High-resolution evolutionary analysis of within-host hepatitis C virus infection

Jayna Raghwani, Chieh-Hsi Wu, Cynthia K. Y. Ho, Menno de Jong, Richard Molenkamp, Janke Schinkel, Oliver G. Pybus, Katrina A. Lythgoe

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background. Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. Methods. We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. Results. We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10?7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. Conclusions. Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.
Original languageEnglish
Pages (from-to)1722-1729
JournalJournal of Infectious Diseases
Volume219
Issue number11
DOIs
Publication statusPublished - 2019

Cite this

Raghwani, J., Wu, C-H., Ho, C. K. Y., de Jong, M., Molenkamp, R., Schinkel, J., ... Lythgoe, K. A. (2019). High-resolution evolutionary analysis of within-host hepatitis C virus infection. Journal of Infectious Diseases, 219(11), 1722-1729. https://doi.org/10.1093/infdis/jiy747
Raghwani, Jayna ; Wu, Chieh-Hsi ; Ho, Cynthia K. Y. ; de Jong, Menno ; Molenkamp, Richard ; Schinkel, Janke ; Pybus, Oliver G. ; Lythgoe, Katrina A. / High-resolution evolutionary analysis of within-host hepatitis C virus infection. In: Journal of Infectious Diseases. 2019 ; Vol. 219, No. 11. pp. 1722-1729.
@article{0b00e245423f4e8a9da97c171c28bed9,
title = "High-resolution evolutionary analysis of within-host hepatitis C virus infection",
abstract = "Background. Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. Methods. We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. Results. We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10?7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. Conclusions. Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.",
author = "Jayna Raghwani and Chieh-Hsi Wu and Ho, {Cynthia K. Y.} and {de Jong}, Menno and Richard Molenkamp and Janke Schinkel and Pybus, {Oliver G.} and Lythgoe, {Katrina A.}",
year = "2019",
doi = "10.1093/infdis/jiy747",
language = "English",
volume = "219",
pages = "1722--1729",
journal = "Journal of Infectious Diseases",
issn = "0022-1899",
publisher = "Oxford University Press",
number = "11",

}

Raghwani, J, Wu, C-H, Ho, CKY, de Jong, M, Molenkamp, R, Schinkel, J, Pybus, OG & Lythgoe, KA 2019, 'High-resolution evolutionary analysis of within-host hepatitis C virus infection' Journal of Infectious Diseases, vol. 219, no. 11, pp. 1722-1729. https://doi.org/10.1093/infdis/jiy747

High-resolution evolutionary analysis of within-host hepatitis C virus infection. / Raghwani, Jayna; Wu, Chieh-Hsi; Ho, Cynthia K. Y.; de Jong, Menno; Molenkamp, Richard; Schinkel, Janke; Pybus, Oliver G.; Lythgoe, Katrina A.

In: Journal of Infectious Diseases, Vol. 219, No. 11, 2019, p. 1722-1729.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - High-resolution evolutionary analysis of within-host hepatitis C virus infection

AU - Raghwani, Jayna

AU - Wu, Chieh-Hsi

AU - Ho, Cynthia K. Y.

AU - de Jong, Menno

AU - Molenkamp, Richard

AU - Schinkel, Janke

AU - Pybus, Oliver G.

AU - Lythgoe, Katrina A.

PY - 2019

Y1 - 2019

N2 - Background. Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. Methods. We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. Results. We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10?7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. Conclusions. Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.

AB - Background. Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population. Methods. We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics. Results. We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10?7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection. Conclusions. Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85062690334&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30602023

U2 - 10.1093/infdis/jiy747

DO - 10.1093/infdis/jiy747

M3 - Article

VL - 219

SP - 1722

EP - 1729

JO - Journal of Infectious Diseases

JF - Journal of Infectious Diseases

SN - 0022-1899

IS - 11

ER -