Prototype strains of SARS-CoV-2 genetic lineages identified in the Primorsky Krai during the COVID-19 pandemic (2020–2023)

Full Text

Introduction

Chiroptera, one of the most numerous and distinctive [1, 2] orders of mammals (Mammalia), serve as hosts for a wide range of epidemiologically significant viruses [3–9], the most well-known of which is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Nidovirales: Coronaviridae), or Betacoronavirus pandemicum[1] (Sarbecovirus subgenus), which caused the COVID-19 pandemic (2020–2023) [10–14]. This pandemic is yet another striking example of a naturally endemic virus [15–17] overcoming the interspecies barrier, leading to the subsequent development of a dangerous epidemic situation—a scenario that experts had repeatedly warned about [18–21].

In the population of the new host — Homo sapiens, which is ubiquitous, has a high population density in areas of permanent settlement, and exhibits a high level of mobility (including transcontinental travel), SARS-CoV-2 rapidly spread across the entire planet, and its evolutionary process began, shaped by the characteristics of population structure, lifestyle, and herd immunity in specific regions [22–25].

In late 2020, the World Health Organization (WHO) proposed a system for classifying SARS-CoV-2 variants based on the risk they pose: Variants of Concern (VOC) and Variants of Interest (VOI); Five main genetic lineages of VOCs were identified: Alpha (B.1.1.7), first described in the United Kingdom [26]; Beta (B.1.351) — in South Africa [27]; Gamma (B.1.1.28.1, or P.1)—in Brazil [28], Delta (B.1.617.2)—in India², and Omicron (B.1.1.529)—in South Africa [29].

In March 2023, the WHO revised the SARS-CoV-2 classification system, defining variants that require enhanced monitoring of their spread due to the presence of genetic changes that are thought to affect pathogenicity, but for which evidence of epidemiological manifestations has not yet been obtained (VUM — Variant under monitoring). Despite significant progress in the development of diagnostic tests, vaccines, and antiviral drugs, which have helped combat the COVID-19 pandemic, SARS-CoV-2 remains widespread throughout the world. According to WHO data, more than 14,000 new cases were reported worldwide in April 2026, of which 586 were fatal³. Currently, the following SARS-CoV-2 variants are circulating globally: VUM (BA.3.2, KP.3.1.1, NB.1.8.1, XFG) and VOI (JN.1)⁴.

As the pandemic unfolded, it became clear that the course of the epidemic and the evolution of the virus could be influenced by geographical characteristics [30]. These characteristics are determined by a combination of factors: geographical location, population density and migration, the timeliness and stringency of restrictive measures, and the level of population immunity. Due to its geographic location and strategic importance in transportation, logistics, and foreign economic relations with the Asia-Pacific region, Primorsky Krai served as a unique model for studying the formation of the pathogen’s regional genetic landscape under the influence of both European and Asian sources of viral introduction [24].

The establishment of a collection of regional reference strains reflecting the key characteristics of the sublineages of the Wuhan, Delta, and Omicron genetic variants that circulated in Primorsky Krai during the pandemic will provide a foundation for subsequent comparative analysis of the genetic polymorphism and biological characteristics of evolving viral variants. Furthermore, prototype strains can be used as test subjects when evaluating the antiviral activity of known and newly developed compounds.

The aim of this study was to create a collection of characterized prototype regional SARS-CoV-2 strains representing the genetic lineages of the major genetic variants—Wuhan, Delta, and Omicron—isolated in Primorsky Krai during the COVID-19 pandemic.

Materials and methods

The study was conducted with the voluntary informed consent of the patients or their legal representatives. The study protocol was approved by the Ethics Committee of the G.P. Somov Research Institute of Epidemiology and Microbiology (hereinafter referred to as RIEM) under Rospotrebnadzor (Protocol No. 2 dated November 16, 2021).

Sample and data collection. Between February 17, 2020, and March 25, 2023, 1,200 nasopharyngeal swab samples were collected from residents of Primorsky Krai, provided by the region’s healthcare facilities and confirmed by positive SARS-CoV-2 RNA polymerase chain reaction (PCR) results (Ct values <  30). Among the patients, there were 648 (54%) women and 552 (46%) men; the mean age for women was 47.7 ± 5.3 years, and for men, 45.5 ± 4.8 years. The disease primarily presented as mild (68.4%) or moderate (29.3%) cases; severe cases were recorded in 2.3% of cases.

Detection of SARS-CoV-2 RNA in nasopharyngeal swabs from patients with clinically and laboratory-confirmed COVID-19 and in cell culture supernatants was performed using the reverse transcription followed by real-time PCR (RT-qPCR) method: RNA extraction was performed using the M-Sorb-NA reagent kit manually or (for large numbers of samples) on the AutoPure 96 automated workstation (Allsheng Instruments); RT-qPCR was performed using the RT-qPCR-SARS-CoV-2 reagent kit (“Sintol”). Positive samples with Ct <  25 (1,050 samples), intended for subsequent use in research, were stored at –20°C without breaking the cold chain. All samples were verified for the absence of other human acute respiratory viral pathogens using RT-qPCR test systems: AmpliSens ARVI-Screen-FL (Central Research Institute of Epidemiology) and AmpliSens Influenza Virus A/B-FL (Central Research Institute of Epidemiology).

SARS-CoV-2 was identified by whole genome sequencing on the Nanopore platform [31, 32] according to the ARTIC SARS-CoV-2 v. 3 protocol: reverse transcription was performed using the Midnight RT-PCR Expansion kit (EXP-MRT001, “Oxford Nanopore Technologies”); amplicons were amplified and barcoded using 29 pairs of overlapping primers and the Rapid Barcoding Kit 96 (SQK-RBK110.96, “Oxford Nanopore Technologies”); cDNA purification was performed using AMPure XP beads (“Nanopore”); the resulting genomic libraries were sequenced on a MinION instrument (“Oxford Nanopore Technologies”) using FLO-MIN106 R9.4.1 cells (“Oxford Nanopore Technologies”). The data obtained in FAST5 format (using the MinKNOW software package⁵ were converted to FASTQ format using Guppy v. 6.3.8⁶. SARS-CoV-2 genomes in FASTA format were assembled by aligning them to reference sequences from VGARus using the Epi2me v. 22 software package and the ARTIC v. 1 module⁷. To assess the quality of the assembled sequences and the distribution of genomes across lineages, we used Nextclade⁸ and Pangolin COVID-19 Lineage Assigner v. 4.3⁹.

Phylogenetic analysis of whole-genome nucleotide sequences was performed after multiple alignment using MAFFT v. 7.475¹⁰ via the “nearest neighbor” method using the MEGA v. 11.0.13 software package¹¹ with a bootstrap support level of 1,000 repetitions. Sequences in which the number of unrecognized or ambiguous nucleotides exceeded 10% of the SARS-CoV-2 whole-genome sequence were excluded from the sample for analysis. Based on the criteria described, 553 nucleotide sequences of SARS-CoV-2 genomes were selected. The obtained data were visualized using the iTOL v. 6 service¹².

Isolation of SARS-CoV-2 strains. Samples were clarified by centrifugation, filtered through Millex 220 nm filter cartridges, and seeded onto an 80% confluent monolayer of Vero E6 African green monkey kidney epithelial cells, grown in plastic conical-bottom tubes with an area of 5.5 cm² in DMEM medium supplemented with 1% fetal bovine serum and 100 IU/mL gentamicin. Infected cell cultures were incubated at 37°C in a 5% CO₂ atmosphere for 5–6 days or until cytopathic effects (CPE) appeared. The presence of the virus in the culture supernatant was confirmed by RT-qPCR. The virus-containing cell culture supernatant was centrifuged at 1,500 rpm, frozen in a cryopreservation solution (70% bovine serum, 10% glycerol) at –70°C, and deposited in the Collection of Pathogenic Microorganisms at the RIEM under the accession numbers R-4016, R-5188, R-5130, R-T37, R-4332, R-8726, R-6843, R-9035, R-P63, R-P60, and the National Database of Viral Genome Sequences (VGARus) (numbers prim000447, prim000100, prim000098, prim000448, prim000080, prim000041, prim000021, prim000051, prim000213, prim000210), GenBank (номера OR883952, OQ363274, OQ363272, OR883953, OQ363254, OQ318430, OQ318410, OQ318440, OR083734, OR083731), GISAID (numbers EPI_ISL_18559832, EPI_ISL_16756943, EPI_ISL_16756941, EPI_ISL_18559835, EPI_ISL_16746963, EPI_ISL_16643370, EPI_ISL_16641839, EPI_ISL_16644009, EPI_ISL_17738935, EPI_ISL_17738932).

The reproductive properties of SARS-CoV-2 strains were assessed based on the decrease in the cycle threshold (Ct) of RT-qPCR during isolation (passage 0) and in three consecutive passages on day 5 after inoculation of the Vero E6 cell line.

The cytopathogenicity of SARS-CoV-2 strains was determined based on the results of the MTT assay. The essence of this method lies in the ability of viable cells to convert the highly soluble yellow 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) into insoluble intracellular crystals of (E,Z)-5-(4,5-dimethylthiazol-2-yl)-1,3-diphenylformazan (MTT-formazan) under the action of intracellular dehydrogenases [33, 34]. On day 5 post-infection, 20 μL of a 5 mg/mL MTT solution was added to the wells containing cells in a 96-well plate; the plates were incubated at 37°C in a 5% CO₂ atmosphere for 2 hours. After removing the culture medium, 150 μL of isopropyl alcohol acidified with 0.4 M HCl was added to each well; the optical density (OD) in each well was determined at 540 nm (near the absorption maximum of MTT-formazan) after subtracting the background OD value at 620 nm using a microplate photometer.

The cytopathogenicity level (CPL) of the strain at a specific dilution was calculated using the formula:

$CPL = (1 – D_v/D_0) \times 100\%$, (1)

where CPL (cytopathogenicity level) is the CPE level; D_v is the OD of the infected sample; D₀ is the OD of the supernatant from an uninfected cell culture.

The infectivity of SARS-CoV-2 strains was expressed in decimal logarithms of the 50% tissue culture infectious dose (TCID₅₀) per 1 mL for Vero E6 cells. The value z lg TCID₅₀/mL means that diluting 1 mL of virus-containing fluid 10^z times in Vero E6 culture medium will result in a CPL value of 50%, according to (1).

The plaque-forming ability of SARS-CoV-2 strains was determined on Vero E6 cell cultures, which were grown for 24 hours in a 24-well culture plate in DMEM medium containing 10% fetal calf serum and 100 IU/mL gentamicin at 37°C, 5% CO₂. Subsequently, the growth medium was removed from the wells, virus-containing liquid (200 μL/well, 2.0 log₁₀ TCID₅₀/mL) was added, and the plates were incubated for 1 hour, after which the medium was removed, a 1.7% carboxymethylcellulose solution in maintenance medium containing 1% fetal bovine serum was added, and the cells were cultured for 5 days at 37°C, 5% CO₂. The carboxymethylcellulose solution was then removed, the cells were washed, and fixed with ice-cold 96% ethyl alcohol. The fixed cells were stained with a 2% alcohol solution of crystal violet, photographed, and the plaque sizes were determined using the ImageJ software¹³.

Assessment of the suitability of strains as test subjects for determining the antiviral activity of the reference drug — the SARS-CoV-2 RNA-dependent RNA polymerase inhibitor remdesivir (RPR).

The antiviral activity of RPR was assessed by the degree of inhibition of cytopathic effect (CPE) using the MTT assay and by viral replication using RT-qPCR. A monolayer of Vero E6 cells at 80% confluence, grown in 96-well plates, was infected with SARS-CoV-2 strains at a dose of 2.0 log₁₀ TCID₅₀/mL with simultaneous addition of RPR at concentrations of 0.125–25 μg/mL, and the cells were cultured for 5 days at 37°C and 5% CO₂. The protection index (PI(C)) for each concentration C was calculated using the formula:

$PI\left(C\right) = (D_{si} – D_i)/(D_0 – D_i) \times 100\%$, (2)

where D is the optical density (OD) in the MTT assay: D₀ is the OD of uninfected cells without the drug; D_i is the OD of infected cells without the drug; D_si — infected cells in the presence of the drug. The 50% inhibitory concentration (IC₅₀) was calculated using linear-logarithmic interpolation as the root of the equation:

$PI\left(I{C}_{50}\right) = 50\%$. (3)

The cytotoxicity index (CI(C)) for each concentration C was calculated using the formula:

$CI\left(C\right) = D_s/D_0 \times 100\%$, (4)

where D_s is the OD in the MTT assay for uninfected cells in the presence of the drug. The 50% cytotoxic concentration (CC₅₀) was calculated using linear-logarithmic interpolation as the root of the equation:

$CI\left(C{C}_{50}\right) = 50\%$. (5)

Similarly:

$CI\left(C{C}_{90}\right) = 90\%$. (6)

The antiviral efficacy of the drug was assessed using the selectivity index (SI):

$SI = C{C}_{50}/I{C}_{50}$. (7)

When using the results of RT-qPCR, the PCR protection index (PPI(C)) serves as an analog of PI(C); for each concentration C, it was calculated using the formula developed by M.Yu. Shchelkanov [35]:

$PPI\left(C\right) = \left(\frac{C_{tsi} – C{t}_i}{2^{{С}_{t0} – C_{ti}} – 1}\right)\times 100\%$, (8)

where C_t represents the threshold cycles in RT-qPCR: C_t0 = 36.0 — uninfected cells without the drug; C_ti — infected cells without the drug; C_tsi — infected cells in the presence of the drug.

Statistical analysis of the data was performed using the Statistica v. 10 software package and MS Excel. The Mann–Whitney nonparametric test was used to assess the significance of differences in quantitative characteristics. The sample parameters presented in the tables below are defined as follows: M — arithmetic mean; n — size of the analyzed subgroup; δ — standard deviation; 95% confidence interval (CI); p — significance level. The confidence level was set at 95%; results were considered statistically significant when the probability of the alternative hypothesis was p <  0.05.

Results

We previously conducted a molecular genetic analysis of 553 SARS-CoV-2 samples isolated in the Primorsky Krai during the COVID-19 pandemic (2020–2023) that represented the genetic lineages of the major genetic variants: Wuhan, Delta, and Omicron [24]. From these, we selected 100 samples that best represented the diversity of SARS-CoV-2 genetic variants and sublineages circulating in this region (2–4 samples for each sublineage). The samples were passaged three times in sequence on Vero E6 cell culture. The virus’s reproductive efficiency after each passage was assessed based on the decrease in the PCR cycle threshold, the level of cytopathogenicity (in the MTT assay), and the viral titer. To conduct a detailed study of the virus’s biological properties and molecular-genetic characteristics, 10 strains with the highest reproductive activity were selected from the SARS-CoV-2 sublineages of the Wuhan, Delta, and Omicron genetic variants, which were dominant in Primorsky Krai during the pandemic. The accession numbers of the whole-genome nucleotide sequences of the selected strains in the VGARus, GenBank, and GISAID molecular genetic databases are presented in Table 1. Phylogenetic analysis of these nucleotide sequences, performed after multiple alignment, revealed a clear division of SARS-CoV-2 strains into clades corresponding to the main WHO genetic variants and genetic lineages (according to the Pango classification): early Wuhan-like variants (B.1.1, B.1.1.317, B.1.1.397, B.1.1.485), Delta (AY.121, AY.122), and Omicron (BA.1.1, XBB.1.36, XBB.1.5.24).

 

Table 1. Genetic Characterization of Prototypical SARS-CoV-2 Strains Isolated in the Primorsky Krai During the COVID-19 Pandemic

Genetic variant	Genetic lineage	Date of sample collection for strain isolation	Severity of the disease	Strain deposit number in the RIEM collection	Deposit number of the whole-genome nucleotide sequence in a molecular genetics database
					VGARus	GenBank	GISAID
Wuhan	B.1.1.	09.11.2020	Severe	R-4016	prim000447	OR883952	EPI_ISL_18559832
	B.1.1.317	23.12.2020		R-5188	prim000100	OQ363274	EPI_ISL_16756943
	B.1.1.397	22.12.2020		R-5130	prim000098	OQ363272	EPI_ISL_16756941
	B.1.1.485	19.02.2021	Severe, Fatal	R-Т37	prim000448	OR883953	EPI_ISL_18559835
	B.1.1.	25.11.2020	Moderate	R-4332	prim000080	OQ363254	EPI_ISL_16746963
Delta	AY.121	23.12.2021	Moderate	R-8726	prim000041	OQ318430	EPI_ISL_16643370
	AY.122	18.06.2021		R-6843	prim000021	OQ318410	EPI_ISL_16641839
Omicron	BA.1.1	15.02.2022	Mild	R-9035	prim000051	OQ318440	EPI_ISL_16644009
	XBB.1.36	14.04.2023		R-P63	prim000213	OR083734	EPI_ISL_17738935
	XBB.1.5.24	14.04.2023		R-P60	prim000210	OR083731	EPI_ISL_17738932

 

Prototype strains of SARS-CoV-2 genetic lineages identified in the Primorsky Krai during the COVID-19 pandemic (2020–2023), deposited in the State Collection of Pathogens of Viral Infections and Rickettsioses at the State Research Center for Virology and Biotechnology Vector under numbers V-3461, V-3462, V-3463, V-3464, V-3465, V-3466, V-3467, V-3468, V-3469, V-3470.

Analysis of SARS-CoV-2 strains revealed the presence of genetic changes (mutations) in the coding regions of genes responsible for the synthesis of both structural proteins (S, M, E, N) and non-structural proteins (ORF1ab, ORF3a, ORF6, ORF7, ORF8) (Table 2). All genetic variants studied were characterized by the presence of key mutations: D614G in the S protein, P314L and P323L—in the RNA-dependent RNA polymerase (NSP12) encoded by ORF1b. These substitutions are associated with a simultaneous decrease in the virus’s pathogenicity and an increase in its transmissibility¹⁴ [36–39]. Strains of the Wuhan genetic variant (R-4016, R-5188, R-5130, R-T37) contained the mutations W64R, M153T, H245R, T259K, A522V, H655Y, N679K, and S686R, which are absent in the reference strain Wuhan-Hu-1. The highest number of these substitutions was detected in strain R-4016 (B.1.1), isolated in the fall of 2020, and strain R-T37 (B.1.1.485), isolated in 2021 from autopsy material of a patient who died of COVID-19 (Table 2). The R-8726/2021 (Delta/AY.121) strain was found to carry the following mutations: T19R, T95I, E156G, F157-, R158-, L452R, T478K, D614G, P681R, D950N, D63G, R203M, G215C, D377Y, and G142D in the S protein, as well as the A520S and G142D substitutions, which are associated with increased infectivity [39–41]. Strain R-6843/2021 (Delta/AY.122) was characterized by a deletion at positions 157–158 (Δ(157–158)) in the S protein, which distinguished it from the typical variant, where an amino acid substitution from E to G (E156G) was observed at this position. Strains R-P60/2023 (Omicron/XBB.1.5.24) and R-P63/2023 (Omicron/XBB.1.36) contained mutations that were both characteristic of the prototypical XBB lineage and distinct from it (R346K in the RBD, Y145D substitution in the N-terminal domain (Table 2)).

 

Table 2. Mutations in prototype SARS-CoV-2 strains isolated in Primorsky Krai during the COVID-19 pandemic

Genetic variants	Genetic lineage	Number of whole-genome sequences in Primorsky Krai	Number of whole-genome sequences worldwide (excluding Primorsky Krai)	Mutations in the S protein of prototype strains		Prevalence of strains with this S-protein phenotype, %
				strain	mutations	Primorsky Krai	Worldwide
Wuhan	B.1.1	180	62267	R-4016	H245R	0.5	0.01
					H655Y	0.5	9.2
					N679K	48	8.8
					S686R	0.5	0.01
				R-4332	M153T	66	1.5
	B.1.1.317	12	2534	R-5188	A522V	8.3	0.01
	B.1.1.397	43	506	R-5130	T768A	2.6	0.01
	B.1.1.485	3	69	R-T37	W64R	100	0.01
					T259K	100	0.01
					N679K	100	0.01
					S686R	100	0.01
Delta	AY.122	82	210870	R-6843	G142D	95	61
	AY.121	3	32032	R-8726	G142D	100	55
					A520S	50	0.01
Omicron	BA.1.1	14	1036912	R-9035	G142D (Y145D)	56	92
					K417N	94	70
					N440K	92	74
	XBB.1.5.24	11	3368	R-P60	H69-	27	0.2
					V70-	27	0.2
	XBB.1.36	3	52	R-P63	H69-	100	1.9
					V70-	100	1.9
					D1260Y	100	1.9

 

The reproductive properties and infectivity levels of SARS-CoV-2 strains during passage in the Vero E6 cell line are presented in Table 3. The strains of the Wuhan genetic variant exhibited the highest replication rate, as assessed by the decrease in the RT-qPCR cycle threshold over three consecutive passages on day 5 after infection of Vero E6 cells. These same strains formed large plaques (up to 0.8 mm); the Omicron genetic variants formed the smallest plaques (0.4 mm) (Figure). A comparative analysis showed that strains of the Wuhan genetic variant exhibited maximum CPL values when interacting with Vero E6 cells starting from the early stages of cultivation (first passage), while strains of the Omicron genetic variant were characterized by minimum CPL values. At the third passage, the CPL was 77.0 ± 1.2 and 56.7 ± 3.3%, with infectivity levels of 6.4 ± 0.4 and 4.5 ± 0.3 lg TCID₅₀/mL, for the Wuhan and Omicron genetic variants, respectively (p <  0.05), indicating a decrease in the virus’s replicative activity during its evolution (Table 3).

 

Table 3. Virulence of prototypical SARS-CoV-2 strains from various genetic lineages, isolated in the Primorsky Krai during the COVID-19 pandemic, in Vero E6 cell culture

Genetic variant	Genetic lineage	Strain deposit number in the RIEM collection	Passage 0		Passage I			Passage II			Passage III
			CPL, %	Сt	CPL, %	Сt	lg TCID50/mL	CPL, %	Сt	lg TCID50/mL	CPL, %	Сt	lg TCID50/mL
Wuhan	B.1.1.	R-4016	90	17.3	90	17.4	4.0	70	15.2	5.0	80	13,2	5,0
	B.1.1.317	R-5188	50	20.0	60	19.1	4.0	75	15.1	5.0	80	12,0	6,0
	B.1.1.397	R-5130	50	20.4	70	16.8	5.0	80	14.8	5.5	75	12,2	7,0
	B.1.1.485	R-T37	80	21.1	80	21.1	4.5	80	14.5	4.5	75	14,1	7,5
	B.1.1.	R-4332	50	21.8	50	19.1	4.5	70	16.6	5.0	80	14,7	6,5
M ± δ (95% CI)			64.0 ± 8.1 (39.7– 88.2)	20.1 ± 0.7 (17.9–22.2)	70.0 ± 7.1 (50.3–89.6)	18.7 ± 0.8 (16.6–20.7)	4.4 ± 0.2 (3.8–4.9)	75 ± 2.2 (68.7–81.2)	15.2 ± 0.4 (14.2–16.2)	5.0 ± 0.2 (4.5–5.4)	77.0 ± 1.2 (74.5–81.4)	13.2 ± 0.5 (11.7–14.7)	6.4 ± 0.4 (5.2–7.5)
Delta	AY.121	R–8726	50	25	60	19.8	4.0	65	16.2	4.0	75	15	5,0
	AY.122	R–6843	60	19	70	18.3	5.0	60	15.5	5.0	70	13,8	6,0
M ± δ			55.0 ± 5.0	22.0 ± 3.0	65.0 ± 5.0	19.1 ± 0.8	4.5 ± 0.5	62.5 ± 2.5	15.8 ± 0.3	4.5 ± 0.5	72.5 ± 2.5	14.4 ± 0.6	5.5 ± 0.5
Omicron	BA.1.1	R–9035	50	34.2	50	32.7	2.5	50	19.5	3.5	50	17,2	4,0
	XBB.1.36	R–P63	50	27.4	50	22.3	2.5	60	18.1	3.5	60	16,2	4,5
	XBB.1.5.24	R–P60	30	20.0	30	23.0	2.5	50	19.0	3.0	60	17,0	5,0
M ± δ (95% CI)			43.3 ± 6.6* (14.6–72.3)	27.2 ± 4.1 (9.5–44.8)	43.3 ± 6.2 (14.6–72.0)	26.0 ± 3.3 (11.5–40.4)	2.5 ± 0.0* (–)	53.0 ± 3.3* (38.9–67.7)	18.8 ± 0.4 (17.1–20.6)	3.3 ± 0.2* (2.6–4.0)	56.7 ± 3.3* (42.3–71.0)	16.8 ± 0.3 (15.4–18.1)	4.5 ± 0.3* (3.2–5.7)

Note. *p <  0.05 compared to the Wuhan genetic variant.

 

Plaque-forming ability of prototypical SARS-CoV-2 strains from various genetic variants on a Vero E6 monolayer coated with carboxymethylcellulose on day 5 after inoculation.

 

A comparison of the intracellular replication of the strains in response to RPR revealed effective suppression of all three virus variants with a high selective index (SI = 80–180) (Table 4). The Vero E6 cell protection index (PPI) increased significantly from 36.5 ± 4.1% upon infection with strain R-5188 (Wuhan, B.1.1.317) to 66.7 ± 7.3% upon exposure to strain R-P63 (Omicron, XBB.1.36) (p <  0.05), while the IC₅₀ decreased from 0.90 ± 0.10 to 0.40 ± 0.05 μg/mL, respectively. These results demonstrate that a lower concentration of RPR is required to effectively inhibit Omicron strain replication in Vero E6 cells, while the CC₅₀ remained unchanged at 72.0 ± 9.1 μg/mL.

 

Table 4. Sensitivity to RPR of prototype SARS-CoV-2 strains from various genetic lineages isolated in the Primorsky Krai during the COVID-19 pandemic, M ± δ (95% CI)

SARS-CoV-2 strains			МТТ test		RT-qPCR
Genetic variant	Genetic lineage	Strain deposit number in the RIEM collection	IC50, mcg/mL	SI	Ctsi	Cti	PPI, %
Wuhan	B.1.1.317	R-5188	0.90 ± 0.10 (0.74–1.01)	80.41 ± 8.12 (67.91–88.08)	24.00 ± 2.90 (20.07–27.92)	9.84 ± 1.10 (8.78–10.79)	36.50 ± 4.10 (30.58–42.01)
Delta	AY.121	R-8726	0.60 ± 0.10W (0.40–0.80)	120.00 ± 14.89W (105.49–142.50)	27.54 ± 3.30 (24.52–31.67)	12.53 ± 1.51 (10.31–15.08)	51.40 ± 6.24W (44.38–57.77)
Omicron	XBB.1.36	R-P63	0.40 ± 0.05W D (0.31–0.50)	180.00 ± 22.45W D (161.09–216.69)	31.37 ± 3.75 (27.88–34.23)	13.25 ± 1.75 (12.24–15.08)	66.74 ± 7.31W D (60.48–73.79)

Note. ^Wp <  0,05 relative to the Wuhan genotype; ^Dp< 0,05 relative to the Delta genetic variant.

 

Discussion

This study characterizes the SARS-CoV-2 strains that circulated in the Primorsky Krai during the COVID-19 pandemic. The data obtained on the molecular-genetic characteristics and biological properties of SARS-CoV-2 strains are consistent with general global trends in the virus’s evolution and reveal regional characteristics that may be relevant for epidemiological forecasting and assessing the effectiveness of protective measures.

Bioinformatics analysis of whole-genome sequencing data from regional SARS-CoV-2 strains revealed not only typical mutations associated with increased transmissibility and altered pathogenicity, but also mutations not characteristic of the prototype genetic lineages.

In Wuhan-like strains circulating in the Primorsky Krai, a range of amino acid substitutions was identified that distinguishes them from the reference strain Wuhan-Hu-1. Notably, some of these mutations (H655Y, N679K) are located near the furin cleavage site (S1/S2) — a region critical for infectivity [40, 41]. This indicates that, even in the early stages of the pandemic, genetically distinct viral lineages were circulating in the region, having evolved along their own path.

The substitutions in the antigenic sites of the S protein in regional SARS-CoV-2 strains, which may influence the immune response, deserve special attention. In particular, the following mutations, which are atypical for the Omicron/BA.1.1 sublineage, have been detected in regional strains: the Y145D substitution in the N-terminal domain (from neutral tyrosine to negatively charged aspartic acid), the (214–216)/EPE (two polar, negatively charged glutamic acids separated by a single neutral proline), which alters the protein’s surface charge, and the R346K mutation in the RBD are potentially capable of influencing immune recognition and leading to escape from neutralizing antibodies [42, 43]. Delta variant strains circulating in the region are characterized by a set of mutations in the N-terminal domain (G142D, E156G, F157G in combination with the Δ157–158 deletion). The G142D mutation in Delta and Omicron variant strains is also a known marker of viral antibody evasion, and the combination of these changes likely significantly alters the conformation of the antigenic supersite, further reducing the effectiveness of the humoral immune response [44].

Thus, mutations in SARS-CoV-2 genetic lineages detected in the Primorsky Krai during the COVID-19 pandemic, affect critical antigenic sites, suggesting possible local evolutionary trends of SARS-CoV-2 and underscoring the importance of regional phylogenetic monitoring for an adequate assessment of epidemiological risks and the effectiveness of preventive measures. Our data are consistent with observations regarding the presence of unique polymorphisms characteristic of SARS-CoV-2 strains detected in various regions of the Russian Federation [30, 45].

The panel of representative regional SARS-CoV-2 strains that has been established can be used for subsequent comparative analysis of genetic polymorphisms and biological characteristics of potentially epidemiologically dangerous variants of the virus in the Primorsky Krai.

Furthermore, the SARS-CoV-2 strains under investigation were used as test subjects to determine their sensitivity to an antiviral drug. It is known that SARS-CoV-2 uses two pathways to enter target cells: fusion of the viral envelope with the membrane (when there is high expression of transmembrane serine protease 2 (TMPRSS2)) and clathrin-dependent endocytosis involving cathepsins (at low levels of TMPRSS2 expression) [46]. The Wuhan and Delta genetic variants predominantly use the TMPRSS2-dependent pathway, while Omicron variants show a marked shift toward endocytosis [47]. Using Vero E6 cells, which express virtually no TMPRSS2 [48], we were able to assess the intracellular replication of the Wuhan, Delta, and Omicron genetic variants under conditions of an identical endocytic, cathepsin L-dependent entry pathway. The Wuhan genetic variant virus strains proved to be the most replicatively active, as confirmed by their maximum cytopathic effect and the highest level of infectivity. The less efficient replication of the Omicron variant was accompanied by a decrease in its cytopathic effect, as evidenced by lower titers and the formation of smaller plaques compared to similar indicators in strains of the Wuhan and Delta genetic variants.

To verify the suitability of the strains under study as test subjects for determining sensitivity to therapeutic agents [49], we used RPR¹⁵ — one of the first chemotherapeutic agents approved for the treatment of COVID-19. This drug was selected due to its antiviral activity, which is based on a targeted mechanism of action (direct inhibition of viral RNA-dependent RNA polymerase (RdRp)) [50].

RPR inhibited the CPE of all viral genetic variants with a high selectivity index (SI), indicating its efficacy (Table 3). At the same time, the Vero E6 cell protection index increased in the sequence Wuhan → Delta → Omicron. These results show that effective suppression of Omicron strains requires a lower concentration of RPR (decreased IC₅₀) while the cytotoxicity of the drug itself (CC₅₀) remains unchanged, which shifts the selective index upward.

It should be noted that differences in the sensitivity of strains to chemotherapeutic agents may be due to the complex interaction of a variety of factors, including replication mechanisms, genetic variability during evolutionary adaptation, the drug’s access to reproductive loci in the endoplasmic reticulum, and the physiology of the infected cell [51].

The most common and clinically significant mutations (P314L and P323L) in the highly conserved RdRp enzyme—which is the target of the drug—are associated with sensitivity to RPR. According to a study [52], the P323L mutation is characteristic of various genetic variants of the SARS-CoV-2 virus, does not affect sensitivity to RPR, and has a prevalence of up to 99.35% of all sequenced genomes worldwide. Less common RdRp mutations associated with drug resistance occur at a frequency of less than 0.5% [53]. In this study, when examining the amino acid composition of SARS-CoV-2 RdRp in strains of all genetic variants circulating in the Primorsky Krai, no differences were found in the prevalence of the P314L and P323L mutations. It follows that the suppression of the Wuhan, Delta, and Omicron strains in Vero E6 cell culture by RPR may be associated not only with the drug’s direct effect on the virus (RdRp inhibition) but also with other biological properties of the virus that have evolved along the Wuhan → Delta → Omicron lineage.

Thus, this study characterizes a panel of prototype SARS-CoV-2 strains isolated in the Primorsky Krai during the COVID-19 pandemic, belonging to the Wuhan (B.1.1, B.1.1.x), Delta (B.1.617.2.x), and Omicron (BA.1.x, XBB.x) genetic variants, which have been deposited in the Collection of Pathogenic Microorganisms at the RIEM. These strains can be used for subsequent comparative analysis of genetic polymorphisms and biological characteristics of evolving virus variants that may emerge in the Primorsky Krai, as well as for the development of treatments and preventive measures for COVID-19.

Conclusion

A regional collection of SARS-CoV-2 prototype strains (Wuhan, Delta, Omicron) that circulated in Primorsky Krai during the COVID-19 pandemic (2020-2023) has been established, and their biological and molecular-genetic properties have been characterized. The strains have been deposited in the State Collection of Pathogens of Viral Infections and Rickettsioses at the Vector State Research Center of Virology and Biotechnology.

The studied strains exhibit mutation patterns characteristic of their genetic lineages. Combinations of these mutations determine the regional specificity of the virus.

The Wuhan strains exhibit the highest replicative activity and caused the most pronounced cytopathic effect on Vero E6 cells. The Omicron strains are characterized by the lowest values for these parameters, reflecting a general trend toward decreased virulence during the course of the pandemic.

Regional prototype strains can be used for further comparative studies of genetic polymorphism and the biological properties of potentially epidemiologically significant evolving variants of the virus, as well as for the development of treatments and preventive measures for COVID-19.

 

¹ Along with traditional virus names, it is now common practice to use binary nomenclature [5] recommended by the International Committee on Taxonomy of Viruses.

² European Centre for Disease Prevention and Control. Threat Assessment Brief: Emergence of SARS-CoV-2 B.1.617 variants in India and situation in the EU/EEA. Stockholm: ECDC; 2021. URL: https://www.ecdc.europa.eu/en/publications-data/threatassessment-emergence-sars-cov-2-b1617-variants

³ WHO COVID-19 dashboard. Number of COVID-19 cases reported to WHO. URL: https://data.who.int/dashboards/covid19/cases?n=c

⁴ WHO COVID-19 dashboard / SARS-CoV-2 variant circulation / Weekly prevalence of SARS-CoV-2 VOIs and VUMs. URL: https://data.who.int/dashboards/covid19/summary?n=c

⁵ Payne A., Holmes N., Rakyan V., Loose M. BulkVis: a graphical viewer for Oxford nanopore bulk FAST5 files. Bioinformatics. 2019;35(13):2193–2198. DOI: https://doi.org/10.1093/bioinformatics/bty841

⁶ Wick R.R., Judd L.M., Holt K.E. Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome Biol. 2019;20(129). DOI: https://doi.org/10.1186/s13059-019-1727-y

⁷ URL: https://epi2me.nanoporetech.com/

⁸ Aksamentov I., Roemer C., Hodcroft E.B., Neher R.A. Nextclade: clade assignment, mutation calling and quality control for viral genomes. JOSS. 2021;6(67):3773. DOI: https://doi.org/10.21105/joss.03773

⁹ O’Toole A., Scher E., Underwood A., et al. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evolution. 2021;7(2):veab064. DOI: https://doi.org/10.1093/ve/veab064

¹⁰ Katoh K., Standley D.M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability.Mol. Biol. Evol. 2013;30(4):772–780. DOI: https://doi.org/10.1093/molbev/mst010

¹¹ Kumar S., Stecher G., Li M. et al. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 2018;35(6):1547–1549. DOI: https://doi.org/10.1093/molbev/msy096

¹² Letunic I., Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation (full article).Nucleic Acids Res. 2021;49(1):293–296. DOI: https://doi.org/10.1093/nar/gkab301

¹³ URL: https://imagej.net

¹⁴ Mutations for genetic lines were verified using the Outbreak.info service.

¹⁵ State Register of Medicines. Remdesivir PSC [lyophilisate for the preparation of concentrate for infusion solution] (2020). Registration Certificate LP-No. (005276)-(RG-RU).

About the authors

Mikhail Yu. Shchelkanov

G.P. Somov Institute of Epidemiology and Microbiology; Far Eastern Federal University

Email: adorob@mail.ru
ORCID iD: 0000-0001-8610-7623

D. Sci. (Biol.), Corresponding member of the Russian Academy of Sciences, Director; Head, Department of epidemiology, microbiology and parasitology with the International scientific and educational center for biological safety of Rospotrebnadzor, School of Life Sciences and Biomedicine

Russian Federation, Vladivostok; Vladivostok

Natalya V. Krylova

G.P. Somov Institute of Epidemiology and Microbiology

Author for correspondence.
Email: krylovanatalya@gmail.com
ORCID iD: 0000-0002-9048-6803
https://niivostok.ru/

D. Sci. (Biol.), leading researcher, Head, Laboratory of respiratory infections

Russian Federation, Vladivostok

Alexey A. Belik

G.P. Somov Institute of Epidemiology and Microbiology

Email: belic_a_a@mail.ru
ORCID iD: 0000-0002-0303-3188

Cand. Sci. (Biol.), researcher, Laboratory of respiratory infections

Russian Federation, Vladivostok

Elena V. Persiyanova

G.P. Somov Institute of Epidemiology and Microbiology

Email: helen-pers@yandex.ru
ORCID iD: 0000-0002-5686-8672

Cand. Sci. (Biol.), researcher, Laboratory of respiratory viral infections

Russian Federation, Vladivostok

Yurii A. Belov

G.P. Somov Institute of Epidemiology and Microbiology; Far Eastern Federal University

Email: belov.ya@dvfu.ru
ORCID iD: 0000-0001-8313-5610

junior researcher, Head, Center for molecular diagnostics; assistant, Department of epidemiology, microbiology and parasitology with the International scientific and educational center for biological safety of Rospotrebnadzor, School of Life Sciences and Biomedicine

Russian Federation, Vladivostok; Vladivostok

Olga S. Maistrovskaya

G.P. Somov Institute of Epidemiology and Microbiology

Email: osmas2103@mail.ru
ORCID iD: 0009-0003-8013-4489

junior researcher, Laboratory of respiratory infections

Russian Federation, Vladivostok

Anastasiya A. Mikhalko

G.P. Somov Institute of Epidemiology and Microbiology; Far Eastern Federal University

Email: nastya.mikhalko@inbox.ru
ORCID iD: 0009-0002-0185-8458

laboratory research assistant, Laboratory of respiratory infections; student, School of Life Sciences and Biomedicine

Russian Federation, Vladivostok; Vladivostok

Mariya F. Trofimova

G.P. Somov Institute of Epidemiology and Microbiology

Email: shestaksin@gmail.com
ORCID iD: 0009-0001-7105-9849

junior researcher, Laboratory of respiratory infections

Russian Federation, Vladivostok

Marina N. Prosyannikova

Center for Hygiene and Epidemiology in Primorsky krai

Email: marpros67@mail.ru
ORCID iD: 0009-0002-5265-8106

Head, Laboratory of viral and particularly dangerous bacterial infections

Russian Federation, Vladivostok

Olga B. Romanova

Center for Hygiene and Epidemiology in Primorsky krai

Email: fguz@pkrpn.ru
ORCID iD: 0009-0006-3852-1014

chief physician

Russian Federation, Vladivostok

Tatyana N. Detkovskaya

Office of Rospotrebnadzor for Primorsky Krai

Email: detkovskaya_tn@pkrpn.ru
ORCID iD: 0000-0002-7543-0633

Head

Russian Federation, Vladivostok

Anna I. Simakova

Pacific State Medical University

Email: anna-inf@yandex.ru
ORCID iD: 0000-0002-3334-4673

D. Sci. (Med.), Head, Department of infectious diseases

Russian Federation, Vladivostok

Sergey P. Kryzhanovskiy

Medical Association of the Far Eastern Branch of the Russian Academy of Sciences

Email: priemmodvoran@mail.ru
ORCID iD: 0000-0002-1981-1079

D. Sci. (Med.), Professor, Corresponding member of the Russian Academy of Sciences, Scientific Head

Russian Federation, Vladivostok

Tatyana S. Zaporozhets

G.P. Somov Institute of Epidemiology and Microbiology

Email: niiem_vl@mail.ru
ORCID iD: 0000-0002-8879-8496

D. Sci. (Med.), leading researcher, Laboratory of respiratory viral infections

Russian Federation, Vladivostok

References

Supplementary files