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      Gut Microbiota, Glucose, Lipid, and Water-Electrolyte Metabolism in Children With Nonalcoholic Fatty Liver Disease

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          Abstract

          There is evidence that nonalcoholic fatty liver disease (NAFLD) is affected by gut microbiota, glucose, and lipid. However, the function of water-electrolyte metabolism remains undefined in children with NAFLD. Therefore, the aim of this case-control study was to better understand these interactions. The sample consisted of 75 children, aged between 7 and 16, of whom 25 had nonalcoholic fatty liver (NAFL), 25 had nonalcoholic steatohepatitis (NASH), and 25 were obese and without NAFLD. These groups were matched by age, sex, and body mass index. Data were collected between June, 2019 and December, 2019 at the Hunan Children’s Hospital, in China. Microbiome composition in fecal samples was assessed using 16S ribosomal RNA amplicon sequencing. In the clinical indices, 12 glucose and lipid metabolism indices were included, and six water-electrolyte metabolism indices were included. The results indicated that microbiomes of NAFLD children had lower alpha diversity but higher beta diversity index than the other two groups. Specifically, anti-inflammatory and probiotics abundance (e.g., Faecalibacterium, Akkermansia, and Bifidobacterium_adolescentis) was significantly decreased in NAFLD, whereas the abundance of harmful bacteria (e.g., Staphylococcaceae) was increased. Moreover, the abundance of butyrate-producing bacteria (e.g., Faecalibacterium, Roseburia_inulinivorans, Roseburia_intestinalis, and Coprococcus_comes) was significantly decreased in NASH. The abundance of these bacteria were associated with glucose, lipid, and water-electrolyte metabolism (e.g., glucose, triglyceride, cholesterol, inorganic salt, total body water, etc.), implying that the NAFLD and its severity were associated with glucose, lipid, and water-electrolyte metabolism dysbiosis. Therefore, these findings suggest that the gut microbiome, especially butyrate-producing bacteria, play an important role in the development of NAFLD in children.

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          Most cited references60

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          QIIME allows analysis of high-throughput community sequencing data.

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            UPARSE: highly accurate OTU sequences from microbial amplicon reads.

            Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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                Author and article information

                Contributors
                Journal
                Front Cell Infect Microbiol
                Front Cell Infect Microbiol
                Front. Cell. Infect. Microbiol.
                Frontiers in Cellular and Infection Microbiology
                Frontiers Media S.A.
                2235-2988
                28 October 2021
                2021
                : 11
                : 683743
                Affiliations
                [1] 1 Xiangya School of Public Health, Central South University , Changsha, China
                [2] 2 Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University , Changsha, China
                [3] 3 Department of Mathematics and Statistics, Mzuzu University , Mzuzu, Malawi
                [4] 4 OMNI Research Group, Ottawa Hospital Research Institute , Ottawa, ON, Canada
                [5] 5 Department of Obstetrics and Gynaecology University of Ottawa Faculty of Medicine , Ottawa, ON, Canada
                [6] 6 School of Epidemiology and Public Health, University of Ottawa Faculty of Medicine , Ottawa, ON, Canada
                Author notes

                Edited by: Hong-Bao Li, Xi’an Jiaotong University, China

                Reviewed by: Xin Liu, Xi’an Jiaotong University, China; Ying Li, Xi’an Jiaotong University, China

                *Correspondence: Miyang Luo, lmy4300@ 123456gmail.com

                This article was submitted to Microbiome in Health and Disease, a section of the journal Frontiers in Cellular and Infection Microbiology

                Article
                10.3389/fcimb.2021.683743
                8581616
                34778099
                019d0a35-6b35-4f83-b969-87de3f9afbd9
                Copyright © 2021 Pan, Kaminga, Liu, Wen, Luo and Luo

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 10 April 2021
                : 09 September 2021
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 60, Pages: 14, Words: 6503
                Categories
                Cellular and Infection Microbiology
                Original Research

                Infectious disease & Microbiology
                gut microbiota,glycolipid metabolism,water-electrolyte metabolism,nonalcoholic fatty liver disease,nonalcoholic steatohepatitis

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