The receptor binding domain (RBD) of SARS-CoV-2 is the primary target of neutralizing antibodies. We designed a trimeric, highly thermotolerant glycan engineered RBD by fusion to a heterologous, poorly immunogenic disulfide linked trimerization domain derived from cartilage matrix protein. The protein expressed at a yield of ∼80–100 mg/L in transiently transfected Expi293 cells, as well as CHO and HEK293 stable cell lines and formed homogeneous disulfide-linked trimers. When lyophilized, these possessed remarkable functional stability to transient thermal stress of up to 100 °C and were stable to long-term storage of over 4 weeks at 37 °C unlike an alternative RBD-trimer with a different trimerization domain. Two intramuscular immunizations with a human-compatible SWE adjuvanted formulation elicited antibodies with pseudoviral neutralizing titers in guinea pigs and mice that were 25–250 fold higher than corresponding values in human convalescent sera. Against the beta (B.1.351) variant of concern (VOC), pseudoviral neutralization titers for RBD trimer were ∼3-fold lower than against wildtype B.1 virus. RBD was also displayed on a designed ferritin-like Msdps2 nanoparticle. This showed decreased yield and immunogenicity relative to trimeric RBD. Replicative virus neutralization assays using mouse sera demonstrated that antibodies induced by the trimers neutralized all four VOC to date, namely B.1.1.7, B.1.351, P.1, and B.1.617.2 without significant differences. Trimeric RBD immunized hamsters were protected from viral challenge. The excellent immunogenicity, thermotolerance, and high yield of these immunogens suggest that they are a promising modality to combat COVID-19, including all SARS-CoV-2 VOC to date.

Saturation suppressor mutagenesis was used to generate thermostable mutants of the SARS-CoV-2 spike receptor-binding domain (RBD). A triple mutant with an increase in thermal melting temperature of ~7°C with respect to the wild-type B.1 RBD and was expressed in high yield in both mammalian cells and the microbial host, Pichia pastoris, was downselected for immunogenicity studies. An additional derivative with three additional mutations from the B.1.351 (beta) isolate was also introduced into this background. Lyophilized proteins were resistant to high-temperature exposure and could be stored for over a month at 37°C. In mice and hamsters, squalene-in-water emulsion (SWE) adjuvanted formulations of the B.1-stabilized RBD were considerably more immunogenic than RBD lacking the stabilizing mutations and elicited antibodies that neutralized all four current variants of concern with similar neutralization titers. However, sera from mice immunized with the stabilized B.1.351 derivative showed significantly decreased neutralization titers exclusively against the B.1.617.2 (delta) VOC. A cocktail comprising stabilized B.1 and B.1.351 RBDs elicited antibodies with qualitatively improved neutralization titers and breadth relative to those immunized solely with either immunogen. Immunized hamsters were protected from high-dose viral challenge. Such vaccine formulations can be rapidly and cheaply produced, lack extraneous tags or additional components, and can be stored at room temperature. They are a useful modality to combat COVID-19, especially in remote and low-resource settings.

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Background South Asia has become a major epicentre of the COVID-19 pandemic. Understanding South Asians’ awareness, attitudes and experiences of early measures for the prevention of COVID-19 is key to improving the effectiveness and mitigating the social and economic impacts of pandemic responses at a critical time for the Region. Methods We assessed the knowledge, behaviours, health and socio-economic circumstances of 29,809 adult men and women, at 93 locations across four South Asian countries. Data were collected during the national lockdowns implemented from March to July 2020, and compared with data collected prior to the pandemic as part of an ongoing prospective surveillance initiative. Results Participants were 61% female, mean age 45.1 years. Almost half had one or more chronic disease, including diabetes (16%), hypertension (23%) or obesity (16%). Knowledge of the primary COVID-19 symptoms and transmission routes was high, but access to hygiene and personal protection resources was low (running water 63%, hand sanitisers 53%, paper tissues 48%). Key preventive measures were not widely adopted. Knowledge, access to, and uptake of COVID-19 prevention measures were low amongst people from disadvantaged socio-economic groups. Fifteen percent of people receiving treatment for chronic diseases reported loss of access to long-term medications; 40% reported symptoms suggestive of anxiety or depression. The prevalence of unemployment rose from 9.3% to 39.4% (P < 0.001), and household income fell by 52% (P < 0.001) during the lockdown. Younger people and those from less affluent socio-economic groups were most severely impacted. Sedentary time increased by 32% and inadequate fruit and vegetable intake increased by 10% (P < 0.001 for both), while tobacco and alcohol consumption dropped by 41% and 80%, respectively (P < 0.001), during the lockdown. Conclusions Our results identified important knowledge, access and uptake barriers to the prevention of COVID-19 in South Asia, and demonstrated major adverse impacts of the pandemic on chronic disease treatment, mental health, health-related behaviours, employment and household finances. We found important sociodemographic differences for impact, suggesting a widening of existing inequalities. Our findings underscore the need for immediate large-scale action to close gaps in knowledge and access to essential resources for prevention, along with measures to safeguard economic production and mitigate socio-economic impacts on the young and the poor.

CTRI/2012/06/002747.

The variability of clinical course and prognosis of COVID-19 highlights the necessity of patient sub-group risk stratification based on clinical data. In this study, clinical data from a cohort of Indian COVID-19 hospitalized patients is used to develop risk stratification and mortality prediction models. We analyzed a set of 70 clinical parameters including physiological and hematological for developing machine learning models to identify biomarkers. We also compared the Indian and Wuhan cohort, and analyzed the role of steroids. A bootstrap averaged ensemble of Bayesian networks was also learned to construct an explainable model for discovering actionable influences on mortality and days to outcome. We discovered blood parameters, diabetes, co-morbidity and SpO2 levels as important risk stratification features, whereas mortality prediction is dependent only on blood parameters. XGboost and logistic regression model yielded the best performance on risk stratification and mortality prediction, respectively (AUC score 0.83, AUC score 0.92). Blood coagulation parameters (ferritin, D-Dimer and INR), immune and inflammation parameters IL6, LDH and Neutrophil (%) are common features for both risk and mortality prediction. Compared with Wuhan patients, Indian patients with extreme blood parameters indicated higher survival rate. Analyses of medications suggest that a higher proportion of survivors and mild patients who were administered steroids had extreme neutrophil and lymphocyte percentages. The ensemble averaged Bayesian network structure revealed serum ferritin to be the most important predictor for mortality and Vitamin D to influence severity independent of days to outcome. The findings are important for effective triage during strains on healthcare infrastructure.

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

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