Microbes are engines of ocean biogeochemical processes. Viruses influence and shape microbial communities via lysis, horizontal gene transfer, and metabolic reprogramming. Viral lysis facilitates the export of carbon from the surface into the deep ocean via aggregates of sinking particles. In fact, they outperform prokaryotes and eukaryotes as the strong predictor for carbon fluxes in the oligotrophic ocean. Viruses also impact the gene flow of their hosts, and the genes transferred from virus-host interactions can be fixed in viral genomes. Viruses are known to carry and express host-derived auxiliary metabolic genes (AMGs) that directly reprogram metabolisms within virus-infected cells, termed virocells. However, viral communities are poorly characterized in the oligotrophic ocean, and their AMG-driven metabolic reprogramming lacks systematic descriptions from the global oceans. The Sargasso Sea is highly stratified and nutrient-depleted each year in the summer months. This seasonal pattern makes the Sargasso Sea one of the ideal model ecosystems to study oligotrophic oceans. In the Sargasso Sea, abundance of viral-like particles has seasonal and depth-associated structuring patterns. Here, to better survey the Sargasso Sea viruses, we apply sequencing approaches to characterize viral communities via metagenomics and uncover their biogeographical and ecological structures locally and globally in the ocean. As described in Chapter 2, comparison with global viral metagenomics revealed that Sargasso Sea viruses were similar across warm oligotrophic oceanic regions but not represented globally. They form discrete populations in the viral and cellular fractions at the viral maximum (80m) and mesopelagic (200m) depths. Inclusion of long-read data captured 1,257 viral genomes in addition to the 1,044 viral genomes derived from short-read assemblies, resulting in the identification of ecologically important and microdiverse viral genomes. Having established lo (open full item for complete abstract)

Lake Erie is one of the five Laurentian Great Lakes, that includes three basins. The central basin is the largest, with a mean volume of 305 km2, covering an area of 16,138 km2. The ice used for this research was collected from the central basin in the winter of 2010. DNA and RNA were extracted from this ice. cDNA was synthesized from the extracted RNA, followed by the ligation of EcoRI (NotI) adapters onto the ends of the nucleic acids. These were subjected to fractionation, and the resulting nucleic acids were amplified by PCR with EcoRI (NotI) primers. The resulting amplified nucleic acids were subject to PCR amplification using 454 primers, and then were sequenced. The sequences were analyzed using BLAST, and taxonomic affiliations were determined. Information about the taxonomic affiliations, important metabolic capabilities, habitat, and special functions were compiled. With a watershed of 78,000 km2, Lake Erie is used for agricultural, forest, recreational, transportation, and industrial purposes. Among the five great lakes, it has the largest input from human activities, has a long history of eutrophication, and serves as a water source for millions of people. These anthropogenic activities have significant influences on the biological community. Multiple studies have found diverse microbial communities in Lake Erie water and sediments, including large numbers of species from the Verrucomicrobia, Proteobacteria, Bacteroidetes, and Cyanobacteria, as well as a diverse set of eukaryotic taxa. Sequences obtained from the metagenomic, and transcriptomic analyses match diverse organisms from thirty-two bacterial, two archaeal, and eight eukaryotic phyla. Some of the organisms found were capable of nitrogen, carbon, iron, sulfur, and hydrocarbon metabolism. Sequences from pathogenic and toxin-producing organisms were found. Organisms associated with several human activities, including pollution, agriculture, cultivation, manufacturing, shipping, and other activ (open full item for complete abstract)

The oral cavity is an open ecosystem with niche-specific microbial colonization. Within a few hours after birth, bacteria colonize the oral cavity and form complex communities called biofilms. These biofilms constantly interact with the host immune system and play an important role in the maintenance of health. Dysbiotic bacterial communities are established as the underlying etiology of periodontitis, a disease that destroys structures tooth-supporting structures and results in tooth loss. Several factors are known to contribute to an individual's susceptibility to periodontitis, notably, smoking and diabetes, however, the mechanisms by which they increase the risk for this bacterially induced inflammatory disease have not been well established. The purpose of this investigation was to examine the relative contributions of smoking and diabetes to shaping the subgingival microbiome. Cross-sectional and longitudinal cohort study designs using were combined with comprehensive systems biology approach to characterize the composition, functional characteristics, gene-expression patterns, and structure of the oral microbial ecosystem in response to these perturbations both in periodontal health and disease. In vitro models were used to validate the clinical findings and to explore a biological basis for the shifts. Smoking, diabetes, and e-cigarettes selectively enriched for disease-associated species and specific virulence functions in this ecosystem even in states of clinical health. Each of these perturbations exerted a unique effect on the microbiome, in terms of species composition, biofilm architecture and functional potential, thus enabling us to identify and validate microbial biomarkers unique to each perturbation. Finally, we investigated whether the associations between bacterial virulence and smoking was causal or casual by examining the responses of the subgingival microbiome to smoking cessation. Quitters demonstrated a significant shift in microbial compos (open full item for complete abstract)