Appraisal of SARS-CoV-2 mutations and their impact on vaccination efficacy: an overview

The dual role of toll-like receptors in COVID-19: Balancing protective immunity and immunopathogenesis

Toll-like receptors (TLRs) of human are considered as the most critical immunological mediators of inflammatory pathogenesis of COVID-19. These immunoregulatory glycoproteins are located on the surface and/or intracellular compartment act as innate immune sensors. Upon binding with distinct SARS-CoV-2 ligand(s), TLRs signal activation of different transcription factors that induce expression of the proinflammatory mediators that collectively induce 'cytokine storm'. Similarly, TLR activation is also pivotal in conferring protection to infection and invasion as well as upregulating the tissue repair pathways. This dual role of the human TLRs in deciding the fate of SARS-CoV-2 has made these receptor proteins as the critical mediators of immunoprotective and immunopathogenic consequences associated with COVID-19. Herein, pathbreaking discoveries exploring the immunobiological importance of the TLRs in COVID-19 and developing TLR-directed therapeutic intervention have been reviewed by accessing the up-to-date literatures available in the public domain/databases. In accordance with our knowledge in association with the importance of TLRs' role against viruses and identification of viral particles, they have been recognized as suitable candidates with high potential as vaccine adjuvants. In this regard, the agonists of TLR4 and TLR9 have effective potential in vaccine technology while the others need further investigations. This comprehensive review suggests that basal level expression of TLRs can act as friends to keep our body safe from strangers but act as a foe via overexpression. Therefore, selective inhibition of the overexpressed TLRs appears to be a solution to counteract the cytokine storm while TLR-agonists as vaccine adjuvants could lessen the risk of infection in the naïve population.

AlphaFold2 Reveals Structural Patterns of Seasonal Haplotype Diversification in SARS-CoV-2 Spike Protein Variants

The slow experimental acquisition of high-quality atomic structures of the rapidly changing proteins of the COVID-19 virus challenges vaccine and therapeutic drug development efforts. Fortunately, deep learning tools such as AlphaFold2 can quickly generate reliable models of atomic structure at experimental resolution. Current modeling studies have focused solely on definitions of mutant constellations of Variants of Concern (VOCs), leaving out the impact of haplotypes on protein structure. Here, we conduct a thorough comparative structural analysis of S-proteins belonging to major VOCs and corresponding latitude-delimited haplotypes that affect viral seasonal behavior. Our approach identified molecular regions of importance as well as patterns of structural recruitment. The S1 subunit hosted the majority of structural changes, especially those involving the N-terminal domain (NTD) and the receptor-binding domain (RBD). In particular, structural changes in the NTD were much greater than just translations in three-dimensional space, altering the sub-structures to greater extents. We also revealed a notable pattern of structural recruitment with the early VOCs Alpha and Delta behaving antagonistically by suppressing regions of structural change introduced by their corresponding haplotypes, and the current VOC Omicron behaving synergistically by amplifying or collecting structural change. Remarkably, haplotypes altering the galectin-like structure of the NTD were major contributors to seasonal behavior, supporting its putative environmental-sensing role. Our results provide an extensive view of the evolutionary landscape of the S-protein across the COVID-19 pandemic. This view will help predict important regions of structural change in future variants and haplotypes for more efficient vaccine and drug development.

Effectiveness of BBV152 vaccine and ChAdOx1-S vaccine in preventing severe disease among vaccinated patients admitted to a designated COVID-19 hospital in India

Purpose

Coronavirus disease 2019 (COVID-19) is a highly formidable disease. Globally, multiple vaccines have been developed to prevent and manage this disease. However, the periodic mutations of severe acute respiratory syndrome coronavirus 2 variants cast doubt on the effectiveness of commonly used vaccines in mitigating severe disease in the Indian population. This study aimed to assess the effectiveness of the BBV152 vaccine and ChAdOx1-S vaccine in preventing severe forms of the disease.

Materials and Methods

This retrospective study, based on hospital records, was conducted on 204 vaccinated COVID-19 patients using a consecutive sampling approach. Data on their vaccination status, comorbidities, and high-resolution computed tomography lung reports' computed tomography severity scores were extracted from their medical records. Fisher's exact test and binomial logistic regression analysis were employed to assess the independent associations of various factors with the dependent variables.

Results

Of the 204 records, 57.9% represented males, with a mean age of 61.5±9.8 years. Both vaccines demonstrated effective protection against severe illness (90.2%), with BBV152 offering slightly better protection compared to ChAdOx1-S. Male gender, partial vaccination, comorbid conditions, and the type of vaccine were identified as independent predictors of severe lung involvement.

Conclusion

This study indicates that both vaccines were highly effective (90%) in preventing severe forms of the disease in fully vaccinated individuals. When comparing the two vaccines, BBV152 was slightly more effective than ChAdOx1-S in preventing severe COVID-19.

Twitter-Based Sentiment Analysis and Topic Modeling of Social Media Posts Using Natural Language Processing, to Understand People's Perspectives Regarding COVID-19 Booster Vaccine Shots in India: Crucial to Expanding Vaccination Coverage

This study analyzed perceptions of Indians regarding COVID-19 booster dose vaccines using natural language processing techniques, particularly, sentiment analysis and topic modeling. We analyzed tweets generated by Indian citizens for this study. In late July 2022, the Indian government hastened the process of COVID-19 booster dose vaccinations. Understanding the emotions and concerns of the citizens regarding the health policy being implemented will assist the government, health policy officials, and policymakers implement the policy efficiently so that desired results can be achieved. Seventy-six thousand nine hundred seventy-nine tweets were used for this study. The sentiment analysis study revealed that out of those 76,979 tweets, more than half (n = 40,719 tweets (52.8%) had negative sentiments, 24,242 tweets (31.5%) had neutral sentiments, and 12,018 tweets (15.6%) had positive sentiments. Social media posts by Indians on the COVID-19 booster doses have focused on the feelings that younger people do not need vaccines and that vaccinations are unhealthy.