Many microbiota-based therapeutics rely on our ability to introduce a microbe of choice into an already-colonized intestine. However, we remain largely blind to the quantitative effects of processes determining colonization success. In this study, we used genetically-barcoded Bacteroides thetaiotaomicron (B.theta) strains in combination with mathematical modeling to quantify population bottlenecks experienced by B.theta during gut colonization. Integrating population bottlenecks sizes with careful quantification of net growth rates in vitro and in vivo allows us to build models describing the events during intestinal colonization in the context of gnotobiotic and complex microbiotas. Using these models, we estimated the decrease in niche size for B.theta colonization with increasing microbiota complexity. In addition, our system can be applied to mechanistically dissect colonization defects of mutant strains. As a proof of concept, we demonstrated that the competitive disadvantage of a B.theta mutant lacking capsular polysaccharide is due to a combination of an increased lag-phase before growth initiation in the gut, combined with an increased clearance rate. Crucially, the requirement for the B.theta capsule depended strongly on microbiota composition, suggesting that the dominant role may be protection from bacterial or phage aggression rather than from host-induced bactericidal mechanisms.
Many microbiota-based therapeutics rely on our ability to introduce a microbe of choice into an already-colonized intestine. In this study, we used genetically barcoded Bacteroides thetaiotaomicron (B. theta) strains to quantify population bottlenecks experienced by a B. theta population during colonization of the mouse gut. As expected, this reveals an inverse relationship between microbiota complexity and the probability that an individual wildtype B. theta clone will colonize the gut. The polysaccharide capsule of B. theta is important for resistance against attacks from other bacteria, phage, and the host immune system, and correspondingly acapsular B. theta loses in competitive colonization against the wildtype strain. Surprisingly, the acapsular strain did not show a colonization defect in mice with a low-complexity microbiota, as we found that acapsular strains have an indistinguishable colonization probability to the wildtype strain on single-strain colonization. This discrepancy could be resolved by tracking in vivo growth dynamics of both strains: acapsular B .theta shows a longer lag-phase in the gut lumen as well as a slightly slower net growth rate. Therefore, as long as there is no niche competitor for the acapsular strain, this has only a small influence on colonization probability. However, the presence of a strong niche competitor (i.e., wildtype B. theta, SPF microbiota) rapidly excludes the acapsular strain during competitive colonization. Correspondingly, the acapsular strain shows a similarly low colonization probability in the context of a co-colonization with the wildtype strain or a complete microbiota. In summary, neutral tagging and detailed analysis of bacterial growth kinetics can therefore quantify the mechanisms of colonization resistance in differently-colonized animals.
The metabolic “handshake” between the microbiota and its mammalian host is a complex, dynamic process with potentially major influences on health. Dissecting the interaction between microbial species/strains and metabolites found in host tissues has been a challenge due to the high diversity of a complete micro-biota and the requirement for invasive sampling, which precludes high-resolution longitudinal analysis. Here we demonstrate that secondary electrospray ionization mass spectrometry can be used to non-invasively monitor metabolic activity of the intestinal microbiome of a live, awake mouse. This was achieved via analysis of the headspace volatile and semi-volatile metabolome of individual gut microbiota bacterial species growing in pure culture, as well as from live gnotobiotic mice specifically colonized with these microbes (i.e. metabolites released to the atmosphere via breath, the skin and from the gut). The microbial origin of these compounds was confirmed by feeding of heavy-isotope labeled microbiota-accessible sugars. This reveals that the microbiota is a major contributor to the released metabolites of a whole live mouse, and that it is possible to capture the catabolism of sugars and cross-feeding within the gut microbiota of a living animal using volatile/semi-volatile metabolite monitoring.
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