The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

Abstract

Background: The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.

Results: The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.

Conclusion: Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.

Keywords: RdRp; SARS-CoV-2; Severity of COVID-19.

Fig. 1

Positions of primer attachment sites and areas corresponding to each of the PCR amplicons, as well as the most specific mutations identified in the RdRp gene among the SARS-CoV-2 samples isolated from COVID-19 patients in relation to the sequence encoding the RdRp enzyme in the genome of the SARS-CoV-2 virus. Legend: Mutations shown in blue-green were identified only in viruses collected from the severe illness study group. The mutation shown in red was identified only in viruses collected from the symptomless study group. The mutation shown in purple was identified in both groups. The conserved domains identified by a Conserved Domain Search tool are shown as green boxes underneath the black line representing the sequence. The blue numbers above the black line are nucleotide positions, concordant with the SARS-CoV-2 reference sequence (NC_045512.2). The figure was prepared using (https://inkscape.org/) 1.3 software

Fig. 2

Study design scheme. Legend: n – number of analyzed cases, in vitro – analyses performed in the laboratory including Polish cohort of patients with different COVID-19 course; in silico – analyses performed with the use of the EpiCoV database in the GISAID repository, vs - versus

Fig. 3

The median number of mutations identified in RdRp gene among the SARS-CoV-2 samples isolated from outpatients and inpatients of Polish cohort. Legend: The dots represent participants (n = 77) identified with four clinical spectrums of COVID-19: 1st – outpatients, 2nd, 3rd and 4th – inpatients; error bars lines: bottom and top - quartiles Q1, Q3; middle - median; the statistically significant differences (p < 0.0001) were measured by U Mann Whitney test, two-tailed

Fig. 4

Spearman’s correlation coefficient between the studied variables: number of mutations, COVID-19 severity and age. Legend: COVID-19 severity was identified on a 5-point scale of clinical spectrum (5th degree of COVID-19 was not present in the studied patients), p < 0.05 was considered statistically significant, r - Spearman’s correlation coefficient, the arrows indicate the correlation between the variables

Fig. 5

The median number of identified mutations in the RdRp gene among the SARS-CoV-2 samples isolated from age-differentiated outpatients and inpatients of the Polish cohort. Legend: The dots represent participants (n = 77) divided into two age groups: 22 ≤ 48 and 51 ≤ 94; outpatients: 1st clinical spectrum of COVID-19; inpatients: 2nd, 3rd and 4th clinical spectrum of COVID-19; error bars lines: bottom and top - quartiles Q1, Q3; middle – median

Fig. 6

The heat map of the identified single nucleotide variants in the RdRp gene among the SARS-CoV-2 samples isolated from patients with different (1st, 2nd, 3rd, 4th) clinical spectrum of COVID-19. Legend: SNVs – single nucleotide variants described by the position in the genome of the SARS-CoV-2 reference strain NC_045512.2 and the type of mutation (nucleotide substitutions marked by >); each cell represents the percentage share of the mutation identified in the clinical group of patients (1st, 2nd, 3rd, 4th), expressed in the appropriate colour

Fig. 7

The percentage of occurrence of selected RdRp single nucleotide variants in the GISAID repository deposited with SARS-CoV-2 genome sequences. Legend: SNVs – single nucleotide variants described by the position in the genome of the SARS-CoV-2 reference strain NC_045512.2 and the type of mutation (nucleotide substitutions marked by >), *negative correlation between the number of positive samples and COVID-19 severity; Data was individually analyzed for Poland, Europe and the world, in all registered genomic sequences and in data deposited only in 2023. The occurrence of SNVs was analyzed using the EpiCoV database