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).