains is but the start of a specific story when looking for a mechanistic understanding. This will in turn require both 1) a broader scan of modulated biomarkers (other cell type for immunity for example) and 2) a reduction of genetic information to tentatively identify for each strain the genes and metabolites involved.
Depending on the number of strains necessary to saturate a given pathophysiological effect, the strains but also the genomes or genome fragments may constitute the most appropriate level to explore functionalities. Hence gnotobiology may be used as the port of entry for screening and later lead to functional characterization of the mode of action of bioactive strains by genome/metabolome level of exploration. Conversely, a culture independent approach can be implemented based on the cloning of large genome fragments and functional screening initially in vitro (Lakhdari et al.) and downstream in gnotobiotic animals to ascertain physiopathological relevance.
Both methods will have advantages and limitations and should likely be viewed as fully complementary. They represent strategic modalities to eventually gain an understanding of the functionalities of intestinal microbes modulated by bacteria-host crosstalk mechanisms.
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