PM2RA: A Framework for Detecting and Quantifying Relationship Alterations in Microbial Community

• Published in: Genomics, proteomics & bioinformatics Vol. 19; no. 1; pp. 154 - 167
• Main Authors: Liu, Zhi, Mi, Kai, Xu, Zhenjiang Zech, Zhang, Qiankun, Liu, Xingyin
• Format: Journal Article
• Language: English
• Published: China Elsevier B.V 01.02.2021; State Key Laboratory of Reproductive Medicine,Center of Global Health,Nanjing Medical University,Nanjing 211166,China; Key Laboratory of Human Functional Genomics of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China; Key Laboratory of Holistic Integrative Enterology,Second Affiliated Hospital of Nanjing Medical University,Nanjing 210003,China; Department of Pathogen Biology-Microbiology Division,Key Laboratory of Pathogen Biology of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China; Key Laboratory of Human Functional Genomics of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China%Department of Pathogen Biology-Microbiology Division,Key Laboratory of Pathogen Biology of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China%School of Food and Technology State,Key Laboratory of Food Science and Technology,Nanchang University,Nanchang 330031,China%Department of Pathogen Biology-Microbiology Division,Key Laboratory of Pathogen Biology of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China; Key Laboratory of Human Functional Genomics of Jiangsu Province,Nanjing Medical University,Nanjing 211166,China%State Key Laboratory of Reproductive Medicine,Center of Global Health,Nanjing Medical University,Nanjing 211166,China; Elsevier
• Subjects: bioinformatics; data collection; dysbiosis; genomics; health status; Human disease; human diseases; intestinal microorganisms; Method; microbial communities; Microbial community; Microbial relationship alteration; Microbiome; Network; pathogenesis; Profile monitoring; proteomics; Profile monitoring; Human disease; Microbial relationship alteration; Microbial community; Network; Microbiome
• ISSN: 1672-0229; 2210-3244
• DOI: 10.1016/j.gpb.2020.07.005

The dysbiosis of gut microbiota is associated with the pathogenesis of human diseases. However, observing shifts in the microbe abundance cannot fully reveal underlying perturbations. Examining the relationship alterations (RAs) in the microbiome between health and disease statuses provides additional hints about the pathogenesis of human diseases, but no methods were designed to detect and quantify the RAs between different conditions directly. Here, we present profile monitoring for microbial relationship alteration (PM2RA), an analysis framework to identify and quantify the microbial RAs. The performance of PM2RA was evaluated with synthetic data, and it showed higher specificity and sensitivity than the co-occurrence-based methods. Analyses of real microbial datasets showed that PM2RA was robust for quantifying microbial RAs across different datasets in several diseases. By applying PM2RA, we identified several novel or previously reported microbes implicated in multiple diseases. PM2RA is now implemented as a web-based application available at http://www.pm2ra-xingyinliulab.cn/.