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      Stool metabolome-microbiota evaluation among children and adolescents with obesity, overweight, and normal-weight using 1H NMR and 16S rRNA gene profiling

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          Abstract

          Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using 1H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

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          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.
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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              An obesity-associated gut microbiome with increased capacity for energy harvest.

              The worldwide obesity epidemic is stimulating efforts to identify host and environmental factors that affect energy balance. Comparisons of the distal gut microbiota of genetically obese mice and their lean littermates, as well as those of obese and lean human volunteers have revealed that obesity is associated with changes in the relative abundance of the two dominant bacterial divisions, the Bacteroidetes and the Firmicutes. Here we demonstrate through metagenomic and biochemical analyses that these changes affect the metabolic potential of the mouse gut microbiota. Our results indicate that the obese microbiome has an increased capacity to harvest energy from the diet. Furthermore, this trait is transmissible: colonization of germ-free mice with an 'obese microbiota' results in a significantly greater increase in total body fat than colonization with a 'lean microbiota'. These results identify the gut microbiota as an additional contributing factor to the pathophysiology of obesity.
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                Author and article information

                Contributors
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Methodology
                Role: Methodology
                Role: Data curationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: Validation
                Role: Investigation
                Role: Conceptualization
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 March 2021
                2021
                : 16
                : 3
                : e0247378
                Affiliations
                [1 ] Department of Food Science, Czech University of Life Sciences Prague, Prague, Czech Republic
                [2 ] Department of Medical Microbiology, 2 nd Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
                [3 ] Department of Paediatrics, 2 nd Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
                [4 ] Human Nutrition, School of Medicine, Dentistry & Nursing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow Royal Infirmary, Glasgow, United Kingdom
                [5 ] Olivova Children’s Medical Institution, Říčany, Czech Republic
                University of Maine, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ‡ These authors also contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1598-1855
                Article
                PONE-D-20-27287
                10.1371/journal.pone.0247378
                7993802
                33765008
                79cb200e-819e-48ba-918a-49c4bdb2adca
                © 2021 Jaimes et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 31 August 2020
                : 5 February 2021
                Page count
                Figures: 6, Tables: 2, Pages: 18
                Funding
                Funded by: Ministry of Education, Youth and Sports of the Czech Republic
                Award ID: LTC19008
                Award Recipient :
                Funded by: Ministry of Education, Youth and Sports of the Czech Republic
                Award ID: LM2018100
                Award Recipient :
                Funding for this research was provided by the Ministry of Education, Youth and Sports of the Czech Republic, research grants INTER-COST LTC19008 and METROFOOD-CZ research infrastructure project LM2018100, both awarded to JH. The funder website is https://www.msmt.cz/. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolites
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Childhood Obesity
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolomics
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Research and analysis methods
                Spectrum analysis techniques
                NMR spectroscopy
                Biology and Life Sciences
                Organisms
                Bacteria
                Enterobacteriaceae
                Escherichia
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Escherichia
                Custom metadata
                All data files are available from Mendeley Data under the following DOI link: http://dx.doi.org/10.17632/cwj76cbvc9.1. The items included there are: 1) S1 Table 1 (as referenced in the manuscript) containing the individual participant’s gender, age, BMI, BMI z-score, as well as the kilocalorie and macronutrient daily percentage composition one and two days prior to sampling; 2) unrarefied source data for the 16S rRNA gene sequencing analysis; 3) Metabolite concentrations in mg/g derived from Chenomx NMR Suite version 7.5 for each of the 52 study participants; and 4) the 1H NMR spectra for the 52 study participants.

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