3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The effect of acute moderate-intensity exercise on the serum and fecal metabolomes and the gut microbiota of cross-country endurance athletes

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Physical exercise can produce changes in the microbiota, conferring health benefits through mechanisms that are not fully understood. We sought to determine the changes driven by exercise on the gut microbiota and on the serum and fecal metabolome using 16S rRNA gene analysis and untargeted metabolomics. A total of 85 serum and 12 fecal metabolites and six bacterial taxa ( Romboutsia, Escherichia coli TOP498, Ruminococcaceae UCG-005, Blautia, Ruminiclostridium 9 and Clostridium phoceensis) were modified following a controlled acute exercise session. Among the bacterial taxa, Ruminiclostridium 9 was the most influenced by fecal and serum metabolites, as revealed by linear multivariate regression analysis. Exercise significantly increased the fecal ammonia content. Functional analysis revealed that alanine, aspartate and glutamate metabolism and the arginine and aminoacyl-tRNA biosynthesis pathways were the most relevant modified pathways in serum, whereas the phenylalanine, tyrosine and tryptophan biosynthesis pathway was the most relevant pathway modified in feces. Correlation analysis between fecal and serum metabolites suggested an exchange of metabolites between both compartments. Thus, the performance of a single exercise bout in cross-country non-professional athletes produces significant changes in the microbiota and in the serum and fecal metabolome, which may have health implications.

          Related collections

          Most cited references53

          • Record: found
          • Abstract: found
          • Article: not found

          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                francois.fenaille@cea.fr
                mar.larrosa@universidadeuropea.es
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 February 2021
                11 February 2021
                2021
                : 11
                : 3558
                Affiliations
                [1 ]GRID grid.119375.8, ISNI 0000000121738416, MAS Microbiota Research Group, Faculty of Biomedical Sciences, , Universidad Europea de Madrid, ; 28670 Villaviciosa de Odón, Madrid Spain
                [2 ]GRID grid.11108.39, ISNI 0000 0001 2324 8920, Departamento de Educación, Métodos de Investigación y Evaluación, , Universidad Pontificia de Comillas, ICAI-ICADE, ; 28015 Cantoblanco, Madrid Spain
                [3 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, ; 91191 Gif sur Yvette, France
                Article
                82947
                10.1038/s41598-021-82947-1
                7878499
                33574413
                69a8f2d9-7dd8-4ada-a8b3-af2858610916
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 July 2020
                : 6 November 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004410, European Molecular Biology Organization;
                Award ID: EMBO, STF 8131
                Award Recipient :
                Funded by: Ministry of Education, Culture and Sports
                Award ID: FPU grant 2016/01110
                Award Recipient :
                Funded by: Ministry of Economy and Competitiveness
                Award ID: AGL2016-77288-R
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                microbiology,physiology
                Uncategorized
                microbiology, physiology

                Comments

                Comment on this article