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      Functional Stability and Community Dynamics during Spring and Autumn Seasons Over 3 Years in Camargue Microbial Mats

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          Microbial mats are complex biofilms in which the major element cycles are represented at a millimeter scale. In this study, community variability within microbial mats from the Camargue wetlands (Rhone Delta, southern France) were analyzed over 3 years during two different seasons (spring and autumn) and at different layers of the mat (0–2, 2–4, and 4–6 mm). To assess bacterial diversity in the mats, amplicons of the V1–V2 region of the 16S rRNA gene were sequenced. The community’s functionality was characterized using two approaches: (i) inferred functionality through 16S rRNA amplicons genes according to PICRUSt, and (ii) a shotgun metagenomic analysis. Based on the reads distinguished, microbial communities were dominated by Bacteria (∼94%), followed by Archaea (∼4%) and Eukarya (∼1%). The major phyla of Bacteria were Proteobacteria, Bacteroidetes, Spirochaetes, Actinobacteria, Firmicutes, and Cyanobacteria, which together represented 70–80% of the total population detected. The phylum Euryarchaeota represented ∼80% of the Archaea identified. These results showed that the total bacterial diversity from the Camargue microbial mats was not significantly affected by seasonal changes at the studied location; however, there were differences among layers, especially between the 0–2 mm layer and the other two layers. PICRUSt and shotgun metagenomic analyses revealed similar general biological processes in all samples analyzed, by season and depth, indicating that different layers were functionally stable, although some taxa changed during the spring and autumn seasons over the 3 years. Several gene families and pathways were tracked with the oxic-anoxic gradient of the layers. Genes directly involved in photosynthesis (KO, KEGG Orthology) were significantly more abundant in the top layer (0–2 mm) than in the lower layers (2–4 and 4–6 mm). In the anoxic layers, the presence of ferredoxins likely reflected the variation of redox reactions required for anaerobic respiration. Sulfatase genes had the highest relative abundance below 2 mm. Finally, chemotaxis signature genes peaked sharply at the oxic/photic and transitional oxic-anoxic boundary. This functional differentiation reflected the taxonomic diversity of the different layers of the mat.

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          Most cited references 71

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          QIIME allows analysis of high-throughput community sequencing data.

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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, 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.

                Author and article information

                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                22 December 2017
                : 8
                1Department of Biology, Environment and Health, Section Microbiology, Faculty of Pharmacy and Food Sciences, University of Barcelona , Barcelona, Spain
                2Laboratory of Molecular Microbiology and Antimicrobials, Department of Pathology and Experimental Therapeutics, Faculty of Medicine, University of Barcelona – Institut d’Investigació Biomédica de Bellvitge , Barcelona, Spain
                3Academia Europaea-Barcelona Knowledge Hub , Barcelona, Spain
                Author notes

                Edited by: Jesus L. Romalde, Universidade de Santiago de Compostela, Spain

                Reviewed by: Asim K. Bej, University of Alabama at Birmingham, United States; Brendan Paul Burns, University of New South Wales, Australia

                *Correspondence: Mercedes Berlanga, mberlanga@

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Copyright © 2017 Berlanga, Palau and Guerrero.

                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.

                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 71, Pages: 13, Words: 0
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