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      The Gut Mycobiome Characterization of Gestational Diabetes Mellitus and Its Association With Dietary Intervention

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          Abstract

          Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The active interface between gut microbiota and diet contributes to metabolic homeostasis in GDM. However, the contributions of gut mycobiome have been neglected. Here, we profiled the gut fungi between GDM and healthy subjects at two time points and investigate whether variations in gut mycobiome correlate with key features of host metabolism and diet management in this observational study. We identified that Hanseniaspora, Torulaspora, Auricularia, Alternaria, and Candida contributed to GDM patient clustering, indicating that these fungal taxa are associated with abnormal blood glucose levels, and the causality needs to be further explored. While Penicillium, Ganoderma, Fusarium, Chaetomium, and Heterobasidion had significant explanatory effects on healthy subject clustering. In addition, spearman analysis further indicated that blood glucose levels were negatively correlated with polysaccharide-producing genera, Ganoderma, which could be reshaped by the short-term diet. The Penicillium which was negatively correlates with metabolic parameters, also exhibited the antimicrobial attribute by the fungal-bacterial interaction analysis. These data suggest that host metabolic homeostasis in GDM may be influenced by variability in the mycobiome and could be reshaped by the diet intervention. This work reveals the potential significance of the gut mycobiome in health and has implications for the beneficial effects of diet intervention on host metabolic homeostasis through regulating gut fungal abundance and metabolites.

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          Most cited references42

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          QIIME allows analysis of high-throughput community sequencing data.

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            UCHIME improves sensitivity and speed of chimera detection

            Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: robert@drive5.com Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information: Supplementary data are available at Bioinformatics online.
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              UniFrac: a new phylogenetic method for comparing microbial communities.

              We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                15 June 2022
                2022
                : 13
                : 892859
                Affiliations
                [1] 1Department of Central Laboratory and Institute of Clinical Molecular Biology, Peking University People’s Hospital , Beijing, China
                [2] 2Department of Stomatology, Peking University People’s Hospital , Beijing, China
                [3] 3Department of Clinical Nutrition, Peking University People’s Hospital , Beijing, China
                [4] 4Department of Obstetrics and Gynecology, Peking University People’s Hospital , Beijing, China
                Author notes

                Edited by: Marina Liso, National Institute of Gastroenterology S. de Bellis Research Hospital (IRCCS), Italy

                Reviewed by: Joseph F. Pierre, University of Wisconsin–Madison, United States; Charikleia Stefanaki, National and Kapodistrian University of Athens, Greece; Yongbo Kang, Shanxi Medical University, China

                *Correspondence: Peng Liu, liupengpku@ 123456163.com

                These authors have contributed equally to this work and share senior authorship

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.892859
                9240440
                35783435
                f114985a-0bf8-4d18-9369-4122f8196d4b
                Copyright © 2022 Wu, Mo, Mu, Liu, Liu and Yu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 March 2022
                : 16 May 2022
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 42, Pages: 13, Words: 7564
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                gdm,gut mycobiome,diet intervention,fungal-bacterial interaction,polysaccharide-producing genera

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