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      H 2-saturation of high affinity H 2-oxidizing bacteria alters the ecological niche of soil microorganisms unevenly among taxonomic groups

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          Abstract

          Soil microbial communities are continuously exposed to H 2 diffusing into the soil from the atmosphere. N 2-fixing nodules represent a peculiar microniche in soil where H 2 can reach concentrations up to 20,000 fold higher than in the global atmosphere (0.530 ppmv). In this study, we investigated the impact of H 2 exposure on soil bacterial community structure using dynamic microcosm chambers simulating soil H 2 exposure from the atmosphere and N 2-fixing nodules. Biphasic kinetic parameters governing H 2 oxidation activity in soil changed drastically upon elevated H 2 exposure, corresponding to a slight but significant decay of high affinity H 2-oxidizing bacteria population, accompanied by an enrichment or activation of microorganisms displaying low-affinity for H 2. In contrast to previous studies that unveiled limited response by a few species, the relative abundance of 958 bacterial ribotypes distributed among various taxonomic groups, rather than a few distinct taxa, was influenced by H 2 exposure. Furthermore, correlation networks showed important alterations of ribotype covariation in response to H 2 exposure, suggesting that H 2 affects microbe-microbe interactions in soil. Taken together, our results demonstrate that H 2-rich environments exert a direct influence on soil H 2-oxidizing bacteria in addition to indirect effects on other members of the bacterial communities.

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          FLASH: fast length adjustment of short reads to improve genome assemblies.

          Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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            R: A Language and environmental for statistical computing

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              Primer and platform effects on 16S rRNA tag sequencing

              Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                10 March 2016
                2016
                : 4
                : e1782
                Affiliations
                [1 ]INRS-Institut Armand-Frappier , Laval, Quebec, Canada
                [2 ]Biomonitoring, National Research Council Canada , Montreal, Quebec, Canada
                [3 ]DOE Joint Genome Institute , Walnut Creek, California, United States of America
                Article
                1782
                10.7717/peerj.1782
                4793312
                26989620
                32255c36-a344-4e00-8d38-189e7f3e42d0
                ©2016 Piché-Choquette et al.

                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
                : 13 January 2016
                : 17 February 2016
                Funding
                Funded by: Natural Sciences and Engineering Research Council of Canada Discovery
                Funded by: Community Sequencing Program of the Joint Genome Institute (US Department of Energy)
                Funded by: US Department of Energy Joint Genome Institute
                Funded by: DOE Office of Science User Facility
                Funded by: Office of Science of the US Department of Energy
                Award ID: DE-AC02-05CH11231
                This work has been supported by a Natural Sciences and Engineering Research Council of Canada Discovery grant to PC and by the Community Sequencing Program of the Joint Genome Institute (US Department of Energy) to PC, JT and SGT. The work conducted by the US Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Microbiology
                Soil Science

                soil,microbial ecology,correlation network
                soil, microbial ecology, correlation network

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