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      Dramatic Remodeling of the Gut Microbiome Around Parturition and Its Relationship With Host Serum Metabolic Changes in Sows

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          Abstract

          Perinatal care is important in mammals due to its contribution to fetal growth, maternal health, and lactation. Substantial changes in host hormones, metabolism, and immunity around the parturition period may be accompanied by alterations in the gut microbiome. However, to our knowledge, changes in the gut microbiome and their contribution to the shifts in host metabolism around parturition have not been investigated in pigs. Furthermore, pigs are an ideal biomedical model for studying the interactions of the gut microbiota with host metabolism, due to the ease of controlling feeding conditions. Here we report dramatic remodeling of the gut microbiota and the potential functional capacity during the late stages of pregnancy (5 days before parturition, LP) to postpartum (within 6 h after delivery, PO) in both experimental and validated populations of sows ( n = 107). The richness of bacteria in the gut of both pregnant and delivery sows significantly decreased, whilst the β-diversity dramatically expanded. The ratio of Bacteroidetes to Firmicutes, and the relative abundance of Prevotella significantly decreased, whilst the relative abundance of the predominant genus Lactobacillus significantly increased from LP to PO state. The predicted functional capacities of the gut microbiome related to amino acid metabolism, the metabolism of cofactors and vitamins, and glycan biosynthesis were significantly decreased from LP to PO state. However, the abundance of the functional capacities associated with carbohydrate and lipid metabolism were increased. Consistent with these changes, serum metabolites enriched at the LP stage were associated with the metabolism of amino acids and vitamins. In contrast, metabolites enriched at the PO stage were related to lipid metabolism. We further identified that the richness and β-diversity of the gut microbiota and the abundance of Lactobacillus accounted for shifts in the levels of bile acid metabolites associated with lipid metabolism. The results suggest that host-microbiota interactions during the perinatal period impact host metabolism. These benefit the lactation of sows by providing energy from lipid metabolism for milk production.

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          Most cited references33

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          WGCNA: an R package for weighted correlation network analysis

          Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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            FLASH: fast length adjustment of short reads to improve genome assemblies.

            Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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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 Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                12 September 2019
                2019
                : 10
                : 2123
                Affiliations
                State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University , Nanchang, China
                Author notes

                Edited by: Jana Seifert, University of Hohenheim, Germany

                Reviewed by: Fiona Fouhy, Teagasc, The Irish Agriculture and Food Development Authority, Ireland; Xia Xiong, Institute of Subtropical Agriculture (CAS), China

                *Correspondence: Congying Chen chcy75@ 123456hotmail.com

                This article was submitted to Systems Microbiology, a section of the journal Frontiers in Microbiology

                †These authors have contributed equally to this work

                Article
                10.3389/fmicb.2019.02123
                6751307
                31572329
                5df74f1a-94c7-424b-a67d-de38d8a34abc
                Copyright © 2019 Huang, Gao, Zhao, He, Ke, Wu, Zhou, Fu, Yang, Chen and Huang.

                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
                : 29 June 2019
                : 29 August 2019
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 49, Pages: 12, Words: 8641
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                gut microbiome,phylogenetic composition,metabolomics,perinatal period,sow
                Microbiology & Virology
                gut microbiome, phylogenetic composition, metabolomics, perinatal period, sow

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