Transcriptome and SARS-CoV-2 Biological Network Directed Analysis for Better Therapeutic Development

Author(s): Om Prakash Sharma, Ruchika Sharma and Vinay Chandil

Background: It has been almost 3.5 years since the first SARS-CoV-2 virus was first reported in the city of Wuhan. While the FDA has approved a number of drugs for Covid-19, the presence of the disease and its symptoms underscores the continued demand for an improved treatment option to effectively address the existing challenges. In this study, our goal is to identify pivotal protein targets, strongly correlated across lung, blood, and peripheral blood mononuclear cell (PBMC) transcriptomics datasets, to suggest promising targets for comprehensive therapeutic development across multiple tissues.

Methods: Transcriptomics datasets were retrieved from Geo Omnibus (GEO). We use relevant datasets to identify the most significant and differentially expressed genes and integrated them into a Research graph called CovInt (a network of Covid-19) that includes all biological molecules associated in the network with their directionalities collected from publicly available and patient-derived multi-omics datasets from millions of unstructured and structured datasets such as publications, patents, grants, preclinical and clinical reports. CovInt utilizes powerful traversal, clustering and centrality algorithms to identify key connections in the pathophysiology of the disease and its treatments.

Results: Leveraging 3M+ connections, important interactions among key 42 drugs, 962 biological processes and molecular functions, 926 pathways, 897 phenotypes, 7103 proteins, 61 tissues were identified. This narrowed interactome was explored further using PageRank, lovain detection & strongly connected components (SSC) algorithms. In our analysis, 63 strongly connected communities were identified which gives us an understanding of hidden underlying mechanisms. We further explored this network to identify and triangulate the key proteins, metabolic pathways and associated risk factors that can regulate moderate to severe Covid-19 infections.

Conclusions: Our study suggests that CREB3L1, SOX2, UBR4, FLNC, ITPA, DLG3, ING4, TECR, NADH, SMAD, HUWE1, DDX17, CREBBP, RELA, HPSE, TRIM33, TNFSF13B are the key regulator proteins in PBMC, Blood and Lungs in Covid19 patients. These proteins are involved in ER-stress, cytokine signaling, T-Cell activation, Activation of NLRP3 Inflammation by SARS-CoV-2, JAK-STAT, IL-4, IL-13 pathways, MAPK signaling pathways, Activation of NMDA receptor & postsynaptic events and TGF-β signaling pathways. This set of proteins needs to be further investigated in experimental studies for better therapeutic design of Covid-19.

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