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

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      Abstract

      Coal bed methane (CBM) is generated primarily through the microbial degradation of coal. Despite a limited understanding of the microorganisms responsible for this process, there is significant interest in developing methods to stimulate additional methane production from CBM wells. Physical techniques including hydraulic fracture stimulation are commonly applied to CBM wells, however the effects of specific additives contained in hydraulic fracture fluids on native CBM microbial communities are poorly understood. Here, metagenomic sequencing was applied to the formation waters of a hydraulically fractured and several non-fractured CBM production wells to determine the effect of this stimulation technique on the in-situ microbial community. The hydraulically fractured well was dominated by two microbial populations belonging to the class Phycisphaerae (within phylum Planctomycetes) and candidate phylum Aminicenantes. Populations from these phyla were absent or present at extremely low abundance in non-fractured CBM wells. Detailed metabolic reconstruction of near-complete genomes from these populations showed that their high relative abundance in the hydraulically fractured CBM well could be explained by the introduction of additional carbon sources, electron acceptors, and biocides contained in the hydraulic fracture fluid.

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      Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

      The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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        RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

        RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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          Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.

          A 16S rRNA gene database (http://greengenes.lbl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.
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            Author and article information

            Affiliations
            1Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland Brisbane, QLD, Australia
            2School of Earth Sciences, The University of Queensland Brisbane, QLD, Australia
            Author notes

            Edited by: Martin Koenneke, University of Bremen, Germany

            Reviewed by: Harold J. Schreier, University of Maryland Baltimore County, USA; Martin Krüger, Federal Institute for Geosciences and Natural Resources, Germany

            *Correspondence: Steven J. Robbins steven.robbins@ 123456uqconnect.edu.au ;

            This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

            Contributors
            Journal
            Front Microbiol
            Front Microbiol
            Front. Microbiol.
            Frontiers in Microbiology
            Frontiers Media S.A.
            1664-302X
            08 June 2016
            2016
            : 7
            27375557 4897734 10.3389/fmicb.2016.00731
            Copyright © 2016 Robbins, Evans, Parks, Golding and Tyson.

            This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

            Counts
            Figures: 7, Tables: 5, Equations: 0, References: 51, Pages: 15, Words: 8954
            Funding
            Funded by: Australian Research Council 10.13039/501100000923
            Award ID: LP100200730
            Categories
            Microbiology
            Original Research

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