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Abstract Gut microbiomes, such as the microbial community that colonizes the rumen, have vast catabolic potential and play a vital role in host health and nutrition. By expanding our understanding of metabolic pathways in these ecosystems, we will garner foundational information for manipulating microbiome structure and function to influence host physiology. Currently, our knowledge of metabolic pathways relies heavily on inferences derived from metagenomics or culturing bacteria in vitro. However, novel approaches targeting specific cell physiologies can illuminate the functional potential encoded within microbial (meta)genomes to provide accurate assessments of metabolic abilities. Using fluorescently labeled polysaccharides, we visualized carbohydrate metabolism performed by single bacterial cells in a complex rumen sample, enabling a rapid assessment of their metabolic phenotype. Specifically, we identified bovine-adapted strains of Bacteroides thetaiotaomicron that metabolized yeast mannan in the rumen microbiome ex vivo and discerned the mechanistic differences between two distinct carbohydrate foraging behaviors, referred to as “medium grower” and “high grower.” Using comparative whole-genome sequencing, RNA-seq, and carbohydrate-active enzyme fingerprinting, we could elucidate the strain-level variability in carbohydrate utilization systems of the two foraging behaviors to help predict individual strategies of nutrient acquisition. Here, we present a multi-faceted study using complimentary next-generation physiology and “omics” approaches to characterize microbial adaptation to a prebiotic in the rumen ecosystem. 

Abstract Changes in the sequence of an organism’s genome, i.e., mutations, are the raw material of evolution. The frequency and location of mutations can be constrained by specific molecular mechanisms, such as diversity-generating retroelements (DGRs). DGRs have been characterized from cultivated bacteria and bacteriophages, and perform error-prone reverse transcription leading to mutations being introduced in specific target genes. DGR loci were also identified in several metagenomes, but the ecological roles and evolutionary drivers of these DGRs remain poorly understood. Here, we analyze a dataset of >30,000 DGRs from public metagenomes, establish six major lineages of DGRs including three primarily encoded by phages and seemingly used to diversify host attachment proteins, and demonstrate that DGRs are broadly active and responsible for >10% of all amino acid changes in some organisms. Overall, these results highlight the constraints under which DGRs evolve, and elucidate several distinct roles these elements play in natural communities.