Temporal variations in the hepatitis C virus intrahost population during chronic infection. J Virol. 2011;85:6369-6380. [PMID: 21525348 DOI: 10.1128/jvi.02204-10]

Widespread hepatitis C virus transmission network among people who inject drugs in Kenya

OBJECTIVES

Hepatitis C virus (HCV) disproportionately affects people who inject drugs (PWID) worldwide. Despite carrying a high HCV burden, little is known about transmission dynamics in low- and middle-income countries.

METHODS

We recruited PWID from Nairobi and coastal cities and towns of Mombasa, Kilifi, and Malindi in Kenya at needle and syringe programs. Next-generation sequencing data from HCV hypervariable region 1 were analyzed using Global Hepatitis Outbreak and Surveillance Technology to identify transmission clusters.

RESULTS

HCV strains belonged to genotype 1a (n = 64, 46.0%), 4a (n = 72, 51.8%) and mixed HCV/1a/4a (n = 3, 2.2%). HCV/1a was dominant (61.2%) in Nairobi, whereas HCV/4a was dominant in Malindi (85.7%) and Kilifi (60.9%), and both genotypes were evenly identified in Mombasa (45.3% for HCV/1a and 50.9% for HCV/4a). Global Hepatitis Outbreak and Surveillance Technology identified 11 transmission clusters involving 90 cases. Strains in the two largest clusters (n = 38 predominantly HCV/4a and n = 32 HCV/1a) were sampled from all four sites.

CONCLUSIONS

Transmission clusters involving 64.7% of cases indicate an effective sampling of major HCV strains circulating among PWID. Large clusters involving 77.8% of clustered strains from Nairobi and Coast suggest successful introduction of two ancestral HCV/1a and HCV/4a strains to PWID and the existence of a widespread transmission network in the country. The disruption of this network is essential for HCV elimination.

Antigenic cooperation in viral populations: Transformation of functions of intra-host viral variants

In this paper, we study intra-host viral adaptation by antigenic cooperation - a mechanism of immune escape that serves as an alternative to the standard mechanism of escape by continuous genomic diversification and allows to explain a number of experimental observations associated with the establishment of chronic infections by highly mutable viruses. Within this mechanism, the topology of a cross-immunoreactivity network forces intra-host viral variants to specialize for complementary roles and adapt to the host's immune response as a quasi-social ecosystem. Here we study dynamical changes in immune adaptation caused by evolutionary and epidemiological events. First, we show that the emergence of a viral variant with altered antigenic features may result in a rapid re-arrangement of the viral ecosystem and a change in the roles played by existing viral variants. In particular, it may push the population under immune escape by genomic diversification towards the stable state of adaptation by antigenic cooperation. Next, we study the effect of a viral transmission between two chronically infected hosts, which results in the merging of two intra-host viral populations in the state of stable immune-adapted equilibrium. In this case, we also describe how the newly formed viral population adapts to the host's environment by changing the functions of its members. The results are obtained analytically for minimal cross-immunoreactivity networks and numerically for larger populations.

Genetic Diversity of Grapevine Virus A in Three Australian Vineyards Using Amplicon High Throughput Sequencing (Amplicon-HTS)

Shiraz disease (SD) is one of the most destructive viral diseases of grapevines in Australia and is known to cause significant economic loss to local growers. Grapevine virus A (GVA) was reported to be the key pathogen associated with this disease. This study aimed to better understand the diversity of GVA variants both within and between individual SD and grapevine leafroll disease (LRD) affected grapevines located at vineyards in South Australia. Amplicon high throughput sequencing (Amplicon-HTS) combined with median-joining networks (MJNs) was used to analyze the variability in specific gene regions of GVA variants. Several GVAII variant groups contain samples from both vineyards studied, suggesting that these GVAII variants were from a common origin. Variant groups analyzed by MJNs using the overall data set denote that there may be a possible relationship between variant groups of GVA and the geographical location of the grapevines.

Primary case inference in viral outbreaks through analysis of intra-host variant population

Background

Investigation of outbreaks to identify the primary case is crucial for the interruption and prevention of transmission of infectious diseases. These individuals may have a higher risk of participating in near future transmission events when compared to the other patients in the outbreak, so directing more transmission prevention resources towards these individuals is a priority. Although the genetic characterization of intra-host viral populations can aid the identification of transmission clusters, it is not trivial to determine the directionality of transmissions during outbreaks, owing to complexity of viral evolution. Here, we present a new computational framework, PYCIVO: primary case inference in viral outbreaks. This framework expands upon our earlier work in development of QUENTIN, which builds a probabilistic disease transmission tree based on simulation of evolution of intra-host hepatitis C virus (HCV) variants between cases involved in direct transmission during an outbreak. PYCIVO improves upon QUENTIN by also adding a custom heterogeneity index and identifying the scenario when the primary case may have not been sampled.

Results

These approaches were validated using a set of 105 sequence samples from 11 distinct HCV transmission clusters identified during outbreak investigations, in which the primary case was epidemiologically verified. Both models can detect the correct primary case in 9 out of 11 transmission clusters (81.8%). However, while QUENTIN issues erroneous predictions on the remaining 2 transmission clusters, PYCIVO issues a null output for these clusters, giving it an effective prediction accuracy of 100%. To further evaluate accuracy of the inference, we created 10 modified transmission clusters in which the primary case had been removed. In this scenario, PYCIVO was able to correctly identify that there was no primary case in 8/10 (80%) of these modified clusters. This model was validated with HCV; however, this approach may be applicable to other microbial pathogens.

Conclusions

PYCIVO improves upon QUENTIN by also implementing a custom heterogeneity index which empowers PYCIVO to make the important ‘No primary case’ prediction. One or more samples, possibly including the primary case, may have not been sampled, and this designation is meant to account for these scenarios.

Difference of Intrahost Dynamics of the Second Human Pegivirus and Hepatitis C Virus in HPgV-2/HCV-Coinfected Patients

Background

The second human pegivirus (HPgV-2) and hepatitis C virus (HCV) belong to the Flaviviridae family and share some common genome features. However, the two viruses exhibit significantly different genetic diversity. The comparison of intrahost dynamics of HPgV-2 and HCV that mainly reflect virus-host interactions is needed to elucidate their intrahost difference of genetic diversity and the possible mechanisms.

Methods

Intrahost single nucleotide variations (iSNVs) were identified by means of next-generation sequencing from both cross-sectional and longitudinal samples from HPgV-2- and HCV-coinfected patients. The levels of human cytokines were quantified in the patient before and after HCV elimination by the treatment of direct-acting antivirals (DAA).

Results

Unlike HCV, the viral sequences of HPgV-2 are highly conserved among HPgV-2-infected patients. However, iSNV analysis confirmed the intrahost variation or quasispecies of HPgV-2. Almost all iSNVs of HPgV-2 did not accumulate or transmit within host over time, which may explain the highly conserved HPgV-2 consensus sequence. Intrahost variation of HPgV-2 mainly causes nucleotide transition in particular at the 3rd codon position and synonymous substitutions, indicating purifying or negative selection posed by host immune system. Cytokine data further indicate that HPgV-2 infection alone may not efficiently stimulate innate immune responses since proinflammatory cytokine expression dramatically decreased with elimination of HCV.

Conclusion

This study provided new insights into the intrahost genomic variations and evolutionary dynamics of HPgV-2 as well as the impact of host immune selection and virus polymerase on virus evolution. The different genetic diversity of HPgV-2 and HCV makes HPgV-2 a potential new model to investigate RNA virus diversity and the mechanism of viral polymerase in modulating virus replication.

Intra-host evolutionary dynamics of the hepatitis C virus among people who inject drugs

Most individuals chronically infected with hepatitis C virus (HCV) are asymptomatic during the initial stages of infection and therefore the precise timing of infection is often unknown. Retrospective estimation of infection duration would improve existing surveillance data and help guide treatment. While intra-host viral diversity quantifications such as Shannon entropy have previously been utilized for estimating duration of infection, these studies characterize the viral population from only a relatively short segment of the HCV genome. In this study intra-host diversities were examined across the HCV genome in order to identify the region most reflective of time and the degree to which these estimates are influenced by high-risk activities including those associated with HCV acquisition. Shannon diversities were calculated for all regions of HCV from 78 longitudinally sampled individuals with known seroconversion timeframes. While the region of the HCV genome most accurately reflecting time resided within the NS3 gene, the gene region with the highest capacity to differentiate acute from chronic infections was identified within the NS5b region. Multivariate models predicting duration of infection from viral diversity significantly improved upon incorporation of variables associated with recent public, unsupervised drug use. These results could assist the development of strategic population treatment guidelines for high-risk individuals infected with HCV and offer insights into variables associated with a likelihood of transmission.

A Phylogenetic Analysis of Hepatitis C Virus Transmission, Relapse, and Reinfection Among People Who Inject Drugs Receiving Opioid Agonist Therapy

BACKGROUND

Understanding hepatitis C virus (HCV) transmission among people who inject drugs (PWID) is essential for HCV elimination. We aimed to differentiate reinfections from treatment failures and to identify transmission linkages and associated factors in a cohort of PWID receiving opioid agonist therapy (OAT).

METHODS

We analyzed baseline and follow-up specimens from 150 PWID from 3 OAT clinics in the Bronx, New York. Next-generation sequencing data from the hypervariable region 1 of HCV were analyzed using Global Hepatitis Outbreak and Surveillance Technology.

RESULTS

There were 3 transmission linkages between study participants. Sustained virologic response (SVR) was not achieved in 9 participants: 7 had follow-up specimens with similar sequences to baseline, and 2 died. In 4 additional participants, SVR was achieved but the participants were viremic at later follow-up: 2 were reinfected with different strains, 1 had a late treatment failure, and 1 was transiently viremic 17 months after treatment. All transmission linkages were from the same OAT clinic and involved spousal or common-law partnerships.

CONCLUSION

This study highlights the use of next-generation sequencing as an important tool for identifying viral transmission and to help distinguish relapse and reinfection among PWID. Results reinforce the need for harm reduction interventions among couples and those who report ongoing risk factors after SVR.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections

Detection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. We studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected features measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. Distributions of the viral population features differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a machine learning classifier for the infection staging, which yielded a detection accuracy of 95.22 per cent, thus providing a higher accuracy than other genomic-based models. The detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, which could potentially complement and/or substitute standard laboratory assays.

Analysis of heterogeneous genomic samples using image normalization and machine learning

BACKGROUND

Analysis of heterogeneous populations such as viral quasispecies is one of the most challenging bioinformatics problems. Although machine learning models are becoming to be widely employed for analysis of sequence data from such populations, their straightforward application is impeded by multiple challenges associated with technological limitations and biases, difficulty of selection of relevant features and need to compare genomic datasets of different sizes and structures.

RESULTS

We propose a novel preprocessing approach to transform irregular genomic data into normalized image data. Such representation allows to restate the problems of classification and comparison of heterogeneous populations as image classification problems which can be solved using variety of available machine learning tools. We then apply the proposed approach to two important problems in molecular epidemiology: inference of viral infection stage and detection of viral transmission clusters using next-generation sequencing data. The infection staging method has been applied to HCV HVR1 samples collected from 108 recently and 257 chronically infected individuals. The SVM-based image classification approach achieved more than 95% accuracy for both recently and chronically HCV-infected individuals. Clustering has been performed on the data collected from 33 epidemiologically curated outbreaks, yielding more than 97% accuracy.

CONCLUSIONS

Sequence image normalization method allows for a robust conversion of genomic data into numerical data and overcomes several issues associated with employing machine learning methods to viral populations. Image data also help in the visualization of genomic data. Experimental results demonstrate that the proposed method can be successfully applied to different problems in molecular epidemiology and surveillance of viral diseases. Simple binary classifiers and clustering techniques applied to the image data are equally or more accurate than other models.

High prevalence of Hepatitis C Virus infection among people who use crack cocaine in an important international drug trafficking route in Central-West Region Brazil

In this study, the prevalence rate, associated risk factors and genetic diversity of hepatitis C virus (HCV) infection were determined among people who use crack from an international drug trafficking route in Central-West, Brazil. Blood samples were collected from 700 users of crack from Campo Grande and two border cities of Mato Grosso do Sul State and tested for HCV infection using serological and molecular testing methodologies. Anti-HCV was detected in 31/700 (4.5%, 95% CI: 2.9-6.0%) and HCV RNA in 26/31 (83.9%) of anti-HCV positive samples. Phylogenetic analysis of three HCV sub-genomic regions (5'UTR, NS5B and HVR-1) revealed the circulation of 1a (73.9%), 1b (8.7%) and 3a (17.4%) genotypes. Next-generation sequencing and phylogenetic analysis of intra-host viral populations of HCV HVR-1 showed a significant variation in intra-host genetic diversity among infected individuals, with 58.8% composed of more than one sub-population. Bayesian analysis estimated that the most recent common HCV ancestor for strains identified here was introduced to this region after 1975 following expansion of intravenous drug use in Brazil. Multivariate analyses showed that only 'ever having injected drugs' was independently associated with HCV infection. These results indicate an increasing spread of multiple HCV strains requiring public health intervention, such as harm reduction, testing services and treatment among crack users in this important border region of Central Brazil.

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

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.

Inferring population genetics parameters of evolving viruses using time-series data

With the advent of deep sequencing techniques, it is now possible to track the evolution of viruses with ever-increasing detail. Here, we present Flexible Inference from Time-Series (FITS)-a computational tool that allows inference of one of three parameters: the fitness of a specific mutation, the mutation rate or the population size from genomic time-series sequencing data. FITS was designed first and foremost for analysis of either short-term Evolve & Resequence (E&R) experiments or rapidly recombining populations of viruses. We thoroughly explore the performance of FITS on simulated data and highlight its ability to infer the fitness/mutation rate/population size. We further show that FITS can infer meaningful information even when the input parameters are inexact. In particular, FITS is able to successfully categorize a mutation as advantageous or deleterious. We next apply FITS to empirical data from an E&R experiment on poliovirus where parameters were determined experimentally and demonstrate high accuracy in inference.

Next-generation sequencing analysis of new genotypes appearing during antiviral treatment of chronic hepatitis C reveals that these are selected from pre-existing minor strains

Coinfection with more than one hepatitis C virus (HCV) genotype is common, but its dynamics, particularly during antiviral treatment, remain largely unknown. We employed next-generation sequencing (NGS) to analyse sequential serum and peripheral blood mononuclear cell (PBMC) samples in seven patients with transient presence or permanent genotype change during antiviral treatment with interferon and ribavirin. Specimens were collected right before the therapy initiation and at 2, 4, 6, 8, 12, 20, 24, 36, 44 and 48 weeks during treatment and 6 months after treatment ceased. A mixture of two different genotypes was detected in the pretreatment samples from five patients and the minor genotype constituted 0.02 to 38 %. A transient or permanent change of the predominant genotype was observed in six patients. In three cases genotype 3 was replaced as the predominant genotype by genotype 4, in two cases genotype 3 was replaced by genotype 1, and in one subject genotype 1 was replaced by genotype 4. The PBMC- and serum-derived sequences were frequently discordant with respect to genotype and/or genotype proportions. In conclusion, pre-existing minor HCV genotypes can be selected rapidly during antiviral treatment and become transiently or permanently predominant. In coinfections involving genotype 3, genotype 3 was eliminated first from both the serum and PBMC compartments. The PBMC- and serum-derived HCV sequences were frequently discordant with respect to genotype and/or genotype proportions, suggesting that they constitute separate compartments with their own dynamics.

Using high-throughput sequencing for investigating intra-host hepatitis C evolution over long retrospective periods

Collections of biological samples held by hospitals represent invaluable resources for conducting retrospective evolutionary studies of chronic infections. Using high-throughput sequencing, those collections permit analysis of within-host genetic diversity over long follow-up periods, and allow a better understanding of resistance to treatment regimes during disease evolution. Here, we studied the evolution of hepatitis C virus (HCV) populations in two patients with an absence of response to dual therapies. We implemented amplicon sequencing to survey genomic variation at the Core and NS5B regions of HCV over a period of 13 years from blood samples obtained at multiple time points. We observed mixed infection by multiple HCV genotypes in both patients. Genetic heterogeneity and sample composition analysis provided information about the changes in viral population over the course of clinical treatment, with NS5B experiencing an increase in diversity after treatment initiation. Secondary infections were estimated to predate treatment year, and our results pointed towards diversifying selection occurring post-treatment, acting on standing genomic variation and maintaining high genetic heterogeneity during infection. For these two patients infected with multiple HCV genotypes, the maintenance of viral diversity was explained with the hypothesis of soft selective sweep started at the same time as antiviral treatment was initiated.

Laboratory Methods in Molecular Epidemiology: Viral Infections

Viruses, which are the most abundant biological entities on the planet, have been regarded as the "dark matter" of biology in the sense that despite their ubiquity and frequent presence in large numbers, their detection and analysis are not always straightforward. The majority of them are very small (falling under the limit of 0.5 μm), and collectively, they are extraordinarily diverse. In fact, the majority of the genetic diversity on the planet is found in the so-called virosphere, or the world of viruses. Furthermore, the most frequent viral agents of disease in humans display an RNA genome, and frequently evolve very fast, due to the fact that most of their polymerases are devoid of proofreading activity. Therefore, their detection, genetic characterization, and epidemiological surveillance are rather challenging. This review (part of the Curated Collection on Advances in Molecular Epidemiology of Infectious Diseases) describes many of the methods that, throughout the last few decades, have been used for viral detection and analysis. Despite the challenge of having to deal with high genetic diversity, the majority of these methods still depend on the amplification of viral genomic sequences, using sequence-specific or sequence-independent approaches, exploring thermal profiles or a single nucleic acid amplification temperature. Furthermore, viral populations, and especially those with RNA genomes, are not usually genetically uniform but encompass swarms of genetically related, though distinct, viral genomes known as viral quasispecies. Therefore, sequence analysis of viral amplicons needs to take this fact into consideration, as it constitutes a potential analytic problem. Possible technical approaches to deal with it are also described here. *This article is part of a curated collection.

Genetic diversity of Hepatitis C Virus in Pakistan using Next Generation Sequencing

BACKGROUND

In Pakistan, HCV disease is considered a major public health issue with about 10-17 million people suffering with this infection and rate is increasing every day without any hindrance. The currently available Pyrosequencing approach used to analyze complex viral genomes as it can determine minor variants. It is crucial to understand viral evolution and quasispecies diversity in complex viral strains.

OBJECTIVES

To assess genetic diversity in patients with HCV using Next Generation Sequencing (NGS) and compare nucleotide diversity of genotype 3a with respect to other genotypes.

STUDY DESIGN

Intra-host viral diversity of HCV was determined using NGS from 13 chronically HCV infected individuals. NGS of three different regions (E2 (HVR1), NS3 and NS5B) of HCV-3a allowed for a comprehensive analysis of the viral population.

RESULT

Phylogenetic analysis of different HCV genes revealed great variability within the Pakistani population. The average nucleotide diversity for HVR1, NS3 and NS5B was 0.029, 0.011 and 0.010 respectively.

CONCLUSION

Our findings clearly indicate that patient-2 greater quasispecies heterogeneity than other patients of same genotype-3a using phylogenetic and one step network analyses. Initially phylogenetic analysis of these three genes showed that genotype 3a samples have greater genetic diversity. However, no significant difference was determined when nucleotide variability of genotype 3a compared with other genotypes (1a, 1b, 2a & 4a).

Incorporation of Social Determinants of Health in the Peer-Reviewed Literature: A Systematic Review of Articles Authored by the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention

OBJECTIVES

Social determinants of health (SDHs) are the complex, structural, and societal factors that are responsible for most health inequities. Since 2003, the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) has researched how SDHs place communities at risk for communicable diseases and poor adolescent health. We described the frequency and types of SDHs discussed in articles authored by NCHHSTP.

METHODS

We used the MEDLINE/PubMed search engine to systematically review the frequency and type of SDHs that appeared in peer-reviewed publications available in PubMed from January 1, 2009, through December 31, 2014, with a NCHHSTP affiliation. We chose search terms to identify articles with a focus on the following SDH categories: income and employment, housing and homelessness, education and schooling, stigma or discrimination, social or community context, health and health care, and neighborhood or built environment. We classified articles based on the depth of topic coverage as "substantial" (ie, one of ≤3 foci of the article) or "minimal" (ie, one of ≥4 foci of the article).

RESULTS

Of 862 articles authored by NCHHSTP, 366 (42%) addressed the SDH factors of interest. Some articles addressed >1 SDH factor (366 articles appeared 568 times across the 7 categories examined), and we examined them for each category that they addressed. Most articles that addressed SDHs (449/568 articles; 79%) had a minimal SDH focus. SDH categories that were most represented in the literature were health and health care (190/568 articles; 33%) and education and schooling (118/568 articles; 21%).

CONCLUSIONS

This assessment serves as a baseline measurement of inclusion of SDH topics from NCHHSTP authors in the literature and creates a methodology that can be used in future assessments of this topic.

Transmissibility of intra-host hepatitis C virus variants

Background

Intra-host hepatitis C virus (HCV) populations are genetically heterogeneous and organized in subpopulations. With the exception of blood transfusions, transmission of HCV occurs via a small number of genetic variants, the effect of which is frequently described as a bottleneck. Stochasticity of transmission associated with the bottleneck is usually used to explain genetic differences among HCV populations identified in the source and recipient cases, which may be further exacerbated by intra-host HCV evolution and differential biological capacity of HCV variants to successfully establish a population in a new host.

Results

Transmissibility was formulated as a property that can be measured from experimental Ultra-Deep Sequencing (UDS) data. The UDS data were obtained from one large hepatitis C outbreak involving an epidemiologically defined source and 18 recipient cases. k-Step networks of HCV variants were constructed and used to identify a potential association between transmissibility and network centrality of individual HCV variants from the source. An additional dataset obtained from nine other HCV outbreaks with known directionality of transmission was used for validation.

Transmissibility was not found to be dependent on high frequency of variants in the source, supporting the earlier observations of transmission of minority variants. Among all tested measures of centrality, the highest correlation of transmissibility was found with Hamming centrality (r = 0.720; p = 1.57 E-71). Correlation between genetic distances and differences in transmissibility among HCV variants from the source was found to be 0.3276 (Mantel Test, p = 9.99 E-5), indicating association between genetic proximity and transmissibility. A strong correlation ranging from 0.565–0.947 was observed between Hamming centrality and transmissibility in 7 of the 9 additional transmission clusters (p < 0.05).

Conclusions

Transmission is not an exclusively stochastic process. Transmissibility, as formally measured in this study, is associated with certain biological properties that also define location of variants in the genetic space occupied by the HCV strain from the source. The measure may also be applicable to other highly heterogeneous viruses. Besides improving accuracy of outbreak investigations, this finding helps with the understanding of molecular mechanisms contributing to establishment of chronic HCV infection.

Characterization of Hepatitis C Virus (HCV) Envelope Diversification from Acute to Chronic Infection within a Sexually Transmitted HCV Cluster by Using Single-Molecule, Real-Time Sequencing

In contrast to other available next-generation sequencing platforms, PacBio single-molecule, real-time (SMRT) sequencing has the advantage of generating long reads albeit with a relatively higher error rate in unprocessed data. Using this platform, we longitudinally sampled and sequenced the hepatitis C virus (HCV) envelope genome region (1,680 nucleotides [nt]) from individuals belonging to a cluster of sexually transmitted cases. All five subjects were coinfected with HIV-1 and a closely related strain of HCV genotype 4d. In total, 50 samples were analyzed by using SMRT sequencing. By using 7 passes of circular consensus sequencing, the error rate was reduced to 0.37%, and the median number of sequences was 612 per sample. A further reduction of insertions was achieved by alignment against a sample-specific reference sequence. However, in vitro recombination during PCR amplification could not be excluded. Phylogenetic analysis supported close relationships among HCV sequences from the four male subjects and subsequent transmission from one subject to his female partner. Transmission was characterized by a strong genetic bottleneck. Viral genetic diversity was low during acute infection and increased upon progression to chronicity but subsequently fluctuated during chronic infection, caused by the alternate detection of distinct coexisting lineages. SMRT sequencing combines long reads with sufficient depth for many phylogenetic analyses and can therefore provide insights into within-host HCV evolutionary dynamics without the need for haplotype reconstruction using statistical algorithms.IMPORTANCE Next-generation sequencing has revolutionized the study of genetically variable RNA virus populations, but for phylogenetic and evolutionary analyses, longer sequences than those generated by most available platforms, while minimizing the intrinsic error rate, are desired. Here, we demonstrate for the first time that PacBio SMRT sequencing technology can be used to generate full-length HCV envelope sequences at the single-molecule level, providing a data set with large sequencing depth for the characterization of intrahost viral dynamics. The selection of consensus reads derived from at least 7 full circular consensus sequencing rounds significantly reduced the intrinsic high error rate of this method. We used this method to genetically characterize a unique transmission cluster of sexually transmitted HCV infections, providing insight into the distinct evolutionary pathways in each patient over time and identifying the transmission-associated genetic bottleneck as well as fluctuations in viral genetic diversity over time, accompanied by dynamic shifts in viral subpopulations.

A Mutation Identified in Neonatal Microcephaly Destabilizes Zika Virus NS1 Assembly in Vitro

An unprecedented epidemic of Zika virus (ZIKV) infection had spread to South and Central America. ZIKV infection was recently confirmed by CDC (the Centers for Disease Control and Prevention) to cause neonatal microcephaly, which posed a significant public health emergency of international concern. No specific vaccines or drugs are currently available to fight ZIKV infection. ZIKV nonstructural protein 1 (NS1) plays an essential role in viral replication and immune evasion. We determined the crystal structure of ZIKV NS1_172–352, which forms a head-to-head, symmetric dimer with a unique 14-stranded β-ladder conserved among flaviviruses. The assembly of the β-ladder dimer is concentration dependent. Strikingly, one pathogenic mutation T233A (NCBI accession no. KU527068), found in the brain tissue of infected fetus with neonatal microcephaly, is located at the dimer interface. Thr233, a unique residue found in ZIKV but not in other flaviviruses, organizes a central hydrogen bonding network at NS1 dimer interface. Mutation of Thr233 to Ala disrupts this elaborated interaction network, and destabilizes the NS1 dimeric assembly in vitro. In addition, our structural comparison of epitopes for protective antibody 22NS1, targeting West Nile Virus NS1, could potentially be valuable in understanding its anti-virus specificities and in the development of antibodies against ZIKV.

Exceptional Heterogeneity in Viral Evolutionary Dynamics Characterises Chronic Hepatitis C Virus Infection

The treatment of HCV infection has seen significant progress, particularly since the approval of new direct-acting antiviral drugs. However these clinical achievements have been made despite an incomplete understanding of HCV replication and within-host evolution, especially compared with HIV-1. Here, we undertake a comprehensive analysis of HCV within-host evolution during chronic infection by investigating over 4000 viral sequences sampled longitudinally from 15 HCV-infected patients. We compare our HCV results to those from a well-studied HIV-1 cohort, revealing key differences in the evolutionary behaviour of these two chronic-infecting pathogens. Notably, we find an exceptional level of heterogeneity in the molecular evolution of HCV, both within and among infected individuals. Furthermore, these patterns are associated with the long-term maintenance of viral lineages within patients, which fluctuate in relative frequency in peripheral blood. Together, our findings demonstrate that HCV replication behavior is complex and likely comprises multiple viral subpopulations with distinct evolutionary dynamics. The presence of a structured viral population can explain apparent paradoxes in chronic HCV infection, such as rapid fluctuations in viral diversity and the reappearance of viral strains years after their initial detection.

Our knowledge of HCV within-host evolution is substantially limited, which is surprising given that highly successful therapies against the virus have been developed. Key aspects of HCV infection, such as rapid fluctuations in viral diversity and the reappearance of viral strains years after their initial detection, remain unexplained. To better understand this problem, we analyse viral sequences from HCV-infected patients sampled over several years. Our findings suggest that the replication dynamics during chronic HCV infection are distinct from those of HIV-1, and dominated by the co-circulation of multiple viral strains. Although a major difference between the two chronic-infecting viruses is the level of recombination, our results indicate that HCV within-host evolution is most likely to be shaped by a structured viral population. Crucially, our study shows that HCV sampled from blood does not fully represent the within-host viral population at that time. This may have important implications for HCV treatment, especially in patients that have seemingly cleared the virus, as well as for molecular epidemiology studies investigating HCV transmission.

A next generation sequencing-based method to study the intra-host genetic diversity of norovirus in patients with acute and chronic infection

Background

Immunocompromised individuals with chronic norovirus (NoV) infection and elderly patients are hypothesized to be reservoirs where NoV might accumulate mutations and evolve into pandemic strains. Next generation sequencing (NGS) methods can monitor the intra-host diversity of NoV and its evolution but low abundance of viral RNA results in sub-optimal efficiency. In this study, we: 1) established a next generation sequencing-based method for NoV using bacterial rRNA depletion as a viral RNA enrichment strategy, and 2) measured the intra-host genetic diversity of NoV in specimens of patients with acute NoV infection (n = 4) and in longitudinal specimens of an immunocompromised patient with chronic NoV infection (n = 2).

Results

A single Illumina MiSeq dataset resulted in near full-length genome sequences for 5 out of 6 multiplexed samples. Experimental depletion of bacterial rRNA in stool RNA provided up to 1.9 % of NoV reads. The intra-host viral population in patients with acute NoV infection was homogenous and no single nucleotide variants (SNVs) were detected. In contrast, the NoV population from the immunocompromised patient was highly diverse and accumulated SNVs over time (51 SNVs in the first sample and 122 SNVs in the second sample collected 4 months later). The percentages of SNVs causing non-synonymous mutations were 27.5 % and 20.5 % for the first and second samples, respectively. The majority of non-synonymous mutations occurred, in increasing order of frequency, in p22, the major capsid (VP1) and minor capsid (VP2) genes.

Conclusions

The results provide data useful for the selection and improvement of NoV RNA enrichment strategies for NGS. Whole genome analysis using next generation sequencing confirmed that the within-host population of NoV in an immunocompromised individual with chronic NoV infection was more diverse compared to that in individuals with acute infection. We also observed an accumulation of non-synonymous mutations at the minor capsid gene that has not been reported in previous studies and might have a role in NoV adaptation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2831-y) contains supplementary material, which is available to authorized users.

Deep sequencing increases hepatitis C virus phylogenetic cluster detection compared to Sanger sequencing

Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters.

Increased Mitochondrial Genetic Diversity in Persons Infected With Hepatitis C Virus

BACKGROUND & AIMS

The host genetic environment contributes significantly to the outcomes of hepatitis C virus (HCV) infection and therapy response, but little is known about any effects of HCV infection on the host beyond any changes related to adaptive immune responses. HCV persistence is associated strongly with mitochondrial dysfunction, with liver mitochondrial DNA (mtDNA) genetic diversity linked to disease progression.

METHODS

We evaluated the genetic diversity of 2 mtDNA genomic regions (hypervariable segments 1 and 2) obtained from sera of 116 persons using next-generation sequencing.

RESULTS

Results were as follows: (1) the average diversity among cases with seronegative acute HCV infection was 4.2 times higher than among uninfected controls; (2) the diversity level among cases with chronic HCV infection was 96.1 times higher than among uninfected controls; and (3) the diversity was 23.1 times higher among chronic than acute cases. In 2 patients who were followed up during combined interferon and ribavirin therapy, mtDNA nucleotide diversity decreased dramatically after the completion of therapy in both patients: by 100% in patient A after 54 days and by 70.51% in patient B after 76 days.

CONCLUSIONS

HCV infection strongly affects mtDNA genetic diversity. A rapid decrease in mtDNA genetic diversity observed after therapy-induced HCV clearance suggests that the effect is reversible, emphasizing dynamic genetic relationships between HCV and mitochondria. The level of mtDNA nucleotide diversity can be used to discriminate recent from past infections, which should facilitate the detection of recent transmission events and thus help identify modes of transmission.

Evolution of hepatitis C virus in HIV coinfected patients under antiretroviral therapy

Five patients (P) were followed-up for an average of 7.73years after highly active antiretroviral therapy (HAART) initiation. Patients' immune and virological status were determined by periodical CD4+T-cell counts and HIV and HCV viral load. HCV populations were studied using longitudinal high throughput sequence data obtained in parallel by virological and immunological parameters. Two patients (P7, P28) with sub-optimal responses to HAART presented HCV viral loads significantly higher than those recorded for two patients (P1, P18) that achieved good responses to HAART. Interestingly, HCV populations from P7 and P28 displayed a stable phylogenetic structure, whereas HCV populations from P1 and P18showeda significant increase in their phylogenetic structure, followed by a decrease after achieving acceptable CD4+T-cell counts (>500 cell/μl). The fifth patient (P25) presented high HCV viral loads, preserved CD4+T-cell counts from baseline and all along the follow-up, and displayed a constant viral phylogenetic structure. These results strongly suggest that HAART-induced immune recovery induces a decrease in HCV viral load and an increase in the HCV population phylogenetic structure likely reflecting the virus diversification in response to the afresh immune response. The relatively low HCV viral load observed in the HAART responder patients suggests that once HCV is adapted it reaches a maximum number of haplotypes higher than that achieved during the initial stages of the immune response as inferred from the two recovering patients. Future studies using larger number of patients are needed to corroborate these hypotheses.

From Mosquitos to Humans: Genetic Evolution of Zika Virus

Initially isolated in 1947, Zika virus (ZIKV) has recently emerged as a significant public health concern. Sequence analysis of all 41 known ZIKV RNA open reading frames to date indicates that ZIKV has undergone significant changes in both protein and nucleotide sequences during the past half century.

Trends in Antiviral Strategies

Viral populations are true moving targets regarding the genomic sequences to be targeted in antiviral designs. Experts from different fields have expressed the need of new paradigms for antiviral interventions and viral disease control. This chapter reviews several strategies that aim at counteracting the adaptive capacity of viral quasispecies. The proposed designs are based on combinations of different antiviral drugs and immune modulators, or in the administration of virus-specific mutagenic agents, in an approach termed lethal mutagenesis of viruses. It consists of decreasing viral fitness by an excess of mutations that render viral proteins sub-optimal or non-functional. Viral extinction by lethal mutagenesis involves several sequential, overlapping steps that recapitulate the major concepts of intra-population interactions and genetic information stability discussed in preceding chapters. Despite the magnitude of the challenge, the chapter closes with some optimistic prospects for an effective control of viruses displaying error-prone replication, based on the combined targeting of replication fidelity and the induction of the innate immune response.

Network Analysis of the Chronic Hepatitis C Virome Defines Hypervariable Region 1 Evolutionary Phenotypes in the Context of Humoral Immune Responses

Hypervariable region 1 (HVR1) of hepatitis C virus (HCV) comprises the first 27 N-terminal amino acid residues of E2. It is classically seen as the most heterogeneous region of the HCV genome. In this study, we assessed HVR1 evolution by using ultradeep pyrosequencing for a cohort of treatment-naive, chronically infected patients over a short, 16-week period. Organization of the sequence set into connected components that represented single nucleotide substitution events revealed a network dominated by highly connected, centrally positioned master sequences. HVR1 phenotypes were observed to be under strong purifying (stationary) and strong positive (antigenic drift) selection pressures, which were coincident with advancing patient age and cirrhosis of the liver. It followed that stationary viromes were dominated by a single HVR1 variant surrounded by minor variants comprised from conservative single amino acid substitution events. We present evidence to suggest that neutralization antibody efficacy was diminished for stationary-virome HVR1 variants. Our results identify the HVR1 network structure during chronic infection as the preferential dominance of a single variant within a narrow sequence space.

IMPORTANCE

HCV infection is often asymptomatic, and chronic infection is generally well established in advance of initial diagnosis and subsequent treatment. HVR1 can undergo rapid sequence evolution during acute infection, and the variant pool is typically seen to diverge away from ancestral sequences as infection progresses from the acute to the chronic phase. In this report, we describe HVR1 viromes in chronically infected patients that are defined by a dominant epitope located centrally within a narrow variant pool. Our findings suggest that weakened humoral immune activity, as a consequence of persistent chronic infection, allows for the acquisition and maintenance of host-specific adaptive mutations at HVR1 that reflect virus fitness.

Multiregion deep sequencing of hepatitis C virus: An improved approach for genetic relatedness studies

Hepatitis C virus (HCV) is a major public health problem that affects more than 180 million people worldwide. Identification of HCV transmission networks is of critical importance for disease control. HCV related cases are often difficult to identify due to the characteristic long incubation period and lack of symptoms during the acute phase of the disease, making it challenging to link related cases to a common source of infection. Additionally, HCV transmission chains are difficult to trace back since viral variants from epidemiologically linked cases are genetically related but rarely identical. Genetic relatedness studies primarily rely on information obtained from the rapidly evolving HCV hypervariable region 1 (HVR1). However, in some instances, the rapid divergence of this region can lead to loss of genetic links between related isolates, which represents an important challenge for outbreak investigations and genetic relatedness studies. Sequencing of multiple and longer sub-genomic regions has been proposed as an alternative to overcome the limitations imposed by the rapid molecular evolution of the HCV HVR1. Additionally, conventional molecular approaches required to characterize the HCV intra-host genetic variation are laborious, time-consuming, and expensive while providing limited information about the composition of the viral population. Next generation sequencing (NGS) approaches enormously facilitate the characterization of the HCV intra-host population by detecting rare variants at much lower frequencies. Thus, NGS approaches using multiple sub-genomic regions should improve the characterization of the HCV intra-host population. Here, we explore the usefulness of multiregion sequencing using a NGS platform for genetic relatedness studies among HCV cases.

Next-Generation Sequencing Reveals Frequent Opportunities for Exposure to Hepatitis C Virus in Ghana

Globally, hepatitis C Virus (HCV) infection is responsible for a large proportion of persons with liver disease, including cancer. The infection is highly prevalent in sub-Saharan Africa. West Africa was identified as a geographic origin of two HCV genotypes. However, little is known about the genetic composition of HCV populations in many countries of the region. Using conventional and next-generation sequencing (NGS), we identified and genetically characterized 65 HCV strains circulating among HCV-positive blood donors in Kumasi, Ghana. Phylogenetic analysis using consensus sequences derived from 3 genomic regions of the HCV genome, 5'-untranslated region, hypervariable region 1 (HVR1) and NS5B gene, consistently classified the HCV variants (n = 65) into genotypes 1 (HCV-1, 15%) and genotype 2 (HCV-2, 85%). The Ghanaian and West African HCV-2 NS5B sequences were found completely intermixed in the phylogenetic tree, indicating a substantial genetic heterogeneity of HCV-2 in Ghana. Analysis of HVR1 sequences from intra-host HCV variants obtained by NGS showed that three donors were infected with >1 HCV strain, including infections with 2 genotypes. Two other donors share an HCV strain, indicating HCV transmission between them. The HCV-2 strain sampled from one donor was replaced with another HCV-2 strain after only 2 months of observation, indicating rapid strain switching. Bayesian analysis estimated that the HCV-2 strains in Ghana were expanding since the 16^th century. The blood donors in Kumasi, Ghana, are infected with a very heterogeneous HCV population of HCV-1 and HCV-2, with HCV-2 being prevalent. The detection of three cases of co- or super-infections and transmission linkage between 2 cases suggests frequent opportunities for HCV exposure among the blood donors and is consistent with the reported high HCV prevalence. The conditions for effective HCV-2 transmission existed for ~ 3–4 centuries, indicating a long epidemic history of HCV-2 in Ghana.

Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.

On the relative roles of background selection and genetic hitchhiking in shaping human cytomegalovirus genetic diversity

A central focus of population genetics has been examining the contribution of selective and neutral processes in shaping patterns of intraspecies diversity. In terms of selection specifically, surveys of higher organisms have shown considerable variation in the relative contributions of background selection and genetic hitchhiking in shaping the distribution of polymorphisms, although these analyses have rarely been extended to bacteria and viruses. Here, we study the evolution of a ubiquitous, viral pathogen, human cytomegalovirus (HCMV), by analysing the relationship among intraspecies diversity, interspecies divergence and rates of recombination. We show that there is a strong correlation between diversity and divergence, consistent with expectations of neutral evolution. However, after correcting for divergence, there remains a significant correlation between intraspecies diversity and recombination rates, with additional analyses suggesting that this correlation is largely due to the effects of background selection. In addition, a small number of loci, centred on long noncoding RNAs, also show evidence of selective sweeps. These data suggest that HCMV evolution is dominated by neutral mechanisms as well as background selection, expanding our understanding of linked selection to a novel class of organisms.

Genetic Diversity Underlying the Envelope Glycoproteins of Hepatitis C Virus: Structural and Functional Consequences and the Implications for Vaccine Design

In the 26 years since the discovery of Hepatitis C virus (HCV) a major global research effort has illuminated many aspects of the viral life cycle, facilitating the development of targeted antivirals. Recently, effective direct-acting antiviral (DAA) regimens with >90% cure rates have become available for treatment of chronic HCV infection in developed nations, representing a significant advance towards global eradication. However, the high cost of these treatments results in highly restricted access in developing nations, where the disease burden is greatest. Additionally, the largely asymptomatic nature of infection facilitates continued transmission in at risk groups and resource constrained settings due to limited surveillance. Consequently a prophylactic vaccine is much needed. The HCV envelope glycoproteins E1 and E2 are located on the surface of viral lipid envelope, facilitate viral entry and are the targets for host immunity, in addition to other functions. Unfortunately, the extreme global genetic and antigenic diversity exhibited by the HCV glycoproteins represents a significant obstacle to vaccine development. Here we review current knowledge of HCV envelope protein structure, integrating knowledge of genetic, antigenic and functional diversity to inform rational immunogen design.

Differentiation of acute from chronic hepatitis C virus infection by nonstructural 5B deep sequencing: a population-level tool for incidence estimation

The ability to classify acute versus chronic hepatitis C virus (HCV) infections at the time of diagnosis is desirable to improve the quality of surveillance information. The aim of this study was to differentiate acute from chronic HCV infections utilizing deep sequencing. HCV nonstructural 5B (NS5B) amplicons (n = 94) were generated from 77 individuals (13 acute and 64 chronic HCV infections) in British Columbia, Canada, with documented seroconversion time frames. Amplicons were deep sequenced and HCV genomic diversity was measured by Shannon entropy (SE) and a single nucleotide variant (SNV) analysis. The relationship between each diversity measure and the estimated days since infection was assessed using linear mixed models, and the ability of each diversity measure to differentiate acute from chronic infections was assessed using generalized estimating equations. Both SE and the SNV diversity measures were significantly different for acute versus chronic infections (P < 0.009). NS5B nucleotide diversity continued to increase for at least 3 years postinfection. Among individuals with the least uncertainty with regard to duration of infection (n = 39), the area under the receiver operating characteristic curve (AUROC) was high (0.96 for SE; 0.98 for SNV). Although the AUROCs were lower (0.86 for SE; 0.80 for SNV) when data for all individuals were included, they remain sufficiently high for epidemiological purposes. Synonymous mutations were the primary discriminatory variable accounting for over 78% of the measured genetic diversity.

CONCLUSIONS

NS5B sequence diversity assessed by deep sequencing can differentiate acute from chronic HCV infections and, with further validation, could become a powerful population-level surveillance tool for incidence estimation.

Antigenic cooperation among intrahost HCV variants organized into a complex network of cross-immunoreactivity

Hepatitis C virus (HCV) has the propensity to cause chronic infection. Continuous immune escape has been proposed as a mechanism of intrahost viral evolution contributing to HCV persistence. Although the pronounced genetic diversity of intrahost HCV populations supports this hypothesis, recent observations of long-term persistence of individual HCV variants, negative selection increase, and complex dynamics of viral subpopulations during infection as well as broad cross-immunoreactivity (CR) among variants are inconsistent with the immune-escape hypothesis. Here, we present a mathematical model of intrahost viral population dynamics under the condition of a complex CR network (CRN) of viral variants and examine the contribution of CR to establishing persistent HCV infection. The model suggests a mechanism of viral adaptation by antigenic cooperation (AC), with immune responses against one variant protecting other variants. AC reduces the capacity of the host's immune system to neutralize certain viral variants. CRN structure determines specific roles for each viral variant in host adaptation, with variants eliciting broad-CR antibodies facilitating persistence of other variants immunoreacting with these antibodies. The proposed mechanism is supported by empirical observations of intrahost HCV evolution. Interference with AC is a potential strategy for interruption and prevention of chronic HCV infection.

A molecular phylogenetics-based approach for identifying recent hepatitis C virus transmission events

Improved surveillance methods are needed to better understand the current hepatitis C virus (HCV) disease burden and to monitor the impact of prevention and treatment interventions on HCV transmission dynamics. Sanger sequencing (HCV NS5B, HVR1 and Core-E1-HVR1) and phylogenetics were applied to samples from individuals diagnosed with HCV in British Columbia, Canada in 2011. This included individuals with two or three sequential samples collected <1 year apart. Patristic distances between sequential samples were used to set cutoffs to identify recent transmission clusters. Factors associated with transmission clustering were analyzed using logistic regression. From 618 individuals, 646 sequences were obtained. Depending on the cutoff used, 63 (10%) to 92 (15%) unique individuals were identified within transmission clusters of predicted recent origin. Clustered individuals were more likely to be <40 years old (Adjusted Odds Ratio (AOR) 2.12, 95% CI 1.21-3.73), infected with genotype 1a (AOR 6.60, 95% CI 1.98-41.0), and to be seroconverters with estimated infection duration of <1 year (AOR 3.13, 95% CI 1.29-7.36) or >1 year (AOR 2.19, 95% CI 1.22-3.97).

CONCLUSION

Systematic application of molecular phylogenetics may be used to enhance traditional surveillance methods through identification of recent transmission clusters.

Intensive temporal mapping of hepatitis C hypervariable region 1 quasispecies provides novel insights into hepatitis C virus evolution in chronic infection

Hepatitis C virus (HCV) is an RNA virus which exists as swarms of closely related viruses known as quasispecies (QS). A number of studies have demonstrated associations between QS hypervariable region 1 (HVR1) characteristics (diversity and complexity) and treatment success. We investigated HCV QS change in chronic infection over intervals of 2-4 weeks in 23 chronically infected individuals to describe the natural history of virus evolution and establish whether HCV QS characteristics could be used to individualize treatment regimens at a molecular level. HVR1 QS diversity, complexity and divergence continue to change in an unpredictable fashion in chronic infection even where there is little phylogenetic change, which is likely to preclude the use of these features in treatment individualization. Our phylogenetic analysis identified no change in the HVR1 QS in 12 subjects, minor change in four subjects and we describe a time-ordered phylogeny for the first time over a period as short as 16 weeks in seven subjects. We identified the existence of multiple subpopulation infections using partitioned analysis of QS and illustrated how subpopulations were sequentially replaced in a number of subjects. We illustrated marked variation in the nucleotide substitution per codon position between patients with sequence change and those without change in the phylogenetic tree. Analysis of codon-specific selection pressures identified a number of codons under purifying selection, suggesting that these code for structurally conserved amino acids. We also identified sections of the HVR1 under positive selection with marked sequence heterogeneity, suggesting that these may be potential epitope-binding sites.

Advanced molecular surveillance of hepatitis C virus

Hepatitis C virus (HCV) infection is an important public health problem worldwide. HCV exploits complex molecular mechanisms, which result in a high degree of intrahost genetic heterogeneity. This high degree of variability represents a challenge for the accurate establishment of genetic relatedness between cases and complicates the identification of sources of infection. Tracking HCV infections is crucial for the elucidation of routes of transmission in a variety of settings. Therefore, implementation of HCV advanced molecular surveillance (AMS) is essential for disease control. Accounting for virulence is also important for HCV AMS and both viral and host factors contribute to the disease outcome. Therefore, HCV AMS requires the incorporation of host factors as an integral component of the algorithms used to monitor disease occurrence. Importantly, implementation of comprehensive global databases and data mining are also needed for the proper study of the mechanisms responsible for HCV transmission. Here, we review molecular aspects associated with HCV transmission, as well as the most recent technological advances used for virus and host characterization. Additionally, the cornerstone discoveries that have defined the pathway for viral characterization are presented and the importance of implementing advanced HCV molecular surveillance is highlighted.

Hepatitis C virus molecular evolution: Transmission, disease progression and antiviral therapy

Hepatitis C virus (HCV) infection represents an important public health problem worldwide. Reduction of HCV morbidity and mortality is a current challenge owned to several viral and host factors. Virus molecular evolution plays an important role in HCV transmission, disease progression and therapy outcome. The high degree of genetic heterogeneity characteristic of HCV is a key element for the rapid adaptation of the intrahost viral population to different selection pressures (e.g., host immune responses and antiviral therapy). HCV molecular evolution is shaped by different mechanisms including a high mutation rate, genetic bottlenecks, genetic drift, recombination, temporal variations and compartmentalization. These evolutionary processes constantly rearrange the composition of the HCV intrahost population in a staging manner. Remarkable advances in the understanding of the molecular mechanism controlling HCV replication have facilitated the development of a plethora of direct-acting antiviral agents against HCV. As a result, superior sustained viral responses have been attained. The rapidly evolving field of anti-HCV therapy is expected to broad its landscape even further with newer, more potent antivirals, bringing us one step closer to the interferon-free era.

Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling

MOTIVATION

Next-generation sequencing (NGS) allows for analyzing a large number of viral sequences from infected patients, providing an opportunity to implement large-scale molecular surveillance of viral diseases. However, despite improvements in technology, traditional protocols for NGS of large numbers of samples are still highly cost and labor intensive. One of the possible cost-effective alternatives is combinatorial pooling. Although a number of pooling strategies for consensus sequencing of DNA samples and detection of SNPs have been proposed, these strategies cannot be applied to sequencing of highly heterogeneous viral populations.

RESULTS

We developed a cost-effective and reliable protocol for sequencing of viral samples, that combines NGS using barcoding and combinatorial pooling and a computational framework including algorithms for optimal virus-specific pools design and deconvolution of individual samples from sequenced pools. Evaluation of the framework on experimental and simulated data for hepatitis C virus showed that it substantially reduces the sequencing costs and allows deconvolution of viral populations with a high accuracy.

AVAILABILITY AND IMPLEMENTATION

The source code and experimental data sets are available at http://alan.cs.gsu.edu/NGS/?q=content/pooling.

Inter and intra-host variability of hepatitis C virus genotype 1a hypervariable envelope coding domains followed for a 4-11 year of human immunodeficiency virus coinfection and highly active antiretroviral therapy

The evolution of hepatitis C virus (HCV) quasispecies in patients with HIV-1 coinfection is not fully understood. The HCV-1a quasispecies heterogeneity was analyzed at inter and intra-host levels along 7.6 years in 21 coinfected patients that showed different virological and immunological responses to highly active antiretroviral therapy (HAART). Two to nine serial samples were subjected to direct and clonal sequence analyses of the envelope glycoprotein 2 (E2) gene. E2-based phylogenies, intra-host HCV evolution and evolutionary rates, as well as dynamics of the quasispecies heterogeneity parameters were evaluated. Bayesian coalescent phylogenies indicated complex evolutionary histories, revealing some viral lineages that persisted along the follow up and others that were detectable at a single or some sampling times, suggesting the occurrence of emergence-extinction cycles. HCV quasispecies underwent very rapid evolution in HAART-treated patients (~3.1 × 10(-2) sub/site/year) following the recovery of the host immunocompetence irrespectively of the virological response to HAART.

Analysis of the evolution and structure of a complex intrahost viral population in chronic hepatitis C virus mapped by ultradeep pyrosequencing

Hepatitis C virus (HCV) causes chronic infection in up to 50% to 80% of infected individuals. Hypervariable region 1 (HVR1) variability is frequently studied to gain an insight into the mechanisms of HCV adaptation during chronic infection, but the changes to and persistence of HCV subpopulations during intrahost evolution are poorly understood. In this study, we used ultradeep pyrosequencing (UDPS) to map the viral heterogeneity of a single patient over 9.6 years of chronic HCV genotype 4a infection. Informed error correction of the raw UDPS data was performed using a temporally matched clonal data set. The resultant data set reported the detection of low-frequency recombinants throughout the study period, implying that recombination is an active mechanism through which HCV can explore novel sequence space. The data indicate that polyvirus infection of hepatocytes has occurred but that the fitness quotients of recombinant daughter virions are too low for the daughter virions to compete against the parental genomes. The subpopulations of parental genomes contributing to the recombination events highlighted a dynamic virome where subpopulations of variants are in competition. In addition, we provide direct evidence that demonstrates the growth of subdominant populations to dominance in the absence of a detectable humoral response.

IMPORTANCE

Analysis of ultradeep pyrosequencing data sets derived from virus amplicons frequently relies on software tools that are not optimized for amplicon analysis, assume random incorporation of sequencing errors, and are focused on achieving higher specificity at the expense of sensitivity. Such analysis is further complicated by the presence of hypervariable regions. In this study, we made use of a temporally matched reference sequence data set to inform error correction algorithms. Using this methodology, we were able to (i) detect multiple instances of hepatitis C virus intrasubtype recombination at the E1/E2 junction (a phenomenon rarely reported in the literature) and (ii) interrogate the longitudinal quasispecies complexity of the virome. Parallel to the UDPS, isolation of IgG-bound virions was found to coincide with the collapse of specific viral subpopulations.

Next-generation sequencing reveals large connected networks of intra-host HCV variants

Background

Next-generation sequencing (NGS) allows for sampling numerous viral variants from infected patients. This provides a novel opportunity to represent and study the mutational landscape of Hepatitis C Virus (HCV) within a single host.

Results

Intra-host variants of the HCV E1/E2 region were extensively sampled from 58 chronically infected patients. After NGS error correction, the average number of reads and variants obtained from each sample were 3202 and 464, respectively. The distance between each pair of variants was calculated and networks were created for each patient, where each node is a variant and two nodes are connected by a link if the nucleotide distance between them is 1. The work focused on large components having > 5% of all reads, which in average account for 93.7% of all reads found in a patient.

The distance between any two variants calculated over the component correlated strongly with nucleotide distances (r = 0.9499; p = 0.0001), a better correlation than the one obtained with Neighbour-Joining trees (r = 0.7624; p = 0.0001). In each patient, components were well separated, with the average distance between (6.53%) being 10 times greater than within each component (0.68%). The ratio of nonsynonymous to synonymous changes was calculated and some patients (6.9%) showed a mixture of networks under strong negative and positive selection. All components were robust to in silico stochastic sampling; even after randomly removing 85% of all reads, the largest connected component in the new subsample still involved 82.4% of remaining nodes. In vitro sampling showed that 93.02% of components present in the original sample were also found in experimental replicas, with 81.6% of reads found in both. When syringe-sharing transmission events were simulated, 91.2% of all simulated transmission events seeded all components present in the source.

Conclusions

Most intra-host variants are organized into distinct single-mutation components that are: well separated from each other, represent genetic distances between viral variants, robust to sampling, reproducible and likely seeded during transmission events. Facilitated by NGS, large components offer a novel evolutionary framework for genetic analysis of intra-host viral populations and understanding transmission, immune escape and drug resistance.

Intra-host diversity and evolution of hepatitis C virus endemic to Côte d'Ivoire

Hepatitis C virus (HCV) infection presents an important, but underappreciated public health problem in Africa. In Côte d'Ivoire, very little is known about the molecular dynamics of HCV infection. Plasma samples (n = 608) from pregnant women collected in 1995 from Côte d'Ivoire were analyzed in this study. Only 18 specimens (∼3%) were found to be HCV PCR-positive. Phylogenetic analysis of the HCV NS5b sequences showed that the HCV variants belong to genotype 1 (HCV1) (n = 12, 67%) and genotype 2 (HCV2) (n = 6, 33%), with a maximum genetic diversity among HCV variants in each genotype being 20.7% and 24.0%, respectively. Although all HCV2 variants were genetically distant from each other, six HCV1 variants formed two tight sub-clusters belonging to HCV1a and HCV1b. Analysis of molecular variance (AMOVA) showed that the genetic structure of HCV isolates from West Africa with Côte d'Ivoire included were significantly different from Central African strains (P = 0.0001). Examination of intra-host viral populations using next-generation sequencing of the HCV HVR1 showed a significant variation in intra-host genetic diversity among infected individuals, with some strains composed of sub-populations as distant from each other as viral populations from different hosts. Collectively, the results indicate a complex HCV evolution in Côte d'Ivoire, similar to the rest of West Africa, and suggest a unique HCV epidemic history in the country.

Intra-host evolution of multiple genotypes of hepatitis C virus in a chronically infected patient with HIV along a 13-year follow-up period

The intra-host evolutionary process of hepatitis C virus (HCV) was analyzed by phylogenetic and coalescent methodologies in a patient co-infected with HCV-1a, HCV-2a, HCV-3a and human immunodeficiency virus (HIV) along a 13-year period. Direct sequence analysis of the E2 and NS5A regions showed diverse evolutionary dynamics, in agreement with different relationships between these regions and the host factors. The Bayesian Skyline Plot analyses of the E2 sequences (cloned) yielded different intra-host evolutionary patterns for each genotype: a steady state of a "consensus" sequence for HCV-1a; a pattern of lineage splitting and extinction for HCV-2a; and a two-phase (drift/diversification) process for HCV-3a. Each genotype evolving in the same patient and at the same time presents a different pattern apparently modulated by the immune pressure of the host. This study provides useful information for the management of co-infected patients and provides insights into the mechanisms behind the intra-host evolution of HCV.