Genomic landscape of alpha-variant of SARS-CoV-2 circulated in Pakistan

Estimation of unconfirmed COVID-19 cases from a cross-sectional survey of >10 000 households and a symptom-based machine learning model in Gilgit-Baltistan, Pakistan

Introduction

Robust estimates of COVID-19 prevalence in settings with limited capacity for SARS-CoV-2 molecular and serologic testing are scarce. We aimed to describe the epidemiology of confirmed and probable COVID-19 in Gilgit-Baltistan, and to develop a symptom-based predictive model to identify infected but undiagnosed individuals with COVID-19.

Methods

We conducted a cross-sectional survey in 10 257 randomly selected households in Gilgit-Baltistan from June to August 2021. Data regarding SARS-CoV-2 testing, healthcare worker (HCW) diagnoses, symptoms and outcomes since March 2020 were self-reported by households. 'Confirmed/probable' infection was defined as a positive test, HCW COVID-19 diagnosis or HCW pneumonia diagnosis with COVID-19-positive contact. Robust Poisson regression was conducted to assess differences in symptoms, outcomes and SARS-CoV-2 testing rates. We developed a symptom-based machine learning model to differentiate confirmed/probable infections from those with negative tests. We applied this model to untested respondents to estimate the total prevalence of SARS-CoV-2 infection.

Results

Data were collected for 77 924 people. Overall, 314 (0.5%) had confirmed/probable infections, 3263 (4.4%) had negative tests and 74 347 (95.1%) were untested. Children were tested less often than adults (adjusted prevalence ratio (aPR) 0.08, 95% CI 0.06 to 0.12 for ages 1-4 years vs 30-39 years), while males were tested more often than females (aPR 1.51, 95% CI 1.40 to 1.63). In the predictive model, area under the receiver operating characteristic curve was 0.92 (95% CI 0.90 to 0.93). We estimate there were 8-17 total SARS-CoV-2 infections for each positive test (8-17:1). The ratio of estimated to confirmed cases was higher for ages 1-4 years (211-480:1), 5-9 years (80-185:1) and for females (13-25:1).

Conclusions

From March 2020 to August 2021, the majority of SARS-CoV-2 infections in Gilgit-Baltistan went unconfirmed, particularly among women and children. Predictive models which incorporate self-reported symptoms may improve understanding of the burden of disease in settings lacking diagnostic capacity.

An ncRNA transcriptomics-based approach to design siRNA molecules against SARS-CoV-2 double membrane vesicle formation and accessory genes

BACKGROUND

The corona virus SARS-CoV-2 is the causative agent of recent most global pandemic. Its genome encodes various proteins categorized as non-structural, accessory, and structural proteins. The non-structural proteins, NSP1-16, are located within the ORF1ab. The NSP3, 4, and 6 together are involved in formation of double membrane vesicle (DMV) in host Golgi apparatus. These vesicles provide anchorage to viral replicative complexes, thus assist replication inside the host cell. While the accessory genes coded by ORFs 3a, 3b, 6, 7a, 7b, 8a, 8b, 9b, 9c, and 10 contribute in cell entry, immunoevasion, and pathological progression.

METHODS

This in silico study is focused on designing sequence specific siRNA molecules as a tool for silencing the non-structural and accessory genes of the virus. The gene sequences of NSP3, 4, and 6 along with ORF3a, 6, 7a, 8, and 10 were retrieved for conservation, phylogenetic, and sequence logo analyses. siRNA candidates were predicted using siDirect 2.0 targeting these genes. The GC content, melting temperatures, and various validation scores were calculated. Secondary structures of the guide strands and siRNA-target duplexes were predicted. Finally, tertiary structures were predicted and subjected to structural validations.

RESULTS

This study revealed that NSP3, 4, and 6 and accessory genes ORF3a, 6, 7a, 8, and 10 have high levels of conservation across globally circulating SARS-CoV-2 strains. A total of 71 siRNA molecules were predicted against the selected genes. Following rigorous screening including binary validations and minimum free energies, final siRNAs with high therapeutic potential were identified, including 7, 2, and 1 against NSP3, NSP4, and NSP6, as well as 3, 1, 2, and 1 targeting ORF3a, ORF7a, ORF8, and ORF10, respectively.

CONCLUSION

Our novel in silico pipeline integrates effective methods from previous studies to predict and validate siRNA molecules, having the potential to inhibit viral replication pathway in vitro. In total, this study identified 17 highly specific siRNA molecules targeting NSP3, 4, and 6 and accessory genes ORF3a, 7a, 8, and 10 of SARS-CoV-2, which might be used as an additional antiviral treatment option especially in the cases of life-threatening urgencies.

Dynamics of water-mediated interaction effects on the stability and transmission of Omicron

SARS-Cov-2 Omicron variant and its highly transmissible sublineages amidst news of emerging hybrid variants strengthen the evidence of its ability to rapidly spread and evolve giving rise to unprecedented future waves. Owing to the presence of isolated RBD, monomeric and trimeric Cryo-EM structures of spike protein in complex with ACE2 receptor, comparative analysis of Alpha, Beta, Gamma, Delta, and Omicron assist in a rational assessment of their probability to evolve as new or hybrid variants in future. This study proposes the role of hydration forces in mediating Omicron function and dynamics based on a stronger interplay between protein and solvent with each Covid wave. Mutations of multiple hydrophobic residues into hydrophilic residues underwent concerted interactions with water leading to variations in charge distribution in Delta and Omicron during molecular dynamics simulations. Moreover, comparative analysis of interacting moieties characterized a large number of mutations lying at RBD into constrained, homologous and low-affinity groups referred to as mutational drivers inferring that the probability of future mutations relies on their function. Furthermore, the computational findings reveal a significant difference in angular distances among variants of concern due 3 amino acid insertion (EPE) in Omicron variant that not only facilitates tight domain organization but also seems requisite for characterization of mutational processes. The outcome of this work signifies the possible relation between hydration forces, their impact on conformation and binding affinities, and viral fitness that will significantly aid in understanding dynamics of drug targets for Covid-19 countermeasures. The emerging scenario is that hydration forces and hydrophobic interactions are crucial variables to probe in mutational analysis to explore conformational landscape of macromolecules and reveal the molecular origins of protein behaviors.

Genomic architecture and evolutionary relationship of BA.2.75: A Centaurus subvariant of Omicron SARS-CoV-2

In this study, we explored the genomic architecture and phylogenomic relationship of BA.2.75, a subvariant of Omicron SARS-CoV-2. A set of 1468 whole-genome sequences of BA.2.75, submitted by 28 countries worldwide were retrieved from GISAID and used for finding genomic mutations. Moreover, the phylogenetic analysis of BA.2.75 was performed by using 2948 whole-genome sequences of all sub-variants of Omicron along with the Delta variant of SAS-CoV-2. We detected 1885 mutations, which were further grouped into 1025 missense mutations, 740 silent mutations, 72 mutations in non-coding regions, 16 in-frame deletions, 02 in-frame insertions, 8 frameshift deletions, 8 frameshift insertions and 14 stop-gained variants. Additionally, we also found 11 characteristic mutations having a prevalence of 81-99% and were not observed in any of the previously reported variant of SARS-CoV-2. Out of these mutations K147E, W152R, F157L, E210V, V213G, G339H were found in the NTD, and G446S & N460K in the RBD region of the Spike protein, whereas S403L and T11A were present in the NSP3, and E protein respectively. The phylogenetic relationship of this variant revealed that BA.2.75 is descended from the Omicron sub-variant BA.5. This evolutionary relationship suggests that the surge of BA.5 infections can reduce the severity of the infections accredited to BA.2.75. These findings would also improve our knowledge and understanding that how genetic similarities in different variants of SARS-CoV-2 can prime the immune system to fight off the infection caused by one subvariant, after defeating the other.