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      A Prospective Metagenomic and Metabolomic Analysis of the Impact of Exercise and/or Whey Protein Supplementation on the Gut Microbiome of Sedentary Adults

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          Abstract

          The gut microbiota of humans is a critical component of functional development and subsequent health. It is important to understand the lifestyle and dietary factors that affect the gut microbiome and what impact these factors may have. Animal studies suggest that exercise can directly affect the gut microbiota, and elite athletes demonstrate unique beneficial and diverse gut microbiome characteristics. These characteristics are associated with levels of protein consumption and levels of physical activity. The results of this study show that increasing the fitness levels of physically inactive humans leads to modest but detectable changes in gut microbiota characteristics. For the first time, we show that regular whey protein intake leads to significant alterations to the composition of the gut virome.

          ABSTRACT

          Many components of modern living exert influence on the resident intestinal microbiota of humans with resultant impact on host health. For example, exercise-associated changes in the diversity, composition, and functional profiles of microbial populations in the gut have been described in cross-sectional studies of habitual athletes. However, this relationship is also affected by changes in diet, such as changes in dietary and supplementary protein consumption, that coincide with exercise. To determine whether increasing physical activity and/or increased protein intake modulates gut microbial composition and function, we prospectively challenged healthy but sedentary adults with a short-term exercise regime, with and without concurrent daily whey protein consumption. Metagenomics- and metabolomics-based assessments demonstrated modest changes in gut microbial composition and function following increases in physical activity. Significant changes in the diversity of the gut virome were evident in participants receiving daily whey protein supplementation. Results indicate that improved body composition with exercise is not dependent on major changes in the diversity of microbial populations in the gut. The diverse microbial characteristics previously observed in long-term habitual athletes may be a later response to exercise and fitness improvement.

          IMPORTANCE The gut microbiota of humans is a critical component of functional development and subsequent health. It is important to understand the lifestyle and dietary factors that affect the gut microbiome and what impact these factors may have. Animal studies suggest that exercise can directly affect the gut microbiota, and elite athletes demonstrate unique beneficial and diverse gut microbiome characteristics. These characteristics are associated with levels of protein consumption and levels of physical activity. The results of this study show that increasing the fitness levels of physically inactive humans leads to modest but detectable changes in gut microbiota characteristics. For the first time, we show that regular whey protein intake leads to significant alterations to the composition of the gut virome.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Highly sensitive feature detection for high resolution LC/MS

            Background Liquid chromatography coupled to mass spectrometry (LC/MS) is an important analytical technology for e.g. metabolomics experiments. Determining the boundaries, centres and intensities of the two-dimensional signals in the LC/MS raw data is called feature detection. For the subsequent analysis of complex samples such as plant extracts, which may contain hundreds of compounds, corresponding to thousands of features – a reliable feature detection is mandatory. Results We developed a new feature detection algorithm centWave for high-resolution LC/MS data sets, which collects regions of interest (partial mass traces) in the raw-data, and applies continuous wavelet transformation and optionally Gauss-fitting in the chromatographic domain. We evaluated our feature detection algorithm on dilution series and mixtures of seed and leaf extracts, and estimated recall, precision and F-score of seed and leaf specific features in two experiments of different complexity. Conclusion The new feature detection algorithm meets the requirements of current metabolomics experiments. centWave can detect close-by and partially overlapping features and has the highest overall recall and precision values compared to the other algorithms, matchedFilter (the original algorithm of XCMS) and the centroidPicker from MZmine. The centWave algorithm was integrated into the Bioconductor R-package XCMS and is available from
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              Global metabolic profiling procedures for urine using UPLC-MS.

              The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mSystems
                mSystems
                msys
                msys
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                24 April 2018
                May-Jun 2018
                : 3
                : 3
                : e00044-18
                Affiliations
                [a ]APC Microbiome Ireland, National University of Ireland, Cork, Ireland
                [b ]Department of Medicine, National University of Ireland, Cork, Ireland
                [c ]Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland
                [d ]Section of Biomolecular Medicine, Division of Computational Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
                [e ]Division of Surgery, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
                [f ]Alimentary Health Ltd., Cork, Ireland
                [g ]Department of Sport and Physical Activity, Human Performance Laboratory, National University of Ireland, Cork, Ireland
                [h ]Department of Sports Medicine, Sports Surgery Clinic, Santry, Dublin, Ireland
                University of Chicago
                Author notes
                Address correspondence to Owen Cronin, owen.cronin@ 123456hotmail.com .

                O.C. and W.B. contributed equally to this article.

                Citation Cronin O, Barton W, Skuse P, Penney NC, Garcia-Perez I, Murphy EF, Woods T, Nugent H, Fanning A, Melgar S, Falvey EC, Holmes E, Cotter PD, O’Sullivan O, Molloy MG, Shanahan F. 2018. A prospective metagenomic and metabolomic analysis of the impact of exercise and/or whey protein supplementation on the gut microbiome of sedentary adults. mSystems 3:e00044-18. https://doi.org/10.1128/mSystems.00044-18.

                Article
                mSystems00044-18
                10.1128/mSystems.00044-18
                5915698
                29719871
                a3a0f131-caef-47cb-a9e9-edefa5b47149
                Copyright © 2018 Cronin et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 30 March 2018
                : 2 April 2018
                Page count
                supplementary-material: 10, Figures: 4, Tables: 1, Equations: 0, References: 71, Pages: 18, Words: 13194
                Funding
                Funded by: Irish Centre for Arthritis Research and Education (ICARE);
                Award ID: N/A
                Award Recipient :
                Funded by: Science Foundation Ireland (SFI), https://doi.org/10.13039/501100001602;
                Award ID: SFI/12/RC/2273
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: Science Foundation Ireland (SFI), https://doi.org/10.13039/501100001602;
                Award ID: SFI/11/PI/1137
                Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: Science Foundation Ireland (SFI), https://doi.org/10.13039/501100001602;
                Award ID: SFI/13/SIRG/2160
                Award Recipient : Award Recipient :
                Funded by: Diabetes Research & Wellness Foundation (DRWF), https://doi.org/10.13039/501100000273;
                Award ID: Sutherland-Earl Clinical Research Fellowship 2015
                Award Recipient :
                Categories
                Research Article
                Host-Microbe Biology
                Custom metadata
                May/June 2018

                bacteriophages,exercise,metabolism,microbial communities,next-generation sequencing,whey protein

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