Genome-Centric Analysis of Microbial Populations Enriched by Hydraulic Fracture Fluid Additives in a Coal Bed Methane Production Well

Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences. The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis. UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. Supplementary data are available at Bioinformatics online.

A great number of the bacteria and archaea on Earth are found in subsurface environments in a physiological state that is poorly represented or explained by laboratory cultures. Microbial cells in these very stable and oligotrophic settings catabolize 10⁴- to 10⁶-fold more slowly than model organisms in nutrient-rich cultures, turn over biomass on timescales of centuries to millennia rather than hours to days, and subsist with energy fluxes that are 1,000-fold lower than the typical culture-based estimates of maintenance requirements. To reconcile this disparate state of being with our knowledge of microbial physiology will require a revised understanding of microbial energy requirements, including identifying the factors that comprise true basal maintenance and the adaptations that might serve to minimize these factors.

Methanogenic and methanotrophic archaea play important roles in the global flux of methane. Culture-independent approaches are providing deeper insight into the diversity and evolution of methane-metabolizing microorganisms, but, until now, no compelling evidence has existed for methane metabolism in archaea outside the phylum Euryarchaeota. We performed metagenomic sequencing of a deep aquifer, recovering two near-complete genomes belonging to the archaeal phylum Bathyarchaeota (formerly known as the Miscellaneous Crenarchaeotal Group). These genomes contain divergent homologs of the genes necessary for methane metabolism, including those that encode the methyl-coenzyme M reductase (MCR) complex. Additional non-euryarchaeotal MCR-encoding genes identified in a range of environments suggest that unrecognized archaeal lineages may also contribute to global methane cycling. These findings indicate that methane metabolism arose before the last common ancestor of the Euryarchaeota and Bathyarchaeota.