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      The Association between Gut Microbiome and Pregnancy-Induced Hypertension: A Nested Case–Control Study

      , , , , ,
      Nutrients
      MDPI AG

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          Abstract

          (1) Background: Pregnancy-induced hypertension (PIH) is associated with obvious microbiota dysbiosis in the third trimester of pregnancy. However, the mechanisms behind these changes remain unknown. Therefore, this study aimed to explore the relationship between the gut microbiome in early pregnancy and PIH occurrence. (2) Methods: A nested case–control study design was used based on the follow-up cohort. Thirty-five PIH patients and thirty-five matched healthy pregnant women were selected as controls. The gut microbiome profiles were assessed in the first trimester using metagenomic sequencing. (3) Results: Diversity analyses showed that microbiota diversity was altered in early pregnancy. At the species level, eight bacterial species were enriched in healthy controls: Alistipes putredinis, Bacteroides vulgatus, Ruminococcus torques, Oscillibacter unclassified, Akkermansia muciniphila, Clostridium citroniae, Parasutterella excrementihominis and Burkholderiales bacterium_1_1_47. Conversely, Eubacterium rectale, and Ruminococcus bromii were enriched in PIH patients. The results of functional analysis showed that the changes in these different microorganisms may affect the blood pressure of pregnant women by affecting the metabolism of vitamin K2, sphingolipid, lipid acid and glycine. (4) Conclusion: Microbiota dysbiosis in PIH patients begins in the first trimester of pregnancy, and this may be associated with the occurrence of PIH. Bacterial pathway analyses suggest that the gut microbiome might lead to the development of PIH through the alterations of function modules.

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          Most cited references63

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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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            MetaPhlAn2 for enhanced metagenomic taxonomic profiling.

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              Species-level functional profiling of metagenomes and metatranscriptomes

              Functional profiling from metagenomic or metatranscriptomic (“meta’omic”) sequencing provides insight into the molecular activities of microbial communities. These analyses are typically carried out using comprehensive search of sequencing reads, which is time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed a tiered meta’omic search strategy (HUMAnN2) which enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community’s known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is 3x faster and produces more accurate gene family profiles (89% vs. 67%). We apply HUMAnN2 to clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species’ genomic vs. transcriptional contributions, and strain profiling. Finally, we introduce “contributional diversity” to explain patterns of ecological assembly across different microbial community types.
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                Author and article information

                Journal
                NUTRHU
                Nutrients
                Nutrients
                MDPI AG
                2072-6643
                November 2022
                November 01 2022
                : 14
                : 21
                : 4582
                Article
                10.3390/nu14214582
                36364844
                b89c9227-b120-422e-a633-961de5060356
                © 2022

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

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