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      Alterations of Gut Microbiome and Metabolite Profiling in Mice Infected by Schistosoma japonicum

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          Abstract

          Schistosoma japonicum ( S. japonicum) is one of the etiological agents of schistosomiasis, a widespread zoonotic parasitic disease. However, the mechanism of the balanced co-existence between the host immune system and S. japonicum as well as their complex interaction remains unclear. In this study, 16S rRNA gene sequencing, combined with metagenomic sequencing approach as well as ultraperformance liquid chromatography–mass spectrometry metabolic profiling, was applied to demonstrate changes in the gut microbiome community structure during schistosomiasis progression, the functional interactions between the gut bacteria and S. japonicum infection in BALB/c mice, and the dynamic metabolite changes of the host. The results showed that both gut microbiome and the metabolites were significantly altered at different time points after the infection. Decrease in richness and diversity as well as differed composition of the gut microbiota was observed in the infected status when compared with the uninfected status. At the phylum level, the gut microbial communities in all samples were dominated by Firmicutes, Bacteroidetes, Proteobacteria, and Deferribacteres, while at the genus level, Lactobacillus, Lachnospiraceae NK4A136 group, Bacteroides, Staphylococcus, and Alloprevotella were the most abundant. After exposure, Roseburia, and Ruminococcaceae UCG-014 decreased, while Staphylococcus, Alistipes, and Parabacteroides increased, which could raise the risk of infections. Furthermore, LEfSe demonstrated several bacterial taxa that could discriminate between each time point of S. japonicum infection. Besides that, metagenomic analysis illuminated that the AMP-activated protein kinase (AMPK) signaling pathway and the chemokine signaling pathway were significantly perturbed after the infection. Phosphatidylcholine and colfosceril palmitate in serum as well as xanthurenic acid, naphthalenesulfonic acid, and pimelylcarnitine in urine might be metabolic biomarkers due to their promising diagnostic potential at the early stage of the infection. Alterations of glycerophospholipid and purine metabolism were also discovered in the infection. The present study might provide further understanding of the mechanisms during schistosome infection in aspects of gut microbiome and metabolites, and facilitate the discovery of new targets for early diagnosis and prognostic purposes. Further validations of potential biomarkers in human populations are necessary, and the exploration of interactions among S. japonicum, gut microbiome, and metabolites is to be deepened in the future.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                08 October 2020
                2020
                : 11
                : 569727
                Affiliations
                [1] 1Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education , Guangzhou, China
                [2] 2Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University , Haikou, China
                [3] 3Joint Program of Pathobiology, Fifth Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University , Guangzhou, China
                [4] 4Instrumental Analysis and Research Center, Sun Yat-sen University , Guangzhou, China
                [5] 5Department of Gastroenterology, The Fifth Affiliated Hospital of Sun Yat-sen University , Zhuhai, China
                [6] 6Provincial Engineering Technology Research Center for Biological Vector Control, Zhongshan School of Medicine, Sun Yat-sen University , Guangzhou, China
                Author notes

                Edited by: Jun-Hu Chen, National Institute of Parasitic Diseases (China), China

                Reviewed by: Wanchai Maleewong, Khon Kaen University, Thailand; Guillaume Sarrabayrouse, Vall d'Hebron Research Institute (VHIR), Spain; Jilong Shen, Anhui Medical University, China

                *Correspondence: Zhiyue Lv lvzhiyue@ 123456mail.sysu.edu.cn

                This article was submitted to Microbial Immunology, a section of the journal Frontiers in Immunology

                †These authors have contributed equally to this work

                Article
                10.3389/fimmu.2020.569727
                7580221
                33162984
                e8e75cb1-a7c2-4d70-95ee-0fe12690afda
                Copyright © 2020 Hu, Chen, Xu, Zhou, Huang, Ma, Gao, Cheng, Zhou and Lv.

                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
                : 04 June 2020
                : 24 August 2020
                Page count
                Figures: 11, Tables: 0, Equations: 0, References: 83, Pages: 20, Words: 13353
                Categories
                Immunology
                Original Research

                Immunology
                schistosoma japonicum,gut microbiome,metagenomics,metabolomics,16s rrna,uplc-ms 3
                Immunology
                schistosoma japonicum, gut microbiome, metagenomics, metabolomics, 16s rrna, uplc-ms 3

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