Hongye Wang1, Xian Wu2, Xiaomei Zhang1, Xin Hou2, Te Liang1, Dan Wang1, Fei Teng3, Jiayu Dai1, Hu Duan1, Shubin Guo3, Yongzhe Li2, Xiaobo Yu1. 1. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing 102206, China. 2. Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100730, China. 3. Department of Emergency Medicine, Beijing Chao-Yang Hospital, Capital Medical University, & Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Beijing 100020, China.
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.
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-2spike 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-19patients and animal models as well as to identify potential targets for diagnosis and treatment.
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-infectedpatients.[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-2coronavirus 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-19patients 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-19patient
(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-19patients 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
IgG
IgM
total number
M
16-LLEQW-20
6-GTITV-10
5
106-TRSMW-110
176-LSYYK-180
196-YSRYR-200
196-YSRYR-200
S
26-PAYTN-30
816-SFIED-820
8
186-FKNLR-190
886-WTFGA-890
356-KRISN-360
1046-GYHLM-1050
456-FRKSN-460
806-LPDPSKPSKRSFIED-820
1196-SLIDL-1200
N
66-FPRGQ-70
206-SPARM-210
8
96-GGDGK-100
386-QKKQQ-390
166-TLPKG-170
206-SPARM-210
226-RLNQL-230
256-KKPRQ-260
316-GMSRI-320
366-TEPKK DKKKKADETQALPQRQKKQQTVTLPAADL-400
Orf1ab
nsp1
166-SSGVT-170
32
nsp2
306-VASPN-310
296-FMGRI-300
386-EYHNESGLKTILRKG-400
336-FVKAT-340
546-SIFSR-550
nsp3
1046-VEEAK-1050
1496-TPEEH-1500
1106-SGHNL-1110
1636-HTTDPSFLGRYMSAL-1650
1346-LKKCK-1350
2656-KLSHQ-2660
2186-TNSRI-2190
nsp4
3206-RYLAL-3210
nsp6
3836-DAFKL-3840
nsp8
4076-DYNTY-4080
nsp9
4226-KYLYF-4230
nsp10
4346-KGKYV-4350
nsp12
4516-MADLV-4520
4616-QTTPG-4620
4676-DRYFK-4680
4716-TSFGP-4720
5136-EFYAY-5140
nsp13
5346-RPFLC-5350
5746-FNSVC-5750
5836-ISPYN-5840
nsp14
6206-AVHEC-6210
5976-YRRLI-5980
6366-QLPFF-6370
nsp15
6716-ELEDF-6720
6536-VIWDY-6540
nsp16
6926-ISDMY-6930
Orf3a
66-LKKRWQ-70
136-KNPLL-140
4
136-KNPLL-140
176-TSPIS-180
176-TSPIS-180
216-STQLS-220
216-STQLS-220
Orf7a
116-LKRKT-120
26-GTTVL-30
3
66-ACPDG-70
116-LKRKT-120
Orf8
36-PCPIHFYSKWYIRVGARKSA
PLIEL-60
36-PCPIHFYSKWYIRVGARKSAPLIEL-60
1
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-2Orf1ab
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-19patients. 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-2Orf1ab 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-19patients. 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-19patients. 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-19patient.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-19patients
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-19patients 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-2S-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-19patients.
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-19patients 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-19patients 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-19patients.[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-19patients (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-2infection may confer protection.[29,30] The results
might also explain why most infectedpeople 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-19patients 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 humanHEK293 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-19patients 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).
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
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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
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
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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
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