Journal of Proteomics & Bioinformatics
Open Access
ISSN: 0974-276X
ISSN: 0974-276X
Lisha Li, Qiongying Hu and Daqian Xiong*
Background: Host-microbiome dysbiosis have been linked to Type 2 Diabetes Mellitus (T2DM). The purpose of this paper is to investigate whether Phascolarctobacterium and Phascolarctobacterium faecium (P. faecium) serve as ideal biomarkers for T2DM. On this basis, to evaluate the key role of multi-omics analysis in the early diagnosis of T2DM.
Method: Detected stool samples from healthy people, T2DM patients and T2DM patients after metformin treatment in our cohort study by 16S ribosomal Ribo-Nucleic Acid (rRNA) gene amplicon sequencing. In addition, various baseline clinical and metabolic index were collected to evaluate the diagnostic models of Receiver Operator Characteristic (ROC) curves which combined use of intestinal bacteria, fatty acids and micro Ribo-Nucleic Acid (miRNA) as predictive tools for early detection of T2DM.
Results: Our multi-omics analysis indicates that T2DM patients had specific gut microbiota dysbiosis, where faecium and P. faecium are correlated with multiple biochemical indicators of T2DM and the intervention of metformin had some influence on the composition of gut microbiota. We also identified the diagnostic models of ROC curves were able to classify T2DM patients from healthy people with a better estimation accuracy.
Conclusion: Phascolarctobacterium and P. faecium can be novel biomarkers for the early diagnosis of T2DM. The multi-omic analysis based on gut microbiome provides insights for elucidating the specific mechanism in the host-microbiome dysbiosis at the early metabolic disorders.
Published Date: 2023-12-04; Received Date: 2023-11-01