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      Unique Pakistani gut microbiota highlights population-specific microbiota signatures of type 2 diabetes mellitus

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          ABSTRACT

          Biogeographic variations in the gut microbiota are pivotal to understanding the global pattern of host–microbiota interactions in prevalent lifestyle-related diseases. Pakistani adults, having an exceptionally high prevalence of type 2 diabetes mellitus (T2D), are one of the most understudied populations in microbiota research to date. The aim of the present study is to examine the gut microbiota across individuals from Pakistan and other populations of non-industrialized and industrialized lifestyles with a focus on T2D. The fecal samples from 94 urban-dwelling Pakistani adults with and without T2D were profiled by bacterial 16S ribosomal RNA gene and fungal internal transcribed spacer (ITS) region amplicon sequencing and eubacterial qPCR, and plasma samples quantified for circulating levels of lipopolysaccharide-binding protein (LBP) and the activation ability of Toll-like receptor (TLR)-signaling. Publicly available datasets generated with comparable molecular methods were retrieved for comparative analysis of the bacterial microbiota. Overall, urbanized Pakistanis’ gut microbiota was similar to that of transitional or non-industrialized populations, depleted in Akkermansiaceae and enriched in Prevotellaceae (dominated by the non-Westernized clades of Prevotella copri). The relatively high proportion of Atopobiaceae appeared to be a unique characteristic of the Pakistani gut microbiota. The Pakistanis with T2D had elevated levels of LBP and TLR-signaling in circulation as well as gut microbial signatures atypical of other populations, e.g., increased relative abundance of Libanicoccus/ Parolsenella, limiting the inter-population extrapolation of gut microbiota-based classifiers for T2D. Taken together, our findings call for a more global representation of understudied populations to extend the applicability of microbiota-based diagnostics and therapeutics.

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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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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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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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                Author and article information

                Journal
                Gut Microbes
                Gut Microbes
                Gut Microbes
                Taylor & Francis
                1949-0976
                1949-0984
                2 November 2022
                2022
                2 November 2022
                : 14
                : 1
                : 2142009
                Affiliations
                [a ]Human Microbiome Research Program, Faculty of Medicine, University of Helsinki; , Helsinki, Finland
                [b ]Department of Microbiology, Faculty of Biological Sciences, Quaid-i-Azam University; , Islamabad, Pakistan
                [c ]Department of Microbiology, Faculty of Basic and Applied Sciences, University of Haripur; , Haripur, Pakistan
                [d ]Department of Virology, National Institute of Health; , Islamabad, Pakistan
                [e ]Department of Food and Nutrition, University of Helsinki; , Helsinki, Finland
                [f ]Laboratory of Microbiology, Wageningen University; , Wageningen, The Netherlands
                Author notes
                CONTACT Ching Jian ching.jian@ 123456helsinki.fi Haartmaninkatu 3, PO box 21, FI-00014 Helsinki, Finland
                [*]

                Equal contribution

                Author information
                https://orcid.org/0000-0002-6960-7447
                https://orcid.org/0000-0003-0577-8834
                Article
                2142009
                10.1080/19490976.2022.2142009
                9635555
                36322821
                60f628c6-0960-4395-97df-2b6c8bec8201
                © 2022 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.

                History
                Page count
                Figures: 7, Tables: 1, References: 88, Pages: 1
                Categories
                Research Article
                Research Paper

                Microbiology & Virology
                lifestyle,urbanization,gut microbiota,t2d,metabolic diseases,toll-like receptor,prevotella,random forest

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