ABSTRACT
SARS-CoV2 entry is mediated by binding of viral spike-protein(S) to the transmembrane Angiotensin-Converting Enzyme-2 (ACE2) of the host cell. Thus, to prevent transmission of disease, strategies to abrogate the interaction are important. However, ACE2 cannot be blocked since its normal function is to convert the Angiotensin II peptide to Angiotensin(1-7) to reduce hypertension. This work reports a recombinant cell line secreting soluble ACE2-ectopic domain (MFcS2), modified to increase binding and production efficacy and fused to human immunoglobulin-Fc. While maintaining its enzymatic activity, the molecule trapped and neutralized SARS CoV2 virus in vitro with an IC50 of 64 nM. In vivo, with no pathology in the vital organs, it inhibited the viral load in lungs in SARS-CoV2 infected Golden-Syrian-hamster. The Intravenous pharmacokinetic profiling of MFcS2 in hamster at a dose of 5 mg/Kg presented a maximum serum concentration of 23.45 {micro}g/mL with a half-life of 29.5 hrs. These results suggest that MFcS2 could be used as an effective decoy based therapeutic strategy to treat COVID19. This work also reports usage of a novel oral-cancer cell line as in vitro model of SARS-Cov2 infection, validated by over expressing viral-defence pathways upon RNA-seq analysis and over-expression of ACE2 and TMPRSS upon growth in hyperglycaemic condition.
ABSTRACT
AimsSARS-CoV-2, an infectious agent behind the ongoing COVID-19 pandemic, induces high levels of cytokines such as IL-1, IL-2, IL-4, IL-6, IL-10, TNF-, IFN-{gamma} etc in infected individuals which contribute towards the underlying disease patho-physiology. Nonetheless, exact association and contribution of every cytokine towards COVID-19 pathology remains poorly understood. Delineation of the role of the cytokines during COVID-19 holds the key of efficient patient management in clinics. This study performed a comprehensive meta-analysis to establish association between induced cytokines and COVID-19 disease severity to help in prognosis and clinical care. Main methodsScientific literature was searched to identify 13 cytokines (IL-1{beta}, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-17, TNF- and IFN-{gamma}) from 18 clinical studies. Standardized mean difference (SMD) for selected 6 cytokines IL-2, IL-4, IL-6, IL-10, TNF- and IFN-{gamma} between severe and non-severe COVID-19 patient groups were summarized using random effects model. A classifier was built using logistic regression model with cytokines having significant SMD as covariates. Key findingsOut of 13 cytokines, IL-6 and IL-10 showed statistically significant SMD across the studies synthesized. Classifier with mean values of both IL-6 and IL-10 as covariates performed well with accuracy of ~ 92% that was significantly higher than accuracy reported in literature with IL-6 and IL-10 as individual covariates. SignificanceSimple panel proposed by us with only two cytokine markers can be used as predictors for fast diagnosis of patients with higher risk of COVID-19 disease deterioration and thus can be managed well for a favourable prognosis.
