ABSTRACT
The COVID-19 associated opportunistic fungal infections have posed major challenges in recent times. Global scientific efforts have identified several SARS-CoV2 host-pathogen interactions in a very short time span. However, information about the molecular basis of COVID-19 associated opportunistic fungal infections is not readily available. Previous studies have identified a number of host targets involved in these opportunistic fungal infections showing association with COVID-19 patients. We screened host targets involved in COVID-19-associated opportunistic fungal infections, in addition to host-pathogen interaction data of SARS-CoV2 from well-known and widely used biological databases. Venn diagram was prepared to screen common host targets involved in studied COVID-19-associated fungal infections. Moreover, an interaction network of studied disease targets was prepared with STRING to identify important targets on the basis of network biological parameters. The host-pathogen interaction (HPI) map of SARS-CoV2 was also prepared and screened to identify interactions of the virus with targets involved in studied fungal infections. Pathway enrichment analysis of host targets involved in studied opportunistic fungal infections and the subset of those involved in SARS-CoV2 HPI were performed separately. This data-based analysis screened six common targets involved in all studied fungal infections, among which CARD9 and CYP51A1 were involved in host-pathogen interactions with SARS-CoV2. Moreover, several signaling pathways such as integrin signaling were screened, which were associated with disease targets involved in SARS-CoV2 HPI. The results of this study indicate several host targets deserving detailed investigation to develop strategies for the management of SARS-CoV2-associated fungal infections.
ABSTRACT
COVID-19 caused a global catastrophe with a large number of cases making it one of the major pandemics of the human history. The clinical presentations of the disease are continuously challenging healthcare workers with the variation of pandemic waves and viral variants. Recently, SARS-CoV2 patients have shown increased occurrence of invasive pulmonary aspergillosis infection even in the absence of traditional risk factors. The mechanism of COVID-19-associated aspergillosis is not completely understood and therefore, we performed this system biological study in order to identify mechanistic implications of aspergillosis susceptibility in COVID-19 patients and the important targets associated with this disease. We performed host-pathogen interaction (HPI) analysis of SARS-CoV2, and most common COVID-19-associated aspergillosis pathogen, Aspergillus fumigatus, using in silico approaches. The known host-pathogen interactions data of SARS-CoV2 was obtained from BIOGRID database. In addition, A. fumigatus host-pathogen interactions were predicted through homology modeling. The human targets interacting with both pathogens were separately analyzed for their involvement in aspergillosis. The aspergillosis human targets were screened from DisGeNet and GeneCards. The aspergillosis targets involved in both HPI were further analyzed for functional overrepresentation analysis using PANTHER. The results indicate that both pathogens interact with a number of aspergillosis targets and altogether they recruit more aspergillosis targets in host-pathogen interaction than alone. Common aspergillosis targets involved in HPI with both SARS-CoV2 and A. fumigatus can indicate strategies for the management of both conditions by modulating these common disease targets.
ABSTRACT
BACKGROUND: In India, laboratory diagnosis of SARS - CoV-2 infection has been mostly based on real-time reverse transcriptase-polymerase chain reaction (RT-PCR). Studies have shown that Viral titres peak within the first week of symptoms but may decline later hampering RT-PCR-based diagnostic strategies. Exact estimate is difficult under high-risk screening strategy with evidences of having large number of asymptomatic cases. This has prompted a call for adoption of antibody testing as potential source of data. MATERIALS AND METHODS: A cross-sectional study with a sample size of 7000 was conducted for 15 days including all the 85 wards under Indore Municipal Corporation. Stratified Random Sampling was used to collect the samples. Trained teams collected basic sociodemographic information and serum samples which were tested for the presence of specific antibodies to COVID-19 using ICMR-Kavach IgG ELISA kits. The data collected was compiled and analysed using appropriate statistical software. RESULTS: Overall weighted seroprevalence of the study population was found to be 7.75%. The prevalence in males and females was comparable (7.91% vs 7.57%). Highest seropositivity (10.04%) was seen among individuals aged more than 60 years. Total number of infections in the population were estimated to be 2,03,160. Overall Case Infection Ratio was found to be 27.43. CONCLUSION: The current seroprevalence study provides information on proportion of the population exposed, but the correlation between presence and absence of antibodies is not a marker of total or partial immunity. It must also be noted that more than 90 percent of the population is still susceptible for COVID-19 infection. Hence, non-pharmaceutical interventions like respiratory hygiene, physical distancing, hand sanitization, usage of personal protective equipment such as masks and implementation of public health measures need to be continued.