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Transcriptome data from human nasal epithelial cells infected by H3N2 influenza virus indicate early unbalanced ROS/RNA levels, temporarily increased aerobic fermentation linked to enhanced α-tubulin and rapid energy-dependent IRF9-marked immunization

Costa, J. H.; Aziz, S.; Arnholdt-Schmitt, B.

2021-10-20 cell biology
10.1101/2021.10.18.464828 bioRxiv
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BackgroundTranscriptome studies of a selected gene set (ReprogVirus) had identified unbalanced ROS/RNS levels, which connected to increased aerobic fermentation that linked to alpha-tubulin-based cell restructuration and cell cycle control, as a major complex trait for early de novo programming (CoV-MAC-TED) upon SARS-CoV-2 infection. Recently, CoV-MAC-TED was confirmed as promising marker by using primary target human nasal epithelial cells (NECs) infected by two SARS-CoV-2 variants with different effects on disease severity. To further explore this marker/cell system as a standardized tool for identifying anti-viral targets in general, testing of further virus types is required. Results: Transcriptome level profiles of H3N2 influenza-infected NECs indicated ROS/RNS level changes and increased transcript accumulation of genes related to glycolysis, lactic fermentation and -tubulin at 8 hours post infection. These early changes linked to energy-dependent, IRF9-marked rapid immunization. However, ReprogVirus-marker genes indicated the absence of initial cell cycle progress, which contrasted our findings during infections with two SARS-CoV-2 variants, where cell cycle progress was linked to delayed IRF9 response. Our results point to the possibility of CoV-MAC-TED-assisted, rapid individual host cell response identification upon virus infections. Conclusion: The complex trait CoV-MAC-TED can identify similar and differential early responses of SARS-CoV-2 and influenza H3N2 viruses. This indicates its appropriateness to search for anti-viral targets in view of therapeutic design strategies. For standardization, human NECs can be used. This marker/cell system is promising to identify differential early cell responses upon viral infections also depending on cell origins.

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