Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Author:

Azzeri Amirah,Mohamed Nurul Azmawati,Wan Rosli Saarah HuurieyahORCID,Abdul Samat Muttaqillah Najihan,Rashid Zetti Zainol,Mohamad Jamali Muhamad Arif,Md Zoqratt Muhammad Zarul HanifahORCID,Mohammad Nasir Muhammad Azamuddeen,Ranjit Singh Harpreet Kaur,Azmi LiyanaORCID

Abstract

Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values—indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

Funder

Universiti Sains Islam Malaysia

Publisher

Public Library of Science (PLoS)

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