The human microbiome plays a key role in a wide range of hostrelated processes and has a profound effect on human health. Comparative analyses of the human microbiome have revealed substantial variation in species and gene composition associated with a variety of disease states but may fall short of providing a comprehensive understanding of the impact of this variation on the community and on the host. Here, we introduce a metagenomic systems biology computational framework, integrating metagenomic data with an in silico systems-level analysis of metabolic networks. Focusing on the gut microbiome, we analyze fecal metagenomic data from 124 unrelated individuals, as well as six monozygotic twin pairs and their mothers, and generate community-level metabolic networks of the microbiome. Placing variations in gene abundance in the context of these networks, we identify both gene-level and network-level topological differences associated with obesity and inflammatory bowel disease (IBD). We show that genes associated with either of these host states tend to be located at the periphery of the metabolic network and are enriched for topologically derived metabolic "inputs." These findings may indicate that lean and obese microbiomes differ primarily in their interface with the host and in the way they interact with host metabolism. We further demonstrate that obese microbiomes are less modular, a hallmark of adaptation to low-diversity environments. We additionally link these topological variations to community species composition. The system-level approach presented here lays the foundation for a unique framework for studying the human microbiome, its organization, and its impact on human health. W e humans are mostly microbes. Microbial communities populate numerous sites in the human anatomy and harbor over 100 trillion microbial cells (1). This complex ensemble of microorganisms, collectively known as the human microbiome, plays an essential role in our development, immunity, and nutrition, and has a tremendous impact on our health (2). Among the various body habitats, the most densely colonized is the distal gut. The normal gut flora alone consists of hundreds of bacterial species, collectively encoding an enormous gene set that is 150-fold larger than the set of human genes (3). The gut microbiome plays a key role in many essential processes, including vitamin and amino acid biosynthesis, dietary energy harvest, and immune development (4). Transferring a donor microbiota into a recipient can induce various donor phenotypes [including increased adiposity (5) and metabolic syndrome (6)] or prompt the recovery of a sick recipient (7), suggesting a promising avenue for clinical application via directed manipulation of the microbiome. Characterizing the capacity of the human microbiome, its interaction with the host, and its contribution to various disease states therefore has the potential to provide deep insight into both normal human physiology and human disease, and calls for a predictive systemslevel understandin...

SUMMARY Within each bacterial species, different strains may vary in the set of genes they encode or in the copy number of these genes. Yet, taxonomic characterization of the human microbiota is often limited to the species level or to previously sequenced strains, and accordingly, the prevalence of intra-species variation, its functional role, and its relation to host health remain unclear. Here we present a first comprehensive large-scale analysis of intra-species copy number variation in the gut microbiome, introducing a rigorous computational pipeline for detecting such variation directly from shotgun metagenomic data. We uncover a large set of variable genes in numerous species and demonstrate that this variation has significant functional and clinically-relevant implications. We additionally infer intra-species compositional profiles, identifying population structure shifts and the presence of yet uncharacterized variants. Our results highlight the complex relationship between microbiome composition and functional capacity, linking metagenome-level compositional shifts to strain-level variation.

Direct observation of evolution in response to natural environmental change can resolve fundamental questions about adaptation, including its pace, temporal dynamics, and underlying phenotypic and genomic architecture. We tracked the evolution of fitness-associated phenotypes and allele frequencies genome-wide in 10 replicate field populations of Drosophila melanogaster over 10 generations from summer to late fall. Adaptation was evident over each sampling interval (one to four generations), with exceptionally rapid phenotypic adaptation and large allele frequency shifts at many independent loci. The direction and basis of the adaptive response shifted repeatedly over time, consistent with the action of strong and rapidly fluctuating selection. Overall, we found clear phenotypic and genomic evidence of adaptive tracking occurring contemporaneously with environmental change, thus demonstrating the temporally dynamic nature of adaptation.