SignificanceIn this very large-scale longitudinal field study of the maize rhizosphere microbiome, we identify heritable taxa. These taxa display variance in their relative abundances that can be partially explained by genetic differences between the maize lines, above and beyond the strong influences of field, plant age, and weather on the diversity of the rhizosphere microbiome. If these heritable taxa are associated with beneficial traits, they may serve as phenotypes in future breeding endeavors.

Multiple factors modulate microbial community assembly in the vertebrate gut, though studies disagree as to their relative contribution. One cause may be a reliance on captive animals, which can have very different gut microbiomes compared to their wild counterparts. To resolve this disagreement, we analyze a new, large, and highly diverse animal distal gut 16 S rRNA microbiome dataset, which comprises 80% wild animals and includes members of Mammalia, Aves, Reptilia, Amphibia, and Actinopterygii. We decouple the effects of host evolutionary history and diet on gut microbiome diversity and show that each factor modulates different aspects of diversity. Moreover, we resolve particular microbial taxa associated with host phylogeny or diet and show that Mammalia have a stronger signal of cophylogeny. Finally, we find that environmental filtering and microbe-microbe interactions differ among host clades. These findings provide a robust assessment of the processes driving microbial community assembly in the vertebrate intestine.

Disturbances act as powerful structuring forces on ecosystems. To ask whether environmental microbial communities have capacity to recover after a large disturbance event, we conducted a whole-ecosystem manipulation, during which we imposed an intense disturbance on freshwater microbial communities by artificially mixing a temperate lake during peak summer thermal stratification. We employed environmental sensors and water chemistry analyses to evaluate the physical and chemical responses of the lake, and bar-coded 16S ribosomal RNA gene pyrosequencing and automated ribosomal intergenic spacer analysis (ARISA) to assess the bacterial community responses. The artificial mixing increased mean lake temperature from 14 to 20 °C for seven weeks after mixing ended, and exposed the microorganisms to very different environmental conditions, including increased hypolimnion oxygen and increased epilimnion carbon dioxide concentrations. Though overall ecosystem conditions remained altered (with hypolimnion temperatures elevated from 6 to 20 °C), bacterial communities returned to their pre-manipulation state as some environmental conditions, such as oxygen concentration, recovered. Recovery to pre-disturbance community composition and diversity was observed within 7 (epilimnion) and 11 (hypolimnion) days after mixing. Our results suggest that some microbial communities have capacity to recover after a major disturbance.

Highlights d The gut virome is highly unique to each individual and dominated by bacteriophages d Gut microbiome diversity, within and between subjects, is mirrored in their viromes d These patterns of diversity are driven by bacteriophages, not by eukaryotic viruses d Microbiome abundances and diversity are predictive of virome richness and diversity

25Multiple factors modulate microbial community assembly in the gut, but the magnitude of 26 each can vary substantially across studies. This may be in part due to a heavy reliance on 27 captive animals, which can have very different gut microbiomes versus their wild counterparts. 28In order to better resolve the influence of evolution and diet on gut microbiome diversity, we 29 generated a large and highly diverse animal distal gut 16S rRNA microbiome dataset, which 30 comprises 80 % wild animals and includes members of Mammalia, Aves, Reptilia, Amphibia, 31 and Actinopterygii. We decoupled the effects of host evolutionary history and diet on gut 32 microbiome diversity and show that each factor explains different aspects of diversity. Moreover, 33we resolved particular microbial taxa associated with host phylogeny or diet, and we show that 34Mammalia have a stronger signal of cophylogeny versus non-mammalian hosts. Additionally, 35 our results from ecophylogenetics and co-occurrence analyses suggest that environmental 36 filtering and microbe-microbe interactions differ among host clades. These findings provide a 37 robust assessment of the processes driving microbial community assembly in the vertebrate 38 intestine. 39 40

Soil microorganisms determine the fate of soil organic matter (SOM), and their activities compose a major component of the global carbon (C) cycle. We employed a multisubstrate, DNA-stable isotope probing experiment to track bacterial assimilation of C derived from distinct sources that varied in bioavailability. This approach allowed us to measure microbial contributions to SOM processing by measuring the C assimilation dynamics of diverse microorganisms as they interacted within soil. We identified and tracked 1,286 bacterial taxa that assimilated 13C in an agricultural soil over a period of 48 d. Overall 13C-assimilation dynamics of bacterial taxa, defined by the source and timing of the 13C they assimilated, exhibited low phylogenetic conservation. We identified bacterial guilds composed of taxa that had similar 13C assimilation dynamics. We show that C-source bioavailability explained significant variation in both C mineralization dynamics and guild structure, and that the growth dynamics of bacterial guilds differed significantly in response to C addition. We also demonstrate that the guild structure explains significant variation in the biogeographical distribution of bacteria at continental and global scales. These results suggest that an understanding of in situ growth dynamics is essential for understanding microbial contributions to soil C cycling. We interpret these findings in the context of bacterial life history strategies and their relationship to terrestrial C cycling.

Highlights d High AMY1 copy number (CN) is associated with higher levels of Porphyromonas in saliva d High AMY1-CN stool has more resistant starch degraders; drives more adiposity in GF mice d Stool short-chain fatty acid levels are predictive of salivary amylase activity d Upon diet standardization, gut microbiomes converged without eliminating differences

DNA Stable isotope probing (DNA-SIP) is a powerful method that links identity to function within microbial communities. The combination of DNA-SIP with multiplexed high throughput DNA sequencing enables simultaneous mapping of in situ assimilation dynamics for thousands of microbial taxonomic units. Hence, high throughput sequencing enabled SIP has enormous potential to reveal patterns of carbon and nitrogen exchange within microbial food webs. There are several different methods for analyzing DNA-SIP data and despite the power of SIP experiments, it remains difficult to comprehensively evaluate method accuracy across a wide range of experimental parameters. We have developed a toolset (SIPSim) that simulates DNA-SIP data, and we use this toolset to systematically evaluate different methods for analyzing DNA-SIP data. Specifically, we employ SIPSim to evaluate the effects that key experimental parameters (e.g., level of isotopic enrichment, number of labeled taxa, relative abundance of labeled taxa, community richness, community evenness, and beta-diversity) have on the specificity, sensitivity, and balanced accuracy (defined as the product of specificity and sensitivity) of DNA-SIP analyses. Furthermore, SIPSim can predict analytical accuracy and power as a function of experimental design and community characteristics, and thus should be of great use in the design and interpretation of DNA-SIP experiments.