ISSN 0006-2979, Biochemistry (Moscow), 2024, Vol. 89, No. 5, pp. 872-882 © Pleiades Publishing, Ltd., 2024.
872
Humoral and Cellular Immune Response
to SARS-CoV-2 S and N Proteins
Zulfiia E. Afridonova
1
, Anna P. Toptygina
1,2,a
*, and Ilya S. Mikhaylov
3
1
G.N.Gabrichevsky Research Institute for Epidemiology and Microbiology, 125212 Moscow, Russia
2
Lomonosov Moscow State University, 119991 Moscow, Russia
3
Moscow Power Engineering Institute, 111250 Moscow, Russia
a
e-mail: toptyginaanna@rambler.ru
Received September 2, 2023
Revised October 12, 2023
Accepted November 1, 2023
AbstractThe pandemic of a new coronavirus infection that has lasted for more than 3 years, is still accompanied
by frequent mutations in the S protein of SARS-CoV-2 and emergence of new virus variants causing new disease
outbreak. Of all coronaviral proteins, the S and N proteins are the most immunogenic. The aim of this study was
to compare the features of the humoral and T-cell immune responses to the SARS-CoV-2 S and N proteins in peo-
ple with different histories of interaction with this virus. The study included 27 individuals who had COVID-19
once, 23 people who were vaccinated twice with the SputnikV vaccine and did not have COVID-19, 22 people who
had COVID-19 and were vaccinated twice with Sputnik V 6-12 months after the disease, and 25 people who had
COVID-19 twice. The level of antibodies was determined by the enzyme immunoassay, and the cellular immunity
was assessed by the expression of CD107a on CD8
high
lymphocytes after recognition of SARS-CoV-2 antigens. It was
shown that the humoral immune response to the N protein was formed mainly by short-lived plasma cells synthe-
sizing IgG antibodies of all four subclasses with a gradual switch from IgG3 to IgG1. The response to the S protein
was formed by short-lived plasma cells at the beginning of the response (IgG1 and IgG3 subclasses) and then by
long-lived plasma cells (IgG1 subclass). The dynamics of antibody level synthesized by the short-lived plasma cells
was described by the Fisher equation, while changes in the level of antibodies synthesized by the long-lived plas-
ma cells were described by the Erlang equation. The level of antibodies in the groups with the hybrid immunity
exceeded that in the group with the post-vaccination immunity; the highest antibody content was observed in
the group with the breakthrough immunity. The cellular immunity to the S and N proteins differed depending
on the mode of immune response induction (vaccination or disease). Importantly, the response of heterologous
CD8
+
Tcell to the N proteins of other coronaviruses may be involved in the immune defense against SARS-CoV-2.
DOI: 10.1134/S0006297924050080
Keywords: COVID-19, SARS-CoV-2, N protein, S protein, antibodies, vaccination, hybrid immunity, cellular immunity,
breakthrough immunity
Abbreviations: BAU, binding antibody unit; COVID-19,coro-
navirus infectious disease 19; SARS-CoV-2,acute respiratory
syndrome coronavirus2.
* To whom correspondence should be addressed.
INTRODUCTION
Recent pandemic of the new coronavirus infection
that has lasted for more than 3 years, is still accompa-
nied by frequent mutations in the S protein of SARS-
CoV-2 (acute respiratory syndrome coronavirus2) and
emergence of new virus variants causing further dis-
ease outbreaks, suggesting that this infection will re-
main with humanity for many more years. Although
it might become less severe, the fight against it may
turn into a permanent problem [1]. The most immuno-
genic of coronavirus proteins are the S and N proteins
[2] that induce generation of large amounts of anti-
bodies in response to the SARS-CoV-2 infection [3, 4].
Anti-SARS-CoV-2 vaccines target the S protein, since an-
tibodies against this protein provide strong protection
against the infection. However, frequent mutations in
IMMUNE RESPONSE TO SARS-CoV-2 S AND N PROTEINS 873
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
the S protein have led to a decrease in the efficacy of
existing vaccines [5, 6]. The interest of researcher in
the S protein has left the N protein somewhat in the
shadows. This protein is highly conserved among coro-
naviruses and is one of the most abundant structural
proteins in the virus-infected cells [7]. The main func-
tion of the N protein is to package the viral genomic
RNA into a long helical ribonucleocapsid complex and
participate in the virion assembly through interaction
with the viral genome and membrane protein  M  [8].
The location of the N protein in the center of the coro-
navirus virion explains why even high levels of anti-
bodies against this protein do not protect against the
disease, as the antibodies cannot enter the assembled
virion and contact the N protein. Moreover, the effects
of anti-N protein antibodies are poorly understood [9].
At the same time, the N-protein is a representative
antigen in the T-cell response against the infection.
Itwas shown that the T-cell response formed against
SARS-CoV-1 persists for many years [10-12]. Since the
N protein is highly conserved, it contains epitopes
that could generate T-cell immune responses that are
cross-reactive across SARS-CoV-2 and other human
coron aviruses [13].
The purpose of this study was to compare the
characteristics of humoral and T-cell immune respons-
es to the SARS-CoV-2 S and N proteins in people with
different histories of interaction with the virus.
MATERIALS AND METHODS
Analyzed cohorts and collection of biological
material. Simple open-label comparative study in-
cluded 97 adult volunteers aged 18-73 years. Of these,
27 people had a history of mild to moderate COVID-19
(coronavirus disease 19) confirmed by at least one
positive PCR test (group  1; post-infectious immunity).
They were examined 4 to 7 times over 1-18 months
from the disease onset. Group  2 (post-vaccination im-
munity) consisted of 23  people who were vaccinated
twice with the Sputnik  V vaccine and did not have
COVID-19. Group 3 (hybrid immunity) included 22  peo-
ple who had COVID-19 and were vaccinated twice
with Sputnik  V 6-12 months after the disease. Group  4
(breakthrough immunity) included 25 people who had
COVID-19 twice: the first time in 2020-2021 and again
in 2022 (omicron strain). Blood for the study was taken
from the ulnar vein into two vacuum tubes (4  ml each)
containing either heparin (cellular immunity studies)
or coagulation activator and gel for isolating blood se-
rum (assessment of the humoral immune response to
the SARS-CoV-2 antigens), respectively. The study was
approved by the Ethics Committee of the Gabrichevsky
Research Institute for Epidemiology and Microbiology
(protocol no.  58; December15, 2021). Informed volun-
tary consent was obtained from each participant in-
cluded in the study.
Evaluation of antibody levels. Blood serum was
obtained by centrifugation, transferred into Eppendorf
tubes, and stored at –70°C until the study. The antibody
content was determined by the enzyme immunoassay
using the SARS-CoV-2-IgG quantitative-ELISA-BEST
kit (JSC Vector-Best, Novosibirsk, Russia) for the anti-
S  protein antibodies and N-CoV-2-IgG PS kit for the
anti-N  protein antibodies (Saint-Petersburg Pasteur
Institute, St. Petersburg, Russia). The subclasses of IgG
antibodies to the SARS-CoV-2 antigens were studied
using a previously developed modification of ELISA
method [14,  15]. Briefly, we used 96-well panels with
adsorbed full-length S antigen from the SARS-CoV-2-
IgG quantitative-ELISA-BEST kit or with the N  protein
from the N-CoV-2-IgG PS kit. Instead of anti-IgG conju-
gates included in the kit, peroxidase-labeled anti-IgG1,
IgG2, IgG3, and IgG4 monoclonal antibodies (Polignost,
St.Petersburg, Russia) were used at a concentration of
1  μg/ml. All other stages of the assay were carried out
according to the kit instructions.
Assessment of cellular immunity. Mononuclear
cells were isolated from heparinized blood under ster-
ile conditions using gradient centrifugation (ρ = 1.077;
PanEco, Russia) and washed from platelets. The cells
were transferred to the wells of a sterile 96-well plate
(2.5  ×  10
5
cells per well) containing RPMI-1640 medium
supplemented with 2  mM L-glutamine, gentamicin, and
10% fetal calf serum (PanEco). Monensin (final con-
centration, 10 μM) and PE-Cy5-labeled monoclonal an-
tibody against CD107a (final dilution, 1  :  100) (control
samples) were added to the wells; the final volume
in the well was 200 μl. In experimental samples the
cells were stimulated with the SARS-CoV-2 S and N
antigens using the plates from the corresponding an-
tibody ELISA kits (see above) that had the S or N pro-
teins adsorbed at the bottom of the wells. Since the
ELISA plates were not sterile, they were sterilized by
ultraviolet irradiation for 30  min before the experi-
ment. All ingredients were added equally to both the
experimental and control wells, according to the pre-
viously developed method. Experimental and control
samples were incubated at 37°C in a humidified atmo-
sphere with 5%  CO
2
for 20  h, transferred into the tubes
for cytofluorimetry, washed with CellWash (300g for
5  min), stained with FITC-labeled antibodies against
CD8 for 20 min in the dark at 4°C, washed again un-
der the same conditions, and immunophenotyped us-
ing a BD FACS CantoII flow cytometer (Becton Dickin-
son Technologies and Software, USA). When analyzing
the results, we established the lymphoid gate and the
gate for lymphocytes highly expressing the CD8 anti-
gen (CD8
high
) within it and calculated the percentage
of CD8
high
CD107a
+
cells, i.e., cytotoxic T lymphocytes
that recognized the S or N antigens and responded by
AFRIDONOVA et al.874
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
releasing the content of cytotoxic granules (cytotoxic
attack). The level of 1% was considered as the limit
of spontaneous expression of the CD107a molecule on
CD8
high
lymphocytes [15].
Statistical analysis. The normality of data distri-
bution was determined by the Kolmogorov–Smirnov
method. The levels of anti-S  protein and anti-N  protein
IgG antibodies did not show the normal distribution.
The antibody content was expressed in antibody bind-
ing unit (BAU) per ml and presented as the median
(1st-3rd quartile) [Me (LQ-HQ)]. The differences be-
tween the groups were assessed using the Mann–Whit-
ney U  test. The percentage content of IgG subclasses
and cellular immunity parameters showed normal dis-
tribution and were presented as mean± standard er-
ror of mean (M  ±  SEM). The correlations were assessed
using the Pearson method. The differences were con-
sidered significant at p<0.05.
Modeling. The data on the changes in the con-
tent of anti-S protein and anti-N protein IgG antibod-
ies over time elapsed from the disease onset were ap-
proximated. The observed changes corresponded to a
distribution with the following characteristics: the ini-
tial value corresponded to the origin of coordinates; a
sharp increase in the function value to a certain max-
imum followed by its smooth decrease. As is known
from mathematical statistics, this type of distribution
is described by the Fisher and Erlang distributions.
These functional dependencies are widely known in
statistical analysis, probability theory, and biology and
belong to the Pearson typeIII distribution group (gam-
ma distributions). Our study examined two of them.
The first one was the Erlang distribution(1)
f(x; k, λ, c) = c ·
λ
k
·x
k−1
·e
λx
(k − 1)!
, (1)
where k is the shape parameter and λ is the rate pa-
rameter. The normalization coefficient c was intro-
duced to scale the function values. The combination
of k and λ determines the graph extremum position,
the function value at the extremum point, and the
function inflection smoothness.
The second one was the Fisher distribution(2):
f(x; n, m, c) =
{
c ·
x
n
2
−1
(
1 +
n·x
)
n+m
m
2
x ≥ 0
,
(2)
where coefficients n and m affect the shape of the
graph and the position and value of the function max-
imum; the coefficient c is also normalizing.
The Erlang distribution is characterized by a
smoother increase and decrease in the function val-
ues, while the Fisher distribution allows to describe
the functions whose values drop sharply after reach-
ing the maximum and then smoothly and asymptoti-
cally tend to zero.
0
x < 0
In this study, the general form of the approximat-
ing function was chosen based on the nature of ob-
served dependencies. We used an algorithmic process
to sort through the coefficient values to achieve the
best estimate of the standard deviation of the resulting
approximation curve from the experimental data.
RESULTS
The changes in the content of IgG antibodies
against SARS-CoV-2 antigens in the blood serum of
patients who had recovered from COVID-19 (group 1)
are presented in Fig.  1. The figure shows that the IgG
antibodies recognizing the N protein (curve 1) ap-
peared earlier and their concentration increased fast-
er in the blood with a sharp peak at 1033.2 (807.04-
1215.6)  BAU/ml 3 months after the disease onset, flowed
by a rapid decrease to 75.5 (25.5-182.2) BAU/ml after
18 months (kit cut-off value, 33.5 BAU/ml). The con-
tent of anti-S protein antibodies (curve  2) increased
more slowly and reached a plateau at 819.5 (614.7-
1538.3)BAU/ml 4 months after the disease onset, where
it remained for a year, and then decreased to 551.6
(372.5-757.5) BAU/ml by 18 months. The curve reflect-
ing the concentration of anti-N  antibodies was well ap-
proximated by the Fisher distribution (Fig. 1, curve 3)
according to the formula(3):
f
Nprotein
(x) = 8 · 10
8
 ·
(0.2x)
5.5
(1 + 0.52x)
9
. (3)
Table  1 compares the data obtained by analyz-
ing the content of anti-N protein IgG antibodies in the
blood serum of individuals who had recovered from
COVID-19 and the results calculated using formula(3).
The experimental and calculated data differ by less
than 15%, while the calculation results strictly fall into
the LQ-HQ interval for all studied time points.
The attempts to approximate curve  2 reflecting
the concentration of anti-S protein antibodies with any
known distribution were unsuccessful. We assumed
that the curve is the result of two processes: forma-
tion of early antibody response to the S protein by
short-lived plasma cells and generation of antibodies
by long-lived plasma cells (curves4 and5 in Fig.1, re-
spectively). Both formation and death of plasma cells
are reflected in the concentration of antibodies they
produce. This process has the following properties: the
initial value corresponds to the origin of coordinates;
the antibody concentration then sharply increases to a
certain maximum value followed by a smooth decrease
in the function value. As is known from mathematical
statistics, this curve can be described by the Fisher
and Erlang distributions. Therefore, it was necessary
to adjust the two distributions so that their sum cor-
responded to curve2 in Fig.1. In this case, formation
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BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
Fig. 1. The content of IgG antibodies to SARS-CoV-2 virus antigens. Curves: 1)IgG antibodies to the N protein (experimental
data); 2)IgG antibodies to the S protein (experimental data); 3)Fisher approximation of the content of IgG antibodies against
the Nprotein (short-lived plasma cells); 4)Fisher approximation of the content of IgG antibodies against the S protein (short-
lived plasma cells); 5)Erlang approximation of the content of IgG antibodies against the S protein (long-lived plasma cells).
Table 1. Comparison of the experimental data on the content (BAU/ml) of IgG antibodies against SARS-CoV-2
N protein in the blood serum from recovered individuals and the results of calculations using formula(3)
Time from
the disease onset
IgG antibodies against
N protein [Me (LQ-HQ)]
Calculation according
to the Fisher formula (3)
Deviation of the calculated value
from the experimental value, %
1 month 230.9 (118.4-430.6) 264.34 –14.5%
2 months 899.2 (497.8-1225.9) 846.74 5.83%
3 months 1033.2 (807.04-1215.6) 1020.38 1.2%
4 months 870.1 (319.7-3790.36) 940.00 –8.0%
6 months 579.3 (374.3-2524.9) 637.55 –10.1%
12 months 211.5 (116.9-507.3) 180.55 14.6%
18 months 75.5 (25.5-182.2) 66.76 11.6%
of antibodies by the early producers was also approx-
imated with the Fisher distribution (curve  4 in Fig.  1)
according to the formula(4):
f
Sprotein Fisher
(x) = 7 · 10
5
 ·
(0.2x)
4.5
(1 + 0.66x)
13.75
, (4)
while the curve describing the synthesis of antibodies
by the long-lived plasma cells (curve 5 in Fig. 1) was
approximated by the Erlang distribution(5):
f
Sprotein Erlang
(x) = 1100 · 
3.1
5.1
· (0.11x)
4.1
 ·e
−3.1x
4!
. (5)
AFRIDONOVA et al.876
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
Table 2. Comparison of the experimental data on the content (BAU/ml) of IgG antibodies against SARS-CoV-2
Sprotein in the blood serum from recovered individuals and the results of calculations using formulas(4) and(5)
Time from
the disease
onset
S protein
[Me (LQ-HQ)]
Calculation
according to the
Fisher formula (4)
Calculation
according to the
Erlang formula (5)
Sum of calculations
obtained using
formulas(4) and (5)
Deviation of the sum
of the calculated values
from the experimental
data, %
1 month
103.3
(73.37-189.1)
89.60 1.23 90.83 12.1%
2 months
456.2
(199.2-1027.1)
439.30 14.96 454.26 0.4%
3 months
787.4
(356.1-1190.2)
687.89 56.07 743.96 5.5%
4 months
819.5
(614.7-1538.3)
718.62 129.69 848.31 –3.5%
6 months
841.8
(614.9-1420.7)
491.38 345.69 837.07 0.6%
12 months
810.9
(504.5-1215.3)
70.82 766.21 837.03 –3.2%
18 months
551.6
(372.5-757.5)
10.98 522.10 533.08 3.4%
When searching for the best values of approxi-
mating curve coefficients, we excluded the data corre-
sponding to 6 months from the disease onset. Instead,
this data point was used as a test point to avoid model
overtraining.
Table  2 compares the experimental data on the
levels of anti-S  protein IgG antibodies and approxima-
tion results obtained using the formulas (4) and (5).
In can be seen that the sums of the value calculated
using formulas (4) and (5) deviate from the experi-
mentally obtained values by no more than 13% and
strictly fall into the calculated LQ-HQ intervals at all
time points. When selecting the optimal coefficients
for the Fisher and Erlang formulas(3),(4), and(5), in
order to assess the quality of the applied models, we
calculated the root mean square error (RMSE) and the
mean absolute percentage error (MAPE) as the quality
metrics. When modeling the changes in the content of
anti-N protein IgG antibody with time occurring from
the disease onset using the coefficients presented in
formula (3), we obtained the minimum values of the
quality metrics (RMSE, 16.505; MAPE, 9.408%), indicat-
ing a good quality of the proposed model.
The minimum values of the quality metrics (RMSE,
8.949; MAPE, 4.096%) calculated using the coefficients
presented in formulas(4) and(5) also indicated a high
quality of the proposed model.
The changes in the relative content of IgG sub-
classes against the N and S proteins are shown in Fig.2.
Interesting, the N protein induced production of all
four IgG subclasses (although IgG2 and IgG4 were mi-
nor), whereas only the IgG1 and IgG3 subclasses of
anti- S  protein antibodies were detected, while anti-
S  protein IgG2 and IgG4 antibodies were absent. The hu-
moral response to both proteins showed the same trend:
IgG3 antibodies were gradually replaced by IgG1 an-
tibodies, indicating antibody response maturation, al-
though the rate and completeness of such replacement
differed. Thus, IgG1 antibodies represented 54.6  ±  2.7%
of all anti-S  protein antibodies already one month after
the disease onset vs. 35.2  ±  1.1% of anti-N protein IgG1
antibodies at the same time point. Within a year, the
fraction of anti-N protein IgG1 antibodies increased
to 71.38  ±  3.2% and remained at this level for another
6  months. In the case of the S protein, the content of
anti-S  protein IgG1 antibodies rapidly increased to
97.4  ±  0.5% 6 months after the disease onset, reached
100% by 12 months in all tested individuals, and re-
mained at this level for at least another 6 months.
Figure  3 shows a comparison between the levels
of anti-N  protein and anti-S  protein IgG antibodies for
the four studied groups 3 months after the disease on-
set (group  1), 3 months after immunization with the
second dose of vaccine (groups2 and3), and 3  months
after the recurrent disease onset (omicron strain)
(group 4). The content of antibodies varied in differ-
ent groups. Thus, in patients who had recovered from
COVID-19 once (group 1), the level of anti-N  protein
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Fig. 2. Changes in the content of different subclasses of IgG antibodies against SARS-CoV-2 antigens. a)N protein. b)S protein.
antibodies varied greatly, but did not significantly
exceed the level of anti-S  protein antibodies. No anti-
N  protein antibodies were detected in individuals vac-
cinated with Sputnik  V (group  2), which can be ex-
plained by the absence of N protein in this vaccine.
Ingroup3 with the hybrid immunity (vaccination 6-12
months after COVID-19), the content of anti-N protein
IgG antibodies was significantly lower (p =  0.018) than
the level of antibodies to the S-protein. The content of
anti-S  protein antibodies in group  3 was significantly
higher (p =  0.004) than in group  2. Group  4 with the
breakthrough immunity (patients who had COVID-19
twice) demonstrated a significant increase in the levels
of both anti-S  protein (p =  0.0006) and anti-N  protein
(p = 0.042) antibodies compared to group1.
Figure 4 shows a contribution of IgG1 antibodies
to the overall IgG response to the N and S proteins.
Interestingly, all anti-S  protein IgGs in all 4 groups
were of the IgG1 subclass. At the same time, the frac-
tion of anti-N  protein IgG1 antibodies was 72.8  ±  3.5%
in group 1. This subclass of antibodies was complete-
ly absent in group 2, since the vaccinated individuals
did not form a response to this protein. In group3, the
relative content of IgG1 antibodies did not differ sig-
nificantly from that in group1 (75.9  ±  3.8%), which is
understandable, since the immune response in these
patients had formed during the primary COVID-19
event, while the vaccine used for the following vacci-
nation later did not contain the N protein. In group4
(patients who had COVID-19 twice), the percentage of
IgG1 antibodies reached 99.1  ±  0.3%, which was signifi-
cantly different from groups1 and3 (p <  0.01), indicat-
ing that maturation of anti-N protein antibodies contin-
ued with the secondary response to the N protein.
AFRIDONOVA et al.878
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
Fig. 3. Comparison of levels of IgG antibodies against N and S proteins in patients recovered from COVID-19 (group1), individu-
als vaccinated twice with SputnikV (group2), patients who had been ill with COVID-19 and then were vaccinated with SputnikV
(group3), and patients who had recovered from COVID-19 twice (group4).
Fig. 4. Contribution of IgG1 antibodies to the overall IgG response to the SARS-CoV-2 N and S proteins.
The results on the cellular immune response to
the N and S antigens are presented in Fig.  5. The cellu-
lar response to the S protein did not differ significant-
ly between the studied groups, although it was slightly
higher in the group with the breakthrough immunity.
The cellular response to the N protein in group3 was
significantly lower than in groups 1 and 4 (p <  0.05).
We expected no cellular response to the N protein in
group  2 (individuals vaccinated with Sputnik V), as
in the case of humoral immune response. Indeed, we
saw no cellular response in 17 people in this group;
however, 6 people, who did not have the antibodies
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BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
Fig. 5. Cellular immune response to the N and S proteins of SARS-CoV-2.
against the N  protein, as well as lacked antibodies to
the S  protein, prior to the vaccination demonstrated
a significant cellular response to the N protein, which
resulted in the average response level of 5.94± 2.3%
in group2. There was a strong positive correlation be-
tween the levels of cellular responses to the N and S
proteins (r =  0.937). We also revealed a weak positive
correlation between the humoral and cellular respons-
es to the S protein (r=0.358) and the absence of such
correlation for the N protein.
DISCUSSION
We found that in the individuals who had recov-
ered from COVID-19, the concentration of IgG anti-
bodies to the N protein in the blood increased faster
than the concentration of anti S-protein antibodies.
The content of anti-N  antibodies showed a higher and
sharper peak and a more rapid decline. Similar results
were obtained by other researchers [16]. The curve
describing changes in the concentration of anti-N  pro-
tein antibodies was well approximated by the Fisher
distribution (Fig.  1), which is a special case of the Pear-
son distribution. In the case under consideration, the
antibody concentration in the blood was influenced
by two independent events: formation of early, short-
lived plasma cells that synthesized these antibodies,
which was followed by the death of these cells over
time, resulting in the decrease in the antibody con-
centration. The changes in the level of anti-S protein
antibodies had a different pattern. The concentration
of these antibodies increased more slowly, and instead
of a peak, reached a plateau that lasted up to a year,
after which the content of the antibodies gradually de-
creased. Our attempts to approximate this curve with a
single function were unsuccessful. We believe that the
curve representing changes in the anti-S  antibody con-
centration is a sum of two independent processes. The
first process, which is formation of early, short-lived
plasma cells synthesizing anti-S  protein antibodies, is
similar to that observed during formation of anti-N
protein antibodies and could be well approximated
by the Fisher distribution. The peak formation of the
antibodies by the short-lived plasma cells occurred at
3 months after the disease onset for both anti-N  pro-
tein and anti-S proteins antibodies. The second parts
of the curves ran almost parallel to each other, indi-
cating that the respective processes were identical (see
Fig. 1). The second event was the formation of long-
lived plasma cells that also synthesized anti-S  protein
antibodies. This second process was more prolonged
in time and could be approximated by the Erlang dis-
tribution (γ-distribution). This function is also a spe-
cial case of the Pearson distribution and is applicable
to describe the results of two continuous independent
events over time, in our case, formation and death of
long-lived plasma cells producing anti-S  protein anti-
bodies, which was reflected in the concentration of
these antibodies in the blood.
It is known that short-lived plasma cells synthe-
size predominantly IgG3 antibodies, while long-lived
AFRIDONOVA et al.880
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
plasma cells produce mainly IgG1 antibodies [17]. In-
terestingly, the initial response to the N protein repre-
sented formation of mostly IgG3 antibodies had been
formed in, while the switch to the IgG1 subclass oc-
curred slowly, with the content of IgG1 reaching ~  70%
within 6 months after the disease onset and remaining
at this level even after 1.5 years. Similar results were
obtained by other researchers [18]. At the same time,
in response to the S protein, this switch had occurred
much faster; the fraction of IgG1 exceeded 90% with-
in 3 months after the disease onset and then reached
100%. Presumably, these differences are due to the
fact that the short-lived plasmacytes dominated in the
response to the N protein, while the response to the
S protein was accompanied by the formation of long-
lived plasmacytes as well. It is also very likely that the
differences in the response to the two highly immu-
nogenic proteins of SARS-CoV-2 are associated with the
functions of these proteins. Thus, the N protein is lo-
cated inside the virion and is active at the stage of vi-
rus replication; anti-N  protein antibodies are not pro-
tective [9]. On the contrary, the S protein is located on
the virion surface and is responsible for the virus at-
tachment and fusion with the infected host cell; there-
fore, the antibodies against this protein can block the
SARS-CoV-2 infection [19].
If our approximations of changes in the antibody
levels are correct, then according to the Erlang func-
tion, the level of anti-S  protein antibodies should fall
slightly below 300  BAU/ml 2 years after the disease on-
set, decrease to ~40  BAU/ml after 3  years, and drop
below 10  BAU/ml (a cut off between the negative and
positive levels of these antibodies) after 4  years. Sim-
ilar dynamics in the antibody levels was observed in
patients who suffered from SARS-CoV-1 and MERS vi-
ruses [20]. Perhaps. this would have been the case if
SARS-CoV-2 had not mutated so often and had been
eliminated from the human population. Unfortunate-
ly, the reality presents a different picture. SARS-CoV-2
actively mutates; most mutations occur in the S pro-
tein, while the N protein remains the most conserved
one [21]. Such mutations allow the virus to evade the
antibody defense, leading to recurrent illnesses. Also,
active vaccination of the population has adjusted the
duration of antibody protection against SARS-CoV-2.
We studied 4 groups of people who had different histo-
ries of contact with SARS-CoV-2. People vaccinated twice
with Sputnik  V did not differ from those who had re-
covered from COVID-19 in the anti-S protein antibody
level and relative content of IgG subclasses. However,
the concentrations of both anti-N protein and anti-
S  protein antibodies in the individuals who had been ill
with COVID-19 twice (at the beginning of the pandemic
and again with the Omicron variant) were significantly
higher than in people who had been ill once. Interest-
ingly, not only the level of anti-N  protein anti bodies in-
creased, but these antibodies have become represented
almost completely by the IgG1 subclass. This suggests
that although the level of anti-N protein antibodies,
and therefore the content of plasma cells that synthe-
size them, were already very low at the time of relapse,
memory B cells responded with the secondary immune
response to the repeated recognition of the N  protein,
resulting in additional maturation of anti-N protein an-
tibodies. Anti-S  protein antibodies demonstrated a high
booster effect in the recurrent disease.
Both S and N proteins induced formation of cel-
lular immune response of CD8
+
cytotoxic lymphocytes.
It has been shown that T  cell respond not only to the
structural, but also to the accessory proteins of SARS-
CoV-2 [22]. The levels of response to the S protein in
the four studied groups did not differ significantly. This
indicates that CD8
+
lymphocytes are actively involved
in the immune response to both the disease and vac-
cination against COVID-19. Thus, it was shown that
pre-existing T  cells specific to the SARS-CoV-2 proteins
are able to prevent the development of the COVID clin-
ical picture [23]. The level of cellular response to the
N-protein in the group with the hybrid immunity (peo-
ple who had recovered from COVID-19 and were lat-
er vaccinated with Sputnik  V) was significantly lower
than in the group of patients who had recovered from
the disease, which could be explained by the absence
of N  protein in the composition of this vaccine. The
discovery of a high cellular immune response to the
N  protein in 6 people in the vaccinated group was
unexpected. However, they did not have anti-N  pro-
tein antibodies, and before vaccination, no antibodies
against the SARS-CoV-2 S  protein were detected. We be-
lieve that his may be due to a heterologous immune
response. It is likely that these people had previously
suffered from one of the common cold coronaviruses,
which had circulated freely in the human population
even before 2019. The N protein is extremely conserved
and contains epitopes that can cause the cross-reactiv-
ity of the T  cell-mediated immunity response among
different coronaviruses [13]. Any viral protein can be
an antigen for a T  cell response and trigger an attack
of cytotoxic cells. It is possible that such heterologous
immune response to the N protein of the common cold
coronaviruses has provided protection in people who
had mild or asymptomatic COVID-19. On the other
hand, it cannot be excluded that these 6 people suf-
fered from SARS-CoV-2 asymptomatically and without
IgG formation, but responded by forming the T cell re-
sponse, as it has been described before [24].
CONCLUSION
In conclusion, we demonstrated that the humor-
al immune responses to the S and N proteins of SARS-
IMMUNE RESPONSE TO SARS-CoV-2 S AND N PROTEINS 881
BIOCHEMISTRY (Moscow) Vol. 89 No. 5 2024
CoV-2 could form independently of each other. In our
case, the N protein induced formation of predominant-
ly short-lived plasma cells synthesizing IgG antibod-
ies of all four subclasses with a gradual switch from
IgG3 to IgG1 (about 70%). The response to the S pro-
tein included formation of both short-lived plasma-
cytes (which formed at the beginning of the response)
and long-lived plasmacytes. Short-lived plasma cells
respond to the S-protein with the synthesis of IgG1
and IgG3 subclasses, while long-lived plasma cells pro-
duced IgG1 antibodies. The changes in the content of
antibodies synthesized by the short-lived plasma cells
were described by the Fisher distribution, while the
Erlang distribution was more suitable to describe the
levels of antibodies synthesized by the long-lived plas-
ma cells. The content of antibodies in the groups with
the hybrid immunity exceeded the antibody levels in
people with the post-vaccination immunity. The con-
tent of antibodies in the group with the breakthrough
immunity it exceeded that in groups with the post-in-
fectious and post-vaccination immunity. The cellular
immunity to the S and N proteins varied depending
on the method of immune response induction (vacci-
nation or disease). Importantly, heterologous immune
response of CD8
+
T cells to the N protein of other coro-
naviruses may be involved in the immune protection
against SARS-CoV-2.
Acknowledgments. The authors express their grat-
itude to the Pasteur Research Institute of Epidemiology
and Microbiology (St.Petersburg, Russia) for providing
N-CoV-2-IgG PS test kits.
Contributions. Z.E.A. conducted experiments;
A.P.T. developed the study concept, supervised the
study, conducted experiments, discussed results, wrote
and edited the manuscript; I.S.M. carried out mathe-
matical modeling and discussed the results.
Funding. The work was carried out within the
framework of R&D project 121021100125-4 (02/10/2021).
Ethics declarations. All studies were conducted
in accordance with the principles of biomedical ethics
as outlined in the 1964 Declaration of Helsinki and its
later amendments. Each participant in the study pro-
vided a voluntary written informed consent after re-
ceiving an explanation of the potential risks and ben-
efits, as well as the nature of the upcoming study. The
authors of this work declare that they have no con-
flicts of interest.
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