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Flux of dimethylsulfide (DMS) from ocean surface waters is the predominant natural source of sulfur to the atmosphere and influences climate by aerosol formation. Marine bacterioplankton regulate sulfur flux by converting the precursor dimethylsulfoniopropionate (DMSP) either to DMS or to sulfur compounds that are not climatically active. Through the discovery of a glycine cleavage T-family protein with DMSP methyltransferase activity, marine bacterioplankton in the Roseobacter and SAR11 taxa were identified as primary mediators of DMSP demethylation to methylmercaptopropionate. One-third of surface ocean bacteria harbor a DMSP demethylase homolog and thereby route a substantial fraction of global marine primary production away from DMS formation and into the marine microbial food web.

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BackgroundComparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes.ResultsWe have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP’s capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution.ConclusionsITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.

Methanogenic archaea are genotypically and phenotypically diverse organisms that are integral to carbon cycling in anaerobic environments. Owing to their genetic tractability and ability to be readily cultivated, Methanosarcina spp. have become a powerful model system for understanding methanogen biology at the cellular systems level. However, relatively little is known of how genotypic and phenotypic variation is partitioned in Methanosarcina populations inhabiting natural environments and the possible ecological and evolutionary implications of such variation. Here, we have identified how genomic and phenotypic diversity is partitioned within and between Methanosarcina mazei populations obtained from two different sediment environments in the Columbia River Estuary (Oregon, USA). Population genomic analysis of 56 M. mazei isolates averaging o1% nucleotide divergence revealed two distinct clades, which we refer to as 'mazei-T' and 'mazei-WC'. Genomic analyses showed that these clades differed in gene content and fixation of allelic variants, which point to potential differences in primary metabolism and also interactions with foreign genetic elements. This hypothesis of niche partitioning was supported by laboratory growth experiments that revealed significant differences in trimethylamine utilization. These findings improve our understanding of the ecologically relevant scales of genomic variation in natural systems and demonstrate interactions between genetic and ecological diversity in these easily cultivable and genetically tractable model methanogens.

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The technological leap of DNA sequencing generated a tension between modern metagenomics and historical microbiology. We are forcibly harmonizing the output of a modern tool with centuries of experimental knowledge derived from culture-based microbiology.