Keywords
Coronavirus, COVID-19, SARS-CoV-2, OC43, HKU1, 229E, NL63, MHC class I, Immunology, Vaccination
This article is included in the Emerging Diseases and Outbreaks gateway.
This article is included in the Coronavirus collection.
Coronavirus, COVID-19, SARS-CoV-2, OC43, HKU1, 229E, NL63, MHC class I, Immunology, Vaccination
From the end of 2019, the world experienced the coronavirus disease 2019 (COVID-19) pandemic caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; aka 2019 novel coronavirus or 2019-nCoV). SARS-CoV-2 shares ~80% nucleotide identity with SARS-CoV-1 (aka SARS-CoV), the causative agent of the SARS epidemy from 2002, and is even more similar to some coronaviruses in bats (Andersen et al., 2020; Ceraolo & Giorgi, 2020; Wu et al., 2020; Zhou et al., 2020). Coronaviruses are membrane-enveloped positive-strand RNA viruses with, for an RNA virus, a large genome of ~30 kb. That genome encodes several structural components of the virion including the nucleocapsid protein N and the membrane proteins S (spike), M, and E, plus also a number of nonstructural proteins involved in RNA replication and other—partly unknown—functions (Weiss & Navas-Martin, 2005). The coronaviruses infecting humans belong to the serological/phylogenetic clades group I (alphacoronaviruses) and group II (betacoronaviruses); group I includes HCoV-229E (human coronavirus 229E) and HCoV-NL63, while group II includes SARS-CoV-1, SARS-CoV-2, Middle East respiratory syndrome coronavirus (MERS-CoV), HCoV-OC43, and HCoV-HKU1. The viruses SARS-CoV-1 and MERS-CoV, on average, cause the most severe symptoms, and their outbreaks were successfully monitored and halted. At the other end of the spectrum, the viruses HCoV-229E, HCoV-NL-63, HCoV-OC43, and HCoV-HKU1 tend to cause only mild symptoms and are very common.
The Centers for Disease Control and Prevention (CDC; https://www.cdc.gov/coronavirus/general-information.html) states: “Common human coronaviruses, including types 229E, NL63, OC43, and HKU1, usually cause mild to moderate upper-respiratory tract illnesses, like the common cold. Most people get infected with one or more of these viruses at some point in their lives.” The same agency lists the common symptoms caused by these viruses as runny nose, sore throat, headache, fever, cough, and general feeling of being unwell, but also explains that they occasionally cause lower-respiratory tract illnesses, such as pneumonia or bronchitis. The viruses 229E and OC43 have been known since the 1960s (reviewed in Kahn & McIntosh, 2005), but NL63 (van der Hoek et al., 2004) and HKU1 (Woo et al., 2005) were only (conclusively) identified following the rise in interest in coronaviruses in the wake of the SARS epidemy. These common coronaviruses are believed to be the second most common cause of the common cold (Mäkelä et al., 1998). In the U.S.A., a 3-year RT-PCR surveillance of respiratory samples of patients revealed that the four viruses 229E, NL63, OC43, and HKU1 were present at levels varying by season and region, with all individual viruses peaking at >3% prevalence in each investigated region (Midwest, Northeast, South, West); co-infection with other coronaviruses was found in only ~2% of infected cases, but co-infection with another respiratory virus was found in a substantial ~30% of infected cases (Killerby et al., 2018). This pattern was reminiscent of findings in the United Kingdom (Gaunt et al., 2010) and Japan (Matoba et al., 2015). Serological investigations in countries as diverse as the U.S.A. (Bradburne & Somerset, 1972; Dijkman et al., 2012), China (Zhou et al., 2013), and Qatar (Al Kahlout et al., 2019), found that most healthy blood donors had antibodies against coronaviruses, supporting that these viruses are widespread indeed.
Since immune memory protection can be induced by related pathogens, as exemplified by the eradication of human smallpox virus (Variola) by immunization with a related “cowpox” virus (Vaccinia) (Plotkin & Plotkin, 2018), it is interesting to consider whether common human coronavirus infections may have induced some level of protection against SARS-CoV-2.
The two major arms of immune memory concern antibody secretion by B cells and killing of infected cells by CD8+ T cells. For a coronavirus infection in mouse, both immune responses were needed to efficiently control the virus (reviewed by Weiss & Navas-Martin, 2005). Based on theoretical considerations alone, it is difficult to predict effective B cell memory across different virus species (Qiu et al., 2020), and very recent experiments concluded that sera from people that likely had been infected with the common human coronaviruses 229E, NL63, OC43, and/or HKU1, possessed no or negligible cross-reactivity with SARS-CoV-2 virus S protein (Amanat et al., 2020) and thus probably possess no neutralizing antibodies. However, for inducing CD8+ T cell memory, the core requirement is merely that an identical peptide is presented by major histocompatibility complex (MHC) class I (MHC-I) molecules. MHC-I molecules present peptide fragments from intracellular proteins, thus also from viral proteins, at the cell surface for screening by CD8+ cytotoxic T cells (Neefjes et al., 2011). CD8+ T cells recognize the combination of MHC-I molecule with peptide by T cell receptors (TCR) that are unique per T cell clone, and if stimulated these clones can proliferate, kill the presenting (virus-infected) cell, and produce memory cells. MHC-I molecules are polymorphic in that they are represented by many diverse allelic forms that differ between human populations and individuals (Robinson et al., 2020), and mostly bind 9 amino acids (aa) length in their binding groove which is closed at either end (Bjorkman et al., 1987; Rammensee et al., 1995; Schellens et al., 2015).
In the present study, we analyzed whether there are linear 9 aa epitopes that are identical between proteins encoded by SARS-CoV-2 and one or more of the common human coronaviruses. We found many of such epitopes indeed, and, by using prediction software, found that some are expected to bind well to certain MHC-I alleles. We therefore expect that common human coronaviruses can induce some level of CD8+ T cell-mediated immune memory recognizing SARS-CoV-2, and consider the possibility of enhancing that immune memory by vaccination.
Proteins encoded by a reported genomic sequence for SARS-CoV-2 (GenBank MN908947; Wu et al., 2020) were compared with those for HCoV-OC43 (NC_005147; Vijgen et al., 2005), HCoV-HKU1 (NC_006577; Woo et al., 2005), HCoV-229E (NC_002645; Thiel et al., 2001), and HCoV-NL63 (NC_005831; van der Hoek et al., 2004) by performing BLAST homology searches at the NCBI database (https://blast.ncbi.nlm.nih.gov/Blast.cgi) and by making multiple sequence alignments using CLUSTALW software (https://www.genome.jp/tools-bin/clustalw); continuous stretches of 9 aa acids identical between SARS-CoV-2 and one of the other viruses were identified manually. All these shared 9 aa epitopes were screened by ANN 4.0 software at IEDB Analysis Resource (http://tools.immuneepitope.org/mhci/) for prediction of their affinity to a set of representative human MHC-I alleles.
Table 1 lists the 9 aa epitopes that are identical between proteins encoded by SARS-CoV-2 and one or more of the common human coronaviruses. Many identical >9 aa stretches were found with ORF1ab encoded polyprotein, one such identical stretch (of 12 aa) was found with the N protein of the other two type II coronaviruses HCoV-OC43 and HCoV-HKU1, and no such stretches were found when comparing with any of the other gene products; ORF1ab-derived mature proteins with such stretches, expected from cleavage of the polyprotein precursor (Wu et al., 2020), were the transmembrane protein nonstructural protein 4 (NSP4), 3C-like cysteine protease NSP5, RNA binding protein NSP9, RNA dependent RNA polymerase NSP12, helicase NSP13, 3’-to-5’ exonuclease NSP14, nidoviral endoribonuclease specific for U NSP15, and S-adenosylmethionine-dependent ribose 2’-O-methyltransferase NSP16 (Table 1). Sequence alignment figures of the ORF1ab and N proteins are shown in Extended data (Dijkstra, 2020) with highlighting of the interesting epitopes. It is of note that the S protein, which is the prime candidate for inducing neutralizing antibodies (Cohen, 2020), is not suitable for inducing an MHC-I-restricted immune memory across the investigated viral species as between S protein of SARS-CoV-2 and S proteins of the common human coronaviruses there are no 9 aa or even 8 aa matches (not shown).
Table 1 shows that there are >200 linear epitopes of 9 aa that are identical between SARS-CoV-2 and at least one of the common human coronaviruses, most of them with OC43 and HKU1 which, like SARS-CoV-2, belong to the group II coronaviruses. In a simplified model, if people would have been exposed to many of these epitopes through common HCoV infections, this kind of equals immunization by a small intracellular protein under natural viral infection conditions. Whereas live virus is commonly considered the gold standard in regard to inducing strong immunity, unless the virus has some tricks up its sleeve to manipulate the immune system, which for common human coronaviruses is not well investigated, a research grant proposal suggesting this as a vaccination strategy would probably fail. Reviewers of such proposal would righteously point out that the strategy would not induce neutralizing antibodies, which for combating some viral infections can be very important, and that for inducing MHC-I-restricted cell-mediated cytotoxicity memory, ideally, a much larger protein or more proteins should be taken. Those reviewers would conclude that for such small intracellular protein to induce strong immune memory it would need too much luck in regard to immunogenicity and it would be too dependent on the MHC alleles of the immunized person as different alleles bind different peptides. Nevertheless, those reviewers would probably also agree that in most persons thus vaccinated some (small) level of immune memory protection would be established, even with such small non-surface protein (e.g. Polakos et al., 2001). Regardless of that this obviously is not the ideal way to induce a population-wide strong protective immunity (see the spread of COVID-19), together with other factors such as health and the number of encountered viruses (the strength of the viral challenge), the induced immune memory could make a difference for whether a person gets sick; at the population scale, it so may somewhat reduce the virus reproduction number. Importantly, by stimulating this HCoV-derived MHC-I restricted immune memory by vaccination (see below), it could become a more significant helper in fighting COVID-19.
Based on combinations of experimental results and computer learning, various software has been created that with some degree of reliability can predict how efficiently peptides can bind to the grooves of various MHC-I alleles. In the present study we used the artificial neural network (ANN) function (Lundegaard et al., 2008) of the IEDB Analysis Resource (http://tools.immuneepitope.org/mhci/) (Dhanda et al., 2019) which may achieve >75% reliability for predicting binding (Lundegaard et al., 2008). The software owners state that IC50 values of <50 nM and <500 nM are considered high and intermediate affinity, respectively, and are found for most epitopes known to stimulate cytotoxic T cells. Therefore, Table 1 only indicates the predicted IC50 values if lower than 500 nM. Table 1 shows these expected affinities for twelve MHC-I alleles that are rather representative for sets of MHC-I alleles with similar binding properties (supertypes) and so represent a large part of the human MHC-I binding repertoire (Lund et al., 2004): HLA-A*0101 (supertype A1), HLA-A*0201 (A2), HLA-A*0301 (A3), HLA-A*2402 (A24), HLA-A*2601(A26), HLA-B*0702 (B7), HLA-B*0801 (B8), HLA-B*1501 (B62), HLA-B*2705 (B27), HLA-B*3901 (B39), HLA-B*4001 (B44), and HLA-B*5801 (B58). It is of note that Li et al. (2008) found that a SARS-CoV-1 15 aa peptide sequence (their “Replicase 4701-4715” peptide) encompassing the SARS-CoV-2/HCoV-shared ORF1ab4725 and ORF1ab4726 epitopes that are predicted to bind well to the MHC-I alleles HLA-A*0201 and HLA-B*3901 (see our Table 1) was associated with a CD8+ T cell response against SARS-CoV-1 in humans. However, Li et al. (2008) also found such CD8+ T cell response associated with a SARS-CoV-1 15 aa peptide (their “Nucleocapsid 106-120” peptide) encompassing the SARS-CoV-2/HCoV-shared N 106, N 107, N 108, an N 109 epitopes for which our analyses did not predict MHC-I binding (see our Table 1).
The MHC-I binding affinity is considered the most selective in determining which peptides are presented, but also steps in the peptide processing and loading pathways may play selective roles which are difficult to capture in prediction software (Nielsen et al., 2005). We argue that, if such steps would be selective for presentation, in most cases they would probably not differentiate between the 9 aa epitope in the SARS-CoV-2 context versus the respective HCoV context, since most of those epitopes are within stretches that also show many similarities in the neighboring residues (Extended data).
Not all stable complexes of MHC-I with non-self peptides elicit a strong immune response, but “immunogenicity” features are hard to predict with meaningful reliability by in silico analysis (Calis et al., 2013), and in the present study we refrain from such predictions. Table 1 should, foremost, be understood as evidence of principle and a list of promising peptides, whereas only future experiments can prove MHC-I-mediated immune memory involving these or other peptides.
In regard to SARS-CoV-2 recognition, the common human coronaviruses may also induce some MHC-II-mediated immune memory by CD4+ helper T cells (for shared epitope use by different coronaviruses see Zhao et al., 2016). CD4+ helper T cells can help stimulate cells involved in antibody or cell-mediated cytotoxic immune responses (Neefjes et al., 2011). However, for this topic we refrained from detailed (software) predictions because comparison of MHC-II epitopes across different viruses is harder than for MHC-I epitopes. Namely, although the core of MHC-II bound peptides is also only 9 aa, the surrounding amino acids are also part of the bound peptide that tends to be 12-25 aa (Brown et al., 1993; Rammensee et al., 1995; Stern & Wiley, 1994) and can affect how the peptide interacts with the receptors on the CD4+ helper T cells (Arnold et al., 2002).
Immune memory means that a secondary immune response, upon renewed encounter with the same pathogen, is faster and stronger than the primary immune response during the first encounter with the pathogen. This is based on expansion of specific B and T cell clones, which specifically recognize pathogen(-derived) epitopes, with some of those cells becoming memory cells (Paul, 2013). This principle also causes that for a booster vaccination/immunization the requirements for efficiently inducing an immune response are lower than for a first vaccination/immunization (e.g. Goding, 1996). Especially in elderly people, who have a decreased ability to mount adaptive immune responses against new antigens, vaccination that stimulates an immune memory response may be beneficial (Reber et al., 2012). As discussed above, people’s past infections with common coronaviruses probably did not induce a B cell memory for making antibodies that can neutralize SARS-CoV-2. However, as the current study shows by analysis of linear 9 aa epitopes, these common human coronaviruses are expected to induce CD8+ T cells that may potentially kill SARS-CoV-2-infected cells and so can help eradicate the virus. There are several possible ways to exploit this probable immune memory. For example, if using RNA for immunization (Cohen, 2020), it may be best to also include SARS-CoV-2 genes that encode MHC-I epitopes that match those of the common coronaviruses. Alternatively, delivery of these epitopes to the MHC-I presentation system may be tried by peptide or protein based vaccines (e.g. Kohyama et al., 2009; Slingluff, 2011; van Montfoort et al., 2014; Yadav et al., 2014), possibly in combination with some of the strategies that are currently being explored for non-specific stimulation of the immune system against COVID-19 (Kupferschmidt & Cohen, 2020). Protein (-coding) vaccines, for example encompassing a large part of the SARS-CoV-2 ORF1ab product, would have an advantage over peptide-vaccines by including multiple possible MHC-I and also MHC-II epitopes, and be less dependent on MHC-allele matching and the quality of software predictions. Naturally, as for any new vaccine strategy, it should be carefully assessed whether the benefits of the induced type of immunity outweigh the potential deleterious health effects caused by an increased inflammation response (Cohen, 2020; Weingart et al., 2004). Important questions are also whether the history of previous—especially recent—infections with common coronaviruses, or people’s MHC alleles, affect people’s resistance to SARS-CoV-2. Most definitely, if discussing possible strategies for vaccination against SARS-CoV-2, pre-existing MHC-I-based immunity derived from previous infections with common coronaviruses should be part of the consideration.
Although we were not aware of this at the time of writing, a recent preprint appeared with overlapping contents (Nguyen et al., 2020).
Severe acute respiratory syndrome coronavirus 2 isolate Wuhan-Hu-1, complete genome, Accession number MN908947: https://www.ncbi.nlm.nih.gov/nuccore/MN908947
Human coronavirus OC43, complete genome, Accession number NC_005147.1: https://www.ncbi.nlm.nih.gov/nuccore/NC_005147.1?report=genbank
Human coronavirus HKU1, complete genome, Accession number NC_006577: https://www.ncbi.nlm.nih.gov/nuccore/NC_006577
Human coronavirus 229E, complete genome, Accession number NC_002645: https://www.ncbi.nlm.nih.gov/nuccore/NC_002645
Human Coronavirus NL63, complete genome, Accession number NC_005831: https://www.ncbi.nlm.nih.gov/nuccore/NC_005831
Harvard Dataverse: Extended data. Sequence alignments of SARS-CoV-2 ORF1ab and N proteins with their counterparts in the common human coronaviruses, https://doi.org/10.7910/DVN/CNPUPA (Dijkstra, 2020).
Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
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Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Immunology
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Nguyen A, David JK, Maden SK, Wood MA, et al.: Human Leukocyte Antigen Susceptibility Map for Severe Acute Respiratory Syndrome Coronavirus 2.J Virol. 2020; 94 (13). PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: T cel viral immunology
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Also on behalf of Keiichiro Hashimoto,
Hans Dijkstra
Also on behalf of Keiichiro Hashimoto,
Hans Dijkstra