Fast, reliable and low cost user-developed protocol for detection, quantification and genotyping of hepatitis C virus

Heterozygous nonsense variants in the ferritin heavy-chain gene FTH1 cause a neuroferritinopathy

Ferritin, the iron-storage protein, is composed of light- and heavy-chain subunits, encoded by FTL and FTH1, respectively. Heterozygous variants in FTL cause hereditary neuroferritinopathy, a type of neurodegeneration with brain iron accumulation (NBIA). Variants in FTH1 have not been previously associated with neurologic disease. We describe the clinical, neuroimaging, and neuropathology findings of five unrelated pediatric patients with de novo heterozygous FTH1 variants. Children presented with developmental delay, epilepsy, and progressive neurologic decline. Nonsense FTH1 variants were identified using whole-exome sequencing, with a recurrent variant (p.Phe171∗) identified in four unrelated individuals. Neuroimaging revealed diffuse volume loss, features of pontocerebellar hypoplasia, and iron accumulation in the basal ganglia. Neuropathology demonstrated widespread ferritin inclusions in the brain. Patient-derived fibroblasts were assayed for ferritin expression, susceptibility to iron accumulation, and oxidative stress. Variant FTH1 mRNA transcripts escape nonsense-mediated decay (NMD), and fibroblasts show elevated ferritin protein levels, markers of oxidative stress, and increased susceptibility to iron accumulation. C-terminal variants in FTH1 truncate ferritin's E helix, altering the 4-fold symmetric pores of the heteropolymer, and likely diminish iron-storage capacity. FTH1 pathogenic variants appear to act by a dominant, toxic gain-of-function mechanism. The data support the conclusion that truncating variants in the last exon of FTH1 cause a disorder in the spectrum of NBIA. Targeted knockdown of mutant FTH1 transcript with antisense oligonucleotides rescues cellular phenotypes and suggests a potential therapeutic strategy for this pediatric neurodegenerative disorder.

Heterozygous Nonsense Variants in the Ferritin Heavy Chain Gene FTH1 Cause a Novel Pediatric Neuroferritinopathy

Ferritin, the iron storage protein, is composed of light and heavy chain subunits, encoded by FTL and FTH1 , respectively. Heterozygous variants in FTL cause hereditary neuroferritinopathy, a type of neurodegeneration with brain iron accumulation (NBIA). Variants in FTH1 have not been previously associated with neurologic disease. We describe the clinical, neuroimaging, and neuropathology findings of five unrelated pediatric patients with de novo heterozygous FTH1 variants. Children presented with developmental delay, epilepsy, and progressive neurologic decline. Nonsense FTH1 variants were identified using whole exome sequencing, with a recurrent de novo variant (p.F171*) identified in three unrelated individuals. Neuroimaging revealed diffuse volume loss, features of pontocerebellar hypoplasia and iron accumulation in the basal ganglia. Neuropathology demonstrated widespread ferritin inclusions in the brain. Patient-derived fibroblasts were assayed for ferritin expression, susceptibility to iron accumulation, and oxidative stress. Variant FTH1 mRNA transcripts escape nonsense-mediated decay (NMD), and fibroblasts show elevated ferritin protein levels, markers of oxidative stress, and increased susceptibility to iron accumulation. C-terminus variants in FTH1 truncate ferritin's E-helix, altering the four-fold symmetric pores of the heteropolymer and likely diminish iron-storage capacity. FTH1 pathogenic variants appear to act by a dominant, toxic gain-of-function mechanism. The data support the conclusion that truncating variants in the last exon of FTH1 cause a novel disorder in the spectrum of NBIA. Targeted knock-down of mutant FTH1 transcript with antisense oligonucleotides rescues cellular phenotypes and suggests a potential therapeutic strategy for this novel pediatric neurodegenerative disorder.

Technical Validation of a Hepatitis C Virus Whole Genome Sequencing Assay for Detection of Genotype and Antiviral Resistance in the Clinical Pathway

Choice of direct acting antiviral (DAA) therapy for Hepatitis C Virus (HCV) in the United Kingdom and similar settings usually requires knowledge of the genotype and, in some cases, antiviral resistance (AVR) profile of the infecting virus. To determine these, most laboratories currently use Sanger technology, but next-generation sequencing (NGS) offers potential advantages in throughput and accuracy. However, NGS poses unique technical challenges, which require idiosyncratic development and technical validation approaches. This applies particularly to virology, where sequence diversity is high and the amount of starting genetic material is low, making it difficult to distinguish real data from artifacts. We describe the development and technical validation of a sequence capture-based HCV whole genome sequencing (WGS) assay to determine viral genotype and AVR profile. We use clinical samples of known subtypes and viral loads, and simulated FASTQ datasets to validate the analytical performances of both the wet laboratory and bioinformatic pipeline procedures. We show high concordance of the WGS assay compared to current "gold standard" Sanger assays. Specificity was 92.3 and 96.1% for AVR and genotyping, respectively. Discordances were due to the inability of Sanger assays to assign the correct subtype or accurately call mixed drug-resistant variants. We show high repeatability and reproducibility with >99.8% sequence similarity between sequence runs as well as high precision for variant frequency detection at >98.8% in the 95th percentile. Post-sequencing bioinformatics quality control workflows allow the accurate distinction between mixed infections, cross-contaminants and recombinant viruses at a threshold of >5% for the minority population. The sequence capture-based HCV WGS assay is more accurate than legacy AVR and genotyping assays. The assay has now been implemented in the clinical pathway of England's National Health Service HCV treatment programs, representing the first validated HCV WGS pipeline in clinical service. The data generated will additionally provide granular national-level genomic information for public health policy making and support the WHO HCV elimination strategy.

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.

A systematic, deep sequencing-based methodology for identification of mixed-genotype hepatitis C virus infections

Hepatitis C virus (HCV) mixed genotype infections can affect treatment outcomes and may have implications for vaccine design and disease progression. Previous studies demonstrate 0-39% of high-risk, HCV-infected individuals harbor mixed genotypes however standardized, sensitive methods of detection are lacking. This study compared PCR amplicon, random primer (RP), and probe enrichment (PE)-based deep sequencing methods coupled with a custom sequence analysis pipeline to detect multiple HCV genotypes. Mixed infection cutoff values, based on HCV read depth and coverage, were identified using receiver operating characteristic curve analysis. The methodology was validated using artificially mixed genotype samples and then applied to two clinical trials of HCV treatment in high-risk individuals (ACTIVATE, 114 samples from 90 individuals; DARE-C II, 26 samples from 18 individuals) and a cohort of HIV/HCV co-infected individuals (Canadian Coinfection Cohort (CCC), 3 samples from 2 individuals with suspected mixed genotype infections). Amplification bias of genotype (G)1b, G2, G3 and G5 was observed in artificially mixed samples using the PCR method while no genotype bias was observed using RP and PE. RP and PE sequencing of 140 ACTIVATE and DARE-C II samples identified the following primary genotypes: 15% (n = 21) G1a, 76% (n = 106) G3, and 9% (n = 13) G2. Sequencing of ACTIVATE and DARE-C II demonstrated, on average, 2% and 1% of HCV reads mapping to a second genotype using RP and PE, respectively, however none passed the mixed infection cutoff criteria and phylogenetics confirmed no mixed infections. From CCC, one mixed infection was confirmed while the other was determined to be a recombinant genotype. This study underlines the risk for false identification of mixed HCV infections and stresses the need for standardized methods to improve prevalence estimates and to understand the impact of mixed infections for management and elimination of HCV.

Development of a Real-Time Reverse Transcription-PCR Assay for Global Differentiation of Yellow Fever Virus Vaccine-Related Adverse Events from Natural Infections

Yellow fever (YF) is a reemerging public health threat, with frequent outbreaks prompting large vaccination campaigns in regions of endemicity in Africa and South America. Specific detection of vaccine-related adverse events is resource-intensive, time-consuming, and difficult to achieve during an outbreak. To address this, we have developed a highly transferable rapid yellow fever virus (YFV) vaccine-specific real-time reverse transcription-PCR (RT-PCR) assay that distinguishes vaccine from wild-type lineages. The assay utilizes a specific hydrolysis probe that includes locked nucleic acids to enhance specific discrimination of the YFV17D vaccine strain genome. Promisingly, sensitivity and specificity analyses reveal this assay to be highly specific to vaccine strain(s) when tested on clinical samples and YFV cell culture isolates of global origin. Taken together, our data suggest the utility of this assay for use in laboratories of varied capacity for the identification and differentiation of vaccine-related adverse events from wild-type infections of both African and South American origin.

Efficient and unbiased metagenomic recovery of RNA virus genomes from human plasma samples

RNA viruses cause significant human pathology and are responsible for the majority of emerging zoonoses. Mainstream diagnostic assays are challenged by their intrinsic diversity, leading to false negatives and incomplete characterisation. New sequencing techniques are expanding our ability to agnostically interrogate nucleic acids within diverse sample types, but in the clinical setting are limited by overwhelming host material and ultra-low target frequency. Through selective host RNA depletion and compensatory protocol adjustments for ultra-low RNA inputs, we are able to detect three major blood-borne RNA viruses – HIV, HCV and HEV. We recovered complete genomes and up to 43% of the genome from samples with viral loads of 10⁴ and 10³ IU/ml respectively. Additionally, we demonstrated the utility of this method in detecting and characterising members of diverse RNA virus families within a human plasma background, some present at very low levels. By applying this method to a patient sample series, we have simultaneously determined the full genome of both a novel subtype of HCV genotype 6, and a co-infecting human pegivirus. This method builds upon earlier RNA metagenomic techniques and can play an important role in the surveillance and diagnostics of blood-borne viruses.

Development and validation of a real-time, reverse transcription PCR assay for rapid and low-cost genotyping of hepatitis C virus genotypes 1a, 1b, 2, and 3a

Hepatitis C virus (HCV) infection affects millions of people and leads to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Treatment regimen selection requires HCV genotype (Gt) and Gt 1 subtype determination. Use of a laboratory developed, reverse transcription (RT)-PCR assay was explored as a low-cost, high-throughput screening approach for the major HCV genotypes and subtypes in North America. A commercial line probe assay (LiPA) was used for comparison. Sequencing and/or an alternative PCR assay were used for discordant analyses. Testing of 155 clinical samples revealed that a paired, duplex real-time RT-PCR assay that targets Gts 1a and 3a in one reaction and Gts 1b and 2 in another had 95% overall sensitivity and individual Gt sensitivity and specificity of 98-100% and 85-98%, respectively. The RT-PCR assay detected mixed HCV Gts in clinical and spiked samples and no false-positive reactions occurred with rare Gts 3b, 4, 5, or 6. Implementation of the RT-PCR assay, with some reflex LiPA testing, would cost only a small portion of the cost of using LiPA alone, and can also save 1.5h of hands-on time. The use of a laboratory developed RT-PCR assay for HCV genotyping has the potential to reduce cost and labour burdens in high-volume testing settings.

Evaluation of sequencing of HCV core/E1, NS5A and NS5B as a genotype predictive tool in comparison with commercial assays targeting 5'UTR

BACKGROUND

Hepatitis C virus (HCV) genotyping is required for tailoring the dose and duration of antiviral therapy, predicting virological response rates, and selecting future treatment options.

OBJECTIVE

To establish whether baseline genotypes, performed by INNO-LiPA Version 1.0 (v1.0), before 2008, were valid for making treatment decisions now or whether genotypic determination should be repeated. Furthermore, to evaluate concordance between Abbott RealTime genotype II assay (RT) and genotyping by sequencing HCV C/E1, NS5A, NS5B.

STUDY DESIGN

Genotyping by RT and sequencing was performed on paired historic and current specimens from 50 patients previously baseline genotyped using INNO-LiPA.

RESULTS

Of 100 samples from 50 patients, ≥ 2 of HCV genomic target regions yielded a sequence that was suitable for genotyping, with 100% concordance, providing no evidence of recombination events. Genotype and subtype prediction based on RT and sequencing agreed in 62.8% historic and 72.7% current specimens, with a kappa coefficient score of 0.48 and 0.76, respectively. LiPA could not subtype 46% of HCV gt1 infections, and LiPA subgenotype was only in agreement with RT and sequencing in 28.6% cases, where matched baseline and historic specimens were available. Three patients were indeterminate by RT, and five patients with HCV gt1 infections could not be subtyped by RT. However, RT revealed mixed infections in five patients where sequencing detected only single HCV infection at 20% threshold.

CONCLUSION

Genotyping by sequencing, exhibited excellent concordance, with moderate to good agreement with RT, and could resolve RT indeterminates and subtype HCV-gt1 infections not possible by LiPA.