Integrative COVID-19 biological network inference with probabilistic core decomposition

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein–protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The major types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

Identification of shared biological features in four different lung cell lines infected with SARS-CoV-2 virus through RNA-seq analysis

“…Genomic sequencing has shown that SARS-CoV-2 shares approximately 79% similarities with SARS-CoV and 50% similarities with MERS-CoV. Recent research indicates that the identifications of molecular mechanisms ( Zhang et al, 2021a ), cellular functions ( Alipoor et al, 2021 ), and biological network activities ( Habibi et al, 2021 ; Guo et al, 2022 ) are important to better understand the intricacies of disease biology and potentially lead to new therapies in treating COVID-19. The virus can invade cellular processes by moving proteins and genetic material from cells, resulting in the formation of new virus particles ( Cohen, 2016 ).…”