首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Diagnostic differentiation of Zika and dengue virus exposure by analyzing T cell receptor sequences from peripheral blood of infected HLA-A2 transgenic mice
Authors:Mariah Hassert  Kyle J Wolf  Ahmad Rajeh  Courtney Schiebout  Stella G Hoft  Tae-Hyuk Ahn  Richard J DiPaolo  James D Brien  Amelia K Pinto
Institution:1. Department of Molecular Microbiology and Immunology, Saint Louis University- School of Medicine, Saint Louis, Missouri, United States of America;2. Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, Missouri, United States of America;3. Department of Computer Science, Saint Louis University, Saint Louis, Missouri, United States of America;University of Glasgow, UNITED KINGDOM
Abstract:Zika virus (ZIKV) is a significant global health threat due to its potential for rapid emergence and association with severe congenital malformations during infection in pregnancy. Despite the urgent need, accurate diagnosis of ZIKV infection is still a major hurdle that must be overcome. Contributing to the inaccuracy of most serologically-based diagnostic assays for ZIKV, is the substantial geographic and antigenic overlap with other flaviviruses, including the four serotypes of dengue virus (DENV). Within this study, we have utilized a novel T cell receptor (TCR) sequencing platform to distinguish between ZIKV and DENV infections. Using high-throughput TCR sequencing of lymphocytes isolated from DENV and ZIKV infected mice, we were able to develop an algorithm which could identify virus-associated TCR sequences uniquely associated with either a prior ZIKV or DENV infection in mice. Using this algorithm, we were then able to separate mice that had been exposed to ZIKV or DENV infection with 97% accuracy. Overall this study serves as a proof-of-principle that T cell receptor sequencing can be used as a diagnostic tool capable of distinguishing between closely related viruses. Our results demonstrate the potential for this innovative platform to be used to accurately diagnose Zika virus infection and potentially the next emerging pathogen(s).
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号