High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection

Mixed Infections Unravel Novel HCV Inter-Genotypic Recombinant Forms within the Conserved IRES Region

Hepatitis C virus (HCV) remains a significant global health challenge, affecting millions of people worldwide, with chronic infection a persistent threat. Despite the advent of direct-acting antivirals (DAAs), challenges in diagnosis and treatment remain, compounded by the lack of an effective vaccine. The HCV genome, characterized by high genetic variability, consists of eight distinct genotypes and over ninety subtypes, underscoring the complex dynamics of the virus within infected individuals. This study delves into the intriguing realm of HCV genetic diversity, specifically exploring the phenomenon of mixed infections and the subsequent detection of recombinant forms within the conserved internal ribosome entry site (IRES) region. Previous studies have identified recombination as a rare event in HCV. However, our findings challenge this notion by providing the first evidence of 1a/3a (and vice versa) inter-genotypic recombination within the conserved IRES region. Utilizing advanced sequencing methods, such as deep sequencing and molecular cloning, our study reveals mixed infections involving genotypes 1a and 3a. This comprehensive approach not only confirmed the presence of mixed infections, but also identified the existence of recombinant forms not previously seen in the IRES region. The recombinant sequences, although present as low-frequency variants, open new avenues for understanding HCV evolution and adaptation.

Evaluation of recombination detection methods for viral sequencing

Recombination is a key evolutionary driver in shaping novel viral populations and lineages. When unaccounted for, recombination can impact evolutionary estimations or complicate their interpretation. Therefore, identifying signals for recombination in sequencing data is a key prerequisite to further analyses. A repertoire of recombination detection methods (RDMs) have been developed over the past two decades; however, the prevalence of pandemic-scale viral sequencing data poses a computational challenge for existing methods. Here, we assessed eight RDMs: PhiPack (Profile), 3SEQ, GENECONV, recombination detection program (RDP) (OpenRDP), MaxChi (OpenRDP), Chimaera (OpenRDP), UCHIME (VSEARCH), and gmos; to determine if any are suitable for the analysis of bulk sequencing data. To test the performance and scalability of these methods, we analysed simulated viral sequencing data across a range of sequence diversities, recombination frequencies, and sample sizes. Furthermore, we provide a practical example for the analysis and validation of empirical data. We find that RDMs need to be scalable, use an analytical approach and resolution that is suitable for the intended research application, and are accurate for the properties of a given dataset (e.g. sequence diversity and estimated recombination frequency). Analysis of simulated and empirical data revealed that the assessed methods exhibited considerable trade-offs between these criteria. Overall, we provide general guidelines for the validation of recombination detection results, the benefits and shortcomings of each assessed method, and future considerations for recombination detection methods for the assessment of large-scale viral sequencing data.

Evolution of within-host variants of the hepatitis C virus

INTRODUCTION

Comprehensive investigation of the within-host evolution of hepatitis C virus (HCV) variants has been difficult without high coverage deep sequencing data and bioinformatics tools to characterise these variants. With the advent of high throughput, long-read sequencing platforms such as Oxford Nanopore Technology (ONT), capturing within-host evolution of HCV using full genome sequences has become feasible. This study aimed to provide the proof of concept that within-host evolutionary analysis of HCV using near-full-length genomes, is achievable.

METHODS

Five treatment naïve subjects with chronic HCV infection were sampled longitudinally from 6 months to 5 years post-infection, with 3-5 sampling timepoints per subject. Near full-length sequences generated using the ONT platform encompassing within-host HCV variants were analysed using an in-house bioinformatic tool. A 200-sequence proxy alignment of the viral variants was made for each subject and timepoint, proportionately representing the observed within-host variants. This alignment was then used in a Bayesian evolutionary analysis using BEAST software suite (v1.8).

RESULTS

The estimated within-host substitution rates ranged between 0.89 and 6.19 × 10^-5 substitutions/site/day. At most timepoints, observed viral lineages were closely related to those from the immediately preceding timepoint, and genetic diversity bottlenecks were observed at intervals in both the acute and chronic phases of infection. The highest within-host mutation rates were observed in the Envelope-P7 and NS5 regions while the Core region was the most conserved.

CONCLUSION

This study demonstrates the feasibility of studying within-host evolution of near-full-length HCV genomes, using long-read sequencing platforms. When considered in conjunction with meta-data such as the host immune response, these methods may offer high resolution insights into immune escape (in vivo or in vitro) to inform vaccine design and to predict spontaneous clearance.

OUP accepted manuscript

Even 30 years after the discovery of the hepatitis C virus (HCV) in humans there is still no vaccine available. Reasons for this include the high mutation rate of HCV, which allows the virus to escape immune recognition and the absence of an immunocompetent animal model for vaccine development. Phylogenetically distinct hepaciviruses (genus Hepacivirus, family Flaviviridae) have been isolated from diverse species, each with a narrow host range: the equine hepacivirus (EqHV) is the closest known relative of HCV. In this study, we used amplicon-based deep-sequencing to investigate the viral intra-host population composition of the genomic regions encoding the surface glycoproteins E1 and E2. Patterns of E1E2 substitutional evolution were compared in longitudinally sampled EqHV-positive sera of naturally and experimentally infected horses and HCV-positive patients. Intra-host virus diversity was higher in chronically than in acutely infected horses, a pattern which was similar in the HCV-infected patients. However, overall glycoprotein variability was higher in HCV compared to EqHV. Additionally, selection pressure in HCV populations was higher, especially within the N-terminal region of E2, corresponding to the hypervariable region 1 (HVR1) in HCV. An alignment of glycoprotein sequences from diverse hepaciviruses identified the HVR1 as a unique characteristic of HCV: hepaciviruses from non-human species lack this region. Together, these data indicate that EqHV infection of horses could represent a powerful surrogate animal model to gain insights into hepaciviral evolution and HCVs HVR1-mediated immune evasion strategy.

Comparative Analysis of Within-Host Mutation Patterns and Diversity of Hepatitis C Virus Subtypes 1a, 1b, and 3a

Understanding within-host evolution is critical for predicting viral evolutionary outcomes, yet such studies are currently lacking due to difficulty involving human subjects. Hepatitis C virus (HCV) is an RNA virus with high mutation rates. Its complex evolutionary dynamics and extensive genetic diversity are demonstrated in over 67 known subtypes. In this study, we analyzed within-host mutation frequency patterns of three HCV subtypes, using a large number of samples obtained from treatment-naïve participants by next-generation sequencing. We report that overall mutation frequency patterns are similar among subtypes, yet subtype 3a consistently had lower mutation frequencies and nucleotide diversity, while subtype 1a had the highest. We found that about 50% of genomic sites are highly conserved across subtypes, which are likely under strong purifying selection. We also compared within-host and between-host selective pressures, which revealed that Hyper Variable Region 1 within hosts was under positive selection, but was under slightly negative selection between hosts, which indicates that many mutations created within hosts are removed during the transmission bottleneck. Examining the natural prevalence of known resistance-associated variants showed their consistent existence in the treatment-naïve participants. These results provide insights into the differences and similarities among HCV subtypes that may be used to develop and improve HCV therapies.

Field validation of phylodynamic analytical methods for inference on epidemiological processes in wildlife

Amongst newly developed approaches to analyse molecular data, phylodynamic models are receiving much attention because of their potential to reveal changes to viral populations over short periods. This knowledge can be very important for understanding disease impacts. However, their accuracy needs to be fully understood, especially in relation to wildlife disease epidemiology, where sampling and prior knowledge may be limited. The release of the rabbit haemorrhagic disease virus (RHDV) as biological control in naïve rabbit populations in Australia in 1996 provides a unique data set with which to validate phylodynamic models. By comparing results obtained from RHDV sequence data with our current understanding of RHDV epidemiology in Australia, we evaluated the performances of these recently developed models. In line with our expectations, coalescent analyses detected a sharp increase in the virus population size in the first few months after release, followed by a more gradual increase. Phylodynamic analyses using a birth-death model generated effective reproductive number estimates (the average number of secondary infections per each infectious case, R_e ) larger than one for most of the epochs considered. However, the possible range of the initial R_e included estimates lower than one despite the known rapid spread of RHDV in Australia. Furthermore, the analyses that accounted for geographical structuring failed to converge. We argue that the difficulties that we encountered most likely stem from the fact that the samples available from 1996 to 2014 were too sparse with respect to both geographic and within outbreak coverage to adequately infer some of the model parameters. In general, while these phylodynamic analyses proved to be greatly informative in some regards, we caution that their interpretation may not be straightforward. We recommend further research to evaluate the robustness of these models to assumption violations and sensitivity to sampling regimes.

Viral and host heterogeneity and their effects on the viral life cycle

Traditionally, the viral replication cycle is envisioned as a single, well-defined loop with four major steps: attachment and entry into a target cell, replication of the viral genome, maturation of viral proteins and genome packaging into infectious progeny, and egress and dissemination to the next target cell. However, for many viruses, a growing body of evidence points towards extreme heterogeneity in each of these steps. In this Review, we reassess the major steps of the viral replication cycle by highlighting recent advances that show considerable variability during viral infection. First, we discuss heterogeneity in entry receptors, followed by a discussion on error-prone and low-fidelity polymerases and their impact on viral diversity. Next, we cover the implications of heterogeneity in genome packaging and assembly on virion morphology. Last, we explore alternative egress mechanisms, including tunnelling nanotubes and host microvesicles. In summary, we discuss the implications of viral phenotypic, morphological and genetic heterogeneity on pathogenesis and medicine. This Review highlights common themes and unique features that give nuance to the viral replication cycle.

Opportunistic treatment of hepatitis C virus infection (OPPORTUNI-C): study protocol for a pragmatic stepped wedge cluster randomized trial of immediate versus outpatient treatment initiation among hospitalized people who inject drugs

Background

Scaled-up direct-acting antiviral (DAA) treatment of hepatitis C virus (HCV) infection among people who inject drugs (PWID) is crucial to reach the World Health Organization HCV elimination targets within 2030. One of the critical obstacles to HCV care in this population is the lack of treatment models within specialist healthcare adapted to marginalized individuals.

Methods

OPPORTUNI-C is a pragmatic stepped wedge cluster randomized trial comparing the efficacy of immediate initiation of HCV treatment with the current standard of care among PWID admitted for inpatient care. Screening for HCV RNA will be performed as soon as possible after admission. The intervention includes immediate non-invasive liver disease assessment, counseling, and initiation of pan-genotypic DAA treatment with individualized follow-up. Standard of care is a referral to outpatient care at discharge. To mimic usual clinical practice as closely as possible, we will use a pragmatic clinical trial approach utilizing clinical infrastructure, broad eligibility criteria, flexible intervention delivery, clinically relevant outcomes, and collection of data readily available from the electronic patient files. The stepped wedge design involves a sequential rollout of the intervention over 16 months, in which seven participating clusters will be randomized from standard of care to intervention in a stepwise manner. Randomization will be stratified according to cluster size to keep high prevalence clusters separated. The trial will include approximately 220 HCV RNA positive individuals recruited from departments of internal medicine, addiction medicine, and psychiatry at Akershus University Hospital, Oslo University Hospital, and Lovisenberg Diaconal Hospital, Oslo, Norway. Individuals not able or willing to give informed consent and those with ongoing HCV assessment or treatment will be excluded. The primary outcome is treatment completion, defined as dispensing of the final prescribed DAA package from the pharmacy within 6 months after inclusion. Secondary outcomes include treatment uptake, virologic response, reinfection incidence, and resistance-associated substitutions.

Discussion

Representing a novel model of care suited to reach and engage marginalized PWID in HCV care, this study will inform HCV elimination efforts locally and internationally. If the model proves efficacious and feasible, it should be considered for broader implementation, replacing the current standard of care.

Trial registration

ClinicalTrials.gov, NCT04220645. Registered on 7 January 2020.

High-throughput sequencing (HTS) for the analysis of viral populations

The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.

Next-generation sequencing for the clinical management of hepatitis C virus infections: does one test fits all purposes?

While the prospect of viral cure is higher than ever for individuals infected with the hepatitis C virus (HCV) due to ground-breaking progress in antiviral treatment, success rates are still negatively influenced by HCV's high genetic variability. This genetic diversity is represented in the circulation of various genotypes and subtypes, mixed infections, recombinant forms and the presence of numerous drug resistant variants among infected individuals. Common misclassifications by commercial genotyping assays in combination with the limitations of currently used targeted population sequencing approaches have encouraged researchers to exploit alternative methods for the clinical management of HCV infections. Next-generation sequencing (NGS), a revolutionary and powerful tool with a variety of applications in clinical virology, can characterize viral diversity and depict viral dynamics in an ultra-wide and ultra-deep manner. The level of detail it provides makes it the method of choice for the diagnosis and clinical assessment of HCV infections. The sequence library provided by NGS is of a higher magnitude and sensitivity than data generated by conventional methods. Therefore, these technologies are helpful to guide clinical practice and at the same time highly valuable for epidemiological studies. The decreasing costs of NGS to determine genotypes, mixed infections, recombinant strains and drug resistant variants will soon make it feasible to employ NGS in clinical laboratories, to assist in the daily care of patients with HCV.

Inconsistent temporal patterns of genetic variation of HCV among high-risk subjects may impact inference of transmission networks

Hepatitis-C Virus (HCV) sequences are often used to establish networks of people who inject drugs (PWID). However, the degree to which within-host evolutionary dynamics affect those inferences has not been carefully studied. Here, we analyzed 702 longitudinally-sampled HCV E1 sequences from 88 HCV+ people who inject drugs (PWID) in the Baltimore Before and After Acute Study of Hepatitis (BBAASH) cohort. Individuals were tested for HCV RNA over multiple visits to the clinic, and the HCV E1 gene was sequenced for HCV+ samples. Genetic clustering was performed on the full set of sequences using a 3% genetic distance threshold to define epidemiological linkage. Maximum-likelihood (ML) phylogenies were inferred to assess evolutionary relationships. We found 22 clusters containing sequences sampled over five or more years (long-term clusters, LTC), of which 17 had >1 subject. In six of the multi-subject LTC, one subject had a sequence sampled >3 years earlier or later than the next-closest subject in the cluster (time-gap LTC). ML trees showed that, in three of the time-gap LTC, two subjects had identical sequences despite 7-10 years separating the sampling times. In four of the time-gap LTC for whom additional data were available, the subject with the later detected shared variant had both different variants and visits with no detectable HCV RNA (RNA-) prior to the appearance of the shared variant. In the subject with the earlier detection of the shared variant, different variants and RNA- visits were also detected in multiple cases subsequent to appearance of the shared variant. Complex patterns of shared viral variation among PWID reflect on-going re-infection, multiple transmission partners, and/or inconsistent detection of viral variants. Our results suggest that transmission events are currently underestimated by analysis of sequences at a single point in time.