Department of Molecular Microbiology and Immunology, Saint Louis University- School of Medicine, Saint Louis, Missouri, United States of America.
Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, Missouri, United States of America.
PLoS Negl Trop Dis. 2020 Dec 3;14(12):e0008896. doi: 10.1371/journal.pntd.0008896. eCollection 2020 Dec.
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).
寨卡病毒(ZIKV)是一个重大的全球健康威胁,因为它有可能在怀孕期间感染时迅速出现,并与严重的先天性畸形相关。尽管有迫切的需求,但寨卡病毒感染的准确诊断仍然是一个必须克服的主要障碍。导致大多数基于血清学的寨卡病毒诊断检测存在不准确性的原因是,它与其他黄病毒(包括登革热病毒的四个血清型)存在大量的地理和抗原重叠。在这项研究中,我们利用了一种新的 T 细胞受体(TCR)测序平台来区分寨卡病毒和登革热病毒感染。通过对感染登革热病毒和寨卡病毒的小鼠的淋巴细胞进行高通量 TCR 测序,我们能够开发出一种算法,该算法可以识别与小鼠中先前的寨卡病毒或登革热病毒感染相关的独特的病毒相关 TCR 序列。使用该算法,我们能够以 97%的准确率将暴露于寨卡病毒或登革热病毒感染的小鼠分开。总的来说,这项研究证明了 T 细胞受体测序可以作为一种诊断工具,用于区分密切相关的病毒。我们的研究结果表明,这种创新平台有可能被用于准确诊断寨卡病毒感染,以及潜在的下一个出现的病原体。