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      Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales

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      PeerJ
      PeerJ Inc.
      Marker genes, mcrA, Data mining, Methanogens, Methanomassiliicoccales

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          Abstract

          Over the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of the Methanomassiliicoccales and reconstruct and analyze a draft genome belonging to the ‘Lake Pavin cluster’, an uncultivated environmental clade of the Methanomassiliicoccales. Analysis of the ‘Lake Pavin cluster’ draft genome suggests that this organism has a more restricted capacity for hydrogenotrophic methylotrophic methanogenesis than previously studied Methanomassiliicoccales, with only genes for growth on methanol present. However, the presence of the soluble subunits of methyltetrahydromethanopterin:CoM methyltransferase ( mtrAH) provide hypothetical pathways for methanol fermentation, and aceticlastic methanogenesis that await experimental verification. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects.

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          Most cited references45

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          Community structure and metabolism through reconstruction of microbial genomes from the environment.

          Microbial communities are vital in the functioning of all ecosystems; however, most microorganisms are uncultivated, and their roles in natural systems are unclear. Here, using random shotgun sequencing of DNA from a natural acidophilic biofilm, we report reconstruction of near-complete genomes of Leptospirillum group II and Ferroplasma type II, and partial recovery of three other genomes. This was possible because the biofilm was dominated by a small number of species populations and the frequency of genomic rearrangements and gene insertions or deletions was relatively low. Because each sequence read came from a different individual, we could determine that single-nucleotide polymorphisms are the predominant form of heterogeneity at the strain level. The Leptospirillum group II genome had remarkably few nucleotide polymorphisms, despite the existence of low-abundance variants. The Ferroplasma type II genome seems to be a composite from three ancestral strains that have undergone homologous recombination to form a large population of mosaic genomes. Analysis of the gene complement for each organism revealed the pathways for carbon and nitrogen fixation and energy generation, and provided insights into survival strategies in an extreme environment.
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            Methanogenic archaea: ecologically relevant differences in energy conservation.

            Most methanogenic archaea can reduce CO(2) with H(2) to methane, and it is generally assumed that the reactions and mechanisms of energy conservation that are involved are largely the same in all methanogens. However, this does not take into account the fact that methanogens with cytochromes have considerably higher growth yields and threshold concentrations for H(2) than methanogens without cytochromes. These and other differences can be explained by the proposal outlined in this Review that in methanogens with cytochromes, the first and last steps in methanogenesis from CO(2) are coupled chemiosmotically, whereas in methanogens without cytochromes, these steps are energetically coupled by a cytoplasmic enzyme complex that mediates flavin-based electron bifurcation.
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              Reordering contigs of draft genomes using the Mauve Aligner

              Summary: Mauve Contig Mover provides a new method for proposing the relative order of contigs that make up a draft genome based on comparison to a complete or draft reference genome. A novel application of the Mauve aligner and viewer provides an automated reordering algorithm coupled with a powerful drill-down display allowing detailed exploration of results. Availability: The software is available for download at http://gel.ahabs.wisc.edu/mauve. Contact: rissman@wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online and http://gel.ahabs.wisc.edu
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                17 September 2018
                2018
                : 6
                : e5614
                Affiliations
                [-1] Division of Geological and Planetary Sciences, California Institute of Technology , Pasadena, CA, United States of America
                Article
                5614
                10.7717/peerj.5614
                6147122
                30245936
                f1fa8603-699d-4bae-9661-9141540b634b
                ©2018 Speth and Orphan

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 8 June 2018
                : 21 August 2018
                Funding
                Funded by: US Department of Energy, Office of Science, Office of Biological and Environmental Research
                Award ID: DE-SC0016469
                Funded by: NWO Rubicon
                Award ID: 019.153LW.039
                This manuscript is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research under award number DE-SC0016469 to Victoria J. Orphan. In addition, Daan R. Speth was supported by NWO Rubicon 019.153LW.039. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Microbiology

                marker genes,mcra,data mining,methanogens,methanomassiliicoccales

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