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      Impact of Yeast-Derived β-Glucans on the Porcine Gut Microbiota and Immune System in Early Life

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          Abstract

          Piglets are susceptible to infections in early life and around weaning due to rapid environmental and dietary changes. A compelling target to improve pig health in early life is diet, as it constitutes a pivotal determinant of gut microbial colonization and maturation of the host’s immune system. In the present study, we investigated how supplementation of yeast-derived β-glucans affects the gut microbiota and immune function pre- and post-weaning, and how these complex systems develop over time. From day two after birth until two weeks after weaning, piglets received yeast-derived β-glucans or a control treatment orally and were subsequently vaccinated against Salmonella Typhimurium. Faeces, digesta, blood, and tissue samples were collected to study gut microbiota composition and immune function. Overall, yeast-derived β-glucans did not affect the vaccination response, and only modest effects on faecal microbiota composition and immune parameters were observed, primarily before weaning. This study demonstrates that the pre-weaning period offers a ‘window of opportunity’ to alter the gut microbiota and immune system through diet. However, the observed changes were modest, and any long-lasting effects of yeast-derived β-glucans remain to be elucidated.

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          Most cited references65

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              Interaction between microbiota and immunity in health and disease

              The interplay between the commensal microbiota and the mammalian immune system development and function includes multifold interactions in homeostasis and disease. The microbiome plays critical roles in the training and development of major components of the host’s innate and adaptive immune system, while the immune system orchestrates the maintenance of key features of host-microbe symbiosis. In a genetically susceptible host, imbalances in microbiota-immunity interactions under defined environmental contexts are believed to contribute to the pathogenesis of a multitude of immune-mediated disorders. Here, we review features of microbiome-immunity crosstalk and their roles in health and disease, while providing examples of molecular mechanisms orchestrating these interactions in the intestine and extra-intestinal organs. We highlight aspects of the current knowledge, challenges and limitations in achieving causal understanding of host immune-microbiome interactions, as well as their impact on immune-mediated diseases, and discuss how these insights may translate towards future development of microbiome-targeted therapeutic interventions.
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                Author and article information

                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                13 October 2020
                October 2020
                : 8
                : 10
                : 1573
                Affiliations
                [1 ]Laboratory of Microbiology, Wageningen University, 6700 EH Wageningen, The Netherlands; hugo.devries@ 123456wur.nl
                [2 ]Host-Microbe Interactomics Group, Wageningen University, 6700 AH Wageningen, The Netherlands; jerry.wells@ 123456wur.nl
                [3 ]Cell Biology and Immunology Group, Wageningen University, 6700 AH Wageningen, The Netherlands; mirelle.geervliet@ 123456wur.nl (M.G.); natalie.groothuis@ 123456hotmail.com (N.G.); huub.savelkoul@ 123456wur.nl (H.F.J.S.); edwin.tijhaar@ 123456wur.nl (E.T.)
                [4 ]Department of Biomolecular Health Sciences, Division of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, 3584 CL Utrecht, The Netherlands; c.a.jansen@ 123456uu.nl (C.A.J.); v.rutten@ 123456uu.nl (V.P.M.G.R.)
                [5 ]Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, Onderstepoort 0110, South Africa
                [6 ]Research and Development, Trouw Nutrition, 3800 AG Amersfoort, The Netherlands; hubert.van.hees@ 123456trouwnutrition.com
                Author notes
                [* ]Correspondence: hauke.smidt@ 123456wur.nl
                [†]

                Authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-8888-7202
                https://orcid.org/0000-0001-8011-4144
                https://orcid.org/0000-0003-0740-0835
                https://orcid.org/0000-0002-6171-1805
                https://orcid.org/0000-0002-1457-1731
                https://orcid.org/0000-0001-6236-7092
                https://orcid.org/0000-0002-9014-0407
                https://orcid.org/0000-0002-6138-5026
                Article
                microorganisms-08-01573
                10.3390/microorganisms8101573
                7601942
                33066115
                5a04ff88-067d-4deb-b972-d65e51de41d9
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 August 2020
                : 09 October 2020
                Categories
                Article

                β-glucans,porcine,gastro-intestinal tract,gut microbiota,immune system,early life

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