Segment-specific kinetics of mRNA, cRNA, and vRNA accumulation during influenza virus infection

Thu Phan, Elizabeth J. Fay, Zion Lee, Stephanie Aron, Wei Shou Hu, Ryan A. Langlois

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Influenza A virus (IAV) is a segmented negative-sense RNA virus and is the cause of major epidemics and pandemics. The replication of IAV is complex, involving the production of three distinct RNA species, namely mRNA, cRNA, and viral RNA (vRNA), for all eight genome segments. While understanding IAV replication kinetics is important for drug development and improving vaccine production, current methods for studying IAV kinetics have been limited by the ability to detect all three different RNA species in a scalable manner. Here, we report the development of a novel pipeline using total stranded RNA sequencing (RNA-Seq), which we named influenza virus enumerator of RNA transcripts (InVERT), that allows for the simultaneous quantification of all three RNA species produced by IAV. Using InVERT, we provide a full landscape of the IAV replication kinetics and found that different groups of viral genes follow different kinetics. The segments coding for RNA-dependent RNA polymerase (RdRP) produced more vRNA than mRNA, while some other segments (NP, NS, and hemagglutinin [HA]) consistently made more mRNA than vRNA. vRNA expression levels did not correlate with cRNA expression, suggesting complex regulation of vRNA synthesis. Furthermore, by studying the kinetics of a virus lacking the capacity to generate new polymerase complexes, we found evidence that further supports a model in which cRNA synthesis requires newly synthesized RdRP and that incoming RdRP can only generate mRNA. Overall, InVERT is a powerful tool for quantifying IAV RNA species to elucidate key features of IAV replication.

Original languageEnglish (US)
Article numbere02102-20
JournalJournal of virology
Volume95
Issue number10
DOIs
StatePublished - May 2021

Bibliographical note

Funding Information:
We thank the University of Minnesota Genomics Center and the Minnesota Supercomputing Institute for their services and support of these studies. This work was funded by R01 AI148669 to R.A.L. E.J.F. was supported by a doctoral dissertation fellowship from the University of Minnesota.

Publisher Copyright:
© 2021 Phan et al.

Keywords

  • Influenza virus

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