Integration of transcriptomic profile of SARS-CoV-2 infected normal human bronchial epi-thelial cells with metabolic and protein-protein interaction networks

Authors : Hamza Umut KARAKURT, Pinar PİR

Pages : 168-177

View : 12 | Download : 8

Publication Date : 2020-12-01

Article Type : Research Paper

Abstract :A novel coronavirus insert ignore into journalissuearticles values(SARS-CoV-2, formerly known as nCoV-2019); that causes an acute respiratory disease has emerged in Wuhan, China and spread globally in early 2020. On January the 30th, the World Health Organization insert ignore into journalissuearticles values(WHO); declared spread of this virus as an epidemic and a public health emergency. With its highly contagious characteristic and long incubation time, confinement of SARS-CoV-2 requires drastic lock-down measures to be taken and therefore early diagnosis is crucial. We analysed transcriptome of SARS-CoV-2 infected human lung epithelial cells, compared it with mock-infected cells, used network-based reporter metabolite approach and integrated the transcriptome data with protein-protein interaction network to elucidate the early cellular response. Significantly affected metabolites have the potential to be used in diagnostics while pathways of protein clusters have the potential to be used as targets for supportive or novel therapeutic approaches. Our results are in accordance with the literature on response of IL6 family of cytokines and their importance, in addition, we find that matrix metalloproteinase 2 insert ignore into journalissuearticles values(MMP2); and matrix metalloproteinase 9 insert ignore into journalissuearticles values(MMP9); with keratan sulfate synthesis pathway may play a key role in the infection. We hypothesize that MMP9 inhibitors have potential to prevent `cytokine storm` in severely affected patients.
Keywords : SARS CoV 2, bioinformatics, transcriptome, metabolome, biological networks, data integration