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.

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HIV-1 RNA quantitation continues to be extremely important for monitoring patients infected with HIV-1, and a number of assays have been utilized for this purpose. Differences in assay performance with respect to log ₁₀ recovery and HIV-1 subtype specificity have been well documented for commercially available assays, although comparisons are usually limited to one or two assay platforms. Two new FDA-approved assays, the Roche Cobas AmpliPrep/Cobas TaqMan HIV-1 test (RT) and the Abbott RealTime HIV-1 assay (AR), that utilize real-time PCR have replaced previous HIV-1 RNA platforms. Inadequate detection of some strains of HIV-1 resulted in the addition of a new primer/probe set and the introduction of a second version of the RT assay. In this study, comparisons of assay performance between the different FDA-approved HIV-1 RNA assay platforms (both new and existing) were performed by using validation data that included both well-characterized virus stock and locally collected clinical samples. Laboratories across diverse geographical regions performed the validation testing and submitted data to the Virology Quality Assurance program (VQA) for analysis. Correlation values for clinical sample testing varied across the assay platforms ( r = 0.832 to 0.986), and average log ₁₀ recoveries for HIV-1 RNA controls (compared to the nominal value) ranged from −0.215 to 0.181. These data demonstrate the need for use of one assay platform for longitudinal patient monitoring, but the data also reinforce the notion that no one assay is superior and that testing across platforms may be required for discordance reconciliation.

Recurrence of symptoms after finishing treatment for COVID-19 with nirmatrelvir-ritonavir (Paxlovid) has become increasingly recognized.^1-3 The biological underpinning of this phenomenon is unclear, and its etiology may be multifactorial, including rapid clearance of nirmatrelvir coupled with delayed immune responses or possible development of drug resistance.^1-3 The contribution of treatment to symptom rebound needs to be differentiated from symptom rebound that might occur during the natural history of COVID-19. In this cohort study, we sought to determine how often COVID-19 symptoms recurred when the disease was untreated.

Next-generation sequencing (NGS) is likely to become the new standard method for HIV drug resistance (HIVDR) genotyping. Despite the significant advances in the development of wet-lab protocols and bioinformatic data processing pipelines, one often-missing critical component of an NGS HIVDR assay for clinical use is external quality assessment (EQA). EQA is essential for ensuring assay consistency and laboratory competency in performing routine biomedical assays, and the rollout of NGS HIVDR tests in clinical practice will require an EQA. In September 2019, the 2^nd International Symposium on NGS HIVDR was held in Winnipeg, Canada. It convened a multidisciplinary panel of experts, including research scientists, clinicians, bioinformaticians, laboratory biologists, biostatisticians, and EQA experts. A themed discussion was conducted on EQA strategies towards such assays during the symposium. This article describes the logistical challenges identified and summarizes the opinions and recommendations derived from these discussions, which may inform the development of an inaugural EQA program for NGS HIVDR in the near future.

The National Institute of Allergy and Infectious Diseases (NIAID) Virology Quality Assurance (VQA) established a robust proficiency testing program for Sanger sequencing (SS)-based HIV-1 drug resistance (HIVDR) testing in 2001. While many of the lessons learned during the development of such programs may also apply to next generation sequencing (NGS)-based HIVDR assays, challenges remain for the ongoing evaluation of NGS-based testing. These challenges include a proper assessment of assay accuracy and the reproducibility of low abundance variant detection, intra- and inter-assay performance comparisons among laboratories using lab-defined tests, and different data analysis pipelines designed for NGS. In collaboration with the World Health Organization (WHO) Global HIVDR Laboratory Network and the Public Health Agency of Canada, the Rush VQA program distributed archived proficiency testing panels to ten laboratories to evaluate internally developed NGS assays. Consensus FASTA files were submitted using 5%, 10%, and 20% variant detection thresholds, and scored based on the same criteria used for SS. This small study showed that the SS External Quality Assurance (EQA) approach can be used as a transitional strategy for using NGS to generate SS-like data and for ongoing performance while using NGS data from the same quality control materials to further evaluate NGS assay performance.