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Article

Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants

by
Rodrigo N. Rodrigues-da-Silva
1,*,
Fernando P. Conte
2,
Gustavo da Silva
1,
Ana L. Carneiro-Alencar
1,3,
Paula R. Gomes
4,
Sergio N. Kuriyama
5,
Antonio A. F. Neto
5 and
Josué C. Lima-Junior
3,*
1
Laboratory of Immunological Technology, Institute of Technology in Immunobiologicals, FIOCRUZ, Rio de Janeiro 21040-900, Brazil
2
Eukaryotic Pilot Laboratory, Institute of Technology in Immunobiologicals, FIOCRUZ, Rio de Janeiro 21040-900, Brazil
3
Laboratory of Immunoparasitology, Oswaldo Cruz Institute, FIOCRUZ, Rio de Janeiro 21040-900, Brazil
4
Getulio Vargas State Hospital, Rio de Janeiro 21070-061, Brazil
5
SENAI Innovation Institute for Green Chemistry, Rio de Janeiro 20271-030, Brazil
*
Authors to whom correspondence should be addressed.
Viruses 2023, 15(4), 923; https://doi.org/10.3390/v15040923
Submission received: 16 March 2023 / Revised: 31 March 2023 / Accepted: 1 April 2023 / Published: 6 April 2023
(This article belongs to the Special Issue SARS-CoV-2 Research in Brazil)
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Abstract

:
The Nucleocapsid (N) protein is highlighted as the main target for COVID-19 diagnosis by antigen detection due to its abundance in circulation early during infection. However, the effects of the described mutations in the N protein epitopes and the efficacy of antigen testing across SARS-CoV-2 variants remain controversial and poorly understood. Here, we used immunoinformatics to identify five epitopes in the SARS-CoV-2 N protein (N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390)) and validate their reactivity against samples from COVID-19 convalescent patients. All identified epitopes are fully conserved in the main SARS-CoV-2 variants and highly conserved with SARS-CoV. Moreover, the epitopes N(185–197) and N(277–287) are highly conserved with MERS-CoV, while the epitopes N(34–48), N(89–104), N(277–287), and N(378–390) are lowly conserved with common cold coronaviruses (229E, NL63, OC43, HKU1). These data are in accordance with the observed conservation of amino acids recognized by the antibodies 7R98, 7N0R, and 7CR5, which are conserved in the SARS-CoV-2 variants, SARS-CoV and MERS-CoV but lowly conserved in common cold coronaviruses. Therefore, we support the antigen tests as a scalable solution for the population-level diagnosis of SARS-CoV-2, but we highlight the need to verify the cross-reactivity of these tests against the common cold coronaviruses.

1. Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current worldwide outbreak, which less than four months after the first case in China [1] was declared by World Health Organization (WHO) as a pandemic [2]. Until now, the coronavirus disease 2019 (COVID-19) affected more than 663 million people and resulted in about 7 million deaths throughout the globe [3]. Currently, despite the use of vaccines to tackle the spread of the virus and minimize the associated morbidity and mortality [4], more than 80,000 cases and about 500 deaths still are daily reported around the world [3]. In this scenario, with about 37 million COVID-19 confirmed cases and more than 698,000 deaths, Brazil currently figures as the second country with more deaths and as the sixth in COVID-19 cases around the world [3].
SARS-CoV-2, like all RNA viruses, is susceptible to rapidly accumulating mutations in its genome [5] leading to changes that can allow the virus to evade the immune response or affect its ability to spread or cause disease, resulting in the rise of lineages that are classified by the Center of Diseases Control and Prevention (CDC) as “variants of interest (VOIs)”, or “variants of concern (VOCs)”, according to its characteristics that impact public health [6]. In this context, the Omicron B.1.1.529 variant (and multiple subvariants) is more transmissible than previous variants and now accounts for the majority of infections [7]. Nowadays, there are several SARS-CoV-2 variants (such as Alpha, Beta, Delta, Epsilon, Eta, Iota, Kappa, Mu, and Omicron); however, only in the Omicron variant are there more than 600 Pango lineages [8]. The steep increase in the number of SARS-CoV-2 variants is a critical obstacle to COVID-19 eradication and reinforces the need for constant and effective surveillance. In addition to SARS-CoV-2 and its variants, there are four common cold coronaviruses (229E, NL63, OC43, and HKU1) that circulate in the human population, usually causing mild respiratory symptoms similar to the common cold, such as cough, runny nose, and sore throat, that should be investigated about cross-reactivity in COVID-19 diagnosis [9,10,11,12].
Regarding diagnostic tests for the surveillance of COVID-19 cases, despite RT-PCR remaining the definitive method to diagnose infection, rapid antigen tests offer a valuable way to offer mass testing, since they can be performed without the need for specialized training or resources [13,14,15]. Among the SARS-CoV-2 structural proteins, while the Spike (S) protein is the immunodominant antigen and the main target for neutralizing antibodies and vaccines, the nucleocapsid (N) protein is highlighted as the main target for diagnostic by antigen detection due to its abundance in circulation early during infection [16,17]. Remarkably, most of the mutations described in SARS-CoV-2 variants are in the S protein, while the N protein seems to be highly conserved among variants and lineages [5,8,18,19]. However, the effects of the described mutations in the N protein epitopes and the efficacy of the antigen test remain unexplored. Considering this, this study aims to identify in silico and experimentally validate B-cell linear epitopes in the SARS-CoV-2 N protein and to evaluate their conservation across main SARS-CoV-2 variants and lineages.

2. Materials and Methods

2.1. Sequences Data and 3D Structures

To predict possible antigenic properties and select potential B-cell epitopes, the sequence of SARS-CoV-2 N protein (UniProt ID: P0DTC9) was used. The complete structure of the N protein was modeled using the Robetta server (http://new.robetta.org/, accessed on 10 September 2020) [20,21] based on the full-length amino acid sequence of the protein. This server is continually evaluated through CAMEO (Continuous Automated Model Evaluation) and generates five models analyzed by MolProbity (molprobity.biochem.duke.edu; accessed on 20 September 2020), which is a widely used system of model validation for protein structures. The best predictive model was selected and used in further analysis.

2.2. In Silico Prediction of Linear B-Cell Epitopes

We used a combination of web-based tools for B-cell epitope prediction: the Immune Epitope Database (IEDB) [22] and ABCpred [23] servers.
The IEDB (http://www.iedb.org/, accessed on 10 March 2020) is a freely available resource funded by NIAID. This server catalogs experimental data on antibody and T cell epitopes studied in humans, non-human primates, and other animal species in the context of infectious disease, allergy, autoimmunity and transplantation. The IEDB also hosts tools to assist in the prediction and analysis of epitopes. In this study, we used the ElliPro [24], Bepipred 1 [25] and EMINI Surface Accessibility [26] modules on the IEDB server with default settings to define B-cell linear epitopes exposed on the protein surface. We also used the ABCpred server [23] to refine our prediction using an artificial neural network (ann) method. All algorithms were accessed on 10 March 2020. Finally, predicted sequences with more than 9 mers and that were predicted by at least three of the algorithms were defined as linear B-cell epitopes.

2.3. Prediction of Antigenicity

To exclude non-antigenic sequences, the predicted linear B-cell epitopes were evaluated by the VaxiJen server (accessed in 12 March 2020), which is the first server for alignment-independent prediction of protective antigens. Its algorithm was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. Viral datasets were selected to derive models for the prediction of whole protein antigenicity, showing prediction accuracy from 70 to 89% [27,28,29]. Using the default threshold (0.5), all sequences predicted as non-antigenic were excluded from the study.

2.4. Peptide Synthesis

The best predicted epitopes were synthesized by fluorenylmethoxycarbonyl (F-moc) solid-phase chemistry [30,31] (GenOne Biotechnologies, Rio de Janeiro, Brazil). Analytical chromatography of the peptide demonstrated a purity of >95%, and mass spectrometric analysis also indicated estimated masses corresponding to the molecular masses of predicted peptides.

2.5. Patients and Samples

Samples from convalescent COVID-19 donors: Twenty individuals (12 women and 8 men), with ages ranging from 25 to 51 years (mean age: 35.8 ± 6.7 years) and confirmed SARS-CoV-2 infections who had been tested using real-time RT-PCR for viral infections or who had tested positive in the serological assay for COVID-19, were invited to enroll in the study. The serum samples were collected only in the convalescent phase. After recovering from COVID-19, convalescent donors were screened for symptoms and had to be symptom-free and approximately 3 weeks out from symptom onset at the time of the blood draw. Asymptomatic individuals, who had had contact with infected patients and were positively tested by RT-PCR but who had not presented symptoms for at least 21 days post-diagnosis, were also invited to enroll in the study. All donors voluntarily gave their informed consent before being enrolled in the study. Individuals did not receive compensation for their participation.
Healthy unexposed donors: A total of 20 samples (13 women and 7 men), from blood donors, in Brazilian blood centers between the years 2010 and 2018 with ages ranging from 20 to 56 years (36.7 ± 10.4 years) were randomly selected from the serum biobank for the development of diagnostic tests of the Institute of Technology in Immunobiologicals. These samples were considered to be from unexposed controls, given that SARS-CoV-2 emerged as a novel pathogen in late 2019, more than one year after the collection of any of these samples.
Peripheral blood samples were collected by venipuncture in EDTA tubes. After centrifugation (350× g, 10 min), the plasma was collected and stored at −30 °C.
Written informed consent was obtained from all COVID-19 donors, and the study was reviewed and approved by the Oswaldo Cruz Foundation Ethical Committee and the National Ethical Committee of Brazil (CEP-FIOCRUZ CAAE 31368620.0.0000.5262).

2.6. Antibody Assays

Plasma samples from donors were screened for the presence of naturally acquired antibodies against the S-ECD and S-RBD recombinant proteins and synthetic peptide, predicted as linear B-cell epitopes in SARS-CoV-2 N protein, by enzyme-linked immunosorbent assay (ELISA) essentially as previously described [32,33,34]. Briefly, MaxiSorp 96-well plates (Nunc, Rochester, NY, USA) were coated with PBS containing 5 µg/mL of recombinant protein or 20 µg/mL of a peptide. After overnight incubation at 4 °C, plates were washed with PBS and blocked with PBS-Tween containing 5% skim milk (PBS-Tween-M) for 1 h at 37 °C. Individual plasma samples diluted 1:100 on PBS-Tween-M were added in duplicate wells, and the plates were incubated at 37 °C for 2 h. After three washes with PBS-Tween, bound antibodies were detected with peroxidase-conjugated goat anti-human IgM (Sigma, St. Louis, MO, USA, cat number A 6907) or peroxidase-conjugated goat anti-human IgG (Southern, AL, cat number 2040-05) followed by the addition of 3,3′,5,5′-tetramethylbenzidine (Sigma St. Louis, MO, cat number N301). Optical density was measured at 450 nm using a SpectraMax microplate spectrophotometer (Molecular Devices, Sunnyvale, CA, USA). The results for total IgM and IgG were expressed as reactivity indexes (RIs), which were calculated by the ratio between the mean optical density of an individual’s tested sample and the mean optical density samples of 20 unexposed individuals plus 2.5 standard deviations. Subjects were classified as responders to an antigen if the RI of IgM or IgG were higher than 1.

2.7. Conservancy Analysis of the Selected Epitopes across SARS-CoV-2 Variants and Other Human Coronaviruses

To evaluate the conservancy of naturally antigenic epitopes among SARS-CoV-2 lineages and variants around the world, we listed the main mutations reported in GISAID-Lineage comparison (https://gisaid.org/lineage-comparison/, accessed on 20 February 2023) [35]. GISAID (Global Initiative on Sharing Avian Influenza Data) is a global science initiative that provides open access to the genomic data of influenza viruses [36] and the coronavirus responsible for the COVID-19 pandemic [37,38]. In this study, we looked for mutations described in the SARS-CoV-2 N-protein from previously Circulating Variants of Concern (Alpha, Beta, Gamma, and Delta) and from Current Variants of Concern (Omicron, Omicron—XBB.1.5.X, Omicron—CH.1.1.X, Omicron—BA.2.75.X, Omicron—BA.5, Omicron BQ.1.X, BQ1.1, and XBB.1), according to GISAID-Lineage comparison. Moreover, we also listed the mutations observed on the top 5 growing lineages in the world on 27 February 2023 (XBB.1.5, CH.1.1.1, BM.4.1, BM.4.1.1, XBB.1.9) and the top five most counted lineages in Brazil until February 2023 (B.1.617.2, P.1.1, BA.2, AY.43, AY.34.1), according to the NCBI-SARS-CoV-2 Variants Overview [8]. The main mutations observed in the SARS-CoV-2 N-protein and their frequencies across SARS-CoV-2 variants are listed in Supplementary Table S1.
Furthermore, the conservancy of SARS-CoV-2 N-protein B-cell epitopes was compared with the N-proteins from other human coronavirus: SARS-CoV (Uniprot ID: P59595), MERS-CoV (ID: K9N4V7), HCoV-229E (ID: P15130), HCoV-NL63 (ID: Q6Q1R8), HCoV-OC43 (ID: P33469), and HCoV-HKU1 (ID: Q5MQC6), using the IEDB server (https://www.iedb.org/conservancy/ accessed on 10 March 2021), with a sequence identity threshold at ‘>20′.

2.8. In Silico Conservancy Analysis of Amino Acid Residues Recognized by Antibodies

To investigate the cross-reactivity of described antibodies against the N protein across the SARS-CoV-2 variants and other coronaviruses, we selected the crystallographic structures of two nanobodies (PDB: 7R98 and 7N0R) and one antibody (PDB: 7CR5). Using the LigPlus, we listed the main SARS-CoV-2 N protein amino acids recognized by antibody/nanobody and compared the conservation of these amino acids between SARS-CoV-2 variants and other coronaviruses, which were aligned by MUSCLE using Meg Align Pro on DNASTAR Lasergene software.

2.9. Statistical Analysis

All statistical analysis was carried out using Prism 5.0 for Windows (GraphPad Software, Inc.). The one-sample Kolmogorov–Smirnoff test was used to determine whether a variable was normally distributed. The Wilcoxon matched pairs test or the paired T-test was used to compare the reactivity indexes of synthetic peptides and recombinant proteins. Differences in the frequency of responder of IgM and/or IgG responders to recombinant proteins were evaluated by chi-square test (χ2).

3. Results

3.1. Prediction of Serological Targets: Linear B-Cell Epitopes in N Protein

Aiming to identify potential serological targets in the SARS-CoV-2 N protein, sequences that were fully or partially predicted as B-cell linear epitopes by at least two of the used prediction algorithms (Bepipred 1.0, ABCpred, EMINI Surface Accessibility, and Ellipro) and also predicted as antigenic (Vaxijen score > 0.5) were screened as predicted epitopes on SARS-CoV-2 N protein. As summarized in Table 1, eleven sequences were predicted as linear B-cell epitopes; however, only five sequences (N(34–48); N(89–104); N(185–197); N(277–287) and N(378–390)) were also predicted as antigenic, presenting a Vaxijen score > 0.5 and were synthesized as peptides to be tested against the plasma of COVID-19 convalescent donors. Corroborating this result, the predicted epitopes were exposed in the N-protein 3D structure, as demonstrated in Figure 1.

3.2. Profile of Convalescent COVID-19 Donors

To experimentally validate B-cell linear epitopes on SARS-CoV-2 N proteins, plasma samples of 20 convalescent COVID-19 donors were obtained in the early months of the pandemic COVID-19 in Brazil: in 2020 July and June. All studied individuals were from the state of Rio de Janeiro in Brazil, where more than 130,000 cases and about 12,000 deaths were reported until early 2020 July. All convalescent donors had recovered from COVID-19 and were screened for symptoms before scheduling blood draws. They had to be symptom-free and approximately 3 weeks out from symptom onset at the time of the blood draw. Regarding the diagnosis of SARS-CoV-2 infection, 60% of donors were positive diagnosed only by RT-PCR to SARS-CoV-2, 30% were positive only by commercial serological assay and 10% of tested individuals were positive by both methods. About the clinical spectral, 80% of donors experienced mild illness and reported fatigue, fever, headache, and cough as the most common symptoms; 10% of donors presented asymptomatic cases, diagnosed by RT-PCR and serological methods, and persisted without symptoms for 25 days between the molecular diagnose and blood draw, while two donors presented complications (thrombosis and bacterial pneumonia); both already recovered at the moment of blood draw. The characteristics of the studied individuals are summarized in Table 2.

3.3. Evaluation of Natural Immunogenicity of Predicted B-Cell Epitopes

Predicted epitopes (N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390)) were synthesized as peptides and tested against samples of COVID-19 convalescent donors and healthy unexposed donors. First, as illustrated in Figure 2, we confirmed that the four predicted epitopes were naturally antigenic in SARS-CoV-2 infections since they were recognized by COVID-19 convalescent donors at different levels and not by healthy individuals unexposed to COVID-19. As illustrated in Figure 2, regarding the specific immune response against each epitope, we observed a statistically similar overall frequency of responders against epitopes that ranged from 40% to 75%. The frequencies of IgM responders were higher against the epitopes N(34–48) (50%) and N(277–287) (55%) than against the peptides N(89–104) (0%, p = 0.0004 and p = 0.0001, respectively), N(185–197) (10%) and N(378–390) (10%) (p = 0.0137 and p = 0.0057, respectively). In addition, we observed higher frequencies of IgG responders against the epitopes N(185–197) (40%) and N(277–287) (40%) than against the N(34–48) (5%, p = 0.0197). Comparing the frequencies of IgG and IgM responders against each epitope, we observed the prevalence of IgM responders against the epitope N(34–48) (p = 0.0033) and the prevalence of IgG responders against N(89–104) (p = 0.0471) (Figure 3a).
Regarding the magnitude of antibody response, we observed no statistical differences between the IgM levels against N(34–48) (mean: 1.33 ± 0.31) and N(277–287) (mean: 1.71 ± 0.61) (p = 0.0986), which are the two epitopes with higher frequencies of responders of IgM responders. In the same way, the IgG levels were similar against the most prevalent epitopes: N(89–104) (mean: 2.28 ± 1.26), N(185–197) (mean: 3.76 ± 3.16), N(277–287) (mean: 4.22 ± 4.10), and N(378–390) (mean: 3.83 ± 3.09) (Figure 3b). Remarkably, 80% of COVID-19 convalescent donors presented antibodies against at least one of the identified epitopes, 15% of studied individuals presented antibodies against only one epitope (10% against N(277–287), and 5% against N(34–48)), 15% were responsive against two epitopes (N(277–287) and (34–48)), 20% were reactive against three epitopes simultaneously (10% against N(185–197), N(277–287) and (378–390)); 5% against N(89–104), N(185–197), and N(277–287); and 5% against N(34–48), N(185–197), and N(277–287)), 15% were reactive against four epitopes (10% against N(34–48), N(185–197), N(277–287), and N(378–390); and 5% against N(34–48), N(185–197), N(277–287), and N(378–390)) and 15% of convalescent donors presented antibodies against all identified epitopes.

3.4. Analysis of Epitope Conservation across SARS-CoV-2 Variants and Lineages

As illustrated in Supplementary Table S1, there are 16 key mutations (D3L, Q9L, P13L, Del31/33, D63G, P80R, E136D, R203M, R203K, G204R, T205I, G215C, L230F, S235F, D377Y, S413R) reported across 12 variants of concern (Alpha, Beta, Gamma, Delta, Omicron, Omicron—XBB.1.5.X, Omicron—CH.1.1.X, Omicron—BA.2.75.X, Omicron—BA.5, Omicron—BQ.1.X, BQ1.1, and XBB.1) and across the five growing lineages in the world (XBB.1.5, CH.1.1.1, BM.4.1, BM.4.1.1, XBB.1.9) and the top five most reported lineages in Brazil (B.1.617.2, P.1.1, BA.2, AY.43, AY.34.1). Remarkably, all the five identified epitopes were completely conserved across studied variants, since there are no mutations detected inside their sequences. As shown in Figure 4, there are mutations located close to the epitopes N(34–48), N(89–104), N(185–197), and N(378–390); however, these changes do not seem to affect the identified epitopes, resulting in no alterations in antigenicity or exposition. Moreover, until now, there are no mutations described in the main SARS-CoV-2 variants near epitope N(277–287).

3.5. Analysis of Epitope Conservation across Other Human Coronaviruses

After verifying the conservancy of identified epitopes among SARS-CoV-2 isolates, we compare its conservancies among other human coronaviruses (SARS-CoV, MERS-CoV, HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1). Firstly, the epitopes N(34–48), and N(89–104) were highly conserved (> 80%) with SARS-CoV but lowly conserved with MERS-CoV and common cold coronaviruses. In the same way, the epitope N(277–287) was fully conserved with SARS-CoV and moderately conserved among MERS-CoV (Conservancy = 73%) and HCoV-HKU1 (conservancy = 55%), while the epitope N(185–197) was moderately conserved (50% < conservancy < 80%) among ‘common cold’ coronaviruses (HCoV-NL63, HCoV-OC43, and HCoV-HKU1) and also highly conserved among epidemic coronaviruses (SARS-CoV and MERS-CoV) and the epitope N(378–390) was the less conserved epitope, presenting 77% of identity with SARS-CoV and less than 40% of identity with MERS and common cold coronaviruses (Table 3).

3.6. Evaluation of Antibody Cross-Reaction against SARS-CoV-2 Variants and Other Coronaviruses

To investigate the cross-reactivity of the described antibodies across the SARS-CoV-2 variants and other coronaviruses, we selected the crystallographic structures of two nanobodies (PDB: 7R98 and 7N0R) and one antibody (PDB: 7CR5). Using the LigPlus, we listed the main SARS-CoV-2 N protein amino acids recognized by antibody/nanobody and compared the conservation of these amino acids between SARS-CoV-2 variants and other coronaviruses.
As shown in Table 4, all amino acids recognized by an antibody were completely conserved across SARS-CoV-2 variants once these amino acids were not among the 16 key mutations related to main variants (D3L, Q9L, P13L, Del31/33, D63G, P80R, E136D, R203M, R203K, G204R, T205I, G215C, L230F, S235F, D377Y, S413R). Regarding the cross-reactivity with other human coronaviruses, we observed different levels of conservation across the human coronaviruses (SARS, MERS, 229E, NL63, OC43, and HKU1). Firstly, the recognized amino acids were completely conserved (100% of identity) with SARS-CoV and highly conserved with MERS-CoV once the residues recognized by the nanobodies 7N0R and 7R98 presented more than 75% of identity and residues recognized by the antibody 7CR5 presented more than 50% of identity with the SARS-CoV-2 N protein.
On the other side, when compared to common cold coronaviruses N proteins, the recognized residues presented lower conservation, which ranged from 0% to 75% of identity. Interestingly, among the three evaluated antibodies, while the residues recognized by nanobody 7N0R and antibody 7CR5 presented a low conservation degree (ranging from 0% to 33% of identity), the residues recognized by the nanobody 7R98 were conserved in coronaviruses 229E (50% of identity) and NL63 (75% of identity), and they were lowly conserved in coronaviruses OC53 and HKU1 (25% of identity) (Table 4).

4. Discussion

Despite the global use of vaccines to control the disease, with a drastic reduction in cases and deaths by COVID-19, the continuous rise of new SARS-CoV-2 variants makes constant and large surveillance essential to avoiding new waves and the spread of infection. In this scenario, due to being highly immunogenic and abundantly present in blood and saliva during early asymptomatic and symptomatic SARS-CoV-2 infection [39,40], the N protein is highlighted as the major target for antigen detection, which is a valuable and inexpensive strategy for COVID-19 epidemiological surveillance [13]. However, studies investigating the sensitivity of antigen tests for SARS-CoV-2 variants [41,42,43] raise the question of the truthful efficacy of antigen detection tests against current and future variants. Therefore, this study aimed to identify B-cell linear epitopes in the SARS-CoV-2 N protein and to investigate their conservation across the variants of concern and variants of interest.
Even before COVID-19 became a pandemic, in silico studies were viewed as an innovative, fast, and necessary approach to tackling the disease [44,45,46]. However, despite epitope prediction being a strategy used in several studies against COVID-19 [47,48,49,50], the constant investigation of epitopes and their cross-reactivities across virus variants in different populations is indispensable to confirm the efficacy of vaccines, therapies, and diagnostic tests. Here, we predicted five B-cell linear epitopes in the SARS-CoV-2 N protein (N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390)) and confirmed their natural immunogenicity based on their recognition by samples from Brazilian COVID-19 convalescent donors. These data are in agreement with previous studies of our group in which we experimentally validated more than 80% of predicted epitopes from viruses [51,52], bacteria [53,54], and protozoa [55,56]. Moreover, our data corroborate previous studies that suggested similar regions as targets of antibodies [4,50,57,58].
Regarding the recognition of identified epitopes, 80% of studied individuals recognized at least one of these, with a prevalence of IgM response against N(34–48), a prevalence of IgG response against N(89–104), and similar frequencies of IgM and IgG reactivity against the epitopes N(185–197), N(277–287), and N(378–390). Interestingly, these data corroborate the IgG prevalence observed against the peptide 96–100 in the study of Wang and collaborators but disagree with the prevalence of IgG response against peptides 386–390 and 366–400, which was observed in the same study [59]. These differences between studies can be related to differences between Brazilian and Chinese populations’ genetics or in the stage of infection since samples were from patients in the convalescent phase in our study and early-stage patients in the Wang et al. study [59]. Notably, the number of individuals studied is a limitation of our study, but we believe it is sufficient to validate the natural immunogenicity of epitopes. In support of this point, the aforementioned study by Wang et al. used samples from only 10 patients to identify peptides recognized by antibodies [59]. However, we believe that a larger number of samples is needed to evaluate the true sensitivity and specificity of these epitopes in serological assays.
Concerning the use of antigen detection tests in COVID-19 massive surveillance, we investigated the conservation of predicted epitopes across the main variants. Remarkably, we did not observe mutations inside the identified epitopes, suggesting that the identified epitope should be recognized by the same antibodies in the main SARS-CoV-2 variants. These data are inconsistent with the study by Kumar et al., who mapped mutations in predicted B cell linear epitopes in the SARS-CoV-2 N protein [4]. From our point of view, this discrepancy could be related to the selection of the variants studied, since we selected the top growing lineages in the world and the most common variants in Brazil, while Kumar’s study used variations present in the N-protein among 831 Indian isolates of SARS-CoV-2 [4], resulting in a local observation of the mutations.
Leuzinger et al. performed a study comparing different immunoassays and showed that the full-length N protein was cross-recognized by pre-existing antibodies, which were produced during previous exposures to other human coronaviruses [60]. Based on this finding, we investigated the conservation of the identified epitopes in other human coronaviruses (SARS, MERS, 229E, NL63, OC43, and HKU1) and found that all identified epitopes are highly conserved in the SARS-CoV N protein, and epitopes N(185–197) and N(277–287) share more than 70% identity with the MERS-CoV N protein. Notably, despite the high conservation compared to SARS and MERS, the identified epitopes share low conservation (identities ranging from 23% to 61%) with common cold coronaviruses (229E, NL63, OC43, and HKU1), suggesting that these epitopes are mainly recognized by antibodies specifics to SARS-CoV-2′s N protein with low cross-reactivity against the most common coronaviruses. These data corroborate studies that suggested the use of N domains with deleted conserved regions as a target for specific antibody-based assays for COVID-19 [60,61]. Furthermore, our study corroborates the study by Wen et al., reporting that monoclonal antibodies to the SARS-CoV-2 nucleocapsid protein cross-react with their counterparts of SARS-CoV but not other human betacoronaviruses [62], and it suggests that knowing the epitope conservation shared among human coronaviruses is a critical step in predicting the cross-reactivity of a protein as an antigen to the serologic test, as the epitope conservation does not necessarily reflect the conservation shared in the whole protein [63,64].
Considering that the N protein is the main target of antigen detection tests and that the sensitivity of the test depends on the specificity and affinity of the antibodies used to detect it, we evaluated the conservation of amino acids recognized by three anti-antibodies to SARS-CoV-2 N protein among the major SARS-CoV-2 variants and other human coronaviruses. Remarkably, the amino acid residues recognized by the three antibodies studied were not located in key-point mutations positions, suggesting that these antibodies can recognize the N protein of the main SARS-CoV-2 variants and corroborating the hypothesis that the decrease in sensitivity of antigen tests can be related to other causes, such as a lower viral load of some variants [43]. Furthermore, our data suggest that these antibodies to the SARS-CoV-2 N protein can cross-recognize the protein of SARS and MERS, corroborating previous studies that demonstrated that antibodies against N protein from SARS and MERS can cross-react with the SARS-CoV-2 protein [64,65,66], and reinforcing that caution should be used while interpreting assay results when the full-length recombinant N protein of SARS-CoV-2 is used as a reagent for the diagnosis of SARS-CoV-2 infections in humans.
Conversely, despite the cross-reactivity with SARS and MERS, our data support the use of antigen testing as a tool for massive epidemiological surveillance of COVID-19. Considering that both coronaviruses, SARS and MERS, are not usually reported worldwide, the common cold coronaviruses (229E, NL63, OC43, and HKU1) should be the main concern for antigen test cross-reactivity. In this context, regarding the potential cross-reactivity with N-protein from common cold coronaviruses, only one studied antibody seems to recognize amino acid conserved in coronaviruses 229E and NL63. Therefore, despite our data showing that most of the identified epitopes are poorly conserved across common cold coronaviruses, there are epitopes identified and amino acids recognized by antibodies that are highly conserved across these viruses. Several studies have reported differences in the sensitivity of antigen tests to detect SARS-CoV-2 infection [67,68,69,70], which may be related to patient characteristics such as days of symptoms, virus variant characteristics such as viral load, or characteristics of the antibodies used in the test, such as affinity and specificity. These data highlight the need to evaluate the cross-reactivity of antigen tests against common cold coronaviruses to prove their specificity.
Concluding, this study gives a comprehensive view of B-cell epitopes of SARS-CoV-2 N protein and their conservation across the main SARS-CoV-2 variants and other coronaviruses. Despite studies that have demonstrated that mutations in the Spike protein of SARS-CoV-2 variants may lead to decreased sensitivity to neutralizing antibodies [71,72,73], it is evident from our study that the main mutations described in major SARS-CoV-2 variants are not inserted in identified epitopes, neither in amino acids recognized by the evaluated antibodies. In this context, our study supports the use of antigen testing as a scalable solution for population-level diagnosis of SARS-CoV-2; however, we highlight the need to verify the cross-reactivity of these tests against the N protein of common cold coronaviruses, which are described worldwide.

5. Conclusions

Our study validated experimentally five predicted B-cell linear epitopes as naturally immunogenic by their reactivity against the serum samples from COVID-19 convalescent patients. Remarkably, these epitopes were conserved across the major SARS-CoV-2 variants, suggesting that antigen tests based on antibodies specific to these epitopes could recognize the N protein of these variants. We also examined the conservation of these epitopes and the amino acid residues recognized by the three antibodies across other human coronaviruses and showed that there is an increased likelihood of cross-reaction with SARS and MERS coronaviruses and a decreased likelihood of cross-reaction with common cold coronaviruses, but these cross-reactions should be verified by antigen test developers.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/v15040923/s1; Table S1: Frequency of N protein key mutations across the SARS-CoV-2 major variants.

Author Contributions

Conceptualization, R.N.R.-d.-S. and F.P.C.; methodology, F.P.C., G.d.S., A.L.C.-A., P.R.G. and S.N.K.; formal analysis R.N.R.-d.-S. and J.C.L.-J.; resources, R.N.R.-d.-S. and J.C.L.-J.; writing—original draft preparation, R.N.R.-d.-S.; writing—review and editing, F.P.C., G.d.S., A.L.C.-A., P.R.G., S.N.K., A.A.F.N. and J.C.L.-J.; supervision, R.N.R.-d.-S.; project administration, R.N.R.-d.-S.; funding acquisition, R.N.R.-d.-S. All authors have read and agreed to the published version of the manuscript.

Funding

R.N.R.-d.-S.: This research was funded by Inova Fiocruz/Fundação Oswaldo Cruz, grant number 3/2020 (VPPCB-005-FIO-20-2-89). J.C.L.-J.: FAPERJ (E26/202.854/2019—JCNE and E26/211.112/2019—Apoio a Grupos Emergentes de Pesquisa), Inovabio grant program; FIOCRUZ (PAEF II, IOC-008-FIO-22-2-49). J.C.L.J. receive a Productivity Research Fellowship CNPq; The APC was funded by Fiocruz.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Ethics Committee of the Oswaldo Cruz Foundation (CEP-FIOCRUZ CAAE 31368620.0.0000.5262, approved on 13 June 2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available upon request for privacy or ethical reasons. The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to confidential information related to donors’ personal data in accordance with the Institutional Ethics Committee of the Oswaldo Cruz Foundation.

Acknowledgments

The financial, administrative, and technical support of the Oswaldo Cruz Foundation and the Institute of Technology on Immunobiologicals were essential to this study.

Conflicts of Interest

The authors declare no conflict of interest and the funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Viruses 15 00923 g001 550
Figure 1. Location of predicted epitopes in SARS-CoV-2 N protein 3D structure. The protein chain is indicated by a gray cartoon and transparent surface. The locations of epitopes N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390) were indicated by colors blue, teal, purple, red, and orange, respectively. In the cartoon, round helices, flat sheets, and smooth loops are applied to allow better visualization of the predicted structure. Different rotations of the protein are shown in (a) and (b).
Figure 1. Location of predicted epitopes in SARS-CoV-2 N protein 3D structure. The protein chain is indicated by a gray cartoon and transparent surface. The locations of epitopes N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390) were indicated by colors blue, teal, purple, red, and orange, respectively. In the cartoon, round helices, flat sheets, and smooth loops are applied to allow better visualization of the predicted structure. Different rotations of the protein are shown in (a) and (b).
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Viruses 15 00923 g002 550
Figure 2. Heatmap of IgM and IgG reactivity indexes against synthetic epitopes. Values higher than 1 represent responder individuals and were indicated in the color scale, and non-responders were indicated by a light blue color.
Figure 2. Heatmap of IgM and IgG reactivity indexes against synthetic epitopes. Values higher than 1 represent responder individuals and were indicated in the color scale, and non-responders were indicated by a light blue color.
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Viruses 15 00923 g003 550
Figure 3. Evaluation of natural immunogenicity of predicted epitopes. (a) Frequencies of IgM, IgG, and overall responders to N(34–48) (blue bar), N(89–104) (green bar), N(185–197) (gray bar), N(277–287) (red bar), and N(378–390) (light blue bar). The frequencies of responders to epitopes were compared by Fisher’s exact test, and statistical differences were indicated by asterisks: (*) = p < 0.05; (**) = p < 0.01; (***) = p < 0.001. (b) IgM (white dots) and IgG (black dots) reactivity indexes against predicted epitopes. Responders to peptides were indicated above the traced line.
Figure 3. Evaluation of natural immunogenicity of predicted epitopes. (a) Frequencies of IgM, IgG, and overall responders to N(34–48) (blue bar), N(89–104) (green bar), N(185–197) (gray bar), N(277–287) (red bar), and N(378–390) (light blue bar). The frequencies of responders to epitopes were compared by Fisher’s exact test, and statistical differences were indicated by asterisks: (*) = p < 0.05; (**) = p < 0.01; (***) = p < 0.001. (b) IgM (white dots) and IgG (black dots) reactivity indexes against predicted epitopes. Responders to peptides were indicated above the traced line.
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Viruses 15 00923 g004 550
Figure 4. B-cell epitopes and key mutations in SARS-CoV-2 N protein—3D structure. The N protein was presented as cartoon (gray), in which the identified epitopes were represented by colored sticks: N(34–48) (Blue), N(89–104) (teal), N(185–197) (magenta), N(277–287) (red), and N(378–390) (orange). The positions of key mutations (D3, Q9, P13, Del31/33, D63, P80, E136, R203, G204, T205, G215, L230, S235, D377, and S413) were represented by green spheres. In the cartoon, round helices, flat sheets, and smooth loops are applied to allow better visualization of the 3D structure.
Figure 4. B-cell epitopes and key mutations in SARS-CoV-2 N protein—3D structure. The N protein was presented as cartoon (gray), in which the identified epitopes were represented by colored sticks: N(34–48) (Blue), N(89–104) (teal), N(185–197) (magenta), N(277–287) (red), and N(378–390) (orange). The positions of key mutations (D3, Q9, P13, Del31/33, D63, P80, E136, R203, G204, T205, G215, L230, S235, D377, and S413) were represented by green spheres. In the cartoon, round helices, flat sheets, and smooth loops are applied to allow better visualization of the 3D structure.
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Table
Table 1. Evaluation of potential serological targets in SARS-CoV-2 N protein.
Table 1. Evaluation of potential serological targets in SARS-CoV-2 N protein.
EpitopeLengthSequenceBepi PredABC PredESAElliproVaxijen
N(4–24)21NGPQNQRNAPRITFGGPSDSTX-XX0.3231
N(34–48)15GARSKQRRPQGLPNNXXXX0.5955
N(89–104)16RATRRIRGGDGKMKDLXXXX0.8755
N(115–127)13TGPEAGLPYGANKX--X0.0561
N(185–197)13RSSSRSRNSSRNSX-X-10.062
N(254–264)11ASKKPRQKRTAX-X-0.2297
N(277–287)11RGPEQTQGNFGX-XX0.9248
N(323–331)9EVTPSGTWLX--X0.4548
N(363–376)14FPPTEPKKDKKKKAXXX-0.4801
N(378–390)13ETQALPQRQKKQQXXXX0.8924
N(405–417)13KQLQQSMSSADST-X-X0.4364
The first column indicates the name of the epitope, representing the start and end position of the sequence. Vaxijen scores above 0.5 were considered antigenic. The “X” indicates that the algorithm in this column predicted, completely or partially, the sequence in the line, while the “-” indicates that the algorithm did not predict the sequence. Sequences predicted as antigenic linear B-cell epitopes were considered promising targets for serological tests and are highlighted in bold.
Table
Table 2. Donors’ Characteristics.
Table 2. Donors’ Characteristics.
CharacteristicsCOVID-19 Convalescent Donors (n = 20)Healthy Unexposed Donors (n = 20)
Age (years)—median (IQR)35.5 (30.75–40.25)31 (20–38)
Gender% (n)
Male40% (8)35% (7)
Female60% (12)65% (13)
Diagnostic% (n)
RT-PCR60% (12)N/A
Serological test30% (6)N/A
RT-PCR and serological10% (2)N/A
Clinical aspectsmedian (IQR) or % (n)
Symptomatic period (days)12.5 (8–16)N/A
Mild illness80% (16)N/A
Asymptomatic case10% (2)N/A
Hospitalization case10% (2)N/A
Symptoms% (n)
Fatigue70% (14)N/A
Fever60% (12)N/A
Headache60% (12)N/A
Cough55% (11)N/A
Diarrhea40% (8)N/A
Pharyngalgia30% (6)N/A
Coryza30% (6)N/A
Nausea30% (6)N/A
Dyspnea25% (5)N/A
Anosmia10% (2)N/A
Myalgia5% (1)N/A
Ageusia5% (1)N/A
Data were expressed as median (IQR) or % (n), where n is the total number of donors with available data. Healthy unexposed donors did not have data for diagnostic, clinical aspects, or symptoms, and because of that were signalized on the table by N/A.
Table
Table 3. SARS-CoV-2 N-protein epitopes conservancy analysis among human coronaviruses.
Table 3. SARS-CoV-2 N-protein epitopes conservancy analysis among human coronaviruses.
SARSMERS229ENL63OC43HKU1
Epitope\Uniprot IDP59595K9N4V7P15130Q6Q1R8P33469Q5MQC6
N(34–48)93.33%33.33%33.33%26.67%33.33%33.33%
N(89–104)87.50%31.25%37.50%31.25%37.50%31.25%
N(185–197)84.62%76.92%46.15%61.54%61.54%53.85%
N(277–287)100%72.73%45.45%36.36%45.45%54.55%
N(378–390)76.92%38.46%23.08%30.77%30.77%30.77%
The values indicate the similarity between the SARS-CoV-2 epitope and the homolog protein in human coronaviruses (SARS-CoV, MERS-CoV, 229E, NL63, OC43, and HKU1). High (>80%), intermediate (80% > conservancy ≥ 50%), and low conservancy degrees (≤50%) were signalized by red, orange, and light blue, respectively. The proteins selected for the comparison between human coronaviruses were indicated by the Uniprot ID.
Table
Table 4. Conservation of SARS-CoV-2 N protein amino acids recognized by nanobodies (7R98 and 7N0R) and the antibody 7CR5 across other human coronaviruses.
Table 4. Conservation of SARS-CoV-2 N protein amino acids recognized by nanobodies (7R98 and 7N0R) and the antibody 7CR5 across other human coronaviruses.
OrganismAntibody
(PDB ID)		Residues Recognized by AntibodiesAligned Residues in Other Human Coronaviruses
SARSMERS229ENL63OC43HKU1
Lama glama7N0RN75N76N66N47G45A89A88
T76T77A67K46K46P90F89
N77N78N68K47G47G91G90
D82D83Q7353KE51E96E95
N153N154N142E123K121S168T167
7R98D81D82A72N52D50T95S94
G137G138G127G107G105Q152Q151
A138A139A128A108A106A153A152
N140N141D130T110T108V155T154
Homo sapiens7CR5Q70Q71Q61N42N40Q84Q83
Q160Q161Q149N160S128R175R174
L161L162F150Q131I129F176F175
P162P163A151K132A130P177P176
T166T167K155G136E134V181I180
K169K170K158V139V137Q184Q183
Non-conserved amino acids in human coronaviruses are indicated by gray cells.
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Rodrigues-da-Silva, R.N.; Conte, F.P.; da Silva, G.; Carneiro-Alencar, A.L.; Gomes, P.R.; Kuriyama, S.N.; Neto, A.A.F.; Lima-Junior, J.C. Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants. Viruses 2023, 15, 923. https://doi.org/10.3390/v15040923

AMA Style

Rodrigues-da-Silva RN, Conte FP, da Silva G, Carneiro-Alencar AL, Gomes PR, Kuriyama SN, Neto AAF, Lima-Junior JC. Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants. Viruses. 2023; 15(4):923. https://doi.org/10.3390/v15040923

Chicago/Turabian Style

Rodrigues-da-Silva, Rodrigo N., Fernando P. Conte, Gustavo da Silva, Ana L. Carneiro-Alencar, Paula R. Gomes, Sergio N. Kuriyama, Antonio A. F. Neto, and Josué C. Lima-Junior. 2023. "Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants" Viruses 15, no. 4: 923. https://doi.org/10.3390/v15040923

APA Style

Rodrigues-da-Silva, R. N., Conte, F. P., da Silva, G., Carneiro-Alencar, A. L., Gomes, P. R., Kuriyama, S. N., Neto, A. A. F., & Lima-Junior, J. C. (2023). Identification of B-Cell Linear Epitopes in the Nucleocapsid (N) Protein B-Cell Linear Epitopes Conserved among the Main SARS-CoV-2 Variants. Viruses, 15(4), 923. https://doi.org/10.3390/v15040923

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