Genomic analysis of the mesophilic Thermotogae genus Mesotoga reveals phylogeographic structure and genomic determinants of its distinct metabolism.

The genus Mesotoga, the only described mesophilic Thermotogae lineage, is common in mesothermic anaerobic hydrocarbon-rich environments. Besides mesophily, Mesotoga displays lineage-specific phenotypes, such as no or little H2 production and dependence on sulfur-compound reduction, which may influence its ecological role. We used comparative genomics of 18 Mesotoga strains (pairwise 16S rRNA identity >99%) and a transcriptome of M. prima to investigate how life at moderate temperatures affects phylogeography and to interrogate the genomic features of its lineage-specific metabolism. We propose that Mesotoga accomplish H2 oxidation and thiosulfate reduction using a sulfide dehydrogenase and a hydrogenase-complex and that a pyruvate:ferredoxin oxidoreductase acquired from Clostridia is responsible for oxidizing acetate. Phylogenetic analysis revealed three distinct Mesotoga lineages (89.6%-99.9% average nucleotide identity [ANI] within lineages, 79.3%-87.6% ANI between lineages) having different geographic distribution patterns and high levels of intra-lineage recombination but little geneflow between lineages. Including data from metagenomes, phylogeographic patterns suggest that geographical separation historically has been more important for Mesotoga than hyperthermophilic Thermotoga and we hypothesize that distribution of Mesotoga is constrained by their anaerobic lifestyle. Our data also suggest that recent anthropogenic activities and environments (e.g., wastewater treatment, oil exploration) have expanded Mesotoga habitats and dispersal capabilities.

Patterns of Endemism and Habitat Selection in Coalbed Microbial Communities.

Microbially produced methane, a versatile, cleaner-burning alternative energy resource to fossil fuels, is sourced from a variety of natural and engineered ecosystems, including marine sediments, anaerobic digesters, shales, and coalbeds. There is a prevailing interest in developing environmental biotechnologies to enhance methane production. Here, we use small-subunit rRNA gene sequencing and metagenomics to better describe the interplay between coalbed methane (CBM) well conditions and microbial communities in the Alberta Basin. Our results show that CBM microbial community structures display patterns of endemism and habitat selection across the Alberta Basin, consistent with observations from other geographical locations. While some phylum-level taxonomic patterns were observed, relative abundances of specific taxonomic groups were localized to discrete wells, likely shaped by local environmental conditions, such as coal rank and depth-dependent physicochemical conditions. To better resolve functional potential within the CBM milieu, a metagenome from a deep volatile-bituminous coal sample was generated. This sample was dominated by Rhodobacteraceae genotypes, resolving a near-complete population genome bin related to Celeribacter sp. that encoded metabolic pathways for the degradation of a wide range of aromatic compounds and the production of methanogenic substrates via acidogenic fermentation. Genomic comparisons between the Celeribacter sp. population genome and related organisms isolated from different environments reflected habitat-specific selection pressures that included nitrogen availability and the ability to utilize diverse carbon substrates. Taken together, our observations reveal that both endemism and metabolic specialization should be considered in the development of biostimulation strategies for nonproductive wells or for those with declining productivity.

Metagenomic scaffolds enable combinatorial lignin transformation.

Engineering the microbial transformation of lignocellulosic biomass is essential to developing modern biorefining processes that alleviate reliance on petroleum-derived energy and chemicals. Many current bioprocess streams depend on the genetic tractability of Escherichia coli with a primary emphasis on engineering cellulose/hemicellulose catabolism, small molecule production, and resistance to product inhibition. Conversely, bioprocess streams for lignin transformation remain embryonic, with relatively few environmental strains or enzymes implicated. Here we develop a biosensor responsive to monoaromatic lignin transformation products compatible with functional screening in E. coli. We use this biosensor to retrieve metagenomic scaffolds sourced from coal bed bacterial communities conferring an array of lignin transformation phenotypes that synergize in combination. Transposon mutagenesis and comparative sequence analysis of active clones identified genes encoding six functional classes mediating lignin transformation phenotypes that appear to be rearrayed in nature via horizontal gene transfer. Lignin transformation activity was then demonstrated for one of the predicted gene products encoding a multicopper oxidase to validate the screen. These results illuminate cellular and community-wide networks acting on aromatic polymers and expand the toolkit for engineering recombinant lignin transformation based on ecological design principles.

Metagenomics of hydrocarbon resource environments indicates aerobic taxa and genes to be unexpectedly common.

Oil in subsurface reservoirs is biodegraded by resident microbial communities. Water-mediated, anaerobic conversion of hydrocarbons to methane and CO2, catalyzed by syntrophic bacteria and methanogenic archaea, is thought to be one of the dominant processes. We compared 160 microbial community compositions in ten hydrocarbon resource environments (HREs) and sequenced twelve metagenomes to characterize their metabolic potential. Although anaerobic communities were common, cores from oil sands and coal beds had unexpectedly high proportions of aerobic hydrocarbon-degrading bacteria. Likewise, most metagenomes had high proportions of genes for enzymes involved in aerobic hydrocarbon metabolism. Hence, although HREs may have been strictly anaerobic and typically methanogenic for much of their history, this may not hold today for coal beds and for the Alberta oil sands, one of the largest remaining oil reservoirs in the world. This finding may influence strategies to recover energy or chemicals from these HREs by in situ microbial processes.

METAGENassist: a comprehensive web server for comparative metagenomics.

With recent improvements in DNA sequencing and sample extraction techniques, the quantity and quality of metagenomic data are now growing exponentially. This abundance of richly annotated metagenomic data and bacterial census information has spawned a new branch of microbiology called comparative metagenomics. Comparative metagenomics involves the comparison of bacterial populations between different environmental samples, different culture conditions or different microbial hosts. However, in order to do comparative metagenomics, one typically requires a sophisticated knowledge of multivariate statistics and/or advanced software programming skills. To make comparative metagenomics more accessible to microbiologists, we have developed a freely accessible, easy-to-use web server for comparative metagenomic analysis called METAGENassist. Users can upload their bacterial census data from a wide variety of common formats, using either amplified 16S rRNA data or shotgun metagenomic data. Metadata concerning environmental, culture, or host conditions can also be uploaded. During the data upload process, METAGENassist also performs an automated taxonomic-to-phenotypic mapping. Phenotypic information covering nearly 20 functional categories such as GC content, genome size, oxygen requirements, energy sources and preferred temperature range is automatically generated from the taxonomic input data. Using this phenotypically enriched data, users can then perform a variety of multivariate and univariate data analyses including fold change analysis, t-tests, PCA, PLS-DA, clustering and classification. To facilitate data processing, users are guided through a step-by-step analysis workflow using a variety of menus, information hyperlinks and check boxes. METAGENassist also generates colorful, publication quality tables and graphs that can be downloaded and used directly in the preparation of scientific papers. METAGENassist is available at http://www.metagenassist.ca.