Affordable next-generation sequencing (NGS) technologies for hepatitis C virus (HCV) may potentially identify both viral genotype and resistance genetic motifs in the era of directly acting antiviral (DAA) therapies. This study compared the ability of high-throughput NGS methods to generate full-length, deep, HCV sequence data sets and evaluated their utility for diagnostics and clinical assessment. NGS methods using (i) unselected HCV RNA (metagenomics), (ii) preenrichment of HCV RNA by probe capture, and (iii) HCV preamplification by PCR implemented in four United Kingdom centers were compared. Metrics of sequence coverage and depth, quasispecies diversity, and detection of DAA resistance-associated variants (RAVs), mixed HCV genotypes, and other coinfections were compared using a panel of samples with different viral loads, genotypes, and mixed HCV genotypes/subtypes [geno(sub)types]. Each NGS method generated near-complete genome sequences from more than 90% of samples. Enrichment methods and PCR preamplification generated greater sequence depth and were more effective for samples with low viral loads. All NGS methodologies accurately identified mixed HCV genotype infections. Consensus sequences generated by different NGS methods were generally concordant, and majority RAVs were consistently detected. However, methods differed in their ability to detect minor populations of RAVs. Metagenomic methods identified human pegivirus coinfections. NGS provided a rapid, inexpensive method for generating whole HCV genomes to define infecting genotypes, RAVs, comprehensive viral strain analysis, and quasispecies diversity. Enrichment methods are particularly suited for high-throughput analysis while providing the genotype and information on potential DAA resistance.

There are few data on the persistence of individual human immunodeficiency virus type 1 (HIV-1) transmitted drug resistance (TDR) mutations in the absence of selective drug pressure. We studied 313 patients in whom TDR mutations were detected at their first resistance test and who had a subsequent test performed while ART-naive. The rate at which mutations became undetectable was estimated using exponential regression accounting for interval censoring. Most thymidine analogue mutations (TAMs) and T215 revertants (but not T215F/Y) were found to be highly stable, with NNRTI and PI mutations being relatively less persistent. Our estimates are important for informing HIV transmission models.

A large simultaneous outbreak of respiratory syncytial virus (RSV) and parainfluenza type 3 (PIV-3) infections occurred on an adult hematology unit. Implementation of enhanced infection control was complicated by cocirculation of the two different viruses, with prolonged viral shedding from infected patients, and placed great pressure on health care staff; of 27 infected hematopoietic stem cell transplant patients, 9 died, and the unit was closed for 2 months. Retrospective molecular investigation of the virus strains involved in the outbreak was performed by analyzing part of the fusion gene of PIV-3 and part of the glycoprotein gene of RSV. Reverse transcription-PCR on nasopharyngeal aspirates from patients infected before and during the simultaneous outbreak generated amplicons for sequence analysis. A single strain of RSV and a single strain of PIV-3 had spread from person to person within the unit; 7 patients were infected with RSV, 22 were infected with PIV-3, and 4 were infected with both viruses. The PIV-3 outbreak had started at the beginning of August 3 months before the RSV outbreak; it had arisen when PIV-3 was introduced from the community by a patient and passed to another patient, who became chronically infected with the identical strain and, in spite of being nursed in isolation, was most likely the source from which widespread infection occurred in November. Had these early cases been linked to a common PIV-3 strain at the time of diagnosis, enhanced infection control precautions might have prevented the eventual extensive spread of PIV-3, making it much easier to deal with the later RSV outbreak.

The polymerase chain reaction (PCR) is widely used as a diagnostic tool in clinical laboratories and is particularly effective for detecting and identifying infectious agents for which routine culture and microscopy methods are inadequate. Invasive fungal disease (IFD) is a major cause of morbidity and mortality in immunosuppressed patients, and optimal diagnostic criteria are contentious. Although PCR-based methods have long been used for the diagnosis of invasive aspergillosis (IA), variable performance in clinical practice has limited their value. This shortcoming is a consequence of differing sample selection, collection and preparation protocols coupled with a lack of standardisation of the PCR itself. Furthermore, it has become clear that the performance of PCR-based assays in general is compromised by the inadequacy of experimental controls, insufficient optimisation of assay performance as well as lack of transparency in reporting experimental details. The recently published “Minimum Information for the publication of real-time Quantitative PCR Experiments” (MIQE) guidelines provide a blueprint for good PCR assay design and unambiguous reporting of experimental detail and results. We report the first real-time quantitative PCR (qPCR) assay targeting Aspergillus species that has been designed, optimised and validated in strict compliance with the MIQE guidelines. The hydrolysis probe-based assay, designed to target the 18S rRNA DNA sequence of Aspergillus species, has an efficiency of 100% (range 95–107%), a dynamic range of at least six orders of magnitude and limits of quantification and detection of 6 and 0.6 Aspergillus fumigatus genomes, respectively. It does not amplify Candida, Scedosporium, Fusarium or Rhizopus species and its clinical sensitivity is demonstrated in histological material from proven IA cases, as well as concordant PCR and galactomannan data in matched broncho-alveolar lavage and blood samples. The robustness, specificity and sensitivity of this assay make it an ideal molecular diagnostic tool for clinical use.

Next-generation sequencing (NGS) is increasingly used for HIV-1 drug resistance genotyping. NGS methods have the potential for a more sensitive detection of low-abundance variants (LAV) compared to standard Sanger sequencing (SS) methods. A standardized threshold for reporting LAV that generates data comparable to those derived from SS is needed to allow for the comparability of data from laboratories using NGS and SS. Ten HIV-1 specimens were tested in ten laboratories using Illumina MiSeq-based methods. The consensus sequences for each specimen using LAV thresholds of 5%, 10%, 15%, and 20% were compared to each other and to the consensus of the SS sequences (protease 4–99; reverse transcriptase 38–247). The concordance among laboratories’ sequences at different thresholds was evaluated by pairwise sequence comparisons. NGS sequences generated using the 20% threshold were the most similar to the SS consensus (average 99.6% identity, range 96.1–100%), compared to 15% (99.4%, 88.5–100%), 10% (99.2%, 87.4–100%), or 5% (98.5%, 86.4–100%). The average sequence identity between laboratories using thresholds of 20%, 15%, 10%, and 5% was 99.1%, 98.7%, 98.3%, and 97.3%, respectively. Using the 20% threshold, we observed an excellent agreement between NGS and SS, but significant differences at lower thresholds. Understanding how variation in NGS methods influences sequence quality is essential for NGS-based HIV-1 drug resistance genotyping.

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.