PHISDetector:A Tool to Detect Diverse In Silico Phage-host Interaction Signals for Virome Studies
- Author:
Zhou FENGXIA
1
;
Gan RUI
;
Zhang FAN
;
Ren CHUNYAN
;
Yu LING
;
Si YU
;
Huang ZHIWEI
Author Information
1. HIT Center for Life Sciences,School of Life Science and Technology,Harbin Institute of Technology,Harbin 150080,China
- Keywords:
Phage-host interaction;
Virome;
CRISPR;
Prophage;
Machine learning
- From:
Genomics, Proteomics & Bioinformatics
2022;20(3):508-523
- CountryChina
- Language:Chinese
-
Abstract:
Phage-microbe interactions are appealing systems to study coevolution,and have also been increasingly emphasized due to their roles in human health,disease,and the development of novel therapeutics.Phage-microbe interactions leave diverse signals in bacterial and phage geno-mic sequences,defined as phage-host interaction signals(PHISs),which include clustered regularly interspaced short palindromic repeats(CRISPR)targeting,prophage,and protein-protein interac-tion signals.In the present study,we developed a novel tool phage-host interaction signal detector(PHISDetector)to predict phage-host interactions by detecting and integrating diverse in silico PHISs,and scoring the probability of phage-host interactions using machine learning models based on PHIS features.We evaluated the performance of PHISDetector on multiple benchmark datasets and application cases.When tested on a dataset of 758 annotated phage-host pairs,PHISDetector yields the prediction accuracies of 0.51 and 0.73 at the species and genus levels,respectively,outper-forming other phage-host prediction tools.When applied to 125,842 metagenomic viral contigs(mVCs)derived from 3042 geographically diverse samples,a detection rate of 54.54％could be achieved.Furthermore,PHISDetector could predict infecting phages for 85.6％of 368 multidrug-resistant(MDR)bacteria and 30％of 454 human gut bacteria obtained from the National Institutes of Health(NIH)Human Microbiome Project(HMP).
