Coordinated evolution of the hepatitis C virus

Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks

The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.

Polyvalent immunization elicits a synergistic broadly neutralizing immune response to hypervariable region 1 variants of hepatitis C virus

A hepatitis C virus (HCV) vaccine is urgently needed. Vaccine development has been hindered by HCV's genetic diversity, particularly within the immunodominant hypervariable region 1 (HVR1). Here, we developed a strategy to elicit broadly neutralizing antibodies to HVR1, which had previously been considered infeasible. We first applied a unique information theory-based measure of genetic distance to evaluate phenotypic relatedness between HVR1 variants. These distances were used to model the structure of HVR1's sequence space, which was found to have five major clusters. Variants from each cluster were used to immunize mice individually, and as a pentavalent mixture. Sera obtained following immunization neutralized every variant in a diverse HCVpp panel (n = 10), including those resistant to monovalent immunization, and at higher mean titers (1/ID50 = 435) than a glycoprotein E2 (1/ID50 = 205) vaccine. This synergistic immune response offers a unique approach to overcoming antigenic variability and may be applicable to other highly mutable viruses.

Synthesis and Analysis of Properties of an Immunogenic Fragment from NS4A Polypeptide of Hepatitis C Virus

Abstract—

The work is aimed at the synthesis and analysis from NS4A of hepatitis C virus (HCV) antigen peptide fragment that contains a conserved B-cell and T-helper epitopes. The 24-mer peptide VIVGRIILSGRPAVIPDREVLYRK-NH2, which contains the main immunogenic site 24–46 of HCV NS4A antigen (corresponding to the 1681–1703 amino acid residues of the HCV polypeptide), subtype 1b, has been prepared via solid-phase synthesis according to the Fmoc-protocol. Particles with diameters of 73 ± 10 nm (30%) and 236 ± 5 nm (70%) have been detected in the water solution of the highly purified peptide (0.5 mg/mL) by dynamic light scattering. The polydispersity index of 0.377 ± 0.012 implies the existence of heterogeneity because of the aggregation of the peptide molecules. The ζ-potential of the peptide aggregates has been determined as 7.0 ± 0.5 mV by means of electrophoretic light scattering. These data confirm the possibility for the development of a nanoscale liposome form of the peptide preparation. Immunoreactivity of the synthesized highly purified peptide has been studied with the use of blood sera of patients with chronic hepatitis C. Antipeptide immunoglobulins G have been detected in 41.7% of serum samples. Thus, this peptide has been shown to reproduce at least one B-epitope, to which antibodies are raised during natural HCV infection. The synthesized 24-mer peptide is a promising candidate for further research and for use as a potential immunogen for the design of a nanoscale therapeutic immunogenic liposomal peptide composition with synthetic lipids as an adjuvant.

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.

Antigenic Variability

Protective vaccines for hypervariable pathogens are urgently needed. It has been proposed that amputating highly variable epitopes from vaccine antigens would induce the production of broadly protective antibodies targeting conserved epitopes. However, so far, these approaches have failed, partially because conserved epitopes are occluded in vivo and partially because co-localizing patterns of immunodominance and antigenic variability render variable epitopes the primary target for antibodies in natural infection. In this Perspective, to recast the challenge of vaccine development for hypervariable pathogens, I evaluate convergent mechanisms of adaptive variation, such as intrahost immune-mediated diversification, spatiotemporally defined antigenic space, and infection-enhancing cross-immunoreactivity. The requirements of broadly protective immune responses targeting variable pathogens are formulated in terms of cross-immunoreactivity, stoichiometric thresholds for neutralization, and the elicitation of antibodies targeting physicochemically conserved signatures within sequence variable domains.

Positional Correlation Natural Vector: A Novel Method for Genome Comparison

Advances in sequencing technology have made large amounts of biological data available. Evolutionary analysis of data such as DNA sequences is highly important in biological studies. As alignment methods are ineffective for analyzing large-scale data due to their inherently high costs, alignment-free methods have recently attracted attention in the field of bioinformatics. In this paper, we introduce a new positional correlation natural vector (PCNV) method that involves converting a DNA sequence into an 18-dimensional numerical feature vector. Using frequency and position correlation to represent the nucleotide distribution, it is possible to obtain a PCNV for a DNA sequence. This new numerical vector design uses six suitable features to characterize the correlation among nucleotide positions in sequences. PCNV is also very easy to compute and can be used for rapid genome comparison. To test our novel method, we performed phylogenetic analysis with several viral and bacterial genome datasets with PCNV. For comparison, an alignment-based method, Bayesian inference, and two alignment-free methods, feature frequency profile and natural vector, were performed using the same datasets. We found that the PCNV technique is fast and accurate when used for phylogenetic analysis and classification of viruses and bacteria.

Identifying immunologically-vulnerable regions of the HCV E2 glycoprotein and broadly neutralizing antibodies that target them

Isolation of broadly neutralizing human monoclonal antibodies (HmAbs) targeting the E2 glycoprotein of Hepatitis C virus (HCV) has sparked hope for effective vaccine development. Nonetheless, escape mutations have been reported. Ideally, a potent vaccine should elicit HmAbs that target regions of E2 that are most difficult to escape. Here, aimed at addressing this challenge, we develop a predictive in-silico evolutionary model for E2 that identifies one such region, a specific antigenic domain, making it an attractive target for a robust antibody response. Specific broadly neutralizing HmAbs that appear difficult to escape from are also identified. By providing a framework for identifying vulnerable regions of E2 and for assessing the potency of specific antibodies, our results can aid the rational design of an effective prophylactic HCV vaccine.

A good vaccine should direct the immune response to virus regions that are most difficult to escape. Here, Quadeer et al. develop a predictive in-silico evolutionary model for HCV E2 which identifies one such antigenic region and identifies multiple broadly neutralizing human antibodies that appear difficult to escape from.

Detecting Amino Acid Coevolution with Bayesian Graphical Models

The comparative study of homologous proteins can provide abundant information about the functional and structural constraints on protein evolution. For example, an amino acid substitution that is deleterious may become permissive in the presence of another substitution at a second site of the protein. A popular approach for detecting coevolving residues is by looking for correlated substitution events on branches of the molecular phylogeny relating the protein-coding sequences. Here we describe a machine learning method (Bayesian graphical models) implemented in the open-source phylogenetic software package HyPhy, http://hyphy.org , for extracting a network of coevolving residues from a sequence alignment.

HCV adaptation to HIV coinfection

Human immunodeficiency virus (HIV) infection is rising as a leading cause of morbidity and mortality among hepatitis C virus (HCV)-infected patients. Both viruses interact in co-infected hosts, which may affect their intra-host evolution, potentially leading to differing genetic composition of viral populations in co-infected (CIP) and mono-infected (MIP) patients. Here, we investigate genetic differences between intra-host variants of the HCV hypervariable region 1 (HVR1) sampled from CIP and MIP. Nucleotide (nt) sequences of intra-host HCV HVR1 variants (N = 28,622) obtained from CIP (N = 112) and MIP (n = 176) were represented using 148 physical-chemical (PhyChem) indexes of DNA nt dimers. Significant (p < .0001) differences in the means and frequency distributions of 7 PhyChem properties were found between HVR1 variants from both groups. Linear projection analysis of 29 PhyChem features extracted from such PhyChem properties showed that the CIP and MIP HVR1 variants have a distinct distribution in the modeled 2D-space, with only ~1.3% of PhyChem profiles (N = 6782), shared by all HVR1 variants, being found in both groups. Probabilistic neural network (PNN) and naïve Bayesian (NB) classifiers trained on the PhyChem features accurately classified HVR1 variants by the group in cross-validation experiments (AUROC ≥ 0.96). Similarly, both models showed a high accuracy (AUROC ≥ 0.95) when evaluated on a test dataset of HVR1 sequences obtained from 10 patients, data from whom were not used for model building. Both models performed at the expected lower accuracy on randomly labeled datasets in cross-validation experiments (AUROC = 0.50). The random-label trained PNN showed a similar drop in accuracy on the test dataset (AUROC = 0.48), indicating that the detected associations were unlikely due to random correlations. Marked differences in genetic composition of HCV HVR1 variants sampled from CIP and MIP suggest differing intra-host HCV evolution in the presence of HIV infection. PhyChem features identified here may be used for detection of HIV infection from intra-host HCV variants alone in co-infected patients, thus facilitating monitoring for HIV introduction to high-risk populations with high HCV prevalence.

Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein-protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.

Epistatic interactions between polymorphisms in DNA are recognized as important drivers of evolution in numerous organisms. Study of epistasis in bacteria has been hampered by the lack of densely sampled population genomic data, suitable statistical models and inference algorithms sufficiently powered for extremely high-dimensional parameter spaces. We introduce the first model-based method for genome-wide epistasis analysis and use two of the largest available bacterial population genome data sets on Streptococcus pneumoniae (the pneumococcus) and Streptococcus pyogenes (group A Streptococcus) to demonstrate its potential for biological discovery. Our approach reveals interacting networks of resistance, virulence and core machinery genes in the pneumococcus, which highlights putative candidates for novel drug targets. We also discover a number of plausible targets of co-selection in S. pyogenes linked to RNA pseudouridine synthases. Our method significantly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.

Comparative analysis of variation and selection in the HCV genome

Genotype 1 of the hepatitis C virus (HCV) is the most prevalent of the variants of this virus. Its two main subtypes, HCV-1a and HCV-1b, are associated to differences in epidemic features and risk groups, despite sharing similar features in most biological properties. We have analyzed the impact of positive selection on the evolution of these variants using complete genome coding regions, and compared the levels of genetic variability and the distribution of positively selected sites. We have also compared the distributions of positively selected and conserved sites considering different factors such as RNA secondary structure, the presence of different epitopes (antibody, CD4 and CD8), and secondary protein structure. <10% of the genome was found to be under positive selection, and purifying selection was the main evolutionary process acting in both subtypes. We found differences in the number of positively selected sites between subtypes in several genes (Core, HVR2 in E2, P7, helicase in NS3 and NS4a). Heterozygosity values in positively selected sites and the rate of non-synonymous substitutions were significantly higher in subtype HCV-1b. Logistic regression analyses revealed that similar selective forces act at the genome level in both subtypes: RNA secondary structure and CD4 T-cell epitopes are associated with conserved sites, while CD8 T-cell epitopes are associated with positive selection in both subtypes. These results indicate that similar selective constraints are acting along HCV-1a and HCV-1 b genomes, despite some differences in the distribution of positively selected sites at independent genes.

Polyprotein-Driven Formation of Two Interdependent Sets of Complexes Supporting Hepatitis C Virus Genome Replication

Hepatitis C virus (HCV) requires proteins from the NS3-NS5B polyprotein to create a replicase unit for replication of its genome. The replicase proteins form membranous compartments in cells to facilitate replication, but little is known about their functional organization within these structures. We recently reported on intragenomic replicons, bicistronic viral transcripts expressing an authentic replicase from open reading frame 2 (ORF2) and a second duplicate nonstructural (NS) polyprotein from ORF1. Using these constructs and other methods, we have assessed the polyprotein requirements for rescue of different lethal point mutations across NS3-5B. Mutations readily tractable to rescue broadly fell into two groupings: those requiring expression of a minimum NS3-5A and those requiring expression of a minimum NS3-5B polyprotein. A cis-acting mutation that blocked NS3 helicase activity, T1299A, was tolerated when introduced into either ORF within the intragenomic replicon, but unlike many other mutations required the other ORF to express a functional NS3-5B. Three mutations were identified as more refractile to rescue: one that blocked cleavage of the NS4B5A boundary (S1977P), another in the NS3 helicase (K1240N), and a third in NS4A (V1665G). Introduced into ORF1, these exhibited a dominant negative phenotype, but with K1240N inhibiting replication as a minimum NS3-5A polyprotein whereas V1665G and S1977P only impaired replication as a NS3-5B polyprotein. Furthermore, an S1977P-mutated NS3-5A polyprotein complemented other defects shown to be dependent on NS3-5A for rescue. Overall, our findings suggest the existence of two interdependent sets of protein complexes supporting RNA replication, distinguishable by the minimum polyprotein requirement needed for their formation.

IMPORTANCE Positive-strand RNA viruses reshape the intracellular membranes of cells to form a compartment within which to replicate their genome, but little is known about the functional organization of viral proteins within this structure. We have complemented protein-encoded defects in HCV by constructing subgenomic HCV transcripts capable of simultaneously expressing both a mutated and functional polyprotein precursor needed for RNA genome replication (intragenomic replicons). Our results reveal that HCV relies on two interdependent sets of protein complexes to support viral replication. They also show that the intragenomic replicon offers a unique way to study replication complex assembly, as it enables improved composite polyprotein complex formation compared to traditional trans-complementation systems. Finally, the differential behavior of distinct NS3 helicase knockout mutations hints that certain conformations of this enzyme might be particularly deleterious for replication.

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.

A Functional Interplay between Human Immunodeficiency Virus Type 1 Protease Residues 77 and 93 Involved in Differential Regulation of Precursor Autoprocessing and Mature Protease Activity

HIV-1 protease (PR) is a viral enzyme vital to the production of infectious virions. It is initially synthesized as part of the Gag-Pol polyprotein precursor in the infected cell. The free mature PR is liberated as a result of precursor autoprocessing upon virion release. We previously described a model system to examine autoprocessing in transfected mammalian cells. Here, we report that a covariance analysis of miniprecursor (p6*-PR) sequences derived from drug naïve patients identified a series of amino acid pairs that vary together across independent viral isolates. These covariance pairs were used to build the first topology map of the miniprecursor that suggests high levels of interaction between the p6* peptide and the mature PR. Additionally, several PR-PR covariance pairs are located far from each other (>12 Å Cα to Cα) relative to their positions in the mature PR structure. Biochemical characterization of one such covariance pair (77-93) revealed that each residue shows distinct preference for one of three alkyl amino acids (V, I, and L) and that a polar or charged amino acid at either of these two positions abolishes precursor autoprocessing. The most commonly observed 77V is preferred by the most commonly observed 93I, but the 77I variant is preferred by other 93 variances (L, V, or M) in supporting precursor autoprocessing. Furthermore, the 77I93V covariant enhanced precursor autoprocessing and Gag polyprotein processing but decreased the mature PR activity. Therefore, both covariance and biochemical analyses support a functional association between residues 77 and 93, which are spatially distant from each other in the mature PR structure. Our data also suggests that these covariance pairs differentially regulate precursor autoprocessing and the mature protease activity.

Coordinated rates of evolution between interacting plastid and nuclear genes in Geraniaceae

Although gene coevolution has been widely observed within individuals and between different organisms, rarely has this phenomenon been investigated within a phylogenetic framework. The Geraniaceae is an attractive system in which to study plastid-nuclear genome coevolution due to the highly elevated evolutionary rates in plastid genomes. In plants, the plastid-encoded RNA polymerase (PEP) is a protein complex composed of subunits encoded by both plastid (rpoA, rpoB, rpoC1, and rpoC2) and nuclear genes (sig1-6). We used transcriptome and genomic data for 27 species of Geraniales in a systematic evaluation of coevolution between genes encoding subunits of the PEP holoenzyme. We detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) within rpoB/sig1 and rpoC2/sig2, but not for other plastid/nuclear gene pairs, and identified the correlation of dN/dS ratio between rpoB/C1/C2 and sig1/5/6, rpoC1/C2 and sig2, and rpoB/C2 and sig3 genes. Correlated rates between interacting plastid and nuclear sequences across the Geraniales could result from plastid-nuclear genome coevolution. Analyses of coevolved amino acid positions suggest that structurally mediated coevolution is not the major driver of plastid-nuclear coevolution. The detection of strong correlation of evolutionary rates between SIG and RNAP genes suggests a plausible explanation for plastome-genome incompatibility in Geraniaceae.

Effective epitope identification employing phylogenetic, mutational variability, sequence entropy, and correlated mutation analysis targeting NS5B protein of hepatitis C virus: from bioinformatics to therapeutics

Hepatitis C virus (HCV) is considered as a foremost cause affecting numerous human liver-related disorders. An effective immuno-prophylactic measure (like stable vaccine) is still unavailable for HCV. We perform an in silico analysis of nonstructural protein 5B (NS5B) based CD4 and CD8 epitopes that might be implicated in improvement of treatment strategies for efficient vaccine development programs against HCV. Here, we report on effective utilization of knowledge obtained from multiple sequence alignment and phylogenetic analysis for investigation and evaluation of candidate epitopes that have enormous potential to be used in formulating proficient vaccine, embracing multiple strains prevalent among major geographical locations. Mutational variability data discussed herein focus on discriminating the region under active evolutionary pressure from those having lower mutational potential in existing experimentally verified epitopes, thus, providing a concrete framework for designing an effective peptide-based vaccine against HCV. Additionally, we measured entropy distribution in NS5B residues and pinpoint the positions in epitopes that are more susceptible to mutations and, thus, account for virus strategy to evade the host immune system. Findings from this study are expected to add more details on the sequence and structural aspects of NS5B protein, ultimately facilitating our understanding about the pathophysiology of HCV and assisting advance studies on the function of NS5B antigen on the epitope level. We also report on the mutational crosstalk between functionally important coevolving residues, using correlated mutation analysis, and identify networks of coupled mutations that represent pathways of allosteric communication inside and among NS5B thumb, finger, and palm domains.

Host proteins associated with Hepatitis C virus encoded NS4A

Virus-associated cancers account for more than 12 % of all the cancers. Hepatitis C virus (HCV) infects nearly 3 % of the population worldwide and has emerged as a major causative agent of liver disease with a big impact on public health. The HCV non-structural protein NS4A is a 54-amino-acid polypeptide that serves as an essential co-factor for the NS3 serine protease. We report here on a proteomic study to identify cellular proteins associated with NS4A. The results of this study show an association of three host cellular proteins with NS4A including two novel NS4A interacting partners. Our data provide evidence for complex involving NS4A with previously unreported cellular proteins including housekeeping protein GAPDH, and PI3P-5 K which is involved in cellular protein trafficking to nucleus. These novel associations add to the diversity of NS4A functions in relation to the virus infection and subsequent pathogenesis.

HCV genome-wide genetic analyses in context of disease progression and hepatocellular carcinoma

Hepatitis C virus (HCV) is a major cause of hepatitis and hepatocellular carcinoma (HCC) world-wide. Most HCV patients have relatively stable disease, but approximately 25% have progressive disease that often terminates in liver failure or HCC. HCV is highly variable genetically, with seven genotypes and multiple subtypes per genotype. This variation affects HCV's sensitivity to antiviral therapy and has been implicated to contribute to differences in disease. We sequenced the complete viral coding capacity for 107 HCV genotype 1 isolates to determine whether genetic variation between independent HCV isolates is associated with the rate of disease progression or development of HCC. Consensus sequences were determined by sequencing RT-PCR products from serum or plasma. Positions of amino acid conservation, amino acid diversity patterns, selection pressures, and genome-wide patterns of amino acid covariance were assessed in context of the clinical phenotypes. A few positions were found where the amino acid distributions or degree of positive selection differed between in the HCC and cirrhotic sequences. All other assessments of viral genetic variation and HCC failed to yield significant associations. Sequences from patients with slow disease progression were under a greater degree of positive selection than sequences from rapid progressors, but all other analyses comparing HCV from rapid and slow disease progressors were statistically insignificant. The failure to observe distinct sequence differences associated with disease progression or HCC employing methods that previously revealed strong associations with the outcome of interferon α-based therapy implies that variable ability of HCV to modulate interferon responses is not a dominant cause for differential pathology among HCV patients. This lack of significant associations also implies that host and/or environmental factors are the major causes of differential disease presentation in HCV patients.

Genetic host specificity of hepatitis E virus

Hepatitis E virus (HEV) causes epidemic and sporadic cases of hepatitis worldwide. HEV genotypes 3 (HEV3) and 4 (HEV4) infect humans and animals, with swine being the primary reservoir. The relevance of HEV genetic diversity to host adaptation is poorly understood. We employed a Bayesian network (BN) analysis of HEV3 and HEV4 to detect epistatic connectivity among protein sites and its association with the host specificity in each genotype. The data imply coevolution among ∼70% of polymorphic sites from all HEV proteins and association of numerous coevolving sites with adaptation to swine or humans. BN models for individual proteins and domains of the nonstructural polyprotein detected the host origin of HEV strains with accuracy of 74-93% and 63-87%, respectively. These findings, taken together with lack of phylogenetic association to host, suggest that the HEV host specificity is a heritable and convergent phenotypic trait achievable through variety of genetic pathways (abundance), and explain a broad host range for HEV3 and HEV4.

Statistical linkage analysis of substitutions in patient-derived sequences of genotype 1a hepatitis C virus nonstructural protein 3 exposes targets for immunogen design

Chronic hepatitis C virus (HCV) infection is one of the leading causes of liver failure and liver cancer, affecting around 3% of the world's population. The extreme sequence variability of the virus resulting from error-prone replication has thwarted the discovery of a universal prophylactic vaccine. It is known that vigorous and multispecific cellular immune responses, involving both helper CD4(+) and cytotoxic CD8(+) T cells, are associated with the spontaneous clearance of acute HCV infection. Escape mutations in viral epitopes can, however, abrogate protective T-cell responses, leading to viral persistence and associated pathologies. Despite the propensity of the virus to mutate, there might still exist substitutions that incur a fitness cost. In this paper, we identify groups of coevolving residues within HCV nonstructural protein 3 (NS3) by analyzing diverse sequences of this protein using ideas from random matrix theory and associated methods. Our analyses indicate that one of these groups comprises a large percentage of residues for which HCV appears to resist multiple simultaneous substitutions. Targeting multiple residues in this group through vaccine-induced immune responses should either lead to viral recognition or elicit escape substitutions that compromise viral fitness. Our predictions are supported by published clinical data, which suggested that immune genotypes associated with spontaneous clearance of HCV preferentially recognized and targeted this vulnerable group of residues. Moreover, mapping the sites of this group onto the available protein structure provided insight into its functional significance. An epitope-based immunogen is proposed as an alternative to the NS3 epitopes in the peptide-based vaccine IC41.

IMPORTANCE

Despite much experimental work on HCV, a thorough statistical study of the HCV sequences for the purpose of immunogen design was missing in the literature. Such a study is vital to identify epistatic couplings among residues that can provide useful insights for designing a potent vaccine. In this work, ideas from random matrix theory were applied to characterize the statistics of substitutions within the diverse publicly available sequences of the genotype 1a HCV NS3 protein, leading to a group of sites for which HCV appears to resist simultaneous substitutions possibly due to deleterious effect on viral fitness. Our analysis leads to completely novel immunogen designs for HCV. In addition, the NS3 epitopes used in the recently proposed peptide-based vaccine IC41 were analyzed in the context of our framework. Our analysis predicts that alternative NS3 epitopes may be worth exploring as they might be more efficacious.

Drug resistance of a viral population and its individual intrahost variants during the first 48 hours of therapy

Using HCV and IFN-resistance as a proof of concept, we have devised a new methodology for calculating the effect of a drug over a viral population and the resistance of its individual intra-host variants.

By means of next-generation sequencing, HCV variants were obtained from sera collected at 9 time-points from 16 patients during the first 48 hours after injection of IFN-α. IFN-resistance coefficients were calculated for individual variants using changes in their relative frequencies, and for the entire intra-host viral population using changes in viral titer during the initial 48 hours.

Population-wide resistance and presence of IFN-resistant variants were highly associated with pegIFN-α2a/RBV treatment outcome at week 12 (p = 3.78×10^-5 and 0.0114, respectively). This new method allows an accurate measurement of resistance based solely on changes in viral titer or the relative frequency of intra-host viral variants during a short observation time.

Phylogeny and molecular evolution of the hepatitis C virus

The hepatitis C virus (HCV) is a globally prevalent human pathogen that causes persistent liver infections in most infected individuals. HCV is classified into seven phylogenetically distinct genotypes, which have different geographical distributions and levels of genetic diversity. Some of these genotypes are endemic and highly divergent, whereas others disseminate rapidly on an epidemic scale but display lower variability. HCV phylogeny has an important impact on disease epidemiology and clinical practice because the viral genotype may determine the pathogenesis and severity of the resultant chronic liver disease. In addition, there is a clear association between the HCV genotype and its susceptibility to antiviral treatment. Similarly to other RNA viruses, in a single host, HCV exists as a combination of related but genetically different variants. The whole formation is the actual target of selection exerted by a host organism and antiviral therapeutics. The genetic structure of the viral population is largely shaped by mutations that are constantly introduced during an error-prone replication. However, it appears that genetic recombination may also contribute to this process. This heterogeneous collection of variants has a significant ability to evolve towards the fitness optimum. Interestingly, negative selection, which restricts diversity, emerges as an essential force that drives HCV evolution. It is becoming clear that HCV evolves to become stably adapted to the host environment. In this article we review the HCV phylogeny and molecular evolution in the context of host-virus interactions.

Evolutionary characterization of the pandemic H1N1/2009 influenza virus in humans based on non-structural genes

The 2009 influenza pandemic had a tremendous social and economic impact. To study the genetic diversity and evolution of the 2009 H1N1 virus, a mutation network for the non-structural (NS) gene of the virus was constructed. Strains of the 2009 H1N1 pandemic influenza A virus could be divided into two categories based on the V123I mutation in the NS1 gene: G1 (characterized as 123 Val) and G2 (characterized as 123 Ile). Sequence homology analysis indicated that one type of NS sequence, primarily isolated from Mexico, was likely the original type in this pandemic. The two genotypes of the virus presented distinctive clustering features in their geographic distributions. These results provide additional insight into the genetics and evolution of human pandemic influenza H1N1.

Epistatic connectivity among HCV genomic sites as a genetic marker of interferon resistance

Until recently, the standard-of-care therapy of patients with HCV infection involves treatment with interferon (IFN) and ribavirin (RBV). Host demographic and genetic factors as well as HCV genetic heterogeneity have been shown to be associated with outcomes of therapy. Although resistance to IFN/RBV remains an important clinical and public health problem, there are no reliable genetic markers for the prediction of the therapy outcomes. Recently, it was shown that adaptation to IFN, a major constituent of the host innate immunity, is reflected in the HCV genetic composition and epistatic connectivity among polymorphic genomic sites, thus providing novel genetic markers of IFN resistance. Consideration of coordinated evolution among HCV genomic sites allows for identification of these genetic markers from short regions of the HCV genome and for accurate prediction of therapeutic outcomes. HCV genomic co-evolution offers a general framework for the detection of predisposition to IFN resistance, and possibly to resistance to direct-acting antivirals.

Level of gene expression is a major determinant of protein evolution in the viral order Mononegavirales

Although the rate at which proteins change is a key parameter in molecular evolution, its determinants are poorly understood in viruses. A variety of factors, including gene length, codon usage bias, protein abundance, protein function, and gene expression level, have been shown to affect the rate of protein evolution in a diverse array of organisms. However, the role of these factors in viral evolution has yet to be addressed. The polar 3'-5' stepwise attenuation of transcription in the Mononegavirales, a group of single-strand negative-sense RNA viruses, provides a unique system to explore the determinants of protein evolution in viruses. We analyzed the relative importance of a variety of factors in shaping patterns of sequence variation in full-length genomes from 13 Mononegavirales species. Our analysis suggests that the level of gene expression, and by extension the relative genomic position of each gene, is a key determinant of the protein evolution in these viruses. This appears to be the consequence of selection for translational robustness, but not for translational accuracy, in highly expressed genes. The small genome size and number of proteins encoded by these viruses allowed us to identify other protein-specific factors that may also play a role in virus evolution, such as host-virus interactions and functional constraints. Finally, we explored the evolutionary pressures acting on noncoding regions in Mononegavirales genomes and observed that, despite being less constrained than coding regions, their evolutionary rates are also associated with genomic position.

Genome-wide networks of amino acid covariances are common among viruses

Coordinated variation among positions in amino acid sequence alignments can reveal genetic dependencies at noncontiguous positions, but methods to assess these interactions are incompletely developed. Previously, we found genome-wide networks of covarying residue positions in the hepatitis C virus genome (R. Aurora, M. J. Donlin, N. A. Cannon, and J. E. Tavis, J. Clin. Invest. 119:225-236, 2009). Here, we asked whether such networks are present in a diverse set of viruses and, if so, what they may imply about viral biology. Viral sequences were obtained for 16 viruses in 13 species from 9 families. The entire viral coding potential for each virus was aligned, all possible amino acid covariances were identified using the observed-minus-expected-squared algorithm at a false-discovery rate of ≤1%, and networks of covariances were assessed using standard methods. Covariances that spanned the viral coding potential were common in all viruses. In all cases, the covariances formed a single network that contained essentially all of the covariances. The hepatitis C virus networks had hub-and-spoke topologies, but all other networks had random topologies with an unusually large number of highly connected nodes. These results indicate that genome-wide networks of genetic associations and the coordinated evolution they imply are very common in viral genomes, that the networks rarely have the hub-and-spoke topology that dominates other biological networks, and that network topologies can vary substantially even within a given viral group. Five examples with hepatitis B virus and poliovirus are presented to illustrate how covariance network analysis can lead to inferences about viral biology.

Novel nucleotide and amino acid covariation between the 5'UTR and the NS2/NS3 proteins of hepatitis C virus: bioinformatic and functional analyses

Molecular covariation of highly polymorphic viruses is thought to have crucial effects on viral replication and fitness. This study employs association rule data mining of hepatitis C virus (HCV) sequences to search for specific evolutionary covariation and then tests functional relevance on HCV replication. Data mining is performed between nucleotides in the untranslated regions 5′ and 3′UTR, and the amino acid residues in the non-structural proteins NS2, NS3 and NS5B. Results indicate covariance of the 243^rd nucleotide of the 5′UTR with the 14^th, 41^st, 76^th, 110^th, 211^th and 212^th residues of NS2 and with the 71^st, 175^th and 621^st residues of NS3. Real-time experiments using an HCV subgenomic system to quantify viral replication confirm replication regulation for each covariant pair between 5′UTR₂₄₃ and NS2-41, -76, -110, -211, and NS3-71, -175. The HCV subgenomic system with/without the NS2 region shows that regulatory effects vanish without NS2, so replicative modulation mediated by HCV 5′UTR₂₄₃ depends on NS2. Strong binding of the NS2 variants to HCV RNA correlates with reduced HCV replication whereas weak binding correlates with restoration of HCV replication efficiency, as determined by RNA-protein immunoprecipitation assay band intensity. The dominant haplotype 5′UTR₂₄₃-NS2-41-76-110-211-NS3-71-175 differs according to the HCV genotype: G-Ile-Ile-Ile-Gly-Ile-Met for genotype 1b and A-Leu-Val-Leu-Ser-Val-Leu for genotypes 1a, 2a and 2b. In conclusion, 5′UTR₂₄₃ co-varies with specific NS2/3 protein amino acid residues, which may have significant structural and functional consequences for HCV replication. This unreported mechanism involving HCV replication possibly can be exploited in the development of advanced anti-HCV medication.

Evaluation of intra-host variants of the entire hepatitis B virus genome

Genetic analysis of hepatitis B virus (HBV) frequently involves study of intra-host variants, identification of which is commonly achieved using short regions of the HBV genome. However, the use of short sequences significantly limits evaluation of genetic relatedness among HBV strains. Although analysis of HBV complete genomes using genetic cloning has been developed, its application is highly labor intensive and practiced only infrequently. We describe here a novel approach to whole genome (WG) HBV quasispecies analysis based on end-point, limiting-dilution real-time PCR (EPLD-PCR) for amplification of single HBV genome variants, and their subsequent sequencing. EPLD-PCR was used to analyze WG quasispecies from serum samples of patients (n = 38) infected with HBV genotypes A, B, C, D, E and G. Phylogenetic analysis of the EPLD-isolated HBV-WG quasispecies showed the presence of mixed genotypes, recombinant variants and sub-populations of the virus. A critical observation was that HBV-WG consensus sequences obtained by direct sequencing of PCR fragments without EPLD are genetically close, but not always identical to the major HBV variants in the intra-host population, thus indicating that consensus sequences should be judiciously used in genetic analysis. Sequence-based studies of HBV WG quasispecies should afford a more accurate assessment of HBV evolution in various clinical and epidemiological settings.

The natural history of early hepatitis C virus evolution; lessons from a global outbreak in human immunodeficiency virus-1-infected individuals

New insights into the early viral evolution and cellular immune response during acute hepatitis C virus (HCV) infection are being gained following a global outbreak in human immunodeficiency virus-1 (HIV)-positive men who have sex with men. Cross-sectional and longitudinal sequence analysis at both the population and individual level have facilitated tracking of the HCV epidemic across the world and enabled the development of tests of viral diversity in individual patients in order to predict spontaneous clearance of HCV and response to treatment. Immunological studies in HIV-positive cohorts have highlighted the role of the CD4⁺ T-cell response in the control of early HCV infection and will increase the opportunity for the identification of protective epitopes that could be used in future vaccine development.

Temporal variations in the hepatitis C virus intrahost population during chronic infection

The intrahost evolution of hepatitis C virus (HCV) holds keys to understanding mechanisms responsible for the establishment of chronic infections and to development of a vaccine and therapeutics. In this study, intrahost variants of two variable HCV genomic regions, HVR1 and NS5A, were sequenced from four treatment-naïve chronically infected patients who were followed up from the acute stage of infection for 9 to 18 years. Median-joining network analysis indicated that the majority of the HCV intrahost variants were observed only at certain time points, but some variants were detectable at more than one time point. In all patients, these variants were found organized into communities or subpopulations. We hypothesize that HCV intrahost evolution is defined by two processes: incremental changes within communities through random mutation and alternations between coexisting communities. The HCV population was observed to incrementally evolve within a single community during approximately the first 3 years of infection, followed by dispersion into several subpopulations. Two patients demonstrated this pattern of dispersion for the rest of the observation period, while HCV variants in the other two patients converged into another single subpopulation after ∼9 to 12 years of dispersion. The final subpopulation in these two patients was under purifying selection. Intrahost HCV evolution in all four patients was characterized by a consistent increase in negative selection over time, suggesting the increasing HCV adaptation to the host late in infection. The data suggest specific staging of HCV intrahost evolution.

Evolution of the influenza A virus untranslated regions

In case of the influenza virus, untranslated regions are considered to possess plural functions. The specific packaging model suggests that each of eight segments contains a unique "packaging signal", situated within the untranslated region and coding regions at the 5' and 3' ends of the genomic RNA. In addition to packaging signal, UTRs play key roles in polyadenylation and signals for genomic replication. In the present study, we report the evolutionary characteristics of untranslated regions of influenza virus. We analyzed 574 sequences of the human influenza A (H3N2) virus. The sequence of the untranslated region is highly conserved. Our analysis produced several observations regarding the untranslated region: (1) it has an extremely low divergence; (2) its evolutionary speed is not associated with the protein(s) it encodes; (3) its evolutionary rate is smaller than that of the open reading frame. We revealed the evolutionary characteristics of the untranslated region; this is the first study on the non-coding region of the influenza virus from the perspective of evolutionary molecular biology. In the future, clarifying the detailed mechanisms of packaging as well as the function of the RNA sequence in the untranslated region will increase the understanding of viral life cycles and evolution.

Coevolution of the hepatitis C virus polyprotein sites in patients on combined pegylated interferon and ribavirin therapy

Genotype-specific sensitivity of the hepatitis C virus (HCV) to interferon-ribavirin (IFN-RBV) combination therapy and reduced HCV response to IFN-RBV as infection progresses from acute to chronic infection suggest that HCV genetic factors and intrahost HCV evolution play important roles in therapy outcomes. HCV polyprotein sequences (n = 40) from 10 patients with unsustainable response (UR) (breakthrough and relapse) and 10 patients with no response (NR) following therapy were identified through the Virahep-C study. Bayesian networks (BNs) were constructed to relate interrelationships among HCV polymorphic sites to UR/NR outcomes. All models showed an extensive interdependence of HCV sites and strong connections (P ≤ 0.003) to therapy response. Although all HCV proteins contributed to the networks, the topological properties of sites differed among proteins. E2 and NS5A together contributed ∼40% of all sites and ∼62% of all links to the polyprotein BN. The NS5A BN and E2 BN predicted UR/NR outcomes with 85% and 97.5% accuracy, respectively, in 10-fold cross-validation experiments. The NS5A model constructed using physicochemical properties of only five sites was shown to predict the UR/NR outcomes with 83.3% accuracy for 6 UR and 12 NR cases of the HALT-C study. Thus, HCV adaptation to IFN-RBV is a complex trait encoded in the interrelationships among many sites along the entire HCV polyprotein. E2 and NS5A generate broad epistatic connectivity across the HCV polyprotein and essentially shape intrahost HCV evolution toward the IFN-RBV resistance. Both proteins can be used to accurately predict the outcomes of IFN-RBV therapy.

Prospects for personalizing antiviral therapy for hepatitis C virus with pharmacogenetics

Chronic hepatitis C virus (HCV) infection is a major cause of liver disease worldwide. HCV infection is currently treated with IFNα plus ribavirin for 24 to 48 weeks. This demanding therapy fails in up to 50% of patients, so the use of pharmacogenetic biomarkers to predict the outcome of treatment would reduce futile treatment of non-responders and help identify patients in whom therapy would be justified. Both IFNα and ribavirin primarily act by modulating the immune system of the patient, and HCV uses multiple mechanisms to counteract the antiviral effects stimulated by therapy. Therefore, response to therapy is influenced by variations in human genes governing the immune system and by differences in HCV genes that blunt antiviral immune responses. This article summarizes recent advances in understanding how host and viral genetic variation affect outcome of therapy. The most notable human associations are polymorphisms within the IL28B gene, but variations in human leukocyte antigen and cytokine genes have also been associated with treatment outcome. The most prominent viral genetic association with outcome of therapy is that HCV genotype 1 is much less sensitive to treatment than genotypes 2 and 3, but genetic differences below the genotype level also influence outcome of therapy, presumably by modulating the ability of viral genes to blunt antiviral immune responses. Pharmacogenetic prediction of the outcome of IFN-based therapy for HCV will require integrating the efficacies of the immunosuppressive mechanisms of a viral isolate, and then interpreting the viral resistance potential in context of the genetic profile of the patient at loci associated with outcome of therapy. Direct-acting inhibitors of HCV that will be used in combination with IFNα are nearing approval, so genetic prediction for anti-HCV therapy will soon need to incorporate viral genetic markers of viral resistance to the new drugs.

Effect of immune pressure on hepatitis C virus evolution: insights from a single-source outbreak

The host's immune response to hepatitis C virus (HCV) can result in the selection of characteristic mutations (adaptations) that enable the virus to escape this response. The ability of the virus to mutate at these sites is dependent on the incoming virus, the fitness cost incurred by the mutation, and the benefit to the virus in escaping the response. Studies examining viral adaptation in chronic HCV infection have shown that these characteristic immune escape mutations can be observed at the population level as human leukocyte antigen (HLA)-specific viral polymorphisms. We examined 63 individuals with chronic HCV infection who were infected from a single HCV genotype 1b source. Our aim was to determine the extent to which the host's immune pressure affects HCV diversity and the ways in which the sequence of the incoming virus, including preexisting escape mutations, can influence subsequent mutations in recipients and infection outcomes.

CONCLUSION

HCV sequences from these individuals revealed 29 significant associations between specific HLA types within the new hosts and variations within their viruses, which likely represent new viral adaptations. These associations did not overlap with previously reported adaptations for genotypes 1a and 3a and possibly reflected a combination of constraint due to the incoming virus and genetic distance between the strains. However, these sites accounted for only a portion of the sites in which viral diversity was observed in the new hosts. Furthermore, preexisting viral adaptations in the incoming (source) virus likely influenced the outcomes in the new hosts.

The acidic domain of hepatitis C virus NS4A contributes to RNA replication and virus particle assembly

Hepatitis C virus NS3-4A is a membrane-bound enzyme complex that exhibits serine protease, RNA helicase, and RNA-stimulated ATPase activities. This enzyme complex is essential for viral genome replication and has been recently implicated in virus particle assembly. To help clarify the role of NS4A in these processes, we conducted alanine scanning mutagenesis on the C-terminal acidic domain of NS4A in the context of a chimeric genotype 2a reporter virus. Of 13 mutants tested, two (Y45A and F48A) had severe defects in replication, while seven (K41A, L44A, D49A, E50A, M51A, E52A, and E53A) efficiently replicated but had severe defects in virus particle assembly. Multiple strategies were used to identify second-site mutations that suppressed these NS4A defects. The replication defect of NS4A F48A was partially suppressed by mutation of NS4B I7F, indicating that a genetic interaction between NS4A and NS4B contributes to RNA replication. Furthermore, the virus assembly defect of NS4A K41A was suppressed by NS3 Q221L, a mutation previously implicated in overcoming other virus assembly defects. We therefore examined the known enzymatic activities of wild-type or mutant forms of NS3-4A but did not detect specific defects in the mutants. Taken together, our data reveal interactions between NS4A and NS4B that control genome replication and between NS3 and NS4A that control virus assembly.

Comparison of selection pressures on the HA gene of pandemic (2009) and seasonal human and swine influenza A H1 subtype viruses

The 2009 human pandemic influenza (H1N1) virus possesses the HA gene of the H1 subtype. The evolutionary process of the 2009 H1N1 virus remains to be defined. We performed genetic analyses of the HA gene by comparing the 2009 H1N1 virus with seasonal human and swine viruses. We analyzed sequences of 116 2009 H1N1 viruses, and obtained 1457 seasonal H1N1, 365 swine H1, and 1332 2009 H1N1 viruses from the database. Selection pressure for the 2009 H1N1 virus was higher than that for the swine virus and equivalent to that for the seasonal virus. Positions 206 and 264 were found to be positively selected sites. We also identified sites under different selection pressures from the seasonal or swine virus that may be involved in imparting significant biological characteristics. The evolutionary characteristics of the H1 gene of the 2009 H1N1 virus differed from those of seasonal and swine viruses.

Molecular epidemiology of health care-associated transmission of hepatitis B and C viruses

The term "molecular epidemiology" has been ascribed to a host of different activities that involve gene-sequence analysis. Some examples of molecular epidemiology include modeling exercises of phylogenetic trees to reconstruct epidemics; studies of the evolution of hepatitis C virus (HCV); rates of nucleotide substitution in the hepatitis B virus (HBV) surface (S) gene; variations in the core promoter/pre-core/core region of HBV genotype C from different sources; analysis of HBV surface antigen mutations; molecular clock analyses of the short-term evolution of HCV; and analyses of clades and surface antigen polymorphisms of HBV. However, for most epidemiologists molecular epidemiology of viral hepatitis usually refers to studies of gene-sequence homology in HBV or HCV recovered from people in the community or an institution that allows better characterization and assignment of related clusters of infection.

Clinical relevance of genetic heterogeneity in HCV

Infection by HCV affects an estimated 170 million people worldwide and it represents one of the major causes of liver transplantation and a heavy burden to healthcare systems. As with many other RNA viruses, HCV is characterized by very high levels of genetic variation, which have been associated to differences in disease progression and efficiency of antiviral treatment. Studies show many contradictory results and little consensus on such associations. Nevertheless, some general guidelines translating research results to clinical practice have been postulated. Here, we review the main research results obtained on HCV variation so far and explore the reasons for their lack of congruence under a population genetics framework. Understanding the factors responsible for the variable dynamics of HCV diversity in human populations and variation within infected individuals is even more necessary in face of the soon-to-arrive new HCV therapies.

Divergent adaptation of hepatitis C virus genotypes 1 and 3 to human leukocyte antigen-restricted immune pressure

Many hepatitis C virus (HCV) infections worldwide are with the genotype 1 and 3 strains of the virus. Cellular immune responses are known to be important in the containment of HCV genotype 1 infection, and many genotype 1 T cell targets (epitopes) that are presented by host human leukocyte antigens (HLAs) have been identified. In contrast, there is almost no information known about the equivalent responses to genotype 3. Immune escape mechanisms used by HCV include the evolution of viral polymorphisms (adaptations) that abrogate this host-viral interaction. Evidence of HCV adaptation to HLA-restricted immune pressure on HCV can be observed at the population level as viral polymorphisms associated with specific HLA types. To evaluate the escape patterns of HCV genotypes 1 and 3, we assessed the associations between viral polymorphisms and specific HLA types from 187 individuals with genotype 1a and 136 individuals with genotype 3a infection. We identified 51 HLA-associated viral polymorphisms (32 for genotype 1a and 19 for genotype 3a). Of these putative viral adaptation sites, six fell within previously published epitopes. Only two HLA-associated viral polymorphisms were common to both genotypes. In the remaining sites with HLA-associated polymorphisms, there was either complete conservation or no significant HLA association with viral polymorphism in the alternative genotype. This study also highlights the diverse mechanisms by which viral evasion of immune responses may be achieved and the role of genotype variation in these processes.

CONCLUSION

There is little overlap in HLA-associated polymorphisms in the nonstructural proteins of HCV for the two genotypes, implying differences in the cellular immune pressures acting on these viruses and different escape profiles. These findings have implications for future therapeutic strategies to combat HCV infection, including vaccine design.

Large-scale sequence analysis of M gene of influenza A viruses from different species: mechanisms for emergence and spread of amantadine resistance

Influenza A virus infects many species, and amantadine is used as an antiviral agent. Recently, a substantial increase in amantadine-resistant strains has been reported, most of which have a substitution at amino acid position 31 in the M2 gene. Understanding the mechanism responsible for the emergence and spread of antiviral resistance is important for developing a treatment protocol for seasonal influenza and for deciding on a policy for antiviral stockpiling for pandemic influenza. The present study was conducted to identify the existence of drug pressure on the emergence and spread of amantadine-resistant influenza A viruses. We analyzed data on more than 5,000 virus sequences and constructed a phylogenetic tree to calculate selective pressures on sites in the M2 gene associated with amantadine resistance (positions 26, 27, 30, and 31) among different hosts. The phylogenetic tree revealed that the emergence and spread of the drug-resistant M gene in different hosts and subtypes were independent and not through reassortment. For human influenza virus, positive selection was detected only at position 27. Selective pressures on the sites were not always higher for human influenza virus than for viruses of other hosts. Additionally, selective pressure on position 31 did not increase after the introduction of amantadine. Although there is a possibility of drug pressure on human influenza virus, we could not find positive pressure on position 31. Because the recent rapid increase in drug-resistant virus is associated with the substitution at position 31, the resistance may not be related to drug use.

Evolution of the M gene of the influenza A virus in different host species: large-scale sequence analysis

Background

Influenza A virus infects not only humans, but also other species including avian and swine. If a novel influenza A subtype acquires the ability to spread between humans efficiently, it could cause the next pandemic. Therefore it is necessary to understand the evolutionary processes of influenza A viruses in various hosts in order to gain better knowledge about the emergence of pandemic virus. The virus has segmented RNA genome and 7th segment, M gene, encodes 2 proteins. M1 is a matrix protein and M2 is a membrane protein. The M gene may be involved in determining host tropism. Besides, novel vaccines targeting M1 or M2 protein to confer cross subtype protection have been under development. We conducted the present study to investigate the evolution of the M gene by analyzing its sequence in different species.

Results

Phylogenetic tree revealed host-specific lineages and evolution rates were different among species. Selective pressure on M2 was stronger than that on M1. Selective pressure on M1 for human influenza was stronger than that for avian influenza, as well as M2. Site-by-site analyses identified one site (amino acid position 219) in M1 as positively selected in human. Positions 115 and 121 in M1, at which consensus amino acids were different between human and avian, were under negative selection in both hosts. As to M2, 10 sites were under positive selection in human. Seven sites locate in extracellular domain. That might be due to host's immune pressure. One site (position 27) positively selected in transmembrane domain is known to be associated with drug resistance. And, two sites (positions 57 and 89) locate in cytoplasmic domain. The sites are involved in several functions.

Conclusion

The M gene of influenza A virus has evolved independently, under different selective pressure on M1 and M2 among different hosts. We found potentially important sites that may be related to host tropism and immune responses. These sites may be important for evolutional process in different hosts and host adaptation.

Predicting response to hepatitis C therapy

Current treatment for chronic hepatitis C is expensive, is often accompanied by burdensome side effects, and, sadly, fails in almost half of cases. The ability to predict such failures prior to treatment could save a great deal of pain and expense for the patient with HCV. In this issue of the JCI, Aurora and colleagues describe the development of genetic markers predictive of treatment response based on a study of viral sequence variation (see the related article beginning on page 225). Genome-wide covariation analyses of pretreatment virus sequences from 94 patients showed distinct patterns of mutations strongly associated with the ultimate success or failure of treatment. Such analyses suggest markers predictive of response to therapy and may lead to new insights into the underlying biology of hepatitis C.

The NS4A protein of hepatitis C virus promotes RNA-coupled ATP hydrolysis by the NS3 helicase

Nonstructural protein 3 (NS3) is an essential replicative component of the hepatitis C virus (HCV) and a member of the DExH/D-box family of proteins. The C-terminal region of NS3 (NS3hel) exhibits RNA-stimulated NTPase and helicase activity, while the N-terminal serine protease domain of NS3 enhances RNA binding and unwinding by NS3hel. The nonstructural protein 4A (NS4A) binds to the NS3 protease domain and serves as an obligate cofactor for NS3 serine protease activity. Given its role in stimulating protease activity, we sought to determine whether NS4A also influences the activity of NS3hel. Here we show that NS4A enhances the ability of NS3hel to bind RNA in the presence of ATP, thereby acting as a cofactor for helicase activity. This effect is mediated by amino acids in the C-terminal acidic domain of NS4A. When these residues are mutated, one observes drastic reductions in ATP-coupled RNA binding and duplex unwinding by NS3. These same mutations are lethal in HCV replicons, thereby establishing in vitro and in vivo that NS4A plays an important role in the helicase mechanism of NS3 and its function in replication.

Genome-wide hepatitis C virus amino acid covariance networks can predict response to antiviral therapy in humans

Hepatitis C virus (HCV) is a common RNA virus that causes hepatitis and liver cancer. Infection is treated with IFN-alpha and ribavirin, but this expensive and physically demanding therapy fails in half of patients. The genomic sequences of independent HCV isolates differ by approximately 10%, but the effects of this variation on the response to therapy are unknown. To address this question, we analyzed amino acid covariance within the full viral coding region of pretherapy HCV sequences from 94 participants in the Viral Resistance to Antiviral Therapy of Chronic Hepatitis C (Virahep-C) clinical study. Covarying positions were common and linked together into networks that differed by response to therapy. There were 3-fold more hydrophobic amino acid pairs in HCV from nonresponding patients, and these hydrophobic interactions were predicted to contribute to failure of therapy by stabilizing viral protein complexes. Using our analysis to detect patterns within the networks, we could predict the outcome of therapy with greater than 95% coverage and 100% accuracy, raising the possibility of a prognostic test to reduce therapeutic failures. Furthermore, the hub positions in the networks are attractive antiviral targets because of their genetic linkage with many other positions that we predict would suppress evolution of resistant variants. Finally, covariance network analysis could be applicable to any virus with sufficient genetic variation, including most human RNA viruses.