Immunoinformatics prediction of potential immunodominant epitopes from human coronaviruses and association with autoimmunity

Cross-reactivity between different human coronaviruses (HCoVs) might contribute to COVID-19 outcomes. Here, we aimed to predict conserved peptides among different HCoVs that could elicit cross-reacting B cell and T cell responses. Three hundred fifty-one full-genome sequences of HCoVs, including SARS-CoV-2 (51), SARS-CoV-1 (50), MERS-CoV (50), and common cold species OC43 (50), NL63 (50), 229E (50), and HKU1 (50) were downloaded aligned using Geneious Prime 20.20. Identification of epitopes in the conserved regions of HCoVs was carried out using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. Further, we identified sequences that bind multiple common MHC and modeled the three-dimensional structures of the protein regions. The search yielded 73 linear and 35 discontinuous epitopes. A total of 16 B-cell and 19 T-cell epitopes were predicted through a comprehensive bioinformatic screening of conserved regions derived from HCoVs. The 16 potentially cross-reactive B-cell epitopes included 12 human proteins and four viral proteins among the linear epitopes. Likewise, we identified 19 potentially cross-reactive T-cell epitopes covering viral proteins. Interestingly, two conserved regions: LSFVSLAICFVIEQF (NSP2) and VVHSVNSLVSSMEVQSL (spike), contained several matches that were described epitopes for SARS-CoV. Most of the predicted B cells were buried within the SARS-CoV-2 protein regions’ functional domains, whereas T-cell stretched close to the functional domains. Additionally, most SARS-CoV-2 predicted peptides (80%) bound to different HLA types associated with autoimmune diseases. We identified a set of potential B cell and T cell epitopes derived from the HCoVs that could contribute to different diseases manifestation, including autoimmune disorders. Supplementary Information The online version contains supplementary material available at 10.1007/s00251-021-01250-5.


Introduction
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019 (COVID-19) pandemic, is a member of the family Coronaviridae (Lai et al. 2020). This single-stranded, positivesense beta coronavirus is closely related to other lethal members of the human coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) (Pal et al. 2020). The genome of SARS-CoV-2 shares 79% and 50% sequence similarity to SARS-CoV-1 and MERS, respectively (Kiyotani et al. 2020). SARS-CoV-2 consists of four main protein components: spike (S), membrane (M), envelope (E), and nucleocapsid (N) (Satarker and Nampoothiri 2020). In addition to the high sequence similarity between SARS-CoV-1 and SARS-CoV-2, both follow the same viral entry mechanism by binding to the host's angiotensin-converting enzyme 2 (ACE2) receptors using S protein specifically (Davidson et al. 2020). Nevertheless, the antigenic epitopes of SARS-CoV-2 are poorly understood, with little information on which parts of SARS-CoV-2 trigger immune response. Shilu Mathew, Aisha D. Fakhroo, and Maria Smatti share first authorship.
Given the high homology between SARS-CoV-2 and other coronaviruses, there is a high possibility of conserved antigenic epitopes (Grifoni et al. 2020a). Therefore, previous exposure to MERS, SARS, or seasonal human coronaviruses (i.e., 229E, NL63, OC43, and HKU1) may contribute to modulating immunity against SARS-CoV-2 infection, particularly B and T cell immune responses.
Notably, the antigenic burden from viral epitopes that do not induce protection could lead to adverse events, including autoimmune reactions or viral-induced enhanced diseases illness (Smatti et al. 2018;Yarmarkovich et al. 2020).
Since the start of the COVID-19 pandemic, multiple reports highlighted the possible relationship between SARS-CoV-2 infection and the autoimmunity. Several cases of autoimmunity have been reported following COVID-19, such as Kawasaki-like multisystem inflammatory syndrome in children (MIS-C), Guillain-Barré syndrome (GBS), autoimmune hemolytic anemia (AIHA), and systemic lupus erythematosus Liu et al. 2021). Additionally, evidence suggested that some autoimmunity medications could have therapeutic effect in patients with severe COVID-19 (Esmaeilzadeh and Elahi 2021). It has been speculated that SARS-CoV-2 can disturb self-tolerance and induce autoimmunity mainly through the production of cross-reactive antibodies. Specifically, viral antigens that are structurally similar to selfantigens could activate B and T cells and lead to a crossreactive response against both self-and non-self-antigens, a mechanism known as "molecular mimicry" (Kim et al. 2006). These antigens are known as mimotopes: pathogen's epitopes that mimic self-antigens, such as self B-cell epitopes and self T-cell epitopes (MHC) . As a consequence of exposing the immune system to these antigens, the immune tolerance can be disrupted, leading to the production of crossreactive autoantibodies.
Despite the currently available data, there is a critical need to understand the molecular basis of autoimmunity in SARS-CoV-2 infection, as well as the role of cross-reactive B and T cell responses in shaping SARS-CoV-2 outcomes. Here, we identified candidate conserved immune epitopes across the whole genome of different human coronaviruses through an immunoinformatics-based approach and propose the potential cross-reactive epitopes that elicit or attribute different diseases manifestation, especially autoimmune disorders.

Prediction of potential B cell epitopes
Identification of epitopes in the conserved regions of human coronaviruses, including SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43, NL63, 229E, and HKU1, were carried out in the Immune-Epitope-Database And Analysis-Resource (IEDB) (Peters et al. 2005). The search criteria were as follows: "linear peptide; blast option: 90%; host: homo sapiens; any MHC restriction; positive assays only; all assays; any disease" . Kolaskar and Tongaonkar antigenicity scale was used to predict the antigenicity score, and Bepipred linear epitope prediction 2.0 was used to predict antibody epitope prediction (Jepersen et al. 2017).

Prediction of potential T cell epitopes
To identify T cell epitopes in the conserved regions of human coronaviruses, including SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43, NL63, 229E, and HKU1, the Immune-Epitope-Database And Analysis-Resource (IEDB) was used (Peters et al. 2005). To identify the smallest peptide (MHC peptide) in an antigen that has the potential to generate immunogenicity and activate T-cell response, we used TepiTool (Paul et al. 2016), available at IEDB (Fleri et al. 2017). For predicting MHC class-I epitopes, the parameter for selecting predicted peptides was set as equal or less than 500 median inhibitory concentrations (IC50), while for MHC class-II epitope prediction, the same parameter was set to equal or less than 1000 nM IC50 (Paul et al. 2013;Wang et al. 2008). The prediction method used for this analysis was IEDB-recommended, Consensus, and NetMH-Cpan (version 2.8). Following the prediction of HLA alleles, we explored the clinical significance of these HLA alleles in previously reported studies as well as in the Genome-Wide Association Studies (GWAS) catalog. Additionally, the overall allelic frequencies of the identified HLA types were extracted from The Allele Frequency Net Database (2020).

Structural analysis of predicted epitopes
SWISS-MODEL server was used to generate a homology model of the protein structure to visualize the conserved epitopes in ORF1ab, spike, and ORF3a using NCBI Reference Sequence: YP_009725298.1 (Waterhouse et al. 2018). The surface confrontations of the potential functional domains and the positions of forecast predicted epitopes in their bound conformations were built using Pymol (DeLano 2002).

Identification of conserved protein sequences across different coronaviruses
We evaluated the presence of protein fragments that are conserved across a wide range of members of the coronavirus family; the full-length consensus open reading frame from SARS-CoV-2 was aligned with other coronavirus sequences. The protein sequences of SARS-CoV-2 shared 108 conserved regions (ranging from 8 to 23 amino acids) that were also found in other coronaviruses, including SARS-CoV-1, MERS-CoV, OC43, NL63, 229E, and HKU1 in the sequence alignment. The search yielded 73 linear epitopes and 35 discontinuous epitopes. Among the linear epitopes, we observed amino acid sequence identity result confirmed a high similarity in ORF1ab which encodes 16 non-structural proteins (NSPs; 68.4%, 50/73), followed by the spike (29%, 21/73) and ORF3a that encodes ORF3 accessory protein (2.6%, 2/73) (Supplementary Tables 1 and 2). Of note, according to our search criteria, we noticed discontinuous epitopes only in the ORF1ab region.

Prediction of potential B-cell epitopes in the conserved regions
We next identified potential B cell epitopes in these conserved regions. We searched the IEDB for described B-cell epitopes similar (> 90% sequence identity) to the conserved peptides present in the SARS-CoV-2 consensus sequence. The IEDB analysis search yielded a total of 16 B-cell epitopes, out of which four epitopes were identified for other viruses, and the rest were similar to human epitopes ( Table 1). The similar epitopes for other viruses, such as epitope LHRVEER-CLLLP (NSP1), was found to be derived for enteroviruses (VP1), TLSLNELLISKLNDNVKRQLYG (spike region) was found to be derived for influenza virus H1N1 (HA), and epitope HNLLSLCRLQLLCFL (spike region) was found to be derived for human herpesvirus 4 (BMRF1). In addition, the majority of epitopes (9ofthe16) were similar to human ones. Similarity to human proteins included serine/threonineprotein kinase PLK4, exosome component 10, and proteinglutamine gamma-glutamyltransferase 2 (Table 1) (Serwas et al. 2019;Baharlooi et al. 2020). We also detected one conserved epitope ESATVLLII located at SARS-CoV-2 exonuclease, similar for parasite Plasmodium falciparum (ORF). Concerning antigenicity among the B cell epitopes, epitope HNLLSLCRLQLLCFL showed the highest score of 1.170 compared to other B-cell epitopes. The potential identified B-cell epitopes are represented in Figs. 1 and 2.

Prediction of potential T-cell epitopes in SARS-CoV-2
Similarly, we utilized the IEDB server to search for potential T cell epitopes in these conserved regions. We looked for peptides with 90% or more similarity to the conserved peptides present in CoVs. The search yielded a total of 19 T cell epitopes that were found to be similar from other viruses. Interestingly, two conserved epitopes: LSFVSLAICFVIEQF (NSP2) and VVHSVNSLVSSMEVQSL (spike region), contained several matches to epitopes of SARS-CoV (Table 2). Other similar epitopes were found to be similar to the following organisms (> 90% sequence identity); human coronavirus: 9, West Nile virus (genome polyprotein): 2, alpha papillomavirus 9 (regulatory protein E2): 2, influenza virus H1N1 (HA): 2, and human beta herpesvirus 6B (capsid protein): 6. Of note, the T-cell epitopes identified were not restricted only to the spike protein; instead, it was distributed across the whole SARS-CoV-2 proteins, including NSP2, RdRp, and ORF3a. Concerning immunogenicity among the T-cell epitopes, epitope NCPRAIAARQIEPA showed the highest score of 0.43328 compared to other T-cell epitopes ( Table 2). The potential T-cell epitopes identified are represented in Figs. 1 and 2.

Structural analysis of B cell and T cell epitopes SARS-CoV-2 protein
Structural analysis of the predicted B cell and T cell epitopes was mapped on SARS-CoV-2 protein structure highlighted with functional domains (Figs. 1 and 2). Based on the NSP1 structure, both B/T cells epitopes (n = 2) were buried within the functional domain (3-809 AA). Likewise, the conserved B cell epitope identified at exonuclease and ORF3a mapped within the respective functional domains located at 18,351-18,650 AA and 25,555 to 25,751 AA ( Fig. 2). Besides, those epitopes lying close to the functional domains were mostly T cell epitopes. More specifically, the T cell epitope in the NSP2 region, RdRp, and spike stretched close to the functional domains located at 1253-1310 AA, 15,675-15,879 AA, and 23,326 to 23,559 AA, respectively (Figs. 1 and 2). Only one B cell epitope in the helicase region mapped far from the functional domain located at 12,953 to 13,765.

Binding of SARS-CoV-2 conserved peptides to HLA alleles
Human leukocyte antigen (HLA) plays a major role in initiating cellular immune responses. Therefore, it is important to investigate the peptides that can bind to HLA alleles and elicit a strong immune response. The 12 conserved epitopes, which were identified as B or T cells epitopes were further analyzed for the binding ability to HLA using IEDB EpiTool. Considering that all sequences were less than 15 AA in length, and HLA II prediction requires peptides of at least 15 AA, the analysis was only performed for HLA class I types. Moreover, we investigated the diseases associated with each predicted HLA type. As shown in Table 3, the resultant peptides were predicted to bind to different HLA types (A, B, and C), with the most enriched binding observed with HLA-A. Notably, the majority of SARS-CoV-2 predicted peptides (80%) bind to different HLA types associated with autoimmune diseases and/or hyper-inflammatory conditions, such as multiple sclerosis (MS), ankylosing spondylitis, polyglandular autoimmune syndrome (PGA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D, autoimmune vitiligo, etc. The binding affinity (IC50) ranges from 5.63 to 498.29 (i.e., high to low affinity) (Table 3). In addition to autoimmune conditions, 70% of SARS-CoV-2 predicted peptides bind to HLA -types associated with other viral infections, including HIV-1 and chickenpox susceptibility, and 40% bind to HLA alleles associated with drug-induced illnesses (Table 3). In parallel, IEDB EpiTool analysis was also performed to predict the binding of all identified 73 linear epitopes to HLA class I molecules (Supplementary Table 3). According to Fig. 3, 68.49% of conserved SARS-CoV-2 peptides (50/73) were shown to bind to HLA-A, B, and C alleles.

Discussion
In spite of the high sequence homology between different coronaviruses, little is known about the conserved epitopes and their impact on modulating the host response to infection. Additionally, it is important to understand the role of conserved T and B cell epitopes between SARS-CoV-2 and other coronaviruses in disease protection or pathogenesis. Several recent studies evidenced the relationship between SARS-CoV-2 and autoimmune conditions; yet, the molecular mechanisms are largely unknown. Through bioinformatics screening of a total of 351 full-length human coronaviruses genome sequences, here, we report a number of cross-reactive B-and T-cell epitopes that could modulate the immune response and mainly lead to autoimmunity. Our analysis resulted in the identification of 108 conserved regions (73linear, 35discontinuous) among different coronaviruses, of which, 16 were B-cell and 19 T-cell immunogenic epitopes, that could be implicated in cross-reactivity and/or autoimmunity. Interestingly, these epitopes were not limited to the spike protein only, as they were identified in both structural and non-structural SARS-CoV-2 proteins. Among the predicted B-cell epitopes, four were potentially cross-reactive with different viruses, such as human herpesvirus 4 and H1N1. This suggests that preexisting immunity to other viruses may contribute to the immune response against SARS-CoV-2, ranging from providing protection to enhanced disease illness. In addition to viruses' crossreactivity, some of the B-cell epitopes are homologous to that of human proteins (blast > 90%), including serine/ threonine-protein kinase PLK4 (QETSNSSLFC), exosome component 10 (VYLEDKFDLL), and protein-glutamine gamma-glutamyltransferase 2 (FLWIKIRVGQSAEFI). This could partially explain the autoimmunity disorders seen in COVID-19 patients as a result of molecular mimicry. Due to the similarity between viral and host antigens, the immune response fails to recognize self from nonself-antigens (Rodríguez et al. 2020). A recent study has identified shared antigenic epitopes between human molecular chaperons and SARS-CoV-2, with a potential role of inducing autoimmunity against endothelial cells using molecular mimicry (Marino et al. 2020). Similarly, it has been proposed that brainstem-related respiratory failure in COVID-19 patients may take place as a result of molecular mimicry between SARS-CoV-2 and neuronal proteins (Lucchese and Flöel 2020). In fact, sequence homology has been identified between three SARS-CoV-2 amino acid sequences (GSQASS, LNEVAK, and SAAEAS) and three proteins, specifically DAB1, AIFM, and SURF1 that are part of the respiratory pacemaker in the brainstem (preBötC). Therefore, immunological responses against DAB1, AIFM, and SURF1 may potentially contribute to neurological-related respiratory complications observed in COVID-19 (Lucchese and Flöel 2020). Several other studies have also reported potential cross-reactivity between SARS-CoV-2 and the human proteome, suggesting the possibility that SARS-CoV-2 could induce cross-reactivity with host autoantigens and lead to various clinical manifestations and autoimmune diseases Kanduc 2020).
In terms of T-cell immunity, 9 out of 19 conserved SARS-CoV T cell epitopes were matching T cell epitopes in repose to other viruses, indicating that these regions are immunogenic in humans, supporting that some degree of Fig. 1 Schematic of modeled SARS-CoV-2 ORF1ab CoV-2 protein regions highlighted B cell (cyan) and T cell epitopes (pink) represented as surface structure (gray). Potential functional domains are mapped as green color. Pymol was utilized to visualize the positions of forecast epitopes on the 3D structure. A NSP1 region representing predicted B-cell epitopes (cyan) located at position 315 and 801. B NSP2 region representing predicted T cell epitope (pink) at position 1367. C Helicase region representing predicted B cell epitope (cyan) at position 16,793. D Exonuclease region denotes predicted B-cell epitope (cyan) at position 18,459. E RDRP region denotes T cell epitopes (pink) at position 15,999. The table to the right denotes list of predicted B cell and T cell epitopes and their start position. Residues underlined and colored in red denotes specific residues that are predicted to elicit antibody response by using Bepipred linear epitope prediction 2.0 cross-reactivity among coronavirus can be expected (Grifoni et al. 2020b;Braun et al. 2020). Pre-COVID-19 pandemic data analysis indicated that most individuals have hCoVreactive antibodies, upon which 20% showed antibodies that were cross-reactive with SARS-CoV-2 spike and nucleocapsid proteins (2020). In spite of the non-neutralizing and unprotective nature of these antibodies, they were boosted upon SARS-CoV-2 infection (Anderson et al. 2020). Thereby, this reinforces the possibility of cross-reactivity between different coronaviruses, particularly in terms of memory B-cell immunity and antibody production.
The IEDB analysis revealed SARS-CoV-2 68.49% of conserved SARS-CoV-2 peptides (50/73) were shown to bind to HLA class I molecules (HLA A, B, and C) with variable affinity, possibly inducing CD8 + and CD4 + T-cell responses (Anderson et al. 2020). The majority of HLA types were associated with autoimmune diseases and hyperinflammatory conditions, such as MS, ankylosing spondylitis, PGA, SLE, T1D, and autoimmune vitiligo. This, again, highlights the potential association between COVID-19 and autoimmunity. The development of autoimmune condition following SARS-CoV-2 infection has been reported in multiple studies. For instance, cold agglutinin syndrome (CAS) and autoimmune hemolytic anemia have been linked to COVID-19 (Jensen et al. 2020;Patil et al. 2020). Moreover, a case of systemic lupus erythematosus has been reported to Fig. 2 Schematic of modeled SARS-CoV-2 spike and ORF3 proteins (gray) highlighted B cell (cyan) and T cell epitopes (pink) represented as surface structure (gray). Potential receptor-binding region (RBD) and cleavage site are mapped as green color. Pymol was utilized to visualize the positions of forecast epitopes on the 3D structure. A The 3D structure denotes site of both B cell and T cell in SARS-CoV-2 spike protein trimer at position 23,587 (orange color), site of B cell epitopes predicted in SARS-CoV-2 spike protein trimer at position 25,133 (cyan), and site of T cell epitopes predicted in SARS-CoV-2 spike protein trimer at position 23,555 (pink). The table below the spike protein denotes list of predicted B cell and T cell epitopes and their start position. Residues underlined and colored in red denotes specific residues that are predicted to elicit antibody response by using Bepipred linear epitope prediction 2.0. B The 3D structure denotes site of B cell epitope (cyan) predicted in ORF3aenvelope protein at position 25,749 and site of T cell epitopes (pink) predicted at position 25,562. Bepipred Linear Epitope Prediction 2.0 tool was used to predict antibody epitopes (red color) in the B cell epitopes. The table below the spike protein denotes list of predicted B cell and T cell epitopes and their start position. Residues underlined and colored in red denotes specific residues that are predicted to elicit antibody response by using Bepipred linear epitope prediction 2.0 Table 3 Predicted SARS-CoV-2 conserved peptides binding to HLA-A, HLA-B, and HLA-C gene alleles using IEDB EpiTool are shown along with the diseases associated with each HLA type    be induced by SARS-CoV-2 infection (Shayestehpour and Zamani 2020). Guillain-Barré syndrome (GBS), another autoimmune disorder, has been also associated with SARS-CoV-2 infection (Finsterer et al. 2021). Most importantly, this area of research is still growing and more COVID-19 associated autoimmune diseases might be identified in future studies. Previous studies have linked autoimmune conditions to other viruses. An interaction has been observed between anti-EBV (Epstein-Barr Virus) antibodies and HLA-DRB1 * 15 increasing the risk for MS (Sundqvist et al. 2012). Additionally, a strong connection has been established between HLA-DRB1*1301 (a marker for pediatric autoimmune hepatitis) and protracted forms of HAV (hepatitis A virus) infection (Fainboim et al. 2001). In terms of SARS-CoV-2, the immunogenic symptoms observed in COVID-19 patients are relatively similar to those observed in autoimmune conditions (Rodríguez et al. 2020). One of these main immunological impacts is the cytokine storm; which was shown to be the leading cause of death in COVID-19 through inducing acute respiratory distress syndrome (ARDS) (Rodríguez et al. 2020). Recent studies suggested a correlation between COVID-19 and an autoimmune conditions in kids, known as Kawasaki disease (Galeotti and Bayry 2020). A proposed mechanism (hypothesis) involves the role of TNF-α (Amirfakhryan 2020). Since children who are susceptible to KD exhibit genetically downregulated ACE2 receptor, SARS-CoV-2 infection will further downregulate ACE2 expression by TNF-α, leading to Kawasakilike disease (Amirfakhryan 2020). Interestingly, 70% of SARS-CoV-2 predicted peptides bind to HLA types associated with other viral infections (e.g., HIV-1 and chickenpox susceptibility). This raises the questions of whether people previously exposed to either virus could have CD8 + and CD4 + T-cell responses against SARS-CoV-2. In addition, HLA polymorphism has been associated with several infectious diseases including COVID-19. An in silico study identified that HLA-B*46:01 variant accounts for susceptibility to COVID-19, whereas HLA-B*15:03 could provide cross-protective T-cell-based immunity against COVID-19 (Nguyen et al. 2020). In another study, HLA-A*01:01 variant was associated with high-risk groups of COVID-19, Fig. 3 Heat map plot sowing the binding of 50 conserved SARS-CoV-2 epitopes to HLA different variants. IEDB EpiTool analysis was performed for all 73 identified linear epitopes to predict binding to HLA class I molecules, out of which, 50 epitopes bind to HLA-A, B, and C gene variants. Each row indicates an epitope's sequence, and each column indicates a different HLA variant. The color gradient for each cell of the heatmap plot represents the affinity, which inversely correlates with the IC50 value while HLA-A*02:01 and HLA-A*03:01 were mainly found in the low-risk groups (Shkurnikov et al. 2020). According to our analysis, some of SARS-CoV-2 conserved epitopes were likely to bind to HLA-A*02:01 and HLA-A*03:01 molecules (i.e., protective variants), which may result in a potential protective role against COVID-19. However, none of the identified SARS-CoV-2 epitopes was shown to bind to HLA risk variants. Although our predictions were based on IEDB's HLA reference set that cover almost all populations, one of the limitations is that South American population is underestimated in the IEDB's database. Requena et al. have presented an updated datasets reporting HLA frequencies of South American populations and reported the identification of several novel candidate epitopes on SARS-CoV-2 proteins for South America specifically (Requena et al. 2020).
According to the structural analysis, the majority of the conserved T and B cell epitopes lay within the functional domain of SARS-CoV-2 proteins. In particular, B and T cell epitopes are localized in close proximity to the receptorbinding domain (RBD) of the spike protein. Since the B-cell epitope is right beneath the functional domain embedded inside the spike, this may trigger the production of protective antibodies that may potentially hinder or induce an allosteric effect on ACE2 binding (Galeotti and Bayry 2020). Similarly, B-cell epitopes were localized within the functional domains of NSP1, exonuclease, and ORF3, potentially inducing a similar antibody effect interfering with the viral proteins' function. On the other hand, the T-cell epitopes were found within the functional domain of NSP1, NSP2, RdRp, and spike (i.e., common in both structural and non-structural SARS-CoV-2 proteins). During response, viral infection, the CD4 + , and CD8 + T cell responses are induced against both structural and non-structural viral proteins (Nguyen et al. 2020). Also, the fact that these epitopes are conserved among different viruses suggests that T and B cell responses provide a broad protection. Although the limited data on the relationship between human coronavirus epitope abundance and immune response, previous reports on vaccinia virus data showed that early peptide antigens could generate CD8 + T-cell responses in contrast to antibody and CD4 + T-cell responses which targets later mRNA expression (Nguyen et al. 2020;Sette et al. 2009). In addition, the induction of memory T and B cells is plausible due to previous coronavirus infection leading to long-term protection against SARS-CoV-2 (Shkurnikov et al. 2020). Specifically, T follicular helper cells (TFH) may induce the production of neutralizing antibodies from memory B cells that can rapidly recognize and block the virus (Shkurnikov et al. 2020). However, this data emphasizes the importance of conducting further studies that experimentally look into the immunogenic effect of these identified conserved epitopes.

Conclusion
In summary, this study presents the identification of highly conserved epitopes among seasonal and zoonotic coronavirus, with their potential implication on development of autoimmune conditions. The description of these conserved target peptides and of the matching cross-reactive epitopes will aid in understanding SARS-CoV-2 pathogenesis and complications. However, these initial results are based on immunoinformatic prediction, and hence, it will be particularly encouraging to measure functional antibodies and immunogenic effect in multiple animal models.