Abstract
SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple organ failure, and mortality in some patients. The gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutics for COVID-19 and related pathologies, such as Neuro-COVID. Here, we used the raw RNA-seq reads (Single-End) in quadruplicates derived using Illumina Next Seq 500 from SARS-CoV-infected primary human bronchial epithelium (NHBE) and mock-treated NHBE cells obtained from the Gene Expression Omnibus (GEO) (GSE147507), and the quality control (QC) was evaluated using the CLC Genomics Workbench 20.0 (Qiagen, United States) before the RNA-seq analysis using BioJupies web tool and iPathwayGuide for gene ontologies (GO), pathways, upstream regulator genes, small molecules, and natural products. Additionally, single-cell transcriptomics data (GSE163005) of meta clusters of immune cells from the cerebrospinal fluid (CSF), such as T-cells/natural killer cells (NK) (TcMeta), dendritic cells (DCMeta), and monocytes/granulocyte (monoMeta) cell types for comparison, namely, Neuro-COVID versus idiopathic intracranial hypertension (IIH), were analyzed using iPathwayGuide. L1000 fireworks display (L1000FWD) and L1000 characteristic direction signature search engine (L1000 CDS2) web tools were used to uncover the small molecules that could potentially reverse the COVID-19 and Neuro-COVID-associated gene signatures. We uncovered small molecules such as camptothecin, importazole, and withaferin A, which can potentially reverse COVID-19 associated gene signatures. In addition, withaferin A, trichostatin A, narciclasine, camptothecin, and JQ1 have the potential to reverse Neuro-COVID gene signatures. Furthermore, the gene set enrichment analysis (GSEA) preranked method and Metascape web tool were used to decipher and annotate the gene signatures that were potentially reversed by these small molecules. In conclusion, our study unravels a rapid approach for applying next-generation knowledge discovery (NGKD) platforms to discover small molecules with therapeutic potential against COVID-19 and its related disease pathologies.
Highlights
Coronaviruses (CoVs) belong to the order Nidovirales, family Coronaviridae, and subfamily Coronavirinae, which can further be divided into four genera: alpha, beta, gamma, and delta CoVs
COVID-19 caused by SARS-CoV-2 infection remains an ongoing pandemic (Huang C. et al, 2020; Liu J. et al, 2020; Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, 2020) and patients with severe COVID-19 may develop neurological complications called Neuro-COVID (Heming et al, 2021)
Because the gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutic targets that could be targeted by known drugs (Daamen et al, 2021), we used RNA-seq datasets from the COVID-19 infection models of NHBE cells, and the scRNA-seq datasets of immune cells isolated from the cerebrospinal fluid (CSF) of Neuro-COVID patients and analyzed using next-generation knowledge discovery (NGKD) platforms to understand the disease-specific gene signatures and pathways and further uncover small molecules from both synthetic and natural sources that potentially reverse these diseases
Summary
Coronaviruses (CoVs) belong to the order Nidovirales, family Coronaviridae, and subfamily Coronavirinae, which can further be divided into four genera: alpha, beta, gamma, and delta CoVs. SARSCoV-2 infected more than 186 million people, resulting in the death of about 4 million people globally (Johns Hopkins COVID19 Data Center on 10th July 2021) (Dong et al, 2020). SARSCoV-2 has a positive-sense RNA genome encapsulated by a nucleocapsid. SARS-CoV-2 infects host cells through surface receptors, angiotensin-converting enzyme 2 (hACE2), and transmembrane protease serine-type 2 (TMPRSS2) (Hoffmann et al, 2020). An increase in the expression of ACE2, a tissueprotective mediator during lung damage, was found to be associated with interferon signaling in airway epithelial cells, and SARS-CoV-2 could exploit interferon-mediated stimulation of ACE2 to augment infection (Ziegler et al, 2020). The differential expression of genes that are necessary for SARS-CoV-2 interaction and subsequent host response determine susceptibility to COVID-19, disease progression, and recovery (Kasela et al, 2021)
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