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Genetically distinct within-host subpopulations of hepatitis C virus persist after Direct-Acting Antiviral treatment failure

Abstract:
Analysis of viral genetic data has previously revealed distinct within-host population structures in both untreated and interferon-treated chronic hepatitis C virus (HCV) infections. While multiple subpopulations persisted during the infection, each subpopulation was observed only intermittently. However, it was unknown whether similar patterns were also present after Direct-Acting Antiviral (DAA) treatment, where viral populations were often assumed to go through narrow bottlenecks. Here we tested for the maintenance of population structure after DAA treatment failure, and whether there were different evolutionary rates along distinct lineages where they were observed. We analysed whole-genome next-generation sequencing data generated from a randomised study using DAAs (the BOSON study). We focused on samples collected from patients (N=84) who did not achieve sustained virological response (i.e., treatment failure) and had sequenced virus from multiple timepoints. Given the short-read nature of the data, we used a number of methods to identify distinct within-host lineages including tracking concordance in intra-host nucleotide variant (iSNV) frequencies, applying sequenced-based and tree-based clustering algorithms to sliding windows along the genome, and haplotype reconstruction. Distinct viral subpopulations were maintained among a high proportion of individuals post DAA treatment failure. Using maximum likelihood modelling and model comparison, we found an overdispersion of viral evolutionary rates among individuals, and significant differences in evolutionary rates between lineages within individuals. These results suggest the virus is compartmentalised within individuals, with the varying evolutionary rates due to different viral replication rates and/or different selection pressures. We endorse lineage awareness in future analyses of HCV evolution and infections to avoid conflating patterns from distinct lineages, and to recognise the likely existence of unsampled subpopulations.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.ppat.1012959

Authors

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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Pandemic Sciences Institute
Role:
Author
ORCID:
0000-0002-2807-1914
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Pandemic Sciences Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Biology
Role:
Author
ORCID:
0000-0001-5518-7843
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Pandemic Sciences Institute
Role:
Author
ORCID:
0000-0002-4123-3287
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Pandemic Sciences Institute
Role:
Author


More from this funder
Funder identifier:
https://ror.org/029chgv08
Grant:
107652/Z/15/A
203141/Z/16/Z
222426/Z/21/Z


Publisher:
Public Library of Science
Journal:
PLoS Pathogens More from this journal
Volume:
21
Issue:
4
Article number:
e1012959
Publication date:
2025-04-01
Acceptance date:
2025-02-05
DOI:
EISSN:
1553-7374
ISSN:
1553-7366


Language:
English
Pubs id:
2084082
Local pid:
pubs:2084082
Deposit date:
2025-02-06
ARK identifier:

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