Metagenomics-based strain-resolved bacterial genomics and transmission dynamics of the human microbiome
Creators: name: Karcher, Nicolai Marius
Publisher: name: Universit� degli studi di Trento
Year: 2022

description: The human gut microbiome is home to many hundreds of different microbes which play a crucial role in human physiology. For most of them, little is known about how their genetic diversity translates into functional traits and how they interact with their host, which is to some extent due to the lack of isolate genomes. Cultivation-free metagenomic approaches yield extensive amounts of bacterial genetic data, and recently developed algorithms allow strain-level resolution and reconstruction of bacterial genomes from metagenomes, yet bacterial within-species diversity and transmission dynamics after fecal microbiota transplantation remain largely unexplored over cohorts and using these technological advances. To investigate bacterial within-species diversity I first undertook large-scale exploratory studies to characterize the population-level genomic makeup of the two key human gut microbes Eubacterium rectale and Akkermansia muciniphila , leveraging many hundreds of bacterial draft genomes reconstructed from short-read shotgun metagenomics datasets from all around the planet. For E. rectale , I extended previous observations about clustering of subspecies with geography, which suggested isolation by distance and the putative ancestral loss of four distinct motility operons, rendering a subspecies specifically found in Europe immotile. For A. muciniphila, I found that there are several closely related but undescribed Akkermansia spp. in the human gut that are all likely human-specific but are differentially associated with host body mass index, showcasing metabolic differences and distinct co-abundance patterns with putative cognate phages . For both species, I discovered distinct subspecies-level genetic variation in structural polysaccharide synthesis operons. Next, utilizing a complementary strain-resolved approach to track strains between individuals, I undertook a fecal microbiota transplantation (FMT) meta-analysis integrating 24 distinct clinical metagenomic datasets. I found that patients with an infectious disease or those who underwent antibiotic treatment displayed increased donor strain uptake and that some bacterial clades engraft more consistently than others. Furthermore, I developed a machine-learning framework that allows optimizing microbial parameters - such as bacterial richness - in the recipient after FMT based on donor microbiome features, representing first steps towards making a rational donor choice. Taken together, in my work I extended the strain-level understanding of human gut commensals and showcased that genomes from metagenomes can be suitable to conduct large-scale bacterial population genetics studies on other understudied human gut commensals. I further confirmed that strain-resolved metagenomics allows tracking of strains and thus inference of strain engraftment characteristics in an FMT meta-analysis, revealing important differences in engraftment over cohorts and species and paving the way towards better designed FMTs. I believe that my work is an important contribution to the field of microbiome research, showcasing the power of shotgun metagenomics, modern algorithms and large-scale data analysis to reveal previously unattainable insights about the human gut microbiome.