PathogenTrack and Yeskit:tools for identifying intracellular pathogens from single-cell RNA-sequencing datasets as illustrated by application to COVID-19

作     者：Wei Zhang Xiaoguang Xu Ziyu Fu Jian Chen Saijuan Chen Yun Tan Wei Zhang;Xiaoguang Xu;Ziyu Fu;Jian Chen;Saijuan Chen;Yun Tan

作者机构：Shanghai Institute of HematologyState Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200025China School of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China Department of Thoracic SurgeryShanghai Pulmonary HospitalTongji University School of MedicineShanghai 200433China 

出 版 物：《Frontiers of Medicine》 (医学前沿（英文版）)

年 卷 期：2022年第16卷第2期

页      面：251-262页

核心收录：

学科分类：1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 100214[医学-肿瘤学] 10[医学] 

基　　金：This work was supported by grants from National Natural Science Foundation of China(Nos.8210010124 and 81890994) Double First-Class Project(No.WF510162602) National Key R&D Program of China(No.2019YFA0905902) Natural Science Foundation of Shanghai(Nos.21ZR1480900 and 21YF1427900) Shanghai Jiao Tong University(No.YG2021-QN19) the Shanghai Guangci Translational Medical Research Development Foundation. 

主　　题：scRNA-seq intracellular pathogen microbe COVID-19 SARS-CoV-2 

摘      要：Pathogenic microbes can induce cellular dysfunction,immune response,and cause infectious disease and other diseases including cancers.However,the cellular distributions of pathogens and their impact on host cells remain rarely explored due to the limited methods.Taking advantage of single-cell RNA-sequencing(scRNA-seq)analysis,we can assess the transcriptomic features at the single-cell level.Still,the tools used to interpret pathogens(such as viruses,bacteria,and fungi)at the single-cell level remain to be explored.Here,we introduced PathogenTrack,a python-based computational pipeline that uses unmapped scRNA-seq data to identify intracellular pathogens at the single-cell level.In addition,we established an R package named Yeskit to import,integrate,analyze,and interpret pathogen abundance and transcriptomic features in host cells.Robustness of these tools has been tested on various real and simulated scRNA-seq datasets.PathogenTrack is competitive to the state-of-the-art tools such as Viral-Track,and the first tools for identifying bacteria at the single-cell level.Using the raw data of bronchoalveolar lavage fluid samples(BALF)from COVID-19 patients in the SRA database,we found the SARS-CoV-2 virus exists in multiple cell types including epithelial cells and macrophages.SARS-CoV-2-positive neutrophils showed increased expression of genes related to type I interferon pathway and antigen presenting module.Additionally,we observed the Haemophilus parahaemolyticus in some macrophage and epithelial cells,indicating a co-infection of the bacterium in some severe cases of COVID-19.The PathogenTrack pipeline and the Yeskit package are publicly available at GitHub.