Use of next-generation sequencing to detect mutations associated with antiviral drug resistance in cytomegalovirus.

Cytomegalovirus (CMV) is a significant cause of morbidity and mortality among immunocompromised hosts, including transplant recipients. Antiviral prophylaxis or treatment is used to reduce the incidence of CMV disease in this patient population; however, there is concern about increasing antiviral resistance. Detection of antiviral resistance in CMV was traditionally accomplished using Sanger sequencing of UL54 and UL97 genes, in which specific mutations may result in reduced antiviral activity. In this study, a novel next-generation sequencing (NGS) method was developed and validated to detect mutations in UL54/UL97 associated with antiviral resistance. Plasma samples (n = 27) submitted for antiviral resistance testing by Sanger sequencing were also analyzed using the NGS method. When compared to Sanger sequencing, the NGS assay demonstrated 100% (27/27) overall agreement for determining antiviral resistance/susceptibility and 88% (22/25) agreement at the level of resistance-associated mutations. The limit of detection of the NGS method was determined to be 500 IU/mL, and the lower threshold for detecting mutations associated with resistance was established at 15%. The NGS assay represents a novel laboratory tool that assists healthcare providers in treating patients who are infected with CMV harboring resistance-associated mutations and who may benefit from tailored antiviral therapy.

Targeted-Sequencing Workflows for Comprehensive Drug Resistance Profiling of Mycobacterium tuberculosis Cultures Using Two Commercial Sequencing Platforms: Comparison of Analytical and Diagnostic Performance, Turnaround Time, and Cost.

BACKGROUND: The emergence of Mycobacterium tuberculosis with complex drug resistance profiles necessitates a rapid and comprehensive drug susceptibility test for guidance of patient treatment. We developed two targeted-sequencing workflows based on Illumina MiSeq and Nanopore MinION for the prediction of drug resistance in M. tuberculosis toward 12 antibiotics. METHODS: A total of 163 M. tuberculosis isolates collected from Hong Kong and Ethiopia were subjected to a multiplex PCR for simultaneous amplification of 19 drug resistance-associated genetic regions. The amplicons were then barcoded and sequenced in parallel on MiSeq and MinION in respective batch sizes of 24 and 12 samples. A web-based bioinformatics pipeline, BacterioChek-TB, was developed to translate the raw datasets into clinician-friendly reports. RESULTS: Both platforms successfully sequenced all samples with mean read depths of 1,127× and 1,649×, respectively. The variant calling by MiSeq and MinION could achieve 100% agreement if variants with an allele frequency of <40% reported by MinION were excluded. Both workflows achieved a mean clinical sensitivity of 94.8% and clinical specificity of 98.0% when compared with phenotypic drug susceptibility test (pDST). Turnaround times for the MiSeq and MinION workflows were 38 and 15 h, facilitating the delivery of treatment guidance at least 17-18 days earlier than pDST, respectively. The higher cost per sample on the MinION platform ($71.56) versus the MiSeq platform ($67.83) was attributed to differences in batching capabilities. CONCLUSION: Our study demonstrates the interchangeability of MiSeq and MinION platforms for generation of accurate and actionable results for the treatment of tuberculosis.

Clinical relevance of the HCV protease inhibitor-resistant mutant viral load assessed by ultra-deep pyrosequencing in treatment failure.

BACKGROUND: The detection of low frequency mutants in patients with hepatitis C virus (HCV) receiving direct-acting antivirals (DAAs) is still debated. The clinical relevance of the mutant viral load has not yet been evaluated. OBJECTIVES: To assess the viral load of resistance associated variants (RAVs) in patients at different time points, including the baseline, virological failure and one year after the cessation of therapy. STUDY DESIGN: The study included 22 patients who were previously treated with protease inhibitors (PI) (with telaprevir and boceprevir). For each patient, three time points were assessed using ultra-deep pyrosequencing (UDPS). RESULTS: Baseline mutations were observed in 14/22 patients (64%). At virological failure, RAVs were detected in 18/22 patients (82%). Persistent RAVs were observed in four HCV GT 1a patients (18%). Persistence mutations were found only in HCV GT 1a patients. The baseline relative V36M, R155K, R155T and A156T mutation load of patients with persistent RAVs was significantly higher (P<0.001) than those of patients without persistent RAVs. CONCLUSION: The UDPS follow-up analysis demonstrated that the presence of BOC or TLP-RAVs persist one year after therapy cessation only in HCV GT 1a patients. The relative mutant viral load should be considered prior to any PI based re-treatment. This concept of the baseline mutation viral load must be validated using current therapy and must be validated on a larger cohort.

Evaluation of GS Junior and MiSeq next-generation sequencing technologies as an alternative to Trugene population sequencing in the clinical HIV laboratory.

Population HIV-1 sequencing is currently the method of choice for the identification and follow-up of HIV-1 antiretroviral drug resistance. It has limited sensitivity and results in a consensus sequence showing the most prevalent nucleotide per position. Moreover concomitant sequencing and interpretation of the results for several samples together is laborious and time consuming. In this study, the practical use of GS Junior and MiSeq bench-top next generation sequencing (NGS) platforms as an alternative to Trugene Sanger-based population sequencing in the clinical HIV laboratory was assessed. DeepChek(®)-HIV TherapyEdge software was used for processing all the protease and reverse transcriptase sequences and for resistance interpretation. Plasma samples from nine HIV-1 carriers, representing the major HIV-1 subtypes in Israel, were compared. The total number of amino acid substitutions identified in the nine samples by GS Junior (232 substitutions) and MiSeq (243 substitutions) was similar and higher than Trugene (181 substitutions), emphasizing the advantage of deep sequencing on population sequencing. More than 80% of the identified substitutions were identical between the GS Junior and MiSeq platforms, most of which (184 of 199) at similar frequency. Low abundance substitutions accounted for 20.9% of the MiSeq and 21.9% of the GS Junior output, the majority of which were not detected by Trugene. More drug resistance mutations were identified by both the NGS platforms, primarily, but not only, at low abundance. In conclusion, in combination with DeepChek, both GS Junior and MiSeq were found to be more sensitive than Trugene and adequate for HIV-1 resistance analysis in the clinical HIV laboratory.

Use of deep sequencing data for routine analysis of HIV resistance in newly diagnosed patients.

INTRODUCTION: Use of deep sequencing is becoming a critical tool in clinical virology, with an important impact in the HIV field for routine diagnostic purposes. Here, we present the comparison of deep and Sanger sequencing in newly diagnosed HIV patients, and the use of DeepChek v1.3 & VisibleChek for their interpretation and integration with virological and clinical data. PATIENTS AND METHODS: Plasma samples from 88 newly diagnosed HIV-1-infected patients were included in the study. Median age (IQR) was 37 (27-47), median CD4 count (IQR) was 387 (220-554), and 85% were males. Median Viral Load (Log, IQR) was 5.03 (4.51-5.53). Deep sequencing was obtained using a GS-Junior (Roche). Sequences were preprocessed with the 454 AVA software; aligned reads were uploaded into the DeepChek v1.3 system (ABL SA). Sanger sequences (Trugene), were uploaded in parallel. Stanford algorithm (version 7.0) resistance interpretation to first line drugs and all the mutations (score≥5) were analyzed. For deep sequencing, 1%, 5% and 10% thresholds were chosen for resistance interpretation. RESULTS: Using VisibleChek for analysis, we were able to describe the detection of any mutation using Sanger in 37/88 patients, with a total number of 50 Stanford ≥5 mutations, K103N and E138A being the most prevalent (n=4). Using UDS-1%, we found 72/88 patients with at least one mutation (total of 206 Stanford ≥5 mutations). Using Sanger data, 9/88 patients (10.22%) showed any resistance to NNRTIs, while none showed resistance to NRTIs or PIs. Using UDS-10% increased resistance to NRTIs [3/88 (3.40%)], to NNRTIs 12/88 (13.63%), and to a lesser extent to PIs [1/88 (1.13%)]. Using UDS-5% increased resistance to NRTIs [4/88 (4.54%)] and to NNRTIs [12/88 (13.63%)], but not to PIs. Using UDS-1% increased resistance to all classes: NRTIs [14/88 (15.90%)], NNRTIs [26/88 (30.68%)], and PIs [6/88 (6.81]. CONCLUSIONS: DeepChek and VisibleChek allow for an easy, reliable and rapid analysis of UDS data from HIV-1. Compared to Sanger data, UDS detected a higher number of resistance mutations. UDS with a 5 &10% threshold resulted in an increase in the number of patients with any degree of resistance mainly to NRTI, NNRTIs. Going down as low as 1% increased resistance to all classes. A correct definition of clinically relevant thresholds for the interpretation of minor variant detection for different classes of ARVs is needed.

Comparison of HIV-1 drug resistance profiles generated from novel software applications for routine patient care.

INTRODUCTION: Clinical laboratories performing routine HIV-1 genotyping antiviral drug resistance (DR) testing need reliable and up-to-date information systems to provide accurate and timely test results to optimize antiretroviral treatment in HIV-1-infected patients. MATERIALS AND METHODS: Three software applications were used to compare DR profiles generated from the analysis of HIV-1 protease (PR) and reverse transcriptase (RT) gene sequences obtained by Sanger sequencing assay in 100 selected clinical plasma samples from March 2013 through May 2014. Interpretative results obtained from the Trugene HIV-1 Genotyping assay (TG; Guidelines v17.0) were compared with a newly FDA-registered data processing module (DPM v1.0) and the research-use-only ViroScore-HIV (VS) software, both of which use the latest versions of Stanford HIVdb (SD v7.0) and geno2pheno (G2P v3.3) interpretive algorithms (IA). Differences among the DR interpretive algorithms were compared according to drug class (NRTI, NNRTI, PI) and each drug. HIV-1 tropism and integrase inhibitor resistance were not evaluated (not available in TG). RESULTS: Overall, only 17 of the 100 TG sequences obtained yielded equivalent DR profiles among all 3 software applications for every IA and for all drug classes. DPM and VS generated equivalent results with >99.9% agreement. Excluding AZT, DDI, D4T and rilpivirine (not available in G2P), ranges of agreement in DR profiles among the three IA (using the DPM) are shown in Table 1. CONCLUSIONS: Substantial discrepancies (<75% agreement) exist among the three interpretive algorithms for ETR, while G2P differed from TG and SD for resistance to TDF and TPV/r. Use of more than one DR interpretive algorithm using well-validated software applications, such as DPM v1.0 and VS, would enable clinical laboratories to provide clinically useful and accurate DR results for patient care needs.

Analysis of transmitted HIV-1 drug resistance using 454 ultra-deep-sequencing and the DeepChek(®)-HIV system.

INTRODUCTION: Next-generation sequencing (NGS) is capable of detecting resistance-associated mutations (RAMs) present at frequencies of 1% or below. Several studies have found that baseline low-frequency RAMs are associated with failure to first-line HAART. One major limitation to the expansion of this technology in routine diagnostics is the complexity and laboriousness integral to bioinformatics analysis. DeepChek (ABL, TherapyEdge) is a CE-marked software that allows automated analysis and resistance interpretation of NGS data. OBJECTIVE: To evaluate the use of 454 ultra-deep-sequencing (Roche(®) 454, Life Sciences; 454-UDS) and DeepChek for routine baseline resistance testing in a clinical diagnostic laboratory. METHODS: 107 newly diagnosed HIV-1-infected patients (subtypes: A, n=9; B, n=52; C, n=21; D, n=2; F, n=3; G, n=1; CRF01, n=7; CRF02, n=7; CRF06, n=1; CRF07, n=1; CRF10, n=1 and unassigned complex, n=2) with a median plasma viral load of 88,727 copies/mL (range: 1380-2,143,543) were tested by 454-UDS and Sanger sequencing for the detection of protease and reverse transcriptase RAMs. In addition, integrase RAMs were investigated in 57 of them. Sequence analysis and resistance interpretation were performed using DeepChek applying 1% and 20% thresholds for variant detections; filters applied were comparison between Sanger and 454-UDS, and Stanford and IAS list for resistance interpretation. RESULTS: The time elapsed from generation of raw 454 data (between 2,000-5,000 sequences/sample) to elaboration of a resistance report was approximately 10 minutes per sample, equivalent to the time required for the same process using Sanger sequencing. Four patients (3.7%) showed baseline resistance by Sanger and 454-UDS at frequencies above 20%, which affected both NRTIs (n=2) and NNRTIs (n=2). In addition, 12 patients (11.2%) showed transmitted drug resistance (TDR) by 454-UDS at frequencies below 20% affecting NRTIs (n=9), NNRTIs (n=7) and PIs (n=2). Integrase resistance was not detected at baseline by 454-UDS or Sanger sequencing. CONCLUSIONS: DeepChek allowed easy and rapid analysis and interpretation of NGS data, thus facilitating the incorporation of this technology in routine diagnostics. The use of NGS considerably increased the detection rates of TDR to NRTI, NNRTIs and PIs. No transmitted resistance to integrase inhibitors was found in our population by Sanger sequencing or UDS.

Improved prediction of salvage antiretroviral therapy outcomes using ultrasensitive HIV-1 drug resistance testing.

BACKGROUND: The clinical relevance of ultrasensitive human immunodeficiency virus type 1 (HIV-1) genotypic resistance testing in antiretroviral treatment (ART)-experienced individuals remains unknown. METHODS: This was a retrospective, multicentre, cohort study in ART-experienced, HIV-1-infected adults who initiated salvage ART including, at least 1 ritonavir-boosted protease inhibitor, raltegravir or etravirine. Presalvage ART Sanger and 454 sequencing of plasma HIV-1 were used to generate separate genotypic sensitivity scores (GSS) using the HIVdb, ANRS, and REGA algorithms. Virological failure (VF) was defined as 2 consecutive HIV-1 RNA levels ≥200 copies/mL at least 12 weeks after salvage ART initiation, whereas subjects remained on the same ART. The ability of Sanger and 454-GSS to predict VF was assessed by receiver operating characteristic (ROC) curves and survival analyses. RESULTS: The study included 132 evaluable subjects; 28 (21%) developed VF. Using HIVdb, 454 predicted VF better than Sanger sequencing in the ROC curve analysis (area under the curve: 0.69 vs 0.60, Delong test P = .029). Time to VF was shorter for subjects with 454-GSS < 3 vs 454-GSS ≥ 3 (Log-rank P = .003) but not significantly different between Sanger-GSS < 3 and ≥3. Factors independently associated with increased risk of VF in multivariate Cox regression were a 454-GSS < 3 (HR = 4.6, 95 CI, [1.5, 14.0], P = .007), and the number of previous antiretrovirals received (HR = 1.2 per additional drug, 95 CI, [1.1, 1.3], P = .001). Equivalent findings were obtained with the ANRS and REGA algorithms. CONCLUSIONS: Ultrasensitive HIV-1 genotyping improves GSS-based predictions of virological outcomes of salvage ART relative to Sanger sequencing. This may improve the clinical management of ART-experienced subjects living with HIV-1. CLINICAL TRIALS REGISTRATION: NCT01346878.

Comparison of ultra-deep versus Sanger sequencing detection of minority mutations on the HIV-1 drug resistance interpretations after virological failure.

OBJECTIVE: Drug-resistance mutations are routinely detected using standard Sanger sequencing, which does not detect minor variants with a frequency below 20%. The impact of detecting minor variants generated by ultra-deep sequencing (UDS) on HIV drug-resistance interpretations has not yet been studied. DESIGN: Fifty HIV-1 patients who experienced virological failure were included in this retrospective study. METHODS: The HIV-1 UDS protocol allowed the detection and quantification of HIV-1 protease and reverse transcriptase variants related to genotypes A, B, C, F and G. DeepChek-HIV simplified drug-resistance interpretation software was used to compare Sanger sequencing and UDS. RESULTS: The total time required for the UDS protocol was found to be approximately three times longer than Sanger sequencing with equivalent reagent costs. UDS detected all of the mutations found by population sequencing and identified additional resistance variants in all patients. An analysis of drug resistance revealed a total of 643 and 224 clinically relevant mutations by UDS and Sanger sequencing, respectively. Three resistance mutations with more than 20% prevalence were detected solely by UDS: A98S (23%), E138A (21%) and V179I (25%). A significant difference in the drug-resistance interpretations for 19 antiretroviral drugs was observed between the UDS and Sanger sequencing methods. Y181C and T215Y were the most frequent mutations associated with interpretation differences. CONCLUSION: A combination of UDS and DeepChek software for the interpretation of drug resistance results would help clinicians provide suitable treatments. A cut-off of 1% allowed a better characterization of the viral population by identifying additional resistance mutations and improving the drug-resistance interpretation.

Uncommon mutations at residue positions critical for enfuvirtide (T-20) resistance in enfuvirtide-naive patients infected with subtype B and non-B HIV-1 strains.

Enfuvirtide (T-20) is the lead compound of the new class of antiretroviral drugs called fusion inhibitors. T-20 resistance-associated mutations located in the heptad repeat 1 (HR-1) domain of gp41 have been described in vitro and in clinical trials. In this study, the authors investigated the primary genotypic T-20 resistance in subtype B and non-B HIV-1 strains from patients at the beginning of their follow-up in the Luxembourg HIV Cohort as well as the emergence of primary resistance to T-20 in patients who had long-term infection with subtype B HIV-1 strains. HR-1 fragments including the gp41 amino acid 36-45, T-20-sensitive region were screened for amino acid variation. No classic T-20 resistance-associated mutations were identified in subtype B or non-B isolates. However, several uncommon mutations were found at residues 37, 39, and 42 for subtype B isolates and at residue 42 for a subtype non-B isolate. The results indicate that primary genotypic T-20 resistance seems to be rare in HIV-1, regardless of subtype or prior antiretroviral therapy (excluding fusion inhibitors). However, episodic variation within HR-1 can occur and needs further phenotypic evaluation in accurate fusion inhibitor resistance assays.