SARS-CoV-2 induces a durable and antigen specific humoral immunity after asymptomatic to mild COVID-19 infection

Current SARS-CoV-2 serological assays generate discrepant results, and the longitudinal characteristics of antibodies targeting various antigens after asymptomatic to mild COVID-19 are yet to be established. This longitudinal cohort study including 1965 healthcare workers, of which 381 participants exhibited antibodies against the SARS-CoV-2 spike antigen at study inclusion, reveal that these antibodies remain detectable in most participants, 96%, at least four months post infection, despite having had no or mild symptoms. Virus neutralization capacity was confirmed by microneutralization assay in 91% of study participants at least four months post infection. Contrary to antibodies targeting the spike protein, antibodies against the nucleocapsid protein were only detected in 80% of previously anti-nucleocapsid IgG positive healthcare workers. Both anti-spike and anti-nucleocapsid IgG levels were significantly higher in previously hospitalized COVID-19 patients four months post infection than in healthcare workers four months post infection (p = 2*10−23 and 2*10−13 respectively). Although the magnitude of humoral response was associated with disease severity, our findings support a durable and functional humoral response after SARS-CoV-2 infection even after no or mild symptoms. We further demonstrate differences in antibody kinetics depending on the antigen, arguing against the use of the nucleocapsid protein as target antigen in population-based SARS-CoV-2 serological surveys.

A computational method for predicting nucleocapsid protein in retroviruses

Nucleocapsid protein (NC) in the group-specific antigen (gag) of retrovirus is essential in the interactions of most retroviral gag proteins with RNAs. Computational method to predict NCs would benefit subsequent structure analysis and functional study on them. However, no computational method to predict the exact locations of NCs in retroviruses has been proposed yet. The wide range of length variation of NCs also increases the difficulties. In this paper, a computational method to identify NCs in retroviruses is proposed. All available retrovirus sequences with NC annotations were collected from NCBI. Models based on random forest (RF) and weighted support vector machine (WSVM) were built to predict initiation and termination sites of NCs. Factor analysis scales of generalized amino acid information along with position weight matrix were utilized to generate the feature space. Homology based gene prediction methods were also compared and integrated to bring out better predicting performance. Candidate initiation and termination sites predicted were then combined and screened according to their intervals, decision values and alignment scores. All available gag sequences without NC annotations were scanned with the model to detect putative NCs. Geometric means of sensitivity and specificity generated from prediction of initiation and termination sites under fivefold cross-validation are 0.9900 and 0.9548 respectively. 90.91% of all the collected retrovirus sequences with NC annotations could be predicted totally correct by the model combining WSVM, RF and simple alignment. The composite model performs better than the simplex ones. 235 putative NCs in unannotated gags were detected by the model. Our prediction method performs well on NC recognition and could also be expanded to solve other gene prediction problems, especially those whose training samples have large length variations.

Antibody profiling reveals gender differences in response to SARS-COVID-2 infection

<abstract> <p>The recent emergence of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an ongoing global COVID-19 pandemic and public health crisis. Detailed study of human immune response to SARS-CoV-2 infection is the important topic for a successful treatment of this disease. Our study was aimed to characterize immune response on the level of antibody profiling in convalescent plasma of patients in Georgia. Antibodies against the following SARS-CoV-2 proteins were studied: nucleocapsid and various regions of spike (S) protein: S1, S2 and receptor binding domain (RBD). Convalescent plasma of patients 6–8 weeks after initial confirmation of SARS-CoV-2 infection were tested. Nearly 80% out of 162 patients studied showed presence of antibodies against nucleocapsid protein. The antibody response to three fragments of S protein was significantly less and varied in the range of 20–30%. Significantly more females as compared to males were producing antibodies against S1 fragment, whereas the difference between genders by the antibodies against nucleocapsid protein and RBD was statistically significant only by one-tailed Fisher exact test. There were no differences between the males and females by antibodies against S2 fragment. Thus, immune response against some viral antigens is stronger in females and we suggest that it could be one of the factors of less female fatality after SARS-CoV-2 infection.</p> </abstract>