2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Helminth-Induced Human Gastrointestinal Dysbiosis: a Systematic Review and Meta-Analysis Reveals Insights into Altered Taxon Diversity and Microbial Gradient Collapse

      research-article
      a , b , a , , a ,
      mBio
      American Society for Microbiology
      helminth, intestinal bacteria, intestinal parasites, microbiome, nematodes, soil-transmitted helminth

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          High-throughput 16S rRNA sequencing has allowed the characterization of helminth-uninfected (HU) and helminth-infected (HI) gut microbiomes, revealing distinct profiles. However, there have been no qualitative or quantitative syntheses of these studies, which show marked variation in participant age, diet, pathogen of interest, and study location. A predefined minimally biased search strategy identified 23 studies in humans. For each of these studies, we qualitatively addressed the effects of helminth infection on within-individual (alpha) and between-individual (beta) fecal microbiome diversity, infection-associated microbial taxa, the effect of helminth clearance on microbiome composition, microbiome composition as a predictor of infection status or treatment outcome, and treatment-specific effects on the fecal microbiome. Concomitantly, we performed a meta-analysis on a subset of 7 of these studies containing raw, paired-end 16S reads and individual-level metadata, comprising 424 pretreatment or untreated HI individuals and 497 HU controls. After reducing the batch effect and adjusting for age, our data demonstrated that intestinal helminth parasites can alter the host gut microbiome by increasing alpha diversity and promoting taxonomic reassortment and gradient collapse. Most strongly influencing the microbiome composition were the helminths found in the large intestine, Enterobius vermicularis and Trichuris trichiura, suggesting that this influence appears to be specific to soil-transmitted helminths (STH) species and host anatomical niche. In summary, using a large and diverse sample set captured in the meta-analysis, we were able to evaluate the influence of individual helminth species as well as species-species interactions, each of which explained a significant portion of the variation in the microbiome.

          Related collections

          Most cited references67

          • Record: found
          • Abstract: found
          • Article: not found

          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

          David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            mixOmics: An R package for ‘omics feature selection and multiple data integration

            The advent of high throughput technologies has led to a wealth of publicly available ‘omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a ‘molecular signature’) to explain or predict biological conditions, but mainly for a single type of ‘omics. In addition, commonly used methods are univariate and consider each biological feature independently. We introduce mixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a systems biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous ‘omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple ‘omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of ‘omics data available from the package.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism

              ABSTRACT The formation of SCFA is the result of a complex interplay between diet and the gut microbiota within the gut lumen environment. The discovery of receptors, across a range of cell and tissue types for which short chain fatty acids SCFA appear to be the natural ligands, has led to increased interest in SCFA as signaling molecules between the gut microbiota and the host. SCFA represent the major carbon flux from the diet through the gut microbiota to the host and evidence is emerging for a regulatory role of SCFA in local, intermediary and peripheral metabolism. However, a lack of well-designed and controlled human studies has hampered our understanding of the significance of SCFA in human metabolic health. This review aims to pull together recent findings on the role of SCFA in human metabolism to highlight the multi-faceted role of SCFA on different metabolic systems.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                mBio
                mBio
                mbio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                21 December 2021
                Nov-Dec 2021
                21 December 2021
                : 12
                : 6
                : e02890-21
                Affiliations
                [a ] Laboratory of Parasitic Diseases, NIAID, National Institutes of Health, , Bethesda, Maryland, USA
                [b ] Bioinformatics and Computational Biosciences Branch, National Institutes of Health, , Bethesda, Maryland, USA
                Washington University School of Medicine
                Author notes

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-6887-4941
                https://orcid.org/0000-0003-4932-2206
                Article
                02890-21 mbio.02890-21
                10.1128/mBio.02890-21
                8689561
                34933444
                130482e8-7516-4be4-9cd9-838a36cc95bf

                This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

                History
                : 20 October 2021
                : 15 November 2021
                Page count
                supplementary-material: 10, Figures: 7, Tables: 3, Equations: 0, References: 64, Pages: 17, Words: 9637
                Funding
                Funded by: Division of Intramural Research, National Institute of Allergy and Infectious Diseases (DIR, NIAID), FundRef https://doi.org/10.13039/100006492;
                Award Recipient :
                Categories
                Research Article
                host-microbial-interactions, Host-Microbial Interactions
                Custom metadata
                November/December 2021

                Life sciences
                helminth,intestinal bacteria,intestinal parasites,microbiome,nematodes,soil-transmitted helminth

                Comments

                Comment on this article