Metagenomics and Faecal Metabolomics Integrative Analysis towards the Impaired Glucose Regulation and Type 2 Diabetes in Uyghur-Related Omics

• Main Authors: Rebiya Nuli, Jureti Azhati, Junxiu Cai, Aizhatiguli Kadeer, Bing Zhang, Patamu Mohemaiti
• Format: Article
• Language: English
• Published: Hindawi Limited 2019-01-01
• Series: Journal of Diabetes Research
• Online Access: http://dx.doi.org/10.1155/2019/2893041
• ISSN: 2314-6745; 2314-6753

Objective. Gut microbiota and their metabolites play an important role in the development of type 2 diabetes mellitus (T2DM). This research was designed to study the relationship between gut microbiota and faecal metabolites of Uyghur newly onset T2DM and impaired glucose regulation (IGR) patients. Materials and Methods. A total of 60 different glycemic Uyghur subjects were enrolled and divided into T2DM, IGR, and normal glucose tolerance (NGT) groups. Metagenomics and LC-MS-based untargeted faecal metabolomics were employed. Correlations between bacterial composition and faecal metabolomics were evaluated. Results. We discovered that the composition and diversity of gut microbiota in newly onset T2DM and IGR were different from those in NGT. The α-diversity was higher in NGT than in T2DM and IGR; β-diversity analysis revealed apparent differences in the bacterial community structures between patients with T2DM, IGR, and NGT. LC-MS faecal metabolomics analysis discovered different metabolomics features in the three groups. Alchornoic acid, PE (14 : 0/20 : 3), PI, L-tyrosine, LysoPC (15 : 0), protorifamycin I, pimelic acid, epothilone A, 7-dehydro-desmosterol, L-lysine, LysoPC (14 : 1), and teasterone are the most significant differential enriched metabolites. Most of the differential enriched metabolites were involved in metabolic processes, including carbohydrate metabolism, starch and sucrose metabolism, phenylpropanoid biosynthesis, and biosynthesis of amino acids. Procrustes analysis and correlation analysis identified correlations between gut microbiota and faecal metabolites. Matricin was positively correlated with Bacteroides and negatively correlated with Actinobacteria; protorifamycin I was negatively correlated with Actinobacteria; epothilone A was negatively correlated with Actinobacteria and positively correlated with Firmicutes; PA was positively correlated with Bacteroides and negatively correlated with Firmicutes; and cristacarpin was positively correlated with Actinobacteria; however, this correlation relationship does not imply causality. Conclusions. This study used joint metagenomics and metabolomics analyses to elucidate the relationship between gut microbiota and faecal metabolites in different glycemic groups, and the result suggested that metabolic disorders and gut microbiota dysbiosis occurred in Uyghur T2DM and IGR. The results provide a theoretical basis for studying the pathological mechanism for further research.