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      Islet autoantibody seroconversion in type-1 diabetes is associated with metagenome-assembled genomes in infant gut microbiomes

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          Abstract

          The immune system of some genetically susceptible children can be triggered by certain environmental factors to produce islet autoantibodies (IA) against pancreatic β cells, which greatly increases their risk for Type-1 diabetes. An environmental factor under active investigation is the gut microbiome due to its important role in immune system education. Here, we study gut metagenomes that are de-novo-assembled in 887 at-risk children in the Environmental Determinants of Diabetes in the Young (TEDDY) project. Our results reveal a small set of core protein families, present in >50% of the subjects, which account for 64% of the sequencing reads. Time-series binning generates 21,536 high-quality metagenome-assembled genomes (MAGs) from 883 species, including 176 species that hitherto have no MAG representation in previous comprehensive human microbiome surveys. IA seroconversion is positively associated with 2373 MAGs and negatively with 1549 MAGs. Comparative genomics analysis identifies lipopolysaccharides biosynthesis in Bacteroides MAGs and sulfate reduction in Anaerostipes MAGs as functional signatures of MAGs with positive IA-association. The functional signatures in the MAGs with negative IA-association include carbohydrate degradation in lactic acid bacteria MAGs and nitrate reduction in Escherichia MAGs. Overall, our results show a distinct set of gut microorganisms associated with IA seroconversion and uncovered the functional genomics signatures of these IA-associated microorganisms

          Abstract

          Here, by characterizing gut metagenomes of at-risk children in the TEDDY project, the authors associate onset of autoimmunity leading to Type-1 diabetes with certain sets of microorganisms in the gut microbiota, and identify metabolic capabilities encoded in the genomes of these microorganisms that provide functional insights to the association.

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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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            Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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              Fast and sensitive protein alignment using DIAMOND.

              The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.
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                Author and article information

                Contributors
                cpan@ou.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                21 June 2022
                21 June 2022
                2022
                : 13
                : 3551
                Affiliations
                [1 ]GRID grid.266902.9, ISNI 0000 0001 2179 3618, Harold Hamm Diabetes Center, , University of Oklahoma Health Sciences Center, ; Oklahoma City, OK USA
                [2 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, Department of Microbiology and Plant Biology, , University of Oklahoma, ; Norman, OK USA
                [3 ]GRID grid.266902.9, ISNI 0000 0001 2179 3618, Department of Biochemistry and Molecular Biology, , University of Oklahoma Health Sciences Center, ; Oklahoma City, OK USA
                [4 ]GRID grid.266900.b, ISNI 0000 0004 0447 0018, School of Computer Science, , University of Oklahoma, ; Norman, OK USA
                [5 ]GRID grid.4391.f, ISNI 0000 0001 2112 1969, Department of Microbiology, , Oregon State University, ; Corvallis, OR USA
                [6 ]GRID grid.266902.9, ISNI 0000 0001 2179 3618, Department of Physiology, , University of Oklahoma Health Sciences Center, ; Oklahoma City, OK USA
                Author information
                http://orcid.org/0000-0002-7929-4886
                http://orcid.org/0000-0003-2860-0334
                Article
                31227
                10.1038/s41467-022-31227-1
                9213500
                35729161
                3c73a168-2bb9-420e-82b1-2305dd7b344e
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 June 2021
                : 9 June 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100008460, U.S. Department of Health & Human Services | NIH | National Center for Complementary and Integrative Health (NCCIH);
                Award ID: R01AT011618
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000057, U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS);
                Award ID: R01AT011618
                Award Recipient :
                Categories
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                © The Author(s) 2022

                Uncategorized
                metagenomics,type 1 diabetes
                Uncategorized
                metagenomics, type 1 diabetes

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