Genotypic resistance testing in routine clinical care

The Evolving Role of Next Generation Sequencing in Pediatric Neurosurgery: a Call for Action for Research, Clinical Practice, and Optimization of Care

NGS (Next-Generation Sequencing) is one of the most promising technologies that have truly revolutionized many aspects of clinical practice in recent years. It has been and is increasingly applied in many disciplines of medicine; however, it appears that pediatric neurosurgery despite its great potential has not truly embraced this new technology and is hesitant to employ it in its routine practice and guidelines. In this review, we briefly summarized the developments that lead to the establishment of NGS technology, reviewed the current applications and potentials of NGS in the disorders treated by pediatric neurosurgeons, and lastly discuss the steps we need to take to better harness NGS in pediatric neurosurgery.

Cost analysis of implementing HIV drug resistance testing in Kenya: a case study of a service delivery site at a tertiary level hospital in Kenya

Background: HIV drug resistance (HIVDR) threatens progress achieved in response to the HIV epidemic. Understanding the costs of implementing HIVDR testing programs for patient management and surveillance in resource-limited settings is critical in optimizing resource allocation. Here, we estimate the unit cost of HIVDR testing and identify major cost drivers while documenting challenges and lessons learnt in implementation of HIVDR testing at a tertiary level hospital in Kenya. Methods: We employed a mixed costing approach to estimate the costs associated with performing a HIVDR test from the provider's perspective. Data collection involved a time and motion study of laboratory procedures and interviewing laboratory personnel and the management personnel. Cost analysis was based on estimated 1000 HIVDR tests per year. Data entry and analysis were done using Microsoft Excel and costs converted to US dollars (2019). Results: The estimated unit cost for a HIVDR test was $271.78 per test. The main cost drivers included capital ($102.42, 37.68%) and reagents (101.50, 37.35%). Other costs included: personnel ($46.81, 17.22%), utilities ($14.69, 5.41%), equipment maintenance costs ($2.37, 0.87%) and quality assurance program ($4, 1.47%). Costs in relation to specific laboratory processes were as follows: sample collection ($2.41, 0.89%), RNA extraction ($22.79, 8.38%), amplification ($56.14, 20.66%), gel electrophoresis ($10.34, 3.80%), sequencing ($160.94, 59.22%), and sequence analysis ($19.16, 7.05%). A user-initiated modification of halving reagent volumes for some laboratory processes (amplification and sequencing) reduced the unit cost for a HIVDR test to $233.81 (13.97%) reduction.  Conclusions: Capital expenditure and reagents remain the most expensive components of HIVDR testing. This cost is bound to change as the sequencing platform is utilized towards maximum capacity or leveraged for use with other tests. Cost saving in offering HIVDR testing services is also possible through reagent volume reduction without compromising on the quality of test results.

Trends in HIV-1 Drug Resistance Mutations from a U.S. Reference Laboratory from 2006 to 2017

Trends in resistance to antiretroviral drugs for HIV-1 may inform clinical support and drug development. We evaluated drug resistance mutation (DRM) trends for nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI), protease inhibitor (PI), and integrase strand transfer inhibitor (INSTI) in a large U.S. reference laboratory database. DRMs with a Stanford HIV Drug Resistance Database mutation score ≥10 from deidentified subtype B NRTI/NNRTI/PI specimens (2006-2017; >10,000/year) and INSTI specimens (2010-2017; >1,000/year) were evaluated. Sequences with NRTI, NNRTI, or PI single- or multiclass DRMs declined from 48.9% to 39.3%. High-level dual- and triple-class resistance declined from 43.3% (2006) to 17.1% (2017), while sequences with only single-class DRMs increased from 40.0% to 52.9%. The prevalence of DRMs associated with earlier treatment regimens declined, while prevalence of some DRMs associated with newer regimens increased. M184V/I decreased from 48.3% to 29.4%. K103N/S/T declined from 42.5% in 2012 to 36.4% in 2017. Rilpivirine and etravirine DRMs E138A/Q/R and E138K increased from 4.9% and 0.4% to 9.7% and 1.7%, respectively. Sequences with ≥1 darunavir DRM declined from 18.1% to 4.8% by 2017. INSTI DRM Q148H/K/R declined from 39.3% (2010) to 13.8% (2017). Prevalence of elvitegravir-associated DRMs T66A/I/K, E92Q, S147G, and the dolutegravir-associated DRM R263K increased. For a subset of patients with serial testing, 50% (2,646/5,290) of those who initially had no reportable DRM subsequently developed ≥1 DRM for NRTI/NNRTI/PI and 49.7% (159/320) for INSTI. These trends may inform the need for baseline genotypic resistance testing. The detection of treatment-emergent DRMs in serially tested patients confirms the value of genotypic testing following virologic failure.

Characterization of minority HIV-1 drug resistant variants in the United Kingdom following the verification of a deep sequencing-based HIV-1 genotyping and tropism assay

BACKGROUND

The widespread global access to antiretroviral drugs has led to considerable reductions in morbidity and mortality but, unfortunately, the risk of virologic failure increases with the emergence, and potential transmission, of drug resistant viruses. Detecting and quantifying HIV-1 drug resistance has therefore become the standard of care when designing new antiretroviral regimens. The sensitivity of Sanger sequencing-based HIV-1 genotypic assays is limited by its inability to identify minority members of the quasispecies, i.e., it only detects variants present above ~ 20% of the viral population, thus, failing to detect minority variants below this threshold. It is clear that deep sequencing-based HIV-1 genotyping assays are an important step change towards accurately monitoring HIV-infected individuals.

METHODS

We implemented and verified a clinically validated HIV-1 genotyping assay based on deep sequencing (DEEPGEN™) in two clinical laboratories in the United Kingdom: St. George's University Hospitals Healthcare NHS Foundation Trust (London) and at NHS Lothian (Edinburgh), to characterize minority HIV-1 variants in 109 plasma samples from ART-naïve or -experienced individuals.

RESULTS

Although subtype B HIV-1 strains were highly prevalent (44%, 48/109), most individuals were infected with non-B subtype viruses (i.e., A1, A2, C, D, F1, G, CRF02_AG, and CRF01_AE). DEEPGEN™ was able to accurately detect drug resistance-associated mutations not identified using standard Sanger sequencing-based tests, which correlated significantly with patient's antiretroviral treatment histories. A higher proportion of minority PI-, NRTI-, and NNRTI-resistance mutations was detected in NHS Lothian patients compared to individuals from St. George's, mainly M46I/L and I50 V (associated with PIs), D67 N, K65R, L74I, M184 V/I, and K219Q (NRTIs), and L100I (NNRTIs). Interestingly, we observed an inverse correlation between intra-patient HIV-1 diversity and CD4⁺ T cell counts in the NHS Lothian patients.

CONCLUSIONS

This is the first study evaluating the transition, training, and implementation of DEEPGEN™ between three clinical laboratories in two different countries. More importantly, we were able to characterize the HIV-1 drug resistance profile (including minority variants), coreceptor tropism, subtyping, and intra-patient viral diversity in patients from the United Kingdom, providing a rigorous foundation for basing clinical decisions on highly sensitive and cost-effective deep sequencing-based HIV-1 genotyping assays in the country.

HIV Drug Resistance Mutations (DRMs) Detected by Deep Sequencing in Virologic Failure Subjects on Therapy from Hunan Province, China

Objective

Determine HIV drug resistance mutations (DRMs) prevalence at low and high levels in ART-experienced patients experiencing virologic failure (VF).

Methods

29 subjects from 18 counties in Hunan Province that experienced VF were evaluated for the prevalence of DRMs (Stanford DRMs with an algorithm value ≥15, include low-, intermediate and high-level resistance) by both Sanger sequencing (SS) and deep sequencing (DS) to 1% frequency levels.

Results

DS was performed on samples from 29 ART-experienced subjects; the median viral load 4.95×10⁴ c/ml; 82.76% subtype CRF01_AE. 58 DRMs were detected by DS. 18 DRMs were detected by SS. Of the 58 mutations detected by DS, 40 were at levels <20% frequency (26 NNRTI, 12 NRTI and 2 PI) and the majority of these 95.00% (38/40) were not detected by standard genotyping. Of these 40 low-level DRMs, 16 (40%) were detected at frequency levels of 1–4% and 24 (60%) at levels of 5–19%. SS detected 15 of 17 (88.24%) DRMs at levels ≥ 20% that were detected by DS. The only variable associated with the detection of DRMs by DS was ART adherence (missed doses in the prior 7 days); all patients that reported missing a dose in the last 7 days had DRMs detected by DS.

Conclusions

DS of VF samples from treatment experienced subjects infected with primarily AE subtype frequently identified Stanford HIVdb NRTI and NNRTI resistance mutations with an algorithm value 15. Low frequency level resistant variants detected by DS were frequently missed by standard genotyping in VF specimens from antiretroviral-experienced subjects.

More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1

In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistance mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here, we use 6717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.

DOI:http://dx.doi.org/10.7554/eLife.10670.001

In the early days of HIV therapy, the strains of the virus that infected patients frequently evolved drug resistance and the therapies would often eventually fail. These treatments generally involved using a single anti-viral drug. Nowadays, better therapies involving combinations of several anti-viral drugs are available and drug resistance in HIV is a much rarer occurrence. This means that now a particular therapy may be an effective treatment for an HIV-infected individual over much longer periods of time.

A theory of population genetics predicts that when it is easy for a population to acquire a beneficial genetic mutation – like one that provides drug resistance – multiple versions of that mutation may spread in the population at the same time. This is called a soft selective sweep. However, when beneficial mutations occur only rarely, it is expected that only one version of that mutation will take over in a population, which is known as a hard selective sweep.

Here, Feder et al. test this theory using data from 6717 patients with HIV who were treated between 1989 and 2013 using a variety of different drug therapies. The experiments aimed to find out whether the transition from the older drug therapies –where the virus frequently acquired resistance – to the newer, more effective drugs was associated with a transition from soft to hard sweeps.

Feder et al. find that HIV more often evolved drug resistance via soft sweeps in patients treated with the less effective drug combinations (like those given in the early days of HIV treatment), while hard sweeps were more common with the more effective drug combinations. This suggests that good drug combinations may allow fewer drug resistance mutations to occur in the HIV population within a patient. This may be because there are fewer virus particles in these patients, or because the specific combinations of mutations that provide resistance occur less often. Feder et al.’s findings are a step towards understanding why modern HIV treatments work so well, which will ultimately help us find better treatments for other infectious diseases.

DOI:http://dx.doi.org/10.7554/eLife.10670.002

Incidence and predictors of antiretroviral resistance in perinatally HIV-1 infected children and adolescents

OBJECTIVES

Individuals with perinatally acquired HIV infection have benefited from antiretroviral therapy. However, they often have complex patterns of major resistance mutations that limit the effectiveness of available antiretroviral medications. Knowledge of incidence rates of major antiretroviral resistance mutations should provide a benchmark enabling comparisons of different HIV care delivery modalities.

METHODS

We test the hypothesis that incidence rate of major antiretroviral resistance mutations will decline with improvement in HIV care between 1998 and 2009 to NRTI, NNRTI, PI and triple class resistance in perinatally HIV infected individuals. Logistic regression is used to evaluate predictors of single and triple class resistance.

RESULTS

Sixty-six individuals are included from a total population of 97 perinatally HIV infected individuals. The incidence rate of NRTI, NNRTI, PI and triple class resistance decreases with decreasing age in parallel with the introduction of new HIV treatment regimens. The youngest children (born 2000-2007) are free of triple class resistance. Mono-therapy associates with major resistance mutations to NRTI (OR 8.7, CI 1.5-50.9, P 0.02); NNRTI exposure associates with major resistance mutations to NNRTI (OR 24.4, CI 5.7-104.5, P 0.01) and triple class resistance (OR 10.7, CI 1.8-67.1, P 0.01). Cumulative viral load is an important predictor of PI resistance (OR 4.0, CI 1.3-12.3, P 0.02).

CONCLUSIONS

There is a progressive decrease in the incidence rate of major resistance mutations to antiretroviral drugs and triple class resistance from the oldest to the youngest birth cohort; where adolescents have the highest risk of harboring resistant viruses. The incidence rate of major antiretroviral resistance mutations provides a benchmark for the comparative measurement of effectiveness of different HIV care delivery modalities.

Next-Generation Sequencing for Infectious Disease Diagnosis and Management: A Report of the Association for Molecular Pathology

Next-generation sequencing (NGS) technologies are increasingly being used for diagnosis and monitoring of infectious diseases. Herein, we review the application of NGS in clinical microbiology, focusing on genotypic resistance testing, direct detection of unknown disease-associated pathogens in clinical specimens, investigation of microbial population diversity in the human host, and strain typing. We have organized the review into three main sections: i) applications in clinical virology, ii) applications in clinical bacteriology, mycobacteriology, and mycology, and iii) validation, quality control, and maintenance of proficiency. Although NGS holds enormous promise for clinical infectious disease testing, many challenges remain, including automation, standardizing technical protocols and bioinformatics pipelines, improving reference databases, establishing proficiency testing and quality control measures, and reducing cost and turnaround time, all of which would be necessary for widespread adoption of NGS in clinical microbiology laboratories.

Japanese external quality assessment program to standardize HIV-1 drug-resistance testing (JEQS2010 program) using in vitro transcribed RNA as reference material

To design appropriate antiretroviral therapy regimens and avoid the emergence of human immunodeficiency virus (HIV)-1 variants with reduced susceptibility to antiretroviral drugs, genotypic drug-resistance testing (HIV genotyping) is strongly recommended. To monitor the quality of HIV genotyping in Japan, we performed an external quality assessment (EQA), named the Japanese external quality assessment program, to standardize HIV genotyping (JEQS). To accurately evaluate the quality of HIV genotyping, we employed as reference material (RM) a well-characterized sample, in vitro transcribed RNA (trRNA) that includes the HIV gag-pol sequence, and created a JEQS2010 panel consisting of three single variant and three mixed trRNA samples. All 11 participating laboratories showed high concordance rates (>96%) for the single variant samples. Eight laboratories also showed good rates of detecting minor variants, but three laboratories failed to detect the variants comprising one-half of the sample. These three laboratories used a common primer that had four internal mismatches to the minor trRNA clone. This program showed the usefulness of trRNA as RM, the high quality of HIV genotyping, and extensive interlaboratory variation in the ability to detect minor variants. These results suggest that improving the quality of HIV genotyping in Japan requires regularly implementing the EQA program and improving the HIV genotyping protocol in each laboratory.

Minority resistant HIV-1 variants and the response to first-line NNRTI therapy

BACKGROUND

The presence of low-frequency HIV-1 variants with mutations making them resistant to non-nucleoside reverse-transcriptase inhibitors (NNRTI) could influence the virological response to first-line NNRTI therapy.

OBJECTIVES

This study was designed to describe the proportions and quantities of NRTI and NNRTI-resistant variants in patients with successful first-line NNRTI therapy.

STUDY DESIGN

We evaluated the presence of drug-resistance mutations (DRMs) prior to treatment initiation in 131 naive chronically HIV-1-infected patients initiating NNRTI-based first-line therapy. DRMs were detected by ultradeep pyrosequencing (UDPS) on a GS Junior instrument (Roche).

RESULTS

The mean HIV RNA concentration was 4.78 ± 0.74 log copies/mL and the mean CD4 cell count was 368 ± 184 CD4 cells/mm(3). Patients were mainly infected with subtype B (68%) and 96% were treated with efavirenz. The sensitivity threshold for each mutation was 0.13-1.05% for 2000 reads. Major NRTI-resistant or NNRTI-resistant mutations were detected in 40 patients (33.6%). The median frequency of major NRTI-resistant mutations was 1.37% [IQR: 0.39-84.1], i.e.: a median of 556 copies/mL [IQR: 123-37,553]. The median frequency of major NNRTI-resistant DRMs was 0.78% [IQR: 0.67-7.06], i.e.: a median of 715 copies/mL [IQR: 391-3452]. The genotypic susceptibility score (GSS) of 9 (7.3%) patients with mutations to given treatment detected by UDPS was 1.5 or 2.

CONCLUSIONS

First-line NNRTI-based treatment can produce virological success in naïve HIV-1-infected patients harboring low-frequency DRMs representing <1% of the viral quasispecies. Further studies are needed to determine the clinical cut-off of low-frequency resistant variants associated to virological failure.

Sensitive deep-sequencing-based HIV-1 genotyping assay to simultaneously determine susceptibility to protease, reverse transcriptase, integrase, and maturation inhibitors, as well as HIV-1 coreceptor tropism

With 29 individual antiretroviral drugs available from six classes that are approved for the treatment of HIV-1 infection, a combination of different phenotypic and genotypic tests is currently needed to monitor HIV-infected individuals. In this study, we developed a novel HIV-1 genotypic assay based on deep sequencing (DeepGen HIV) to simultaneously assess HIV-1 susceptibilities to all drugs targeting the three viral enzymes and to predict HIV-1 coreceptor tropism. Patient-derived gag-p2/NCp7/p1/p6/pol-PR/RT/IN- and env-C2V3 PCR products were sequenced using the Ion Torrent Personal Genome Machine. Reads spanning the 3' end of the Gag, protease (PR), reverse transcriptase (RT), integrase (IN), and V3 regions were extracted, truncated, translated, and assembled for genotype and HIV-1 coreceptor tropism determination. DeepGen HIV consistently detected both minority drug-resistant viruses and non-R5 HIV-1 variants from clinical specimens with viral loads of ≥1,000 copies/ml and from B and non-B subtypes. Additional mutations associated with resistance to PR, RT, and IN inhibitors, previously undetected by standard (Sanger) population sequencing, were reliably identified at frequencies as low as 1%. DeepGen HIV results correlated with phenotypic (original Trofile, 92%; enhanced-sensitivity Trofile assay [ESTA], 80%; TROCAI, 81%; and VeriTrop, 80%) and genotypic (population sequencing/Geno2Pheno with a 10% false-positive rate [FPR], 84%) HIV-1 tropism test results. DeepGen HIV (83%) and Trofile (85%) showed similar concordances with the clinical response following an 8-day course of maraviroc monotherapy (MCT). In summary, this novel all-inclusive HIV-1 genotypic and coreceptor tropism assay, based on deep sequencing of the PR, RT, IN, and V3 regions, permits simultaneous multiplex detection of low-level drug-resistant and/or non-R5 viruses in up to 96 clinical samples. This comprehensive test, the first of its class, will be instrumental in the development of new antiretroviral drugs and, more importantly, will aid in the treatment and management of HIV-infected individuals.

The prevalence of transmitted resistance to first-generation non-nucleoside reverse transcriptase inhibitors and its potential economic impact in HIV-infected patients

Non-nucleoside reverse transcriptase inhibitor (NNRTI)-based highly active antiretroviral therapy (HAART) including efavirenz is recommended as a 1^st-line treatment choice in international HIV guidelines, and it is one of the most common components of initial therapy. Resistance to 1^st-generation NNRTIs is found among treated and untreated HIV-infected individuals creating a subpopulation of HIV-infected individuals in whom efavirenz is not fully effective. This analysis reviewed published articles and conference abstracts to examine the prevalence of 1^st-generation NNRTI resistance in Europe, the United States (US), and Canada and to identify published evidence of the economic consequences of resistance. The reported prevalence of NNRTI resistance was generally higher in US/Canada than in Europe and increased in both regions from their introduction in the late 1990s until the early 2000s. The most recent time-based trends suggest that NNRTI-resistance prevalence may be stable or decreasing. These estimates of resistance may be understated as resistance estimates using ultra-sensitive genotypic testing methods, which identify low-frequency mutations undetected by standard testing methods, showed increased prevalence of resistance by more than two-fold. No studies were identified that explicitly investigated the costs of drug resistance. Rather, most studies reported costs of treatment change, failure, or disease progression. Among those studies, annual HIV medical costs of those infected with HIV increased 1) as CD4 cells decreased, driven in part by hospitalization at lower CD4 cell counts; 2) for treatment changes, and 3) for each virologic failure. The possible erosion of efficacy or of therapy choices through resistance transmission or selection, even when present with low frequency, may become a barrier to the use of 1^st-generation NNRTIs and the increased costs associated with regimen failure and disease progression underlie the importance of identification of treatment resistance to ensure optimal initial therapy choice and regimen succession.

Evaluation of a benchtop HIV ultradeep pyrosequencing drug resistance assay in the clinical laboratory

Detection of low-abundance drug resistance mutations (DRMs) of HIV-1 is an evolving approach in clinical practice. Ultradeep pyrosequencing has shown to be effective in detecting such mutations. The lack of a standardized commercially based assay limits the wide use of this method in clinical settings. 454 Life Sciences (Roche) is developing an HIV ultradeep pyrosequencing assay for their benchtop sequencer. We assessed the prototype plate in the clinical laboratory. Plasma samples genotyped by the standardized TruGene kit were retrospectively tested by this assay. Drug-treated subjects failing therapy and drug-naive patients were included. DRM analysis was based on the International AIDS Society USA DRM list and the Stanford algorithm. The prototype assay detected all of the DRMs detected by TruGene and additional 50 low-abundance DRMs. Several patients had low-abundance D67N, K70R, and M184V reverse transcriptase inhibitor mutations that persisted long after discontinuation of the drug that elicited these mutations. Additional patient harbored low-abundance V32I major protease inhibitor mutation, which under darunavir selection evolved later to be detected by TruGene. Stanford analysis suggested that some of the low-abundance DRMs were likely to affect the resistance burden in these subjects. The prototype assay performs at least as well as TruGene and has the advantage of detecting low-abundance drug resistance mutations undetected by TruGene. Its ease of use and lab-scale platform will likely facilitate its use in the clinical laboratory. The extent to which the detection of low-abundance DRMs will affect patient management is still unknown, but it is hoped that use of such an assay in clinical practice will help resolve this important question.

Low prevalence of transmitted HIV type 1 drug resistance among antiretroviral-naive adults in a rural HIV clinic in Kenya

Low levels of HIV-1 transmitted drug resistance (TDR) have previously been reported from many parts of sub-Saharan Africa (sSA). However, recent data, mostly from urban settings, suggest an increase in the prevalence of HIV-1 TDR. Our objective was to determine the prevalence of TDR mutations among HIV-1-infected, antiretroviral (ARV)-naive adults enrolling for care in a rural HIV clinic in Kenya. Two cross-sectional studies were carried out between July 2008 and June 2010. Plasma samples from ARV-naive adults (>15 years old) at the time of registering for care after HIV diagnosis and before starting ARVs were used. A portion of the pol subgenomic region of the virus containing the protease and part of the reverse transcriptase genes was amplified and sequenced. TDR mutations were identified and interpreted using the Stanford HIV drug resistance database and the WHO list for surveillance of drug resistance strains. Overall, samples from 182 ARV-naive adults [mean age (95% CI): 34.9 (33.3-36.4) years] were successfully amplified and sequenced. Two TDR mutations to nucleoside reverse transcriptase inhibitors [n=1 (T215D)] and protease inhibitors [n=1 (M46L)] were identified, giving an overall TDR prevalence of 1.1% (95% CI: 0.1-3.9). Despite reports of an increase in the prevalence of HIV-1 TDR in some urban settings in sSA, we report a prevalence of HIV-1 TDR of less than 5% at a rural HIV clinic in coastal Kenya. Continued broader surveillance is needed to monitor the extent of TDR in sSA.

Clinical Evaluation of an In-House Human Immunodeficiency Virus (HIV) Genotyping Assay for the Detection of Drug Resistance Mutations in HIV-1 Infected Patients in Singapore

Introduction: Human immunodeficiency virus type 1 (HIV-1) genotyping resistance test (GRT) is essential for monitoring HIV-1 drug resistance mutations (DRMs). High cost and HIV-1 genetic variability are challenges to assay availability in Singapore. An in-house Sanger sequencing-based GRT method was developed at the Communicable Disease Centre (CDC), Singapore’s HIV national treatment reference centre for both subtype B and non-subtype B HIV-1. Materials and Methods: The in-house GRT sequenced the first 99 codons of protease (PR) and 244 codons of reverse transcriptase (RT) in the pol gene. The results were compared with the Food and Drug Administration (FDA)-approved ViroSeqTM HIV-1 Genotyping System. Results: Subtype assignment for the 46 samples were as follows: 31 (67.4%) CRF01_AE, 14 (30.5%) subtype B and 1 (2.1%) subtype C. All 46 samples had viral load of ≥500 copies/mL, and were successfully amplified by the in-house primer sets. Compared to the ViroSeqTM test, our in-house assay showed drug-resistance conferring codon concordance of 99.9% at PR and 98.9% at RT, and partial concordance of 0.1% at PR and 1.1% at RT. No discordant result was observed. Conclusion: The assay successfully identifi ed DRMs in both subtype AE and B, making it suitable for the efficient treatment monitoring in genetically diverse population. At less than half of the running cost compared to the ViroSeqTM assay, the broadly sensitive in-house assay could serve as a useful addition to the currently limited HIV genotyping assay options for resource-limited settings, thereby enhancing the DRM surveillance and monitoring in the region. Key words: Drug resistance mutations, Genotypic resistance test, HIV-1

Past, present and future molecular diagnosis and characterization of human immunodeficiency virus infections

Substantive and significant advances have been made in the last two decades in the characterization of human immunodeficiency virus (HIV) infections using molecular techniques. These advances include the use of real-time measurements, isothermal amplification, the inclusion of internal quality assurance protocols, device miniaturization and the automation of specimen processing. The result has been a significant increase in the availability of results to a high level of accuracy and quality. Molecular assays are currently widely used for diagnostics, antiretroviral monitoring and drug resistance characterization in developed countries. Simple and cost-effective point-of-care versions are also being vigorously developed with the eventual goal of providing timely healthcare services to patients residing in remote areas and those in resource-constrained countries. In this review, we discuss the evolution of these molecular technologies, not only in the context of the virus, but also in the context of tests focused on human genomics and transcriptomics.