Biology subjects

STOP-HCV Consortium,

Publications and source records attributed to STOP-HCV Consortium,.

4 recordsLinked to original sources

bioRxiv2023

Inference of host-pathogen interaction matrices from genome-wide polymorphism data

Coevolution is defined as the evolutionary change in one antagonist (host) in response to changes in the other antagonist (pathogen). At the genetic level, these changes are determined by genotype x genotype (GxG) interactions. We build on a general theoretical model of a host-pathogen interaction to derive four indices to retrieve key features of GxG interactions. The four developed indices extract relevant information from polymorphism data of randomly sampled uninfected hosts as well as infected hosts and their respective pathogen strains. Using these indices as summary statistics in an Approximate Bayesian Computation method, we can show their power to discriminate between GxG interaction matrices. Second, we apply our ABC method to a SNP data set of 451 European humans and their infecting Hepatitis C Virus (HCV) strains supplemented by polymorphism data of 503 individuals from the 1,000 genomes project. As our indices encompass and extend previous natural co-GWAs we recover many of the associations previously reported for this dataset and infer their underlying interaction matrix. We reveal a new candidate gene for resistance to HCV in the human genome, and two groups of significant GxG associations exhibiting gene-for-gene interactions. We suggest that the inferred types of GxG interactions result from the recent expansion, adaptation and low prevalence of the HCV virus population in Europe. Significance statementWhy are some host individuals susceptible/resistant to infection by certain pathogen genotypes and others not? Understanding the genetic characteristics of genes driving host-pathogen interactions is crucial to predict epidemics. We develop four indices based on a mathematical model and build a Bayesian statistical method computing these indices on full genome data of infected hosts and their infecting pathogen strains and data of non-infected hosts. We can pinpoint the genes underlying host-pathogen interactions and infer their characteristics. Applying our framework to data from European humans and the Hepatitis C virus, we discover a new potential resistance gene in humans and reveal how the virus has adapted in the last 150 years to match the genetic diversity of the European human population.

evolutionary biology↗

bioRxiv2020

Impact of virus subtype and host IFNL4 genotype on large-scale RNA structure formation in the genome of hepatitis C virus

Mechanisms underlying the ability of hepatitis C virus (HCV) to establish persistent infections and induce progressive liver disease remain poorly understood. HCV is one of several positive-stranded RNA viruses capable of establishing persistence in their immunocompetent vertebrate hosts, an attribute associated with formation of large scale RNA structure in their genomic RNA. We developed novel methods to analyse and visualise genome-scale ordered RNA structure (GORS) predicted from the increasingly large datasets of complete genome sequences of HCV. Structurally conserved RNA secondary structure in coding regions of HCV localised exclusively to polyprotein ends (core, NS5B). Coding regions elsewhere were also intensely structured based on elevated minimum folding energy difference (MFED) values, but the actual stem-loop elements involved in genome folding were structurally entirely distinct, even between subtypes 1a and 1b. Dynamic remodelling was further evident from comparison of HCV strains in different host genetic background. Significantly higher MFED values, greater suppression of UpA dinucleotide frequencies and restricted diversification were found in subjects with the TT genotype of the rs12979860 SNP in the IFNL4 gene compared to the CC (non-expressing) allele. These structural and compositional associations with expression of interferon-{lambda}4 were recapitulated on a larger scale by higher MFED values and greater UpA suppression of genotype 1 compared to genotype 3a, associated with previously reported HCV genotype-associated differences in hepatic interferon-stimulated gene induction. Associations between innate cellular responses with HCV structure and further evolutionary constraints represents an important new element in RNA virus evolution and the adaptive interplay between virus and host.

genomics↗

bioRxiv2020

Viral genome wide association study identifies novel hepatitis C virus polymorphisms associated with sofosbuvir treatment failure

Chronic hepatitis C virus (HCV) infection is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma worldwide. With the recent development of direct acting antivirals (DAA), treatment of chronically infected patients has become highly effective although a subset of patients do not respond to therapy. Sofosbuvir is a common component of current de novo or salvage combination therapies. We used pre-treatment whole genome sequencing of HCV from 507 patients infected with HCV subtype 3a and treated with sofosbuvir containing regimens to detect viral polymorphisms associated with response to treatment. We found that three common polymorphisms present in HCV NS2 and NS3 proteins (not direct targets of sofosbuvir) were associated with reduced treatment response. These polymorphisms were enriched in post-treatment HCV sequences of patients unresponsive to treatment; they were also associated with lower reductions in viral load in the first week of therapy. The finding of polymorphisms in NS2 and NS3 proteins associated with poor treatment outcomes emphasises the value of more systematic genome-wide analyses of HCV in uncovering indirect but clinically relevant mechanisms of antiviral resistance.

microbiology↗

bioRxiv2018

Interferon lambda 4 impacts broadly on hepatitis C virus diversity.

Type III interferons (IFN-{lambda}) are part of the innate immune response to hepatitis C virus (HCV) infection however the specific role of IFN-{lambda}4 and the nature of the viral adaption to this pressure have not been defined. Here we use paired genome-wide human and viral genetic data in 485 patients infected with HCV genotype 3a to explore the role of IFN-{lambda}4 on HCV evolution during chronic infection. We show that genetic variations within the host IFNL4 locus have a broad and systematic impact on HCV amino acid diversity. We also demonstrate that this impact is larger in patients producing a more active form of IFN-{lambda}4 protein compared to the less active form. A similar observation was noted for viral load. We conclude that IFN-{lambda}4 protein is a likely causal agent driving widespread HCV amino acid changes and associated with viral load and possibly other clinical and biological outcomes of HCV infection.

genomics↗