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 alteratio...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(PM2 RA),an analysis framework to identify and quantify the microbial RAs.The performance of PM2 RA 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 PM2 RA was robust for quantifying microbial RAs across different datasets in several diseases.By applying PM2 RA,we identified several novel or previously reported microbes implicated in multiple diseases.PM2 RA is now implemented as a web-based application available at http://www.pm2 ra-xingyinliulab.cn/.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.81671983 and 81871628)the Natural Science Funding from Jiangsu province,China(Grant No.BK20161572)+1 种基金the starting package from Nanjing Medical University,Chinathe starting funding for the team of gut microbiota research in Nanjing Medical University,China
文摘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(PM2 RA),an analysis framework to identify and quantify the microbial RAs.The performance of PM2 RA 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 PM2 RA was robust for quantifying microbial RAs across different datasets in several diseases.By applying PM2 RA,we identified several novel or previously reported microbes implicated in multiple diseases.PM2 RA is now implemented as a web-based application available at http://www.pm2 ra-xingyinliulab.cn/.
