As the rapidly unfolding COVID-19 pandemic claims its victims around the world, it has also inspired the scientific community to come up with solutions to meet an urgent and unmet need ?i.e., ameliorate the severity of Covid- 19 and reduce mortality. Two obstacles make that task difficult?First, the pathophysiology of Covid-19 remains a mystery; the emerging reports generally agree that the disease has a very slow onset and that those who succumb typically mount a ?cytokine storm?, i.e., an overzealous immune response. However, despite being implicated as a culprit behind the observed mortality and morbidity in COVID-19, we know virtually nothing about what constitutes (nature, extent) or contributes to (cell or origin) such an overzealous response. A significant number of patients have GI symptoms. The treatment goals in COVID-19 have been formulated largely as a ?trial and error?-approach; this is reflected in the mixed results of the trials that have concluded. Second, the process of drug discovery is comprised of time-consuming steps; to avoid delays, we need to define the nature of the fatal cellular response before deciding how to model it in animals or matching therapeutics to curb it. Our preliminary work has helped us define the aberrant host cellular response in COVID-19. We used machine learning tools that can look beyond interindividual variability to extract underlying gene expression patterns within complex data across multiple cohorts of viral pandemics, including COVID-19. The resultant pattern, i.e., signature, was subsequently exploited as a predictive model to navigate COVID-19 for GI symptoms. Surprisingly, the 166-gene signature was conserved in all viral pandemics, including COVID-19, inspiring the nomenclature-- (ViP)-signature. The ViP signature identified and predicted the disease severity of SARS-CoV2-infected patients. We hypothesized that the ViP signature provides a quantitative and qualitative framework for titrating the cellular response in viral pandemics and could serve as a powerful unbiased tool in our armamentarium to vet candidate drugs rapidly. In this proposal, our predicted model, experimental datasets and the information from published literature will be used to screen drugs/nutritional components/probiotics in the GI organoid derived monolayers in a semi-HTP format. We will experimentally validate the effect of the therapeutics predicted in ViP gene signature of the host. The following two aims will provide a translational impact on the COVID-19 emergency.
Aim 1 : Identify the gastro-intestinal pathogenic pathways during COVID-19.
Aim 2 : Determine the impact of drugs, nutrients and supplements in gut-in-a-dish model of COVID-19. Impact: This proposal will identify the gastro-intestinal pathways (in healthy and patients with chronic diseases) involved in the GI symptoms of COVID 19 and provide new treatment options in COVID-19.
Coronavirus Disease 2019 (Covid-19) continues to rapidly claim lives and challenge the limits of our knowledge and our healthcare system. Other than ?cytokine storm,? a significant amount of the patient shows gastrointestinal symptoms and nothing is known for the cellular pathways and any relevant treatment of COVID-19. The published literature, Artificial Intelligence (AI)-guided approaches, and our experimental datasets with GI- organoid-based cell models are used to identify host gastrointestinal pathways that can be targeted using drug/pro-prebiotics and nutritional supplements to combat the disease.
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