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‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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then thawed; the DNA was extracted from each sample; sequencing of the variable V3–V4 16S rRNA gene regions was performed (after the total DNA isolation and library preparation) by using an MiSeq Reagent Kit v2 (300 cycles) and MiSDefault (Illumina, San
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Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Steno Diabetes Center Copenhagen, Gentofte, Denmark
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course with the alpha-glucosidase inhibitor, acarbose, on GM profiles (evaluated by 16S rRNA gene-based high-throughput sequencing) in Caucasian individuals with metformin-treated T2D. Materials and methods Ethics and study approvals This
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), anthranilic acid (AA), 3-hydroxyanthranilic acid (HAA), 5-hydroxyindole-3-acetic acid (HIAA), indole-3-lactic acid (ILA), indole-3-acetic acid (IAA) and indole-3-propionic acid (IPA). Gut microbiome Stool specimens for 16S rRNA-based gut microbiome
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extraction kit, and the quality of the extracted DNA was detected using a Qubit dsDNA HS Assay Kit (Carlsbad, CA, USA). After eliminating the samples that did not meet the test standard, the V3–V4 variable region of the 16S rRNA was specifically amplified by
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Polycystic ovary syndrome (PCOS) is a chronic endocrine and metabolic disease. Gut microbiota is closely related to many chronic diseases. In this study, we conducted a cross-sectional study and recruited 30 obese (OG) and 30 non-obese (NG) women with PCOS, 30 healthy women (NC) and 11 healthy but obese women (OC) as controls to investigate the characteristic gut microbiota and its metabolic functions in obese and non-obese patients with PCOS. The blood and non-menstrual faecal samples of all the participants were collected and analysed. As a result, the Hirsutism score, LH/FSH and serum T level in NG and OG both increased significantly compared with their controls (P < 0.05). High-throughput 16S rRNA gene sequencing revealed that the abundance and diversity of the gut microbiota changed in patients with PCOS. The linear discriminant analysis (LDA) indicated that Lactococcus was the characteristic gut microbiota in NG, while Coprococcus_2 in OG. Correlation heatmap analysis revealed that the sex hormones and insulin levels in human serum were closely related to the changes in the gut microbiota of NG and OG. Functional prediction analysis demonstrated that the citrate cycle pathway enriched both in NG and OG, and other 12 gut bacterial metabolic pathways enriched in NG. This study highlighted significant differences in the gut microbiota and predictive functions of obese and non-obese women with PCOS, thereby providing insights into the role and function of the gut microbiota that may contribute to the occurrence and development of PCOS in obese and non-obese women.
Department of Endocrinology, Zunyi Medical University, Zunyi, China
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targets, and sample-specific barcode sequences were used for PCR amplification of the variable regions of the 16S rRNA gene (Q5 HiFi DNA polymerase; NEB, Ipswich, MA, USA). The amplification products were subjected to 2% agarose gel electrophoresis, and
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.01 vs NFD group. # P < 0.05, ## P < 0.01 vs HGD group. Effects of HGD on the gut microbiota The composition of the gut microbiota was analyzed by bacterial 16S rRNA sequencing of the intestinal feces. After dereplication of unqualified