Speaker
Description
Populations are fundamental units of ecology and evolution, and delineating ecologically meaningful populations among microbes is important for identifying how they adapt to and interact with their local environment. Here, we develop a method to assign closely related isolates to populations by inferring their gene flow information through a tri-partitioning of SNPs distributed across the genome. By applying this method to the whole genomes of over 16,000 publicly available human gut microbiome isolates, we found that approximately 50% of the microbial taxa in the human gut microbiome are highly recombinogenic, while the other 50% consist of one or more “clonal” populations. Especially representative of the “clonal” taxa are Bacteroides: they can be classified into many “clonal” populations, where isolates in each population share the same unique clonal frame, but harbor different genomic islands. Comparative genomics between the different clonal populations revealed their clonal frames mostly differed by genes that were involved in capsule biosynthesis and vitamin B12 metabolism, as well as carbohydrate active enzymes and flagella related proteins. Often isolates from the same Bacteroides population could be found in biogeographically different human populations, indicating the frequent dispersal and recolonization of human gut Bacteroides populations. We are thus currently investigating the distribution of the clonal Bacteroides populations in humans with different health states, and their links to the population “clonal frame” specific genes. We hope that this work will eventually allow us to develop a general “reverse ecology” framework that uses genomic information to find disease associated microbial populations and adaptations in the human gut microbiome.
