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Rakoff-Nahoum, Seth

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Rakoff-Nahoum

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Seth

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Rakoff-Nahoum, Seth

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  • Publication

    The evolution of cooperation within the gut microbiota

    (2016) Rakoff-Nahoum, Seth; Foster, Kevin R.; Comstock, Laurie

    Cooperative phenotypes are considered central to the functioning of microbial communities in many contexts, including communication via quorum sensing, biofilm formation, antibiotic resistance, and pathogenesis1-5. The human intestine houses a dense and diverse microbial community critical to health1,2,4-9, yet we know little about cooperation within this important ecosystem. Here we experimentally test for evolved cooperation within the Bacteroidales, the dominant Gram-negative bacteria of the human intestine. We show that during growth on certain dietary polysaccharides, the model member Bacteroides thetaiotaomicron exhibits only limited cooperation. Although this organism digests these polysaccharides extracellularly, mutants lacking this ability are outcompeted. In contrast, we discovered a dedicated cross-feeding enzyme system in the prominent gut symbiont Bacteroides ovatus, which digests polysaccharide at a cost to itself but at a benefit to another species. Using in vitro systems and gnotobiotic mouse colonization models, we find that extracellular digestion of inulin increases the fitness of B.ovatus due to reciprocal benefits when it feeds other gut species such as Bacteroides vulgatus. This is a rare example of naturally-evolved cooperation between microbial species. Our study reveals both the complexity and importance of cooperative phenotypes within the mammalian intestinal microbiota.

  • Publication

    Harnessing single-cell genomics to improve the physiological fidelity of organoid-derived cell types

    (BioMed Central, 2018) Mead, Benjamin E.; Ordovas-Montanes, Jose; Braun, Alexandra P.; Levy, Lauren E.; Bhargava, Prerna; Szucs, Matthew J.; Ammendolia, Dustin A.; MacMullan, Melanie A.; Yin, Xiaolei; Hughes, Travis; Wadsworth, Marc H.; Ahmad, Rushdy; Rakoff-Nahoum, Seth; Carr, Steven A.; Langer, Robert; Collins, James; Shalek, Alex K.; Karp, Jeffrey

    Background: Single-cell genomic methods now provide unprecedented resolution for characterizing the component cell types and states of tissues such as the epithelial subsets of the gastrointestinal tract. Nevertheless, functional studies of these subsets at scale require faithful in vitro models of identified in vivo biology. While intestinal organoids have been invaluable in providing mechanistic insights in vitro, the extent to which organoid-derived cell types recapitulate their in vivo counterparts remains formally untested, with no systematic approach for improving model fidelity. Results: Here, we present a generally applicable framework that utilizes massively parallel single-cell RNA-seq to compare cell types and states found in vivo to those of in vitro models such as organoids. Furthermore, we leverage identified discrepancies to improve model fidelity. Using the Paneth cell (PC), which supports the stem cell niche and produces the largest diversity of antimicrobials in the small intestine, as an exemplar, we uncover fundamental gene expression differences in lineage-defining genes between in vivo PCs and those of the current in vitro organoid model. With this information, we nominate a molecular intervention to rationally improve the physiological fidelity of our in vitro PCs. We then perform transcriptomic, cytometric, morphologic and proteomic characterization, and demonstrate functional (antimicrobial activity, niche support) improvements in PC physiology. Conclusions: Our systematic approach provides a simple workflow for identifying the limitations of in vitro models and enhancing their physiological fidelity. Using adult stem cell-derived PCs within intestinal organoids as a model system, we successfully benchmark organoid representation, relative to that in vivo, of a specialized cell type and use this comparison to generate a functionally improved in vitro PC population. We predict that the generation of rationally improved cellular models will facilitate mechanistic exploration of specific disease-associated genes in their respective cell types. Electronic supplementary material The online version of this article (10.1186/s12915-018-0527-2) contains supplementary material, which is available to authorized users.