Screening of candidate genes associated with high titer production of oncolytic measles virus based on systems biology approach.
Malihe RastegarpanahKayhan AzadmaneshBabak NegahdariYazdan AsgariMohammadali MazloomiPublished in: Virus genes (2022)
The number of viral particles required for oncolytic activity of measles virus (MV) can be more than a million times greater than the reported amount for vaccination. The aim of the current study is to find potential genes and signaling pathways that may be involved in the high-titer production of MV. In this study, a systems biology approach was considered including collection of gene expression profiles from the Gene Expression Omnibus (GEO) database, obtaining differentially expressed genes (DEGs), performing gene ontology, functional enrichment analyses, and topological analyses on the protein-protein interaction (PPI) network. Then, to validate the in-silico data, total RNA was isolated from five cell lines, and full-length cDNA from template RNA was synthesized. Subsequently, quantitative reverse transcription-PCR (RT-qPCR) was employed. We identified five hub genes, including RAC1, HSP90AA1, DNM1, LTBP1, and FSTL1 associated with the enhancement in MV titer. Pathway analysis indicated enrichment in PI3K-Akt signaling pathway, axon guidance, proteoglycans in cancer, regulation of actin cytoskeleton, focal adhesion, and calcium signaling pathways. Upon verification by RT-qPCR, the relative expression of candidate genes was generally consistent with our bioinformatics analysis. Hub genes and signaling pathways may be involved in understanding the pathological mechanisms by which measles virus manipulates host factors in order to facilitate its replication. RAC1, HSP90AA1, DNM1, LTBP1, and FSTL1 genes, in combination with genetic engineering techniques, will allow the direct design of high-throughput cell lines to answer the required amounts for the oncolytic activity of MV.
Keyphrases
- bioinformatics analysis
- signaling pathway
- pi k akt
- genome wide
- genome wide identification
- gene expression
- protein protein
- high throughput
- epithelial mesenchymal transition
- dna methylation
- induced apoptosis
- cell proliferation
- copy number
- cell cycle arrest
- small molecule
- heat shock protein
- emergency department
- poor prognosis
- squamous cell carcinoma
- heat shock
- escherichia coli
- machine learning
- cell migration
- transcription factor
- heat stress
- molecular docking
- mass spectrometry
- network analysis
- nucleic acid
- staphylococcus aureus
- big data
- squamous cell
- biofilm formation