Whole Genome Sequencing for Revealing the Point Mutations of SARS-CoV-2 Genome in Bangladeshi Isolates and their Structural Effects on Viral Proteins (preprint)

Coronavirus disease-19 (COVID-19) is the recent global pandemic caused by the virus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The virus has already killed more than one million people worldwide and billions are at risk of getting infected. As of now, there is neither any drug nor any vaccine in sight with conclusive scientific evidence that it can cure or provide protection against the illness. Since novel coronavirus is a new virus, mining its genome sequence is of crucial importance for drug/vaccine(s) development. Whole genome sequencing is a helpful tool in identifying genetic changes that occur in a virus when it spreads through the population. In this study, we performed complete genome sequencing of SARS-CoV-2 to unveil the genomic variation and indel, if present. We discovered thirteen (13) mutations in Orf1ab, S and N gene where seven (7) of them turned out to be novel mutations from our sequenced isolate. Besides, we found one (1) insertion and seven (7) deletions from the indel analysis among the 323 Bangladeshi isolates. However, the indel did not show any effect on proteins. Our energy minimization analysis showed both stabilizing and destabilizing impact on viral proteins depending on the mutation. Interestingly, all the variants were located in the binding site of the proteins. Furthermore, drug binding analysis revealed marked difference in interacting residues in mutants when compared to the wild type. Our analysis also suggested that eleven (11) mutations could exert damaging effects on their corresponding protein structures. The analysis of SARS-CoV-2 genetic variation and their impacts presented in this study might be helpful in gaining a better understanding of the pathogenesis of this deadly virus.

Machine learning analysis highlights the down-trending of the proportion of COVID-19 patients with a distinct laboratory result profile (preprint)

BackgroundNew York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2 confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. MethodsWe performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. ResultsA COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle-threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without COVID19-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. ConclusionsOur study visualized the down-trending of the proportion of SARS-CoV-2 patients with the distinct COVID19-HRP. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.