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      Epigallocatechin-3-Gallate Improves Intestinal Gut Microbiota Homeostasis and Ameliorates Clostridioides difficile Infection

      , , , , , , , , ,
      Nutrients
      MDPI AG

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          Abstract

          Clostridioides difficile infection is closely related to the intestinal flora disorders induced by antibiotics, and changes in the intestinal flora may cause the occurrence and development of Clostridioides difficile infection. Epigallocatechin-3-gallate (EGCG) is one of the major bioactive ingredients of green tea and has been suggested to alleviate the growth of C. difficile in vitro. EGCG can ameliorate several diseases, such as obesity, by regulating the gut microbiota. However, whether EGCG can attenuate C. difficile infection by improving the gut microbiota is unknown. After establishing a mouse model of C. difficile infection, mice were administered EGCG (25 or 50 mg/kg/day) or PBS intragastrically for 2 weeks to assess the benefits of EGCG. Colonic pathology, inflammation, the intestinal barrier, gut microbiota composition, metabolomics, and the transcriptome were evaluated in the different groups. Compared with those of the mice in the CDI group, EGCG improved survival rates after infection, improved inflammatory markers, and restored the damage to the intestinal barrier. Furthermore, EGCG could improve the intestinal microbial community caused by C. difficile infection, such as by reducing the relative abundance of Enterococcaceae and Enterobacteriaceae. Moreover, EGCG can increase short-chain fatty acids, improve amino acid metabolism, and downregulate pathways related to intestinal inflammation. EGCG alters the microbiota and alleviates C. difficile infection, which provides new insights into potential therapies.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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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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              HISAT: a fast spliced aligner with low memory requirements.

              HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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                Author and article information

                Journal
                NUTRHU
                Nutrients
                Nutrients
                MDPI AG
                2072-6643
                September 2022
                September 11 2022
                : 14
                : 18
                : 3756
                Article
                10.3390/nu14183756
                36145133
                247c2e1f-2884-4046-a19b-51be3421b5da
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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