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      Blueberry polyphenols alter gut microbiota & phenolic metabolism in rats

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          Abstract

          Metabolism of orally dosed blueberry polyphenols is dependent upon both dose and food matrix, resulting in different compositions of phenolic metabolites and the gut microbiota.

          Abstract

          Consuming polyphenol-rich fruits and vegetables, including blueberries, is associated with beneficial health outcomes. Interest in enhancing polyphenol intakes via dietary supplements has grown, though differences in fruit versus supplement matrix on gut microbiota and ultimate phenolic metabolism to bioactive metabolites are unknown. To evaluate this, 5-month-old, ovariectomized, Sprague-Dawley rats were gavaged for 90 d with a purified extract of blueberry polyphenols (0, 50, 250, or 1000 mg total polyphenols per kg bw per d) or lyophilized blueberries (50 mg total polyphenols per kg bw per d, equivalent to 150 g fresh blueberries per day in humans). Urine, feces, and tissues were assessed for gut microbiota and phenolic metabolism. Significant dose- and food matrix-dependent effects were observed at all endpoints measured. Gut microbial populations showed increased diversity at moderate doses but decreased diversity at high doses. Urinary phenolic metabolites were primarily observed as microbially derived metabolites and underwent extensive host xenobiotic phase II metabolism. Thus, blueberry polyphenols in fruit and supplements induce differences in gut microbial communities and phenolic metabolism, which may alter intended health effects.

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          Most cited references53

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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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            • Record: found
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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              • Record: found
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              Is Open Access

              Metagenomic biomarker discovery and explanation

              This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
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                Journal
                FFOUAI
                Food & Function
                Food Funct.
                Royal Society of Chemistry (RSC)
                2042-6496
                2042-650X
                March 29 2021
                2021
                : 12
                : 6
                : 2442-2456
                Affiliations
                [1 ]Dept. of Food Science
                [2 ]Purdue University
                [3 ]W Lafayette
                [4 ]USA
                [5 ]Dept. of Agronomy
                [6 ]Plants for Human Health Institute
                [7 ]North Carolina State University
                [8 ]Kannapolis
                Article
                10.1039/D0FO03457F
                33629093
                5603a6ec-f7dd-4b05-b675-dc16355674ea
                © 2021

                http://rsc.li/journals-terms-of-use

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