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      Hyperbaric oxygen augments susceptibility to C. difficile infection by impairing gut microbiota ability to stimulate the HIF-1α-IL-22 axis in ILC3

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          ABSTRACT

          Hyperbaric oxygen (HBO) therapy is a well-established method for improving tissue oxygenation and is typically used for the treatment of various inflammatory conditions, including infectious diseases. However, its effect on the intestinal mucosa, a microenvironment known to be physiologically hypoxic, remains unclear. Here, we demonstrated that daily treatment with hyperbaric oxygen affects gut microbiome composition, worsening antibiotic-induced dysbiosis. Accordingly, HBO-treated mice were more susceptible to Clostridioides difficile infection (CDI), an enteric pathogen highly associated with antibiotic-induced colitis. These observations were closely linked with a decline in the level of microbiota-derived short-chain fatty acids (SCFAs). Butyrate, a SCFA produced primarily by anaerobic microbial species, mitigated HBO-induced susceptibility to CDI and increased epithelial barrier integrity by improving group 3 innate lymphoid cell (ILC3) responses. Mice displaying tissue-specific deletion of HIF-1 in RORγt-positive cells exhibited no protective effect of butyrate during CDI. In contrast, the reinforcement of HIF-1 signaling in RORγt-positive cells through the conditional deletion of VHL mitigated disease outcome, even after HBO therapy. Taken together, we conclude that HBO induces intestinal dysbiosis and impairs the production of SCFAs affecting the HIF-1α-IL-22 axis in ILC3 and worsening the response of mice to subsequent C. difficile infection.

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          Most cited references111

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          Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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            MultiQC: summarize analysis results for multiple tools and samples in a single report

            Motivation: Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis. Results: We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization. Availability and implementation: MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.info Contact: phil.ewels@scilifelab.se
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              Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin

              Background Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. Results We present q2-feature-classifier (https://github.com/qiime2/q2-feature-classifier), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated “novel” marker-gene sequences, are available in our extensible benchmarking framework, tax-credit (https://github.com/caporaso-lab/tax-credit-data). Conclusions Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.
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                Author and article information

                Journal
                Gut Microbes
                Gut Microbes
                Gut Microbes
                Taylor & Francis
                1949-0976
                1949-0984
                2 January 2024
                2024
                2 January 2024
                : 16
                : 1
                : 2297872
                Affiliations
                [a ]Department of Pathology and Immunology, Washington University School of Medicine; , St. Louis, MO, USA
                [b ]Department of Genetics and Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas; , Campinas, Brazil
                [c ]Hematology and Hemotherapy Center, University of Campinas; , Campinas, Brazil
                [d ]Department of Immunology, Institute of Biomedical Sciences, University of São Paulo; , São Paulo, Brazil
                [e ]Department of Animal Biology, Institute of Biology, University of Campinas; , Campinas, Brazil
                [f ]Experimental Medicine Research Cluster, Institute of Biology, University of Campinas; , Campinas, Brazil
                [g ]Obesity and Comorbidities Research Center (OCRC), University of Campinas; , Campinas, Brazil
                Author notes
                CONTACT José L. Fachi fachijl@ 123456wustl.edu Department of Pathology and Immunology, Washington University School of Medicine; , 660 S. Euclid Ave, St. Louis, MO 63110, USA
                Marco A. R. Vinolo mvinolo@ 123456unicamp.br Department of Genetics and Evolution, Microbiology and Immunology, Institute of Biology, University of Campinas; , 255 Monteiro Lobato St, Campinas, SP 13083-862, Brazil
                [*]

                Contributed equally.

                Author information
                https://orcid.org/0000-0002-1035-5193
                Article
                2297872
                10.1080/19490976.2023.2297872
                10763646
                38165200
                cbd40852-7def-48da-9af0-e79ca3761141
                © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 7, References: 111, Pages: 1
                Categories
                Research Article
                Research Paper

                Microbiology & Virology
                hyperbaric oxygen,microbiota,butyrate,clostridioides difficile,innate lymphoid cells,ilc3,hif-1

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