Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis.

BACKGROUND: Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF. METHODS: We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. RESULTS: A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B). CONCLUSIONS: This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

ORF10-Cullin-2-ZYG11B complex is not required for SARS-CoV-2 infection.

In order to understand the transmission and virulence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it is necessary to understand the functions of each of the gene products encoded in the viral genome. One feature of the SARS-CoV-2 genome that is not present in related, common coronaviruses is ORF10, a putative 38-amino acid protein-coding gene. Proteomic studies found that ORF10 binds to an E3 ubiquitin ligase containing Cullin-2, Rbx1, Elongin B, Elongin C, and ZYG11B (CRL2ZYG11B). Since CRL2ZYG11B mediates protein degradation, one possible role for ORF10 is to "hijack" CRL2ZYG11B in order to target cellular, antiviral proteins for ubiquitylation and subsequent proteasomal degradation. Here, we investigated whether ORF10 hijacks CRL2ZYG11B or functions in other ways, for example, as an inhibitor or substrate of CRL2ZYG11B While we confirm the ORF10-ZYG11B interaction and show that the N terminus of ORF10 is critical for it, we find no evidence that ORF10 is functioning to inhibit or hijack CRL2ZYG11B Furthermore, ZYG11B and its paralog ZER1 are dispensable for SARS-CoV-2 infection in cultured cells. We conclude that the interaction between ORF10 and CRL2ZYG11B is not relevant for SARS-CoV-2 infection in vitro.