Interferon lambda 4 variant rs12979860 is not associated with RAV NS5A Y93H in hepatitis C virus genotype 3a

International audienc

Inference of Host–Pathogen Interaction Matrices from Genome-Wide Polymorphism Data

Host–pathogen coevolution is defined as the reciprocal evolutionary changes in both species due to genotype × genotype (G×G) interactions at the genetic level determining the outcome and severity of infection. While co-analyses of hosts and pathogen genomes (co-genome-wide association studies) allow us to pinpoint the interacting genes, these do not reveal which host genotype(s) is/are resistant to which pathogen genotype(s). The knowledge of this so-called infection matrix is important for agriculture and medicine. Building on established theories of host–pathogen interactions, we here derive four novel indices capturing the characteristics of the infection matrix. These indices can be computed from full genome polymorphism data of randomly sampled uninfected hosts, as well as infected hosts and their pathogen strains. We use these indices in an approximate Bayesian computation method to pinpoint loci with relevant G×G interactions and to infer their underlying interaction matrix. In a combined single nucleotide polymorphism dataset of 451 European humans and their infecting hepatitis C virus (HCV) strains and 503 uninfected individuals, we reveal a new human candidate gene for resistance to HCV and new virus mutations matching human genes. For two groups of significant human–HCV (G×G) associations, we infer a gene-for-gene infection matrix, which is commonly assumed to be typical of plant–pathogen interactions. Our model-based inference framework bridges theoretical models of G×G interactions with host and pathogen genomic data. It, therefore, paves the way for understanding the evolution of key G×G interactions underpinning HCV adaptation to the European human population after a recent expansion

A systematic review of Hepatitis B virus (HBV) prevalence and genotypes in Kenya: Data to inform clinical care and health policy

The aim of this systematic review and meta-analysis is to evaluate available prevalence and viral sequencing data representing chronic hepatitis B (CHB) infection in Kenya. More than 20% of the global disease burden from CHB is in Africa, however there is minimal high quality seroprevalence data from individual countries and little viral sequencing data available to represent the continent. We undertook a systematic review of the prevalence and genetic data available for hepatitis B virus (HBV) in Kenya using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) 2020 checklist. We identified 23 studies reporting HBV prevalence and 8 studies that included HBV genetic data published in English between January 2000 and December 2021. We assessed study quality using the Joanna Briggs Institute critical appraisal checklist. Due to study heterogeneity, we divided the studies to represent low, moderate, high and very high-risk for HBV infection, identifying 8, 7, 5 and 3 studies in these groups, respectively. We calculated pooled HBV prevalence within each group and evaluated available sequencing data. Pooled HBV prevalence was 3.4% (95% CI 2.7–4.2%), 6.1% (95% CI 5.1–7.4%), 6.2% (95% CI 4.64–8.2) and 29.2% (95% CI 12.2–55.1), respectively. Study quality was overall low; only three studies detailed sample size calculation and 17/23 studies were cross sectional. Eight studies included genetic information on HBV, with two undertaking whole genome sequencing. Genotype A accounted for 92% of infections. Other genotypes included genotype D (6%), D/E recombinants (1%) or mixed populations (1%). Drug resistance mutations were reported by two studies. There is an urgent need for more high quality seroprevalence and genetic data to represent HBV in Kenya to underpin improved HBV screening, treatment and prevention in order to support progress towards elimination targets

A systematic review of Hepatitis B virus (HBV) prevalence and genotypes in Kenya: data to inform clinical care and health policy

The aim of this systematic review and meta-analysis is to evaluate available prevalence and viral sequencing data representing chronic hepatitis B (CHB) infection in Kenya. More than 20% of the global disease burden from CHB is in Africa, however there is minimal high quality seroprevalence data from individual countries and little viral sequencing data available to represent the continent. We undertook a systematic review of the prevalence and genetic data available for hepatitis B virus (HBV) in Kenya using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) 2020 checklist. We identified 23 studies reporting HBV prevalence and 8 studies that included HBV genetic data published in English between January 2000 and December 2021. We assessed study quality using the Joanna Briggs Institute critical appraisal checklist. Due to study heterogeneity, we divided the studies to represent low, moderate, high and very high-risk for HBV infection, identifying 8, 7, 5 and 3 studies in these groups, respectively. We calculated pooled HBV prevalence within each group and evaluated available sequencing data. Pooled HBV prevalence was 3.4% (95% CI 2.7-4.2%), 6.1% (95% CI 5.1-7.4%), 6.2% (95% CI 4.64-8.2) and 29.2% (95% CI 12.2-55.1), respectively. Study quality was overall low; only three studies detailed sample size calculation and 17/23 studies were cross sectional. Eight studies included genetic information on HBV, with two undertaking whole genome sequencing. Genotype A accounted for 92% of infections. Other genotypes included genotype D (6%), D/E recombinants (1%) or mixed populations (1%). Drug resistance mutations were reported by two studies. There is an urgent need for more high quality seroprevalence and genetic data to represent HBV in Kenya to underpin improved HBV screening, treatment and prevention in order to support progress towards elimination targets

Changes in the prevalence of hepatitis B and C viral infections in Sindh province, Pakistan: Findings from two sero‐surveys in 2007 and 2019

Pakistan harbours a large burden of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection. We utilised repeat sero‐surveys to assess progress achieved towards hepatitis elimination in Pakistan. Multilevel logistic regression evaluated the change in HBV infection (HBV surface antigen (HBsAg)‐positive) prevalence and HCV exposure (HCV antibody (HCV‐Ab)‐positive) prevalence between two sero‐surveys from 2007 and 2019 for Sindh province and associated risk factors. Adjusted odds ratios (aORs) were estimated and population‐attributable fractions (PAF) for modifiable risk factors for HCV exposure. The 2007 and 2019 surveys included 8855 and 6672 individuals. HBsAg prevalence decreased from 2.6% (95% confidence intervals (95% CI): 2.2–2.9) in 2007 to 1.1% (95% CI: 0.8–1.3) in 2019, while HCV‐Ab prevalence increased from 5.1% (95% CI: 4.6%–5.5%) to 6.2% (95% CI: 5.6%–6.8%). The age and gender‐adjusted HBsAg prevalence decreased by 80% (aOR = 0.2, 95% CI: 0.1–0.4) among children and 60% (aOR = 0.4, 95% CI: 0.3–0.6) among adults over 2007–2019, while HCV‐Ab prevalence decreased by 60% (aOR = 0.4, 95%CI:0.2–0.7) in children and increased by 40% (aOR = 1.4, 95% CI: 1.2–1.7) in adults. HCV‐Ab prevalence was lower in adults with secondary (aOR = 0.6, 95% CI: 0.5–0.8) and higher (aOR = 0.5, 95%CI:0.3–0.8) education compared to illiterates and higher among adults reporting blood transfusion (aOR = 1.7, 95% CI: 1.2–2.4), family history of hepatitis (aOR = 2.5, 95% CI: 1.9–3.3), past year medical injection (aOR = 2.1, 95% CI: 1.6–2.7), being tattooed (aOR = 1.4, 95% CI: 1.0–1.9) and shaved by traditional barber (aOR = 1.2, 95% CI: 1.0–1.5). Modifiable risk factors accounted for 45% of HCV exposure, with medical injection(s) accounting for 38% (95%CI,25.7–48.4%). Overall HCV has increased over 2007–2019 in Sindh province, while HBV prevalence has decreased. Medical injections should be an important focus of prevention activities

An enrichment protocol and analysis pipeline for long read sequencing of the hepatitis B virus transcriptome

Hepatitis B virus (HBV) is one of the smallest human DNA viruses and its 3.2 Kb genome encodes multiple overlapping open reading frames, making its viral transcriptome challenging to dissect. Previous studies have combined quantitative PCR and Next Generation Sequencing to identify viral transcripts and splice junctions, however the fragmentation and selective amplification used in short read sequencing precludes the resolution of full length RNAs. Our study coupled an oligonucleotide enrichment protocol with state-of-the-art long read sequencing (PacBio) to identify the repertoire of HBV RNAs. This methodology provides sequencing libraries where up to 25 % of reads are of viral origin and enable the identification of canonical (unspliced), non-canonical (spliced) and chimeric viral-human transcripts. Sequencing RNA isolated from de novo HBV infected cells or those transfected with 1.3 × overlength HBV genomes allowed us to assess the viral transcriptome and to annotate 5' truncations and polyadenylation profiles. The two HBV model systems showed an excellent agreement in the pattern of major viral RNAs, however differences were noted in the abundance of spliced transcripts. Viral-host chimeric transcripts were identified and more commonly found in the transfected cells. Enrichment capture and PacBio sequencing allows the assignment of canonical and non-canonical HBV RNAs using an open-source analysis pipeline that enables the accurate mapping of the HBV transcriptome

An enrichment protocol and analysis pipeline for long read sequencing of the hepatitis B virus transcriptome

Hepatitis B virus (HBV) is one of the smallest human DNA viruses and its 3.2 Kb genome encodes multiple overlapping open reading frames, making its viral transcriptome challenging to dissect. Previous studies have combined quantitative PCR and Next Generation Sequencing to identify viral transcripts and splice junctions, however the fragmentation and selective amplification used in short read sequencing precludes the resolution of full length RNAs. Our study coupled an oligonucleotide enrichment protocol with state-of-the-art long read sequencing (PacBio) to identify the repertoire of HBV RNAs. This methodology provides sequencing libraries where up to 25 % of reads are of viral origin and enable the identification of canonical (unspliced), non-canonical (spliced) and chimeric viral-human transcripts. Sequencing RNA isolated from de novo HBV infected cells or those transfected with 1.3 × overlength HBV genomes allowed us to assess the viral transcriptome and to annotate 5′ truncations and polyadenylation profiles. The two HBV model systems showed an excellent agreement in the pattern of major viral RNAs, however differences were noted in the abundance of spliced transcripts. Viral-host chimeric transcripts were identified and more commonly found in the transfected cells. Enrichment capture and PacBio sequencing allows the assignment of canonical and non-canonical HBV RNAs using an open-source analysis pipeline that enables the accurate mapping of the HBV transcriptome

Interpreting viral deep sequencing data with GLUE

Using deep sequencing technologies such as Illumina’s platform, it is possible to obtain reads from the viral RNA population revealing the viral genome diversity within a single host. A range of software tools and pipelines can transform raw deep sequencing reads into Sequence Alignment Mapping (SAM) files. We propose that interpretation tools should process these SAM files, directly translating individual reads to amino acids in order to extract statistics of interest such as the proportion of different amino acid residues at specific sites. This preserves per-read linkage between nucleotide variants at different positions within a codon location. The samReporter is a subsystem of the GLUE software toolkit which follows this direct read translation approach in its processing of SAM files. We test samReporter on a deep sequencing dataset obtained from a cohort of 241 UK HCV patients for whom prior treatment with direct-acting antivirals has failed; deep sequencing and resistance testing have been suggested to be of clinical use in this context. We compared the polymorphism interpretation results of the samReporter against an approach that does not preserve per-read linkage. We found that the samReporter was able to properly interpret the sequence data at resistance-associated locations in nine patients where the alternative approach was equivocal. In three cases, the samReporter confirmed that resistance or an atypical substitution was present at NS5A position 30. In three further cases, it confirmed that the sofosbuvir-resistant NS5B substitution S282T was absent. This suggests the direct read translation approach implemented is of value for interpreting viral deep sequencing data