Literature DB >> 33372199

SARS-CoV-2 Proteome Microarray for Mapping COVID-19 Antibody Interactions at Amino Acid Resolution.

Hongye Wang1, Xian Wu2, Xiaomei Zhang1, Xin Hou2, Te Liang1, Dan Wang1, Fei Teng3, Jiayu Dai1, Hu Duan1, Shubin Guo3, Yongzhe Li2, Xiaobo Yu1.   

Abstract

Comprehensive profiling of humoral antibody response to severe acute respiratory syndrome (SARS) coronavirus-2 (CoV-2) proteins is essential in understanding the host immunity and in developing diagnostic tests and vaccines. To address this concern, we developed a SARS-CoV-2 proteome peptide microarray to analyze antibody interactions at the amino acid resolution. With the array, we demonstrate the feasibility of employing SARS-CoV-1 antibodies to detect the SARS-CoV-2 nucleocapsid phosphoprotein. The first landscape of B-cell epitopes for SARS-CoV-2 IgM and IgG antibodies in the serum of 10 coronavirus disease of 2019 (COVID-19) patients with early infection is also constructed. With array data and structural analysis, a peptide epitope for neutralizing antibodies within the SARS-CoV-2 spike receptor-binding domain's interaction interface with the angiotensin-converting enzyme 2 receptor was predicted. All the results demonstrate the utility of our microarray as a platform to determine the changes of antibody responses in COVID-19 patients and animal models as well as to identify potential targets for diagnosis and treatment.
© 2020 American Chemical Society.

Entities:  

Year:  2020        PMID: 33372199      PMCID: PMC7586461          DOI: 10.1021/acscentsci.0c00742

Source DB:  PubMed          Journal:  ACS Cent Sci        ISSN: 2374-7943            Impact factor:   14.553


Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has since proven to be highly contagious, with the median incubation period of 4 d.[1−3] Infection of SARS-CoV-2, called COVID-19, results in a range of symptoms, ranging from a mild cough to pneumonia. It is estimated that 17.9% of patients might be asymptomatic,[4] which may lead to two or even three transmissions per infected individual.[3,5,6] Particular subsets of the population are extremely vulnerable to COVID-19, including the elderly, those with underlying conditions, and immunocompromised individuals. On the evening of January 30, 2020, the World Health Organization listed the novel coronavirus outbreak as a public health emergency of international concern.[7] The novel coronavirus had spread worldwide by August 11, 2020,[8] with 20 014 574 confirmed cases and 734 755 deaths in 188 countries.[9] The high transmission rates of SARS-CoV-2, limited diagnostic tests, and no antiviral treatment options pose huge challenges for the control and treatment of SARS-CoV-2-infected patients.[10,11] SARS-CoV-2 is 82% similar to the original SARS virus attributed to the outbreak in 2003.[12] Generally, a SARS-CoV-2 virus has a polyprotein (the open reading frame 1a and 1b, Orf1ab), four structural proteins (envelope, E; membrane, M; nucleocapsid phosphoprotein, N; spike, S), and five accessary proteins (Orf3a, Orf6, Orf7a, Orf8, Orf10).[13] The largest polyprotein encoded by Orf1ab can be proteolytically cleaved into 16 putative nonstructural proteins (nsps), which might be involved in viral RNA replication and transcription.[12] The E and M proteins are important in the viral assembly of a coronavirus. The N protein forms complexes with genomic RNA and is important to enhance the efficiency of viral transcription and assembly.[14] The S protein is on the surface of the viral particle, enabling the infection of host cells by binding to the host cell receptor, angiotensin-converting enzyme 2 (ACE2), via the S-protein’s receptor binding domain (RBD) within the S-protein’s subunit 1.[15,16] The accessory proteins may have functions in signaling inhibition, apoptosis induction, and cell cycle arrest.[13] The identification of B-cell and T-cell epitopes for SARS-CoV-2 proteins is essential in developing effective diagnostic tests and vaccines, especially for structural N and S proteins. These epitopes have thus far been predicted either by bioinformatics or measured using T-cell based assays.[17−20] However, proteome-wide analysis of the humoral antibody response to SARS-CoV-2 proteins using an immuno-proteomics platform has not been performed to date. Here, we use a peptide-based SARS-CoV-2 peptide microarray to analyze antibody interactions in high throughput at the amino acid resolution.

Results

Development of a SARS-CoV-2 Proteome Microarray

To produce the SARS-CoV-2 proteome microarray (Figure a), we first extracted the reference sequences of 10 proteins encoded by the SARS-CoV-2 coronavirus genome from the National Center for Biotechnology Information (NCBI) database (Accession No. MN908947.3). Using these reference sequences, we prepared a peptide library containing 966 peptides representing SARS-CoV-2 proteins, in which each peptide was 15 amino acids long with a 5 amino acid overlap. All peptides were labeled with a C-terminal biotin group and printed onto a three-dimensional (3D) modified microscope slide using biotin–streptavidin chemistry,[21] such that the peptides were immobilized on the slide via their C-terminus. Full-length SARS-CoV-2 N protein, full-length E, and five S truncated proteins were also printed (Supporting Information Table 1).
Figure 1

SARS-CoV-2 proteome microarray fabrication and application in antibody characterization. (a) The schematic illustration of SARS-CoV-2 proteome microarray fabrication and biomedical applications. (b) Dynamic range of serum antibody detection using SARS-CoV-2 proteome microarray. The LOD was calculated using the signal of the buffer control plus two standard deviations. (c) Reproducibility of serum antibody detection using the SARS-CoV-2 proteome microarray. (d) Epitope binding of the anti-SARS-CoV-1 N protein antibody using the SARS-CoV-2 proteome microarray. The specific antibody binding to the target epitope is selected with a Z-score higher than 3 as a threshold. The false-colored rainbow color from blue to red corresponds to the Z-score from low to high, respectively.

SARS-CoV-2 proteome microarray fabrication and application in antibody characterization. (a) The schematic illustration of SARS-CoV-2 proteome microarray fabrication and biomedical applications. (b) Dynamic range of serum antibody detection using SARS-CoV-2 proteome microarray. The LOD was calculated using the signal of the buffer control plus two standard deviations. (c) Reproducibility of serum antibody detection using the SARS-CoV-2 proteome microarray. (d) Epitope binding of the anti-SARS-CoV-1 N protein antibody using the SARS-CoV-2 proteome microarray. The specific antibody binding to the target epitope is selected with a Z-score higher than 3 as a threshold. The false-colored rainbow color from blue to red corresponds to the Z-score from low to high, respectively. Using serum spiked with anti-SARS antibodies, we next determined the optimal lengths of time to block the array, incubate with serum samples, and incubate with the detection antibody. Optimal signal-to-noise ratios were obtained with blocking for 1 min, serum incubation for 30 min, and detection antibody incubation for 30 min (Supporting Information, Figures 1–3). Serum screening using the SARS-CoV-2 proteome microarray can be performed in 1.5 h while keeping a good dynamic range (∼2 orders of magnitude) and lowest limit of detection (LOD) (94 pg/mL) (Figure b). This represents a significant decrease in time compared to the standard ∼18 h using protein microarrays.[22] The intra- and inter-array R correlations were 0.9992 and 0.9978, respectively, demonstrating that the SARS-CoV-2 proteome microarray has a high reproducibility (Figure c).

Epitope Mapping of SARS-COV-1 Antibodies for SARS-CoV-2 N Protein Detection

Since the SARS-CoV-1 and SARS-CoV-2 genomes are highly similar, we tested rabbit monoclonal and polyclonal anti-SARS-CoV-1 N protein antibodies on the SARS-CoV-2 proteome microarray (Figure d and Supporting Information, Figure 4). The monoclonal Ab displayed high specificity to two epitopes (RRGPE and PAADL) on the SARS-CoV-2 N protein with a Z-score higher than 3.[23] Minor cross-reactivity was observed on the epitope (SVLLF) of the E protein. The polyclonal antibody bound to 11 epitopes (E1-E11) on the N protein with cross reactivity to six epitopes on M, S, Orf8, and Orf1ab proteins. The cross-reactive epitopes on M, S, Orf8, and Orf1ab proteins are different than those present in the N-protein (Figure d), and the results were validated using full-length N- and S-proteins (Supporting Information, Figure 5).

Landscape of B-Cell Epitopes of IgM and IgG Antibodies in the Serum of COVID-19 Patients

Using the SARS-CoV-2 proteome microarray, we screened IgM and IgG antibodies in the serum of 10 COVID-19 patients who were in the early stage of infection (days of symptoms onset, 3.0 ± 5.92) (Supporting Information, Table S2) to construct a landscape of humoral responses to the SARS-CoV-2 proteome (Figure ). Sixty-one (61) IgG and IgM antibody epitopes were identified in seven SARS-CoV-2 proteins (M, N, S, Orf1ab, Orf3a, Orf7a, and Orf8) with a Z-score higher than 3 in at least one COVID-19 patient (Table ).[23] The Orf1ab has the maximal number of IgM and IgG epitopes (n = 32). These epitopes were distributed on the proteins of nsp1–4, nsp6, nsp8–10, and nsp12–16 (Figures and 3). Additional binding epitopes were identified on S (n = 8), N (n = 8), M (n = 5), Orf3a (n = 4), Orf7a (n = 3), and Orf8 (n = 1) proteins (Figure and Table ). Notably, four immunodominant epitopes with antibodies in more than 80% of the COVID-19 patients were present in the N (residue 206–210, SPARM), S (residue 816–820, SFIED), and Orf3a (residue 136–140, KNPLL; residue 176–180, SPISE) proteins. However, antibodies to E, Orf6, and Orf10 were not detected (Figure ).
Figure 2

Landscape of humoral IgM antibody response to SARS-CoV-2 Orf1ab proteome. The x-axis represents the sequence of amino acids of SARS-CoV-2 nonstructural proteins (nsps) from the N-terminal to C-terminal. The y-axis represents the serum samples from COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively.

Table 1

Epitopes Identified in the Serum of COVID-19 Patients using SARS-CoV-2 Proteome Microarrays

  epitopea
protein name IgGIgMtotal number
M 16-LLEQW-206-GTITV-105
  106-TRSMW-110176-LSYYK-180 
  196-YSRYR-200196-YSRYR-200 
S 26-PAYTN-30816-SFIED-8208
  186-FKNLR-190886-WTFGA-890 
  356-KRISN-3601046-GYHLM-1050 
  456-FRKSN-460  
  806-LPDPSKPSKRSFIED-820  
  1196-SLIDL-1200  
N 66-FPRGQ-70206-SPARM-2108
  96-GGDGK-100386-QKKQQ-390 
  166-TLPKG-170  
  206-SPARM-210  
  226-RLNQL-230  
  256-KKPRQ-260  
  316-GMSRI-320  
  366-TEPKK DKKKKADETQALPQRQKKQQTVTLPAADL-400  
Orf1abnsp1166-SSGVT-170 32
 nsp2306-VASPN-310296-FMGRI-300 
  386-EYHNESGLKTILRKG-400336-FVKAT-340 
  546-SIFSR-550  
 nsp31046-VEEAK-10501496-TPEEH-1500 
  1106-SGHNL-11101636-HTTDPSFLGRYMSAL-1650 
  1346-LKKCK-13502656-KLSHQ-2660 
  2186-TNSRI-2190  
 nsp43206-RYLAL-3210  
 nsp63836-DAFKL-3840  
 nsp84076-DYNTY-4080  
 nsp94226-KYLYF-4230  
 nsp104346-KGKYV-4350  
 nsp124516-MADLV-45204616-QTTPG-4620 
  4676-DRYFK-4680  
  4716-TSFGP-4720  
  5136-EFYAY-5140  
 nsp135346-RPFLC-5350  
  5746-FNSVC-5750  
  5836-ISPYN-5840  
 nsp146206-AVHEC-62105976-YRRLI-5980 
  6366-QLPFF-6370  
 nsp156716-ELEDF-67206536-VIWDY-6540 
 nsp166926-ISDMY-6930  
Orf3a 66-LKKRWQ-70136-KNPLL-1404
  136-KNPLL-140176-TSPIS-180 
  176-TSPIS-180216-STQLS-220 
  216-STQLS-220  
Orf7a 116-LKRKT-12026-GTTVL-303
   66-ACPDG-70 
   116-LKRKT-120 
Orf8 36-PCPIHFYSKWYIRVGARKSA PLIEL-6036-PCPIHFYSKWYIRVGARKSAPLIEL-601

Bound by serological antibodies identified with a Z-score higher than 3 in at least one COVID-19 patient.

Figure 3

Landscape of the humoral IgG antibody response to the SARS-CoV-2 Orf1ab proteome. The x-axis represents the sequence of amino acids of the SARS-CoV-2 nonstructural proteins (nsps) from the N-terminal to C-terminal. The y-axis represents the serum samples from the COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively.

Figure 4

Landscape of the humoral antibody response to SARS-CoV-2 proteins other than Orf1ab. (a, b) The distribution of human IgM and IgG antibodies to SARS-CoV-2 individual proteins (S, E, M, N, Orf3a, Orf6, Orf7a, Orf8, and Orf10), respectively. The x-axis represents the sequence of amino acids of SARS-CoV-2 proteins from the N-terminal to C-terminal. The y-axis represents the serum samples from COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively.

Landscape of humoral IgM antibody response to SARS-CoV-2 Orf1ab proteome. The x-axis represents the sequence of amino acids of SARS-CoV-2 nonstructural proteins (nsps) from the N-terminal to C-terminal. The y-axis represents the serum samples from COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively. Landscape of the humoral IgG antibody response to the SARS-CoV-2 Orf1ab proteome. The x-axis represents the sequence of amino acids of the SARS-CoV-2 nonstructural proteins (nsps) from the N-terminal to C-terminal. The y-axis represents the serum samples from the COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively. Landscape of the humoral antibody response to SARS-CoV-2 proteins other than Orf1ab. (a, b) The distribution of human IgM and IgG antibodies to SARS-CoV-2 individual proteins (S, E, M, N, Orf3a, Orf6, Orf7a, Orf8, and Orf10), respectively. The x-axis represents the sequence of amino acids of SARS-CoV-2 proteins from the N-terminal to C-terminal. The y-axis represents the serum samples from COVID-19 patients. The false-colored rainbow color from blue to red corresponds to the signals of antibody binding from low to high, respectively. Bound by serological antibodies identified with a Z-score higher than 3 in at least one COVID-19 patient. Furthermore, with overlapping peptides representing the full-length S protein, human IgM and human IgG antibodies were found to target three and six epitopes, respectively (Figure and Table ). Likewise for the N-protein, IgM antibodies targeted two epitopes, and IgG antibodies bound to eight epitopes (Figure and Table ). Structural analysis shows that all epitope peptides within the RNA binding domain loop of the N protein are easily accessible to antibodies (Figure a). Six epitopes were identified in the S protein, with three epitopes located at the surface and three epitopes located inside the protein (Figure b).
Figure 5

Structural analysis of immunogenic epitopes in SARS-CoV-2 proteins. (a, b) The structural analysis of the nucleocapsid phosphoprotein RNA binding domain (PDB ID: 6VYO) and spike trimer protein (PDB ID: 6VXX). The epitope is labeled with yellow or red and indicated with a red arrow.

Structural analysis of immunogenic epitopes in SARS-CoV-2 proteins. (a, b) The structural analysis of the nucleocapsid phosphoprotein RNA binding domain (PDB ID: 6VYO) and spike trimer protein (PDB ID: 6VXX). The epitope is labeled with yellow or red and indicated with a red arrow. To help understand the translational potential of these peptide epitopes in COVID-19 diagnosis, we compared the expression of serum antibodies targeting these immunogenic epitopes in 10 COVID-19 patients with 10 control patients with nucleic acid testing negative (Supporting Information, Table 1). These control patients were suspected to have COVID-19 due to displaying similar symptoms but were confirmed to not have COVID-19 via polymerase chain reaction (PCR) testing. Statistical analyses identified one IgG epitope and five IgM epitopes (Mann–Whitney U-test, p < 0.01) (Figure a). One IgG and IgM epitope (816-SFIED-820) was located on the S protein, and one IgM epitope (206-SPARM-210) was located on the N protein; both of these proteins have been utilized as biomarkers in COVID-19 diagnosis. In addition, we identified three potential new epitope biomarkers from Orf3a (136-KNPLL-140 and 176-TSPIS-180) and nsp2 (296-FMGRI-300), which should be validated in a different cohort in the future (Table ).
Figure 6

Identification of potential peptide epitopes for SARS-CoV-2 detection and neutralization. (a) Box-plot analysis of antibody responses to immunogenic epitopes of SARS-COV-2 between COVID-19 patients and control patients. The significance was performed using the Mann–Whitney U-test (p-value < 0.01). (**), (***), and (****) represent a p-value less than 0.01, 0.001, and 0.0001, respectively. (b) Z-Score of serum antibody binding to the peptides within the spike protein’s RBD (amino acid residues 431–505). (c) Identification of antibody binding epitope (FRKSN) through sequence alignment. (d) Schematic illustration of the epitope on the RBD (FRKSN) recognized by potential neutralizing antibody in S-protein-ACE2 protein complex (PDB ID: 6M17).

Identification of potential peptide epitopes for SARS-CoV-2 detection and neutralization. (a) Box-plot analysis of antibody responses to immunogenic epitopes of SARS-COV-2 between COVID-19 patients and control patients. The significance was performed using the Mann–Whitney U-test (p-value < 0.01). (**), (***), and (****) represent a p-value less than 0.01, 0.001, and 0.0001, respectively. (b) Z-Score of serum antibody binding to the peptides within the spike protein’s RBD (amino acid residues 431–505). (c) Identification of antibody binding epitope (FRKSN) through sequence alignment. (d) Schematic illustration of the epitope on the RBD (FRKSN) recognized by potential neutralizing antibody in S-protein-ACE2 protein complex (PDB ID: 6M17).

Identification of an Epitope for Potential Neutralizing Antibodies in the Serum of COVID-19 Patients

There is a subdomain (residue 438–498) within the SARS-CoV-2 S-protein’s RBD that directly engages the ACE2 receptor, which makes it a potential target for developing neutralizing antibodies.[24] However, the identification of neutralizing antibodies to competitively inhibit the binding of the SARS-CoV-2 virus to the host ACE2 receptor has proved challenging. In this work, we analyzed the immunological response to seven peptide sequences within the RBD subdomain (residue 438–498). Some IgM antibodies from patients “P45” and “P52” and IgG antibodies from patients “P10”, “P15”, “P33”, “P45”, and “P52” bind to the same epitope (residues 456–460, FRKSN) (Figure b,c). Structural analysis of the RBD-ACE2 complex demonstrates that the epitope located within the RBD loop engages with the ACE2 receptor[25] (Figure d), thus supporting our data. Interestingly, this epitope (residues 456–460, FRKSN) was validated from a neutralizing antibody (B38) isolated from a convalescent patient.[26] With a mouse model, the antibody blocked the binding of S-RBD to ACE2 and reduced virus titers in infected lung. The results provide evidence for the existence of a linear epitope for neutralizing antibodies in COVID-19 patients.

Discussion

Comprehensive profiling of the humoral antibody response to SARS-CoV-2 proteins is essential to understand the host immunity and identify the targets for COVID-19 diagnostics and treatment. In this work, we created an SARS-CoV-2 proteome microarray with good reproducibility and sensitivity (Figure a–c) that enables the high-throughput scanning of serum antibodies with SARS-CoV-2 proteins within 1.5 h. By epitope mapping a set of monoclonal and polyclonal antibodies previously prepared to target SARS-CoV-1 proteins, we demonstrate that the antibodies can also be used to detect SARS-CoV-2 proteins (Figure d and Supporting Information Figure S5).[27] SARS-CoV-1 antibodies could provide a quick alternative for developing an immunoassay to detect SARS-CoV-2 antigens. Furthermore, we constructed the first landscape of B-cell epitopes of serum IgM and IgG antibodies, representing the comprehensive antibody response of COVID-19 patients to SARS-CoV-2 infection (Figures –4). In addition, we experimentally validated four B-cell epitopes previously predicted by bioinformatics,[17,19] including two epitopes on the S protein (residues 806–820, LPDPSKPSKRSFIED; residues 456–460, FRKSN), one epitope on the N protein (residues 166–170, TLPKG), and one epitope on the M protein (residues 6–10, GTITV). IgG and IgM serum antibodies to one and five epitopes, respectively, were differentially expressed between 10 COVID-19 patients and 10 control patients with similar symptoms but negative for SARS-CoV-2. These epitopes should be validated in future studies (Figure a). As part of the humoral response of the adaptive immune system, neutralizing antibodies is critical in viral clearance and saving the lives of COVID-19 patients.[16,26] In this work, we identified a peptide epitope (residue 456–460, FRKSN) located at the interface of the SARS-CoV-2 S-RBD-ACE2 receptor interaction in the serum of five mild COVID-19 patients (P10, P15, P33, P45, P52) (Figure b). This epitope may serve as an antigen to stimulate neutralizing antibodies to the RBD-ACE2 interaction and increase CD4+/CD8+ T-cell responses.[17,28] The number of days after symptom onset ranged from 1 to 20 d (P10, 20 d; P15, 1 d; P33, 3 d; P45, 5 d; P52, 2 d). The result is consistent with previous reports and indicates humoral antibodies in early SARS-CoV-2 infection may confer protection.[29,30] The results might also explain why most infected people can recover without medical intervention. There are several limitations to this study. First, the chemically synthesized peptides on the microarray do not have conformational epitopes. To address this issue, we included full-length N, S, and E proteins on our microarrays as a comparison. Second, the peptides do not have post-translational modifications, yet the SARS-CoV-2 S protein is glycosylated in vivo.[15] However, specific glycosylation on peptides is challenging and thus was not considered in this study.[31] Third, 80 000 genomic sequences of SARS-CoV-2 have been submitted to the Global Initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/) since the preparation of our proteome microarray. These new strains could be included in the next version of the SARS-CoV-2 proteome microarrays. Fourth, we specifically studied the binding of IgG and IgM antibodies in serum to the peptide array; however, the influence of total immunoglobulins on binding was not explored. Total immunoglobulin profiling and the analysis of purified antibodies should be investigated in the future.

Conclusion

Altogether, we demonstrate that our SARS-CoV-2 peptide-based microarray can serve as a platform to determine the changes of humoral antibody response in COVID-19 patients and animal models. The array can also help identify potential targets for COVID-19 diagnosis and treatment. Scientists who wish to acquire these arrays to help fight this COVID-19 pandemic are encouraged to contact us.

Materials and Methods

Preparation of SARS-CoV-2 Proteome Microarray

All biotin-labeled peptides were obtained from China Peptides and Guoping Pharmaceutical Company. All SARS-CoV-2 E, N, and S proteins were obtained from Sino Biological, Inc. Among them, the SARS-CoV-2 E protein (catalogue No. DRA33) was expressed in Escherichia coli. The N protein (catalogue No. 40588-V08B) was expressed in insect cells. Three S proteins (S1+S2 ECD: catalogue No. 40589-V08B1, S2 ECD: catalogue No. 40590-V08B, S1 Subunit: catalogue No. 40591-V08B1) were expressed in insect cells, and two S proteins (S1 Subunit: catalogue No. 40591-V08H, RBD: catalogue No. 40592-V05H) were expressed in human HEK293 cells. These peptides and proteins were printed onto a 3D modified slide surface (Capital Biochip Corp) in parallel and in duplicate using an Arrayjet microarrayer. Phosphate buffered saline (PBS), bovine serum albumin (BSA, 100 μg/mL) (Sigma-Aldrich), and hemagglutinin (HA) peptides (500 μg/mL) (China Peptides) were used as negative controls. Biotinylated BSA (100 μg/mL), human IgG and IgM (10 μg/mL), and polio peptides (500 μg/mL) (China Peptides) were used as positive controls. The peptide microarrays were stored at −20 °C until ready to use. No unexpected or unusually high safety hazards were encountered in this work.

Characterization of Anti-SARS Antibody using SARS-CoV-2 Proteome Microarray

The peptide microarrays were assembled in an incubation tray and blocked with 5% (w/v) milk in 1X PBS with 0.2% (v/v) Tween-20 (PBST) for 1 min at room temperature. After it was washed with PBST three times, the array was incubated with a rabbit anti-SARS-CoV-1 N-protein monoclonal or a rabbit anti-SARS-CoV-1 N-protein polyclonal antibody (1 μg/mL) (catalogue Nos. 40143-R001 and 40143-T62, respectively; Sino Biological) for 30 min at room temperature. After it was washed again, the array was incubated with an Alexa Fluor 555 labeled goat antirabbit IgG (H+L), cross-adsorbed, secondary antibody (Jackson ImmunoResearch) for 30 min. The arrays were washed, dissembled from the tray, and dried with centrifugation for 2 min at 2000 rpm. The resulting array was scanned with a GenePix 4300A microarray scanner (Molecular Devices). The median fluorescent signal intensity of each spot was extracted using GenePix Pro7 software (Molecular Devices). The median background signal was subtracted from the median spot signal intensity.

Detection of Serum Antibody using SARS-CoV-2 Proteome Microarray

All COVID-19 patients were diagnosed according to the “Diagnosis and Management Plan of Pneumonia with New Coronavirus Infection” (trial version 7). The serum samples of COVID-19 and control patients were collected with written informed consent under the approval of the intuitional review board (IRB) from Peking Union Medical College Hospital (Ethical No. ZS-2303) and Beijing Proteome Research Center. All experiments were performed according to the standards of the Declaration of Helsinki. Prior to the antibody detection, the peptide microarrays were assembled in an incubation tray and blocked with 5% (w/v) milk in 1X PBS with 0.2% (v/v) Tween-20 (PBST) for 1 min at room temperature. After it was washed with PBST three times, the array was incubated with 1:300 diluted serum for 30 min at room temperature. After it was washed again, the array was then incubated for 30 min with a mixture containing Cy3 Affinipure donkey antihuman IgG(H+L) and Alexa fluor 647 Affinipure goat antihuman IgM FC5 μantibody (Jackson ImmunoResearch) (2 μg/mL). Finally, the array was washed with PBST and water, dissembled from the tray, and dried with centrifugation for 2 min at 2000 rpm. The array was scanned with a GenePix 4300A microarray scanner (Molecular Devices) at 10 μm resolution using a laser at 532 nm with 100% power/PMT Gain 800 for IgG and 635 nm with 100% power/PMT Gain 900 for IgM. The median fluorescent signal intensity with background subtraction was extracted using GenePix Pro7 software (Molecular Devices).

Data Analysis

The raw fluorescence signal intensity was the median signal intensity subtracted by the median background intensity of each spot, and then averaged across duplicate spots. The resulting signals were normalized with a Z-score, which is shown below.[23]where P is any peptide or protein on the microarray, and P1···Pn represents the aggregate measure of all of the peptides or proteins. The heatmap of antibody response to the peptides was visualized using the MultiExperiment Viewer software version 4.9 (Dana-Farber Cancer Institute).[32] Statistical analyses were performed using the GraphPad Prism software version 6.0 (GraphPad Software, Inc.) with the Mann–Whitney U-test (p-value < 0.01).
  29 in total

1.  A human monoclonal antibody blocking SARS-CoV-2 infection.

Authors:  Chunyan Wang; Wentao Li; Dubravka Drabek; Nisreen M A Okba; Rien van Haperen; Albert D M E Osterhaus; Frank J M van Kuppeveld; Bart L Haagmans; Frank Grosveld; Berend-Jan Bosch
Journal:  Nat Commun       Date:  2020-05-04       Impact factor: 14.919

2.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

3.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

4.  Importation and Human-to-Human Transmission of a Novel Coronavirus in Vietnam.

Authors:  Lan T Phan; Thuong V Nguyen; Quang C Luong; Thinh V Nguyen; Hieu T Nguyen; Hung Q Le; Thuc T Nguyen; Thang M Cao; Quang D Pham
Journal:  N Engl J Med       Date:  2020-01-28       Impact factor: 91.245

5.  A novel coronavirus outbreak of global health concern.

Authors:  Chen Wang; Peter W Horby; Frederick G Hayden; George F Gao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

6.  First Case of 2019 Novel Coronavirus in the United States.

Authors:  Michelle L Holshue; Chas DeBolt; Scott Lindquist; Kathy H Lofy; John Wiesman; Hollianne Bruce; Christopher Spitters; Keith Ericson; Sara Wilkerson; Ahmet Tural; George Diaz; Amanda Cohn; LeAnne Fox; Anita Patel; Susan I Gerber; Lindsay Kim; Suxiang Tong; Xiaoyan Lu; Steve Lindstrom; Mark A Pallansch; William C Weldon; Holly M Biggs; Timothy M Uyeki; Satish K Pillai
Journal:  N Engl J Med       Date:  2020-01-31       Impact factor: 91.245

Review 7.  SARS coronavirus accessory proteins.

Authors:  Krishna Narayanan; Cheng Huang; Shinji Makino
Journal:  Virus Res       Date:  2007-11-28       Impact factor: 3.303

8.  A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2.

Authors:  Alba Grifoni; John Sidney; Yun Zhang; Richard H Scheuermann; Bjoern Peters; Alessandro Sette
Journal:  Cell Host Microbe       Date:  2020-03-16       Impact factor: 21.023

9.  An interactive web-based dashboard to track COVID-19 in real time.

Authors:  Ensheng Dong; Hongru Du; Lauren Gardner
Journal:  Lancet Infect Dis       Date:  2020-02-19       Impact factor: 25.071

10.  Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein.

Authors:  Alexandra C Walls; Young-Jun Park; M Alejandra Tortorici; Abigail Wall; Andrew T McGuire; David Veesler
Journal:  Cell       Date:  2020-03-09       Impact factor: 41.582

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  40 in total

1.  Receptor-binding domain-based immunoassays for serosurveillance differentiate efficiently between SARS-CoV2-exposed and non-exposed farmed mink.

Authors:  Jorge Pulido; Marga García-Durán; Ricardo Fernández-Antonio; Carmen Galán; Lissette López; Carmen Vela; Ángel Venteo; Paloma Rueda; Luis A Rivas
Journal:  J Vet Diagn Invest       Date:  2021-12-02       Impact factor: 1.279

2.  Plasmonically Enhanced Ultrasensitive Epitope-Specific Serologic Assay for COVID-19.

Authors:  Zheyu Wang; Jeremiah J Morrissey; Lin Liu; Yixuan Wang; Qingjun Zhou; Rajesh R Naik; Srikanth Singamaneni
Journal:  Anal Chem       Date:  2021-12-22       Impact factor: 6.986

Review 3.  Applications of Peptide Microarrays in Autoantibody, Infection, and Cancer Detection.

Authors:  Carsten Grötzinger
Journal:  Methods Mol Biol       Date:  2023

4.  SARS-CoV-2 Epitopes following Infection and Vaccination Overlap Known Neutralizing Antibody Sites.

Authors:  Li Yang; Te Liang; Lane M Pierson; Hongye Wang; Jesse K Fletcher; Shu Wang; Duran Bao; Lili Zhang; Zhen Huang; Wenshu Zheng; Xiaomei Zhang; Heewon Park; Yuwen Li; James E Robinson; Amy K Feehan; Christopher J Lyon; Jing Cao; Lisa A Morici; Chenzhong Li; Chad J Roy; Xiaobo Yu; Tony Hu
Journal:  Research (Wash D C)       Date:  2022-07-09

5.  De novo design of modular and tunable protein biosensors.

Authors:  Alfredo Quijano-Rubio; Hsien-Wei Yeh; Jooyoung Park; Hansol Lee; Robert A Langan; Scott E Boyken; Marc J Lajoie; Longxing Cao; Cameron M Chow; Marcos C Miranda; Jimin Wi; Hyo Jeong Hong; Lance Stewart; Byung-Ha Oh; David Baker
Journal:  Nature       Date:  2021-01-27       Impact factor: 49.962

Review 6.  COVID-19 Diagnostic Strategies Part II: Protein-Based Technologies.

Authors:  Tina Shaffaf; Ebrahim Ghafar-Zadeh
Journal:  Bioengineering (Basel)       Date:  2021-04-28

7.  Peptide microarray-based analysis of antibody responses to SARS-CoV-2 identifies unique epitopes with potential for diagnostic test development.

Authors:  Pavlo Holenya; Paul Joris Lange; Ulf Reimer; Wolfram Woltersdorf; Thomas Panterodt; Michael Glas; Mark Wasner; Maren Eckey; Michael Drosch; Jörg-Michael Hollidt; Michael Naumann; Florian Kern; Holger Wenschuh; Robert Lange; Karsten Schnatbaum; Frank F Bier
Journal:  Eur J Immunol       Date:  2021-05-07       Impact factor: 5.532

8.  Cryo-EM structure of SARS-CoV-2 ORF3a in lipid nanodiscs.

Authors:  Ben Sorum; Sonali S Mali; Christopher M Hoel; David M Kern; Savitha Sridharan; Jonathan P Remis; Daniel B Toso; Abhay Kotecha; Diana M Bautista; Stephen G Brohawn
Journal:  Nat Struct Mol Biol       Date:  2021-06-22       Impact factor: 15.369

9.  Landscape and selection of vaccine epitopes in SARS-CoV-2.

Authors:  Christof C Smith; Kelly S Olsen; Benjamin G Vincent; Alex Rubinsteyn; Kaylee M Gentry; Maria Sambade; Wolfgang Beck; Jason Garness; Sarah Entwistle; Caryn Willis; Steven Vensko; Allison Woods; Misha Fini; Brandon Carpenter; Eric Routh; Julia Kodysh; Timothy O'Donnell; Carsten Haber; Kirsten Heiss; Volker Stadler; Erik Garrison; Adam M Sandor; Jenny P Y Ting; Jared Weiss; Krzysztof Krajewski; Oliver C Grant; Robert J Woods; Mark Heise
Journal:  Genome Med       Date:  2021-06-14       Impact factor: 15.266

10.  Immunity against seasonal human coronavirus OC43 mitigates fatal deterioration of COVID-19.

Authors:  Tomoyuki Yamaguchi; Toshie Shinagawa; Hisanobu Kobata; Hidemitsu Nakagawa
Journal:  Int J Infect Dis       Date:  2021-07-14       Impact factor: 3.623

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