[This corrects the article DOI: 10.1128/mSphere.00169-17.].

Bacteria play a key role in freshwater biogeochemical cycling, but long-term trends in freshwater bacterial community composition and dynamics are not yet well characterized. We used a multiyear time series of 16S rRNA gene amplicon sequencing data from eight bog lakes to census the freshwater bacterial community and observe annual and seasonal trends in abundance. The sites that we studied encompassed a range of water column mixing frequencies, which we hypothesized would be associated with trends in alpha and beta diversity. Each lake and layer contained a distinct bacterial community, with distinct levels of richness and indicator taxa that likely reflected the environmental conditions of each lake type sampled, including Actinobacteria in polymictic lakes (i.e., lakes with multiple mixing events per year), Methylophilales in dimictic lakes (lakes with two mixing events per year, usually in spring and fall), and "Candidatus Omnitrophica" in meromictic lakes (lakes with no recorded mixing events). The community present during each year at each site was also surprisingly unique. Despite unexpected interannual variability in community composition, we detected a core community of taxa found in all lakes and layers, including Actinobacteria tribe acI-B2 and Betaprotobacteria lineage PnecC. Although trends in abundance did not repeat annually, each freshwater lineage within the communities had a consistent lifestyle, defined by persistence, abundance, and variability. The results of our analysis emphasize the importance of long-term multisite observations, as analyzing only a single year of data or one lake would not have allowed us to describe the dynamics and composition of these freshwater bacterial communities to the extent presented here. IMPORTANCE Lakes are excellent systems for investigating bacterial community dynamics because they have clear boundaries and strong environmental gradients. The results of our research demonstrate that bacterial community composition varies by year, a finding which likely applies to other ecosystems and has implications for study design and interpretation. Understanding the drivers and controls of bacterial communities on long time scales would improve both our knowledge of fundamental properties of bacterial communities and our ability to predict community states. In this specific ecosystem, bog lakes play a disproportionately large role in global carbon cycling, and the information presented here may ultimately help refine carbon budgets for these lakes. Finally, all data and code in this study are publicly available. We hope that this will serve as a resource for anyone seeking to answer their own microbial ecology questions using a multiyear time series.

Although microbes mediate much of the biogeochemical cycling in freshwater, the categories of carbon and nutrients currently used in models of freshwater biogeochemical cycling are too broad to be relevant on a microbial scale. One way to improve these models is to incorporate microbial data. Here, we analyze both genes and genomes from three metagenomic time series and propose specific roles for microbial taxa in freshwater biogeochemical cycles. Our metagenomic time series span multiple years and originate from a eutrophic lake (Lake Mendota) and a humic lake (Trout Bog Lake) with contrasting water chemistry. Our analysis highlights the role of polyamines in the nitrogen cycle, the diversity of diazotrophs between lake types, the balance of assimilatory vs. dissimilatory sulfate reduction in freshwater, the various associations between types of phototrophy and carbon fixation, and the density and diversity of glycoside hydrolases in freshwater microbes. We also investigated aspects of central metabolism such as hydrogen metabolism, oxidative phosphorylation, methylotrophy, and sugar degradation. Finally, by analyzing the dynamics over time in nitrogen fixation genes and Cyanobacteria genomes, we show that the potential for nitrogen fixation is linked to specific populations in Lake Mendota. This work represents an important step towards incorporating microbial data into ecosystem models and provides a better understanding of how microbes may participate in freshwater biogeochemical cycling.

Viruses influence the fate of nutrients and human health by killing microorganisms and altering metabolic processes. Organosulfur metabolism and biologically derived hydrogen sulfide play dynamic roles in manifestation of diseases, infrastructure degradation, and essential biological processes. Although microbial organosulfur metabolism is well studied, the role of viruses in organosulfur metabolism is unknown. Here, we report the discovery of 39 gene families involved in organosulfur metabolism encoded by 3,749 viruses from diverse ecosystems, including human microbiomes. The viruses infect organisms from all three domains of life. Six gene families encode for enzymes that degrade organosulfur compounds into sulfide, whereas others manipulate organosulfur compounds and may influence sulfide production. We show that viral metabolic genes encode key enzymatic domains, are translated into protein, and are maintained after recombination, and sulfide provides a fitness advantage to viruses. Our results reveal viruses as drivers of organosulfur metabolism with important implications for human and environmental health.