Superinfection and cure of infected cells as mechanisms for hepatitis C virus adaptation and persistence.
Ruian KeHui LiShuyi WangWenge DingRuy M RibeiroElena E GiorgiTanmoy BhattacharyaRichard J O BarnardBeatrice H HahnGeorge M ShawAlan S PerelsonPublished in: Proceedings of the National Academy of Sciences of the United States of America (2018)
RNA viruses exist as a genetically diverse quasispecies with extraordinary ability to adapt to abrupt changes in the host environment. However, the molecular mechanisms that contribute to their rapid adaptation and persistence in vivo are not well studied. Here, we probe hepatitis C virus (HCV) persistence by analyzing clinical samples taken from subjects who were treated with a second-generation HCV protease inhibitor. Frequent longitudinal viral load determinations and large-scale single-genome sequence analyses revealed rapid antiviral resistance development, and surprisingly, dynamic turnover of dominant drug-resistant mutant populations long after treatment cessation. We fitted mathematical models to both the viral load and the viral sequencing data, and the results provided strong support for the critical roles that superinfection and cure of infected cells play in facilitating the rapid turnover and persistence of viral populations. More broadly, our results highlight the importance of considering viral dynamics and competition at the intracellular level in understanding rapid viral adaptation. Thus, we propose a theoretical framework integrating viral and molecular mechanisms to explain rapid viral evolution, resistance, and persistence despite antiviral treatment and host immune responses.
Keyphrases
- hepatitis c virus
- sars cov
- drug resistant
- human immunodeficiency virus
- induced apoptosis
- loop mediated isothermal amplification
- immune response
- cell cycle arrest
- single cell
- signaling pathway
- electronic health record
- toll like receptor
- cell death
- cross sectional
- machine learning
- genome wide
- postmenopausal women
- cell proliferation
- cystic fibrosis
- artificial intelligence
- genetic diversity
- newly diagnosed
- wild type