Time-dependent contraction of the SARS-CoV-2-specific T-cell responses in convalescent individuals

康复者体内SARS-CoV-2特异性T细胞反应随时间推移而减弱

阅读:2

Abstract

BACKGROUND: Adaptive immunity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is decisive for disease control. Delayed activation of T cells is associated with a worse outcome in coronavirus disease 2019 (COVID-19). Although convalescent individuals exhibit solid T-cell immunity, to date, long-term immunity to SARS-CoV-2 is still under investigation. OBJECTIVES: We aimed to characterize the specific T-cell response on the basis of the in vitro recall of IFN-γ-producing cells to in silico-predicted peptides in samples from SARS-CoV-2 convalescent individuals. METHODS: The sequence of the SARS-CoV-2 genome was screened, leading to the identification of specific and promiscuous peptides predicted to be recognized by CD4(+) and CD8(+) T cells. Next, we performed an in vitro recall of specific T cells from PBMC samples from the participants. The results were analyzed according to clinical features of the cohort and HLA diversity. RESULTS: Our results indicated heterogeneous T-cell responsiveness among the participants. Compared with patients who exhibited mild symptoms, hospitalized patients had a significantly higher magnitude of response. In addition, male and older patients showed a lower number of IFN-γ-producing cells. Analysis of samples collected after 180 days revealed a reduction in the number of specific circulating IFN-γ-producing T cells, suggesting decreased immunity against viral peptides. CONCLUSION: Our data are evidence that in silico-predicted peptides are highly recognized by T cells from convalescent individuals, suggesting a possible application for vaccine design. However, the number of specific T cells decreases 180 days after infection, which might be associated with reduced protection against reinfection over time.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。