Quantification and statistical analysis
Data analyses were performed using FlowJo (version 10.1, BD Bioscience, Ashland, OR). Statistical analyses were performed using SPSS for Windows (version 26.0, SPSS Inc., Chicago, IL) and Prism for Windows (version 8.0.1, GraphPad Software, San Diego, CA). Data are expressed as mean ± standard deviation (SD), and statistical details are provided in the respective figure legends. Comparison analysis was carried out by two-tailed Student’s t test with p<0.05 considered statistically significant. The antigenicity effect size of the different SARS-CoV-2 peptides on T cell activation was assessed by Cohen’s d.[35]
To examine SARS-CoV-2-specific T cell response in recovered patients, we measured the upregulation status of the early activation marker CD69 and expression of intracellular cytokine IFN-γ, a functional T cell marker for protective immunity and analyzed the double-positive status of CD69/IFN-γ in CD4+ and CD8+ T cells, normalized to DMSO control.[36-38]. To estimate the half-life of SARS-CoV-2 RBD IgG, we calculated t1/2 = Ao/2k, where Ao is the initial amount of the antibody obtained from the y-intercept of the trendline and k is the slope of the trendline obtained from the scattered plot of RBD IgG ratio against recovery time. The recovery time is defined as the time between the date of the patient’s clinical diagnosis to the date of the blood sample collections. To analyze the relationship between anti-RBD IgG level and T cells response, we performed Spearman’s correlations and expressed as correlation coefficient (r).