A Synthetic Biology Approach for Vaccine Candidate Design against Delta Strain of SARS-CoV-2 Revealed Disruption of Favored Codon Pair as a Better Strategy over Using Rare Codons.

The SARS-CoV-2 delta variant (B.1.617.2) appeared for the first time in December 2020 and later spread worldwide. Currently available vaccines are not so efficacious in curbing the viral pathogenesis of the delta strain of COVID; therefore, the development of a safe and effective vaccine is required. In the present study, we envisaged molecular patterns in the structural genes' spike, nucleoprotein, membrane, and envelope of the SARS-CoV-2 delta variant. The study was based on determining compositional features, dinucleotide odds ratio, synonymous codon usage, positive and negative codon contexts, rare codons, and insight into relatedness between the human host isoacceptor tRNA and preferred codons from the structural genes. We found specific patterns, including a significant abundance of T nucleotide over all other three nucleotides. The underrepresentation of GpA, GpG, CpC, and CpG dinucleotides and the overrepresentation of TpT, ApA, CpT, and TpG were observed. A preference towards ACT- (Thr), AAT- (Asn), TTT- (Phe), and TTG- (Leu) initiated codons and aversion towards CGG (Arg), CCG (Pro), and CAC (His) was present in the structural genes of the delta strain. The interaction between the host tRNA pool and preferred codons of the envisaged structural genes revealed that the virus preferred the codons for those suboptimal numbers of isoacceptor tRNA were present. We see this as a strategy adapted by the virus to keep the translation rate low to facilitate the correct folding of viral proteins. The information generated in the study helps design the attenuated vaccine candidate against the SARS-CoV-2 delta variant using a synthetic biology approach. Three strategies were tested: changing TpT to TpA, introducing rare codons, and disrupting favored codons. It found that disrupting favored codons is a better approach to reducing virus fitness and attenuating SARS-CoV-2 delta strain using structural genes.

Codon Usage and Context Analysis of Genes Modulated during SARS-CoV-2 Infection and Dental Inflammation.

The overexpression of SARS-CoV-2 primary receptors and co-receptors (ACE2, TMPRSS2, FURIN, and CD147) enhance the likeliness of SARS-CoV-2 infection. The genes for same receptors are overexpressed in the periodontal tissues of periodontitis patients. On the other hand, BMAL1 is recognized to play a crucial role in regulating pulmonary inflammation and enhancing susceptibility to viral infection. Silenced BMAL1 disrupts circadian transcriptional regulations, enhances vulnerability to SARS-CoV-2 infections, and may trigger the further production of TNF-α and other pro-inflammatory cytokines that propagate the cytokine storm and exacerbate periodontal inflammation. Therefore ACE2, TMPRSS2, FURIN, CD147, and BMAL1 are the crossroads between SARS-CoV-2 and Periodontitis genes. The enhanced expression of ACE2, TMPRSS2, FURIN, and CD147 and the diminished expression of BMAL1 may be a strategy to check both ailments simultaneously. In gene manipulation techniques, oligos are introduced, which contain all the necessary information to manipulate gene expression. The data are derived from the studies on genes' molecular patterns, including nucleotide composition, dinucleotide patterns, relative synonymous codon usage, codon usage bias, codon context, and rare and abundant codons. Such information may be used to manipulate the overexpression and underexpression of the genes at the time of SARS-CoV-2 infection and periodontitis to mitigate both ailments simultaneously; it can be explored to uncover possible future treatments.

A comprehensive genomic study, mutation screening, phylogenetic and statistical analysis of SARS-CoV-2 and its variant omicron among different countries.

BACKGROUND: With the rapid development of the genomic sequence data for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants Delta (B.1.617.2) and Omicron (B.1.1.529), it is vital to successfully identify mutations within the genome. OBJECTIVE: The main objective of the study is to investigate the full-length genome mutation analysis of 157 SARS-CoV-2 and its variant Delta and Omicron isolates. This study also provides possible effects at the structural level to understand the role of mutations and new insights into the evolution of COVID-19 and evaluates the differential level analysis in viral genome sequence among different nations. We have also tried to offer a mutation snapshot for these differences that could help in vaccine formulation. This study utilizes a unique and efficient method of targeting the stable genes for the drug discovery approach. METHODS: Complete genome sequence information of SARS-CoV-2, Delta, and Omicron from online resources were used to predict structure domain identification, data mining, and screening; employing different bioinformatics tools. BioEdit software was used to perform their genomic alignments across countries and a phylogenetic tree as per the confidence of 500 bootstrapping values was constructed. Heterozygosity ratios were determined in-silico. A minimum spanning network (MSN) of selected populations was determined by Bruvo's distance role-based framework. RESULTS: Out of all 157 different strains of SARS-CoV-2 and its variants, and their complete genome sequences from different countries, Corona nucleoca and DUF5515 were observed to be the most conserved domains. All genomes obtained changes in comparison to the Wuhan-Hu-1 strain, mainly in the TRS region (CUAAAC or ACGAAC). We discovered 596 mutations in all genes, with the highest number (321) found in ORF1ab (QHD43415.1), or TRS site mutations found only in ORF7a (1) and ORF10 (2). The Omicron variant has 30 mutations in the Spike protein and has a higher alpha-helix shape (23.46%) than the Delta version (22.03%). T478 was also discovered to be a prevalent polymorphism in Delta and Omicron variations, as well as genomic gaps ranging from 45 to 65aa. All 157 sequences contained variations and conformed to Nei's Genetic distance. We discovered heterozygosity (Hs) 0.01, mean anticipated Hs 0.32, the genetic diversity index (GDI) 0.01943989, and GD within population 0.01266951. The Hedrick value was 0.52324978, the GD coefficient was 0.52324978, the average Hs was 0.01371452, and the GD coefficient was 0.52324978. Among other countries, Brazil has the highest standard error (SE) rate (1.398), whereas Japan has the highest ratio of Nei's gene diversity (0.01). CONCLUSIONS: The study's findings will assist in comprehending the shape and kind of complete genome, their streaming genomic sequences, and mutations in various additions of SARS-CoV-2, as well as its different variant strains like Omicron. These results will provide a scientific basis to design the vaccines and understand the genomic study of these viruses.

Role of Therapeutic Plasmapheresis in SARS-CoV-2 Induced Cytokine Release Syndrome: A Retrospective Cohort Study on COVID-19 Patients.

Background: Cytokine release syndrome (CRS) significantly contributes to the pathophysiology and progression of COVID-19. It is speculated that therapeutic plasma exchange (TPE) can dampen CRS via elimination of pathogenic cytokines. Objectives: The study is intended to compare the outcomes of COVID-19 patients with CRS treated with TPE and standard care (SC) to their counterparts receiving SC alone. Methodology: A retrospective cohort study of severe COVID-19 confirmed patients presenting with CRS and admitted to the medical ICU was conducted between March and August 2021. Using case-control (CC) matching 1:1, 162 patients were selected and divided into two equal groups. The primary outcome was 28-day in-hospital survival analysis in severe COVID-19 patients with CRS. However, secondary outcomes included the effect of plasmapheresis on inflammatory markers, the need for mechanical ventilation, the rate of extubation, and the duration of survival. Results: After CC matching, the study cohort had a mean age of 55.41 (range 56.41±11.56 in TP+SC and 54.42±8.94 in SC alone; p=0.22). There were 25.95% males and 74.05% females in both groups. The mean time from first day of illness to hospitalization was 6.53±2.18 days. The majority of patients with CRS had comorbid conditions (75.9%). Diabetes mellitus was the most common comorbidity (40.1%), followed by hypertension (25.3%), and chronic kidney disease (21%). Notable reduction in some inflammatory markers (D-dimers, LDH, CRP and serum ferritin) (p<0.0001) was observed in the group that received TPE+SC. Moreover, the patients in the plasmapheresis plus standard care group required relatively less mechanical ventilation as compared to the group receiving SC alone (46.9% vs 58.1%, respectively; p>0.05). The rate of extubation in the TP+SC group vs SC alone was 60.5% vs 44.7%, respectively (p>0.05). Similarly, the mortality percentages in both groups were 19.8% and 24.7%, respectively. Conclusion: For this particular group of matched patients with COVID-19-induced CRS, TPE+SC was linked with relatively better overall survival, early extubation, and earlier discharge compared to SC alone. As these results were not statistically significant, multi-centered randomized control trials are needed to further elaborate the role of therapeutic plasmapheresis in COVID-19 induced CRS.

Beneficial Effects of Anticoagulants on the Clinical Outcomes of COVID-19 Patients.

(1) Background: Severe coronavirus disease can be complicated by a hypercoagulable state in conjunction with sepsis, increasing the risk of venous thromboembolism. This study aimed to observe the effect of anticoagulants on 30-day high-dependency unit (HDU) outcomes of moderate to severe coronavirus disease 2019 (COVID-19) patients of a tertiary care hospital at Rawalpindi, Pakistan. (2) Methods: A retrospective propensity-based case-control study was carried out to examine COVID-19 patients admitted to the HDU. Patient groups who did and did not receive anticoagulants were labeled as "anticoagulant" and "non-anticoagulant", respectively. Case-control matching (1:1) was performed via propensity scores (calculated by a regression model). Kaplan-Meier and logrank analyses were used to study survival probability. Single predictors of outcomes were determined by Cox regression analysis. (3) Results: The anticoagulant group had elevated D-dimers, advanced age, more comorbidities and a higher frequency of severe disease compared to the non-anticoagulant group (p < 0.05). Therefore, 47 cases and 47 matched controls were selected based on their propensity scores. The primary endpoint was outcome (survived vs. died). The 30-day in-HDU mortality was 25.5% for cases and 61.7% for controls (p = 0.0004). The median time from admission to death was 16 days for the case group and 7 days for the control group (p < 0.0001). The 30-day mortality was 19.1% for the enoxaparin group and 16.4% for the heparin group (p > 0.05). Enoxaparin (therapeutic and prophylactic doses) and heparin (prophylactic dose) were found to be independent factors affecting the outcomes of these patients (p < 0.001). (4) Conclusions: Anticoagulants play a beneficial role in reducing mortality among COVID-19 patients. Both anticoagulant formulations, enoxaparin (therapeutic and prophylactic doses) and heparin (prophylactic dose), were associated with improving survival among these patients.