Grapes harbor complex microbial communities. It is well known that yeasts, typically Saccharomyces cerevisiae, and bacteria, commonly the lactic acid fermenting Oenococcus oeni, work sequentially during primary and secondary wine fermentation. In addition to these main players, several microbes, often with undesirable effects on wine quality, have been found in grapes and during wine fermentation. However, still little is known about the dynamics of the microbial community during the fermentation process. In previous studies culture dependent methods were applied to detect and identify microbial organisms associated with grapes and grape products, which resulted in a picture that neglected the non-culturable fraction of the microbes. To obtain a more complete picture of how microbial communities change during grape fermentation and how different fermentation techniques might affect the microbial community composition, we employed next-generation sequencing (NGS)—a culture-independent method. A better understanding of the microbial dynamics and their effect on the final product is of great importance to help winemakers produce wine styles of consistent and high quality. In this study, we focused on the bacterial community dynamics during wine vinification by amplifying and sequencing the hypervariable V1–V3 region of the 16S rRNA gene—a phylogenetic marker gene that is ubiquitous within prokaryotes. Bacterial communities and their temporal succession was observed for communities associated with organically and conventionally produced wines. In addition, we analyzed the chemical characteristics of the grape musts during the organic and conventional fermentation process. These analyses revealed distinct bacterial population with specific temporal changes as well as different chemical profiles for the organically and conventionally produced wines. In summary these results suggest a possible correlation between the temporal succession of the bacterial population and the chemical wine profiles.

Crude oils can be major contaminants of the marine ecosystem and microorganisms play a significant role in the degradation of its main constituents. To increase our understanding of the microbial hydrocarbon degradation process in the marine ecosystem, we collected crude oil from an active seep area located in the Santa Barbara Channel (SBC) and generated a total of about 52 Gb of raw metagenomic sequence data. The assembled data comprised ~500 Mb, representing ~1.1 million genes derived primarily from chemolithoautotrophic bacteria. Members of Oceanospirillales, a bacterial order belonging to the Deltaproteobacteria, recruited less than 2% of the assembled genes within the SBC metagenome. In contrast, the microbial community associated with the oil plume that developed in the aftermath of the Deepwater Horizon (DWH) blowout in 2010, was dominated by Oceanospirillales, which comprised more than 60% of the metagenomic data generated from the DWH oil plume. This suggests that Oceanospirillales might play a less significant role in the microbially mediated hydrocarbon conversion within the SBC seep oil compared to the DWH plume oil. We hypothesize that this difference results from the SBC oil seep being mostly anaerobic, while the DWH oil plume is aerobic. Within the Archaea, the phylum Euryarchaeota, recruited more than 95% of the assembled archaeal sequences from the SBC oil seep metagenome, with more than 50% of the sequences assigned to members of the orders Methanomicrobiales and Methanosarcinales. These orders contain organisms capable of anaerobic methanogenesis and methane oxidation (AOM) and we hypothesize that these orders – and their metabolic capabilities – may be fundamental to the ecology of the SBC oil seep.

Although recent nucleotide sequencing technologies have significantly enhanced our understanding of microbial genomes, the function of ∼35% of genes identified in a genome currently remains unknown. To improve the understanding of microbial genomes and consequently of microbial processes it will be crucial to assign a function to this "genomic dark matter." Due to the urgent need for additional carbohydrate-active enzymes for improved production of transportation fuels from lignocellulosic biomass, we screened the genomes of more than 5,500 microorganisms for hypothetical proteins that are located in the proximity of already known cellulases. We identified, synthesized and expressed a total of 17 putative cellulase genes with insufficient sequence similarity to currently known cellulases to be identified as such using traditional sequence annotation techniques that rely on significant sequence similarity. The recombinant proteins of the newly identified putative cellulases were subjected to enzymatic activity assays to verify their hydrolytic activity towards cellulose and lignocellulosic biomass. Eleven (65%) of the tested enzymes had significant activity towards at least one of the substrates. This high success rate highlights that a gene context-based approach can be used to assign function to genes that are otherwise categorized as "genomic dark matter" and to identify biomass-degrading enzymes that have little sequence similarity to already known cellulases. The ability to assign function to genes that have no related sequence representatives with functional annotation will be important to enhance our understanding of microbial processes and to identify microbial proteins for a wide range of applications.

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