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Groundwater Isolation Governs Chemistry and Microbial Community Structure along Hydrologic Flowpaths

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      Abstract

      This study deals with the effects of hydrodynamic functioning of hard-rock aquifers on microbial communities. In hard-rock aquifers, the heterogeneous hydrologic circulation strongly constrains groundwater residence time, hydrochemistry, and nutrient supply. Here, residence time and a wide range of environmental factors were used to test the influence of groundwater circulation on active microbial community composition, assessed by high throughput sequencing of 16S rRNA. Groundwater of different ages was sampled along hydrogeologic paths or loops, in three contrasting hard-rock aquifers in Brittany (France). Microbial community composition was driven by groundwater residence time and hydrogeologic loop position. In recent groundwater, in the upper section of the aquifers or in their recharge zone, surface water inputs caused high nitrate concentration and the predominance of putative denitrifiers. Although denitrification does not seem to fully decrease nitrate concentrations due to low dissolved organic carbon concentrations, nitrate input has a major effect on microbial communities. The occurrence of taxa possibly associated with the application of organic fertilizers was also noticed. In ancient isolated groundwater, an ecosystem based on Fe(II)/Fe(III) and S/SO 4 redox cycling was observed down to several 100 of meters below the surface. In this depth section, microbial communities were dominated by iron oxidizing bacteria belonging to Gallionellaceae. The latter were associated to old groundwater with high Fe concentrations mixed to a small but not null percentage of recent groundwater inducing oxygen concentrations below 2.5 mg/L. These two types of microbial community were observed in the three sites, independently of site geology and aquifer geometry, indicating hydrogeologic circulation exercises a major control on microbial communities.

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      Most cited references 72

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      Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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        Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

        mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            Author and article information

            Affiliations
            1OSUR-UMR 6553 ECOBIO, Université de Rennes 1 and Centre National de la Recherche Scientifique Rennes, France
            2OSUR-UMR 6118 Géosciences, Université de Rennes 1 and Centre National de la Recherche Scientifique Rennes, France
            3BRGM, Laboratory Department Orléans, France
            4OSUR-UMS 3343, Université de Rennes 1 and Centre National de la Recherche Scientifique Rennes, France
            Author notes

            Edited by: Partha Basu, Duquesne University, USA

            Reviewed by: John W. Moreau, University of Melbourne, Australia; Mustafa Yucel, Middle East Technical University, Turkey; Jarrod Scott, Bigelow Laboratory for Ocean Sciences, USA

            *Correspondence: Alexis Dufresne, alexis.dufresne@ 123456univ-rennes1.fr

            This article was submitted to Microbiological Chemistry and Geomicrobiology, 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
            22 December 2015
            2015
            : 6
            4686674 10.3389/fmicb.2015.01457
            Copyright © 2015 Ben Maamar, Aquilina, Quaiser, Pauwels, Michon-Coudouel, Vergnaud-Ayraud, Labasque, Roques, Abbott and Dufresne.

            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: 5, Tables: 0, Equations: 0, References: 76, Pages: 13, Words: 0
            Funding
            Funded by: Conseil Régional de Bretagne 10.13039/501100004584
            Funded by: Centre National de la Recherche Scientifique 10.13039/501100004794
            Award ID: EC2CO-AQUADIV & PEPII-AQUASYST
            Funded by: Bureau de Recherches Géologiques et Minières 10.13039/501100006273
            Categories
            Microbiology
            Original Research

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