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.

A Novel Information-Theory-Based Genetic Distance That Approximates Phenotypic Differences.

Application of genetic distances to measure phenotypic relatedness is a challenging task, reflecting the complex relationship between genotype and phenotype. Accurate assessment of proximity among sequences with different phenotypic traits depends on how strongly the chosen distance is associated with structural and functional properties. In this study, we present a new distance measure Mutual Information and Entropy H (MIH) for categorical data such as nucleotide or amino acid sequences. MIH applies an information matrix (IM), which is calculated from the data and captures heterogeneity of individual positions as measured by Shannon entropy and coordinated substitutions among positions as measured by mutual information. In general, MIH assigns low weights to differences occurring at high entropy positions or at dependent positions. MIH distance was compared with other common distances on two experimental and two simulated data sets. MIH showed the best ability to distinguish cross-immunoreactive sequence pairs from non-cross-immunoreactive pairs of variants of the hepatitis C virus hypervariable region 1 (26,883 pairwise comparisons), and Major Histocompatibility Complex (MHC) binding peptides (n = 181) from non-binding peptides (n = 129). Analysis of 74 simulated RNA secondary structures also showed that the ratio between MIH distance of sequences from the same RNA structure and MIH of sequences from different structures is three orders of magnitude greater than for Hamming distances. These findings indicate that lower MIH between two sequences is associated with greater probability of the sequences to belong to the same phenotype. Examination of rule-based phenotypes generated in silico showed that (1) MIH is strongly associated with phenotypic differences, (2) IM of sequences under selection is very different from IM generated under random scenarios, and (3) IM is robust to sampling. In conclusion, MIH strongly approximates structural/functional distances and should have important applications to a wide range of biological problems, including evolution, artificial selection of biological functions and structures, and measuring phenotypic similarity.

Entropy of mitochondrial DNA circulating in blood is associated with hepatocellular carcinoma.

BACKGROUND: Ultra-Deep Sequencing (UDS) enabled identification of specific changes in human genome occurring in malignant tumors, with current approaches calling for the detection of specific mutations associated with certain cancers. However, such associations are frequently idiosyncratic and cannot be generalized for diagnostics. Mitochondrial DNA (mtDNA) has been shown to be functionally associated with several cancer types. Here, we study the association of intra-host mtDNA diversity with Hepatocellular Carcinoma (HCC). RESULTS: UDS mtDNA exome data from blood of patients with HCC (n = 293) and non-cancer controls (NC, n = 391) were used to: (i) measure the genetic heterogeneity of nucleotide sites from the entire population of intra-host mtDNA variants rather than to detect specific mutations, and (ii) apply machine learning algorithms to develop a classifier for HCC detection. Average total entropy of HCC mtDNA is 1.24-times lower than of NC mtDNA (p = 2.84E-47). Among all polymorphic sites, 2.09% had a significantly different mean entropy between HCC and NC, with 0.32% of the HCC mtDNA sites having greater (p < 0.05) and 1.77% of the sites having lower mean entropy (p < 0.05) as compared to NC. The entropy profile of each sample was used to further explore the association between mtDNA heterogeneity and HCC by means of a Random Forest (RF) classifier The RF-classifier separated 232 HCC and 232 NC patients with accuracy of up to 99.78% and average accuracy of 92.23% in the 10-fold cross-validation. The classifier accurately separated 93.08% of HCC (n = 61) and NC (n = 159) patients in a validation dataset that was not used for the RF parameter optimization. CONCLUSIONS: Polymorphic sites contributing most to the mtDNA association with HCC are scattered along the mitochondrial genome, affecting all mitochondrial genes. The findings suggest that application of heterogeneity profiles of intra-host mtDNA variants from blood may help overcome barriers associated with the complex association of specific mutations with cancer, enabling the development of accurate, rapid, inexpensive and minimally invasive diagnostic detection of cancer.

Intelligent Network DisRuption Analysis (INDRA): A targeted strategy for efficient interruption of hepatitis C transmissions.

Hepatitis C virus (HCV) infection is a global public health problem. The implementation of public health interventions (PHI) to control HCV infection could effectively interrupt HCV transmission. PHI targeting high-risk populations, e.g., people who inject drugs (PWID), are most efficient but there is a lack of tools for prioritizing individuals within a high-risk community. Here, we present Intelligent Network DisRuption Analysis (INDRA), a targeted strategy for efficient interruption of hepatitis C transmissions.Using a large HCV transmission network among PWID in Indiana as an example, we compare effectiveness of random and targeted strategies in reducing the rate of HCV transmission in two settings: (1) long-established and (2) rapidly spreading infections (outbreak). Identification of high centrality for the network nodes co-infected with HIV or > 1 HCV subtype indicates that the network structure properly represents the underlying contacts among PWID relevant to the transmission of these infections. Changes in the network's global efficiency (GE) were used as a measure of the PHI effects. In setting 1, simulation experiments showed that a 50% GE reduction can be achieved by removing 11.2 times less nodes using targeted vs random strategies. A greater effect of targeted strategies on GE was consistently observed when networks were simulated: (1) with a varying degree of errors in node sampling and link assignment, and (2) at different levels of transmission reduction at affected nodes. In simulations considering a 10% removal of infected nodes, targeted strategies were ~2.8 times more effective than random in reducing incidence. Peer-education intervention (PEI) was modeled as a probabilistic distribution of actionable knowledge of safe injection practices from the affected node to adjacent nodes in the network. Addition of PEI to the models resulted in a 2-3 times greater reduction in incidence than from direct PHI alone. In setting 2, however, random direct PHI were ~3.2 times more effective in reducing incidence at the simulated conditions. Nevertheless, addition of PEI resulted in a ~1.7-fold greater efficiency of targeted PHI. In conclusion, targeted PHI facilitated by INDRA outperforms random strategies in decreasing circulation of long-established infections. Network-based PEI may amplify effects of PHI on incidence reduction in both settings.

GHOST: global hepatitis outbreak and surveillance technology.

BACKGROUND: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. RESULTS: We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. CONCLUSIONS: GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

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.

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 16th 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.

Geno-geographic origin of Y-specific STR haplotypes in a sample of Caucasian-Mestizo and African-descent male individuals from Colombia / Origen geno-geográfico de haplotipos STR del cromosoma Y en una muestra caucásico-mestiza y afrodescendiente de Colombia

Introduction: Y chromosome STR haplotypes have been widely used in population studies to establish the origin of diverse populations. Objective: We analyzed Y chromosome STR haplotypes (8 loci) in 134 Caucasian-mestizo and 137 African-descent Colombian unrelated individuals to correlate the geographical origin with historical data as well as the genetic relationships and possible admixture patterns. Materials and methods: One hundred samples of African descent and 137 Caucasian-mestizo samples analyzed for Y chromosome STR haplotypes by PCR followed by acrylamide electrophoresis. Results: No evidence of population substructure was found for the African descent. Two point fifty nine per cent of the haplotypes were shared between the two groups with the possible existence of Caucasian gene flow towards Afro-descendants. Conclusion: The Caucasian-Mestizo Colombian population is grouped with other populations of the Iberian Peninsula and Europe, while the Afro-Colombian population is grouped with other African populations reported.

Introducción. Los haplotipos STR de cromosoma Y han sido ampliamente utilizados en estudios de poblaciones para establecer el origen de diversas poblaciones. Objetivo. Se analizaron haplotipos STR del cromosoma Y (8 loci ) en 134 afrodescendientes y caucásico-mestizos no relacionados de Colombia, para correlacionar el origen geográfico con los datos históricos, así como las relaciones genéticas y posibles patrones de mezcla. Materiales y métodos. Se analizaron los haplotipos STR del cromosoma Y mediante PCR seguidas de electroforesis en acrilamida, de 134 muestras de afrodescendientes y 137 muestras de caucásicos mestizos. Resultados. No se encontró evidencia de subestructuración de la población afrodescendiente. El 2,59 % de los haplotipos eran compartidos en los dos grupos analizados, con la posible existencia de flujo génico de caucásico-mestizos hacia los afrodescendientes. Conclusión. La población caucásico-mestiza colombiana se agrupa con otras poblaciones de la península Ibérica y Europa, mientras que la población afrodescendiente colombiana se agrupa con otras poblaciones africanas reportadas.

Hepatitis C virus antigenic convergence.

Vaccine development against hepatitis C virus (HCV) is hindered by poor understanding of factors defining cross-immunoreactivity among heterogeneous epitopes. Using synthetic peptides and mouse immunization as a model, we conducted a quantitative analysis of cross-immunoreactivity among variants of the HCV hypervariable region 1 (HVR1). Analysis of 26,883 immunological reactions among pairs of peptides showed that the distribution of cross-immunoreactivity among HVR1 variants was skewed, with antibodies against a few variants reacting with all tested peptides. The HVR1 cross-immunoreactivity was accurately modeled based on amino acid sequence alone. The tested peptides were mapped in the HVR1 sequence space, which was visualized as a network of 11,319 sequences. The HVR1 variants with a greater network centrality showed a broader cross-immunoreactivity. The entire sequence space is explored by each HCV genotype and subtype. These findings indicate that HVR1 antigenic diversity is extensively convergent and effectively limited, suggesting significant implications for vaccine development.