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      Cytolethal distending toxin B inoculation leads to distinct gut microtypes and IBS-D-like microRNA-mediated gene expression changes in a rodent model

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          ABSTRACT

          Diarrhea-predominant irritable bowel syndrome (IBS-D), associated with increased intestinal permeability, inflammation, and small intestinal bacterial overgrowth, can be triggered by acute gastroenteritis. Cytolethal distending toxin B (CdtB) is produced by gastroenteritis-causing pathogens and may underlie IBS-D development, through molecular mimicry with vinculin. Here, we examine the effects of exposure to CdtB alone on gut microbiome composition, host intestinal gene expression, and IBS-D-like phenotypes in a rat model. CdtB-inoculated rats exhibited increased anti-CdtB levels, which correlated with increased stool wet weights, pro-inflammatory cytokines (TNFα, IL2) and predicted microbial metabolic pathways including inflammatory responses, TNF responses, and diarrhea. Three distinct ileal microbiome profiles (microtypes) were identified in CdtB-inoculated rats. The first microtype (most like controls) had altered relative abundance (RA) of genera Bifidobacterium, Lactococcus, and Rothia. The second had lower microbial diversity, higher Escherichia-Shigella RA, higher absolute E. coli abundance, and altered host ileal tissue expression of immune-response and TNF-response genes compared to controls. The third microtype had higher microbial diversity, higher RA of hydrogen sulfide (H 2S)-producer Desulfovibrio, and increased expression of H 2S-associated pain/serotonin response genes. All CdtB-inoculated rats exhibited decreased ileal expression of cell junction component mRNAs, including vinculin-associated proteins. Significantly, cluster-specific microRNA-mRNA interactions controlling intestinal permeability, visceral hypersensitivity/pain, and gastrointestinal motility genes, including several previously associated with IBS were seen. These findings demonstrate that exposure to CdtB toxin alone results in IBS-like phenotypes including inflammation and diarrhea-like stool, decreased expression of intestinal barrier components, and altered ileal microtypes that influenced changes in microRNA-modulated gene expression and predicted metabolic pathways consistent with specific IBS-D symptoms.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

              Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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                Author and article information

                Journal
                Gut Microbes
                Gut Microbes
                Gut Microbes
                Taylor & Francis
                1949-0976
                1949-0984
                18 December 2023
                2024
                18 December 2023
                : 16
                : 1
                : 2293170
                Affiliations
                [a ]Medically Associated Science and Technology (MAST) Program, Cedars-Sinai; , Los Angeles, CA, USA
                [b ]Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai; , Los Angeles, CA, USA
                [c ]Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai; , Los Angeles, CA, USA
                Author notes
                CONTACT Mark Pimentel mark.pimentel@ 123456cshs.org Medically Associated Science and Technology (MAST) Program, Cedars-Sinai; , Los Angeles, CA, USA
                Author information
                https://orcid.org/0000-0002-0619-5115
                Article
                2293170
                10.1080/19490976.2023.2293170
                10730147
                38108386
                4a62857e-f995-489d-804d-2fa6a20b7495
                © 2023 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-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial 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: 8, Tables: 1, References: 88, Pages: 1
                Categories
                Research Article
                Research Paper

                Microbiology & Virology
                irritable bowel syndrome,cytolethal distending toxin,gut microbiome,host gene expression,micrornas

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