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. Electronic supplementary material The online version of this article (10.1186/s12981-018-0206-y) contains supplementary material, which is available to authorized users.


Background
The United Kingdom (U.K.) has a relatively small HIV-1 epidemic, with just over 100,000 people living with HIV-1 and an adult prevalence of 0.16%, despite the recent increase in the annual number of new diagnoses, particularly in people born in the country [1]. Nonetheless, the U.K. is a clear example of how access to combination antiretroviral therapy (cART) can transform a national HIV-1 epidemic: 98% of the people living with HIV-1 were receiving cART in 2017 with 97% achieving virus suppression [1,2]. The prevalence of resistance to any antiretroviral drug among ART-experienced patients in the country seems to have remained stable -around 30%-since 2011, while transmitted HIV-1 drug resistance (prevalence in ART-naïve individuals) is approximately 7% [3][4][5][6]. These results highlight the fact that monitoring HIV-1 drug resistance is not only crucial to controlling plasma viremia in patients receiving antiretroviral drugs but also in the surveillance of transmitted drug resistance, a critical public health issue in the fight against HIV/AIDS.
HIV-1 genotyping assays, based on population (Sanger) sequencing, have been the most common method to manage patients infected with HIV-1 for almost 20 years [7][8][9][10][11]. Our current understanding of HIV-1 drug resistance, and the great success controlling HIV-1 disease during the last decade, have been the result of a myriad of HIV-1 studies using this standard methodology [7,12,13]. Nevertheless, HIV-1 genotypes based on Sanger sequencing can only detect HIV-1 variants present at frequencies above approximately 20% of the viral quasispecies [14][15][16][17][18], failing to quantify low-levels of HIV-1 drug resistant variants [10,19]. These variants, usually present as minority members of the virus population, can be selected and become predominant under the appropriate pressure by antiretroviral drugs [20][21][22]. With the advent of deep (next-generation) sequencing, several new HIV-1 genotyping approaches based on this ultrasensitive methodology have been developed with the goal of detecting drug resistant HIV-1 variants at low frequencies, i.e., below 20% of the viral population [19,[23][24][25][26], with only a few assays being used in the clinical setting [19,27,28]. Although the clinical significance of these minority drug resistant HIV-1 variants is still on discussion [29][30][31][32][33], numerous groups are now using these assays not only to monitor HIV-1 drug resistance but also to better understand the role of low-level HIV-1 variants on transmission, disease progression, and HIV-1 cure strategies [reviewed on [10,11]].
Several groups in the U.K. have used deep sequencing to investigate minority HIV-1 variants associated with transmitted drug resistance [3,6,34], selection and prevalence of low-abundance drug resistant HIV-1 variants [35], genetic diversity in full-length HIV-1 genomes [36], HIV-1 coreceptor tropism [37][38][39], and their potential contribution to virologic failure [40]; however, inhouse HIV-1 genotyping based on deep sequencing is only available in reference laboratories in the United Kingdom. In this verification study, we implemented DEEPGEN ™ , a validated deep sequencing-based HIV-1 genotyping assay used in a CLIA/CAP-accredited laboratory in the United States since 2013 [19] and in Uganda since January 2017 [41], in two clinical laboratories in the U.K. i.e., St. George's University Hospitals Healthcare NHS Foundation Trust (London) and at NHS Lothian (Edinburgh). A comprehensive list of comparative studies first verified the feasibility of using DEEPGEN ™ to monitor HIV-infected individuals in the U.K., while we characterized majority and minority drug resistant HIV-1 variants in these cohorts of patients and their correlation with virological and immunological parameters.

HIV-1 genotyping and tropism determination based on deep sequencing of the gag-p2/NCp7/p1/p6/pol-PR/RT/ IN-and env-C2V3-coding regions
HIV-1 drug resistance and co-receptor tropism was determined using an all-inclusive deep sequencingbased assay, DEEPGEN ™ , as described [19]. Briefly, plasma viral RNA was purified and three RT-PCR products corresponding to the gag-p2/NCp7/p1/p6/pol-PR/ RT-(1657 bp fragment), pol-IN-(1114 bp fragment), and env-C2V3-(480 bp fragment) coding region of HIV-1 amplified. These amplicons were purified, quantified, and used to construct a multiplexed library for shotgun sequencing on the Ion Personal Genome Machine (PGM, ThermoFisher Scientific). Reads were mapped and aligned against sample-specific reference sequences constructed for the gag-p2/NCp7/p1/p6/pol-PR/RT/IN or env-gp120 HIV-1 genomic regions using the DEEP-GEN ™ Software Tool Suite v2 (Alouani and Quiñones-Mateu, unpublished) as described [19]. Plasma samples were classified as containing non-R5 viruses if at least 2% of the individual sequences, as determined by deep sequencing, were predicted to be non-R5 [42,43]. In this study, minority variants were defined as amino acid substitutions detected at ≥ 1% (based on the intrinsic error rate of the system [19]) and < 20% of the virus population, corresponding to those mutations that cannot be determined using population sequencing [14][15][16][17][18].

Phylogenetic and HIV-1 diversity analysis
Three consensus sequences, corresponding to the three amplicons (PR/RT, INT, and C2V3), were generated for each patient-derived virus, aligned using ClustalW [44] and their phylogeny reconstructed using the neighborjoining statistical method as implemented within MEGA 6.06 [45]. HIV-1 subtype, initially predicted by phylogenetic analysis, was confirmed using pol-PR/RT/INT and env-V3 sequences with the DEEPGEN ™ Software Tool Suite v2 and Geno2Pheno tools (http://www.geno2 pheno .org). Inter-patient genetic distances were determined using the Maximum Composite Likelihood model with bootstrap as the variance estimation method (1000 replicates) within MEGA 6.06 [45]. Intra-patient HIV-1 quasispecies diversity was determined using all three PR/ RT-, INT-, and C2V3-coding regions based on the p-distance model as described for deep sequencing [46].

Statistical analyses
Descriptive results are expressed as median values, standard deviations, range, and confidence intervals. The non-parametric Kruskal-Wallis one-way analysis of variance test was used to compare the mutations detected among the different groups. All differences with a p value of < 0.05 were considered statistically significant. The kappa coefficient, calculated using ComKappa2 v.2.0.4 [47], was used to quantify the concordance between HIV-1 coreceptor tropism determinations. The kappa coefficient calculates a chance-adjusted measure of the agreement between any number of categories, in this case HIV-1 coreceptor tropism determined by the same assay in two different locations. All statistical analyses were performed using GraphPad Prism v.6.0b (GraphPad Software, La Jolla, CA) unless otherwise specified. gag-p2/NCp7/p1/ p6/pol-PR/RT/IN and env-C2V3 nucleotide sequences obtained by deep sequencing in this study have been submitted to the Los Alamos National Laboratory HIVdb Next Generation Sequence Archive (http://www.hiv. lanl.gov/conte nt/seque nce/HIV/NextG enArc hive/Silve r2018 ).

Epidemiological, clinical, and virological characteristics of HIV-infected individuals
As described above, for this study we selected 109 plasma samples from HIV-1 patients being monitored at two hospitals in the United Kingdom: 59 from St. George's University Hospitals Healthcare NHS Foundation Trust (St. George's) and 50 from NHS Lothian (Table 1 and  Additional file 1: Table S1, Additional file 2:  Table S2).

Implementing DEEPGEN ™ in the United Kingdom
Our deep sequencing-based HIV-1 genotyping and coreceptor tropism assay (DEEPGEN ™ ) has been characterized and validated for clinical use in the US. since late 2013 [19]. Here we transferred the technology to two independent clinical laboratories in the U.K. (St. George's and NHS Lothian) to evaluate assay performance and the feasibility to detect minority HIV-1 drug resistance variants in different populations of HIV-infected individuals. Each clinical laboratory multiplexed their respective samples into three Ion 318 chips with median loading efficiencies of 65% and 61%, generating a total of 11,831,865 and 11,542,222 quality reads, with equal median read lengths of 226 bp for St. George's and NHS Lothian, respectively. Although comparable, the average sequencing coverage at each nucleotide position varied with each sample and HIV-1 genomic region analyzed, with no significant differences between laboratories, i.e., PR/RT/INT (mean 7205 and 8878 reads) and V3 (16,893 and 20,218 reads) for St. George's and NHS Lothian, respectively (Fig. 1). More importantly, these metrics ensured the minimum coverage of 1000 per nucleotide position sequenced required guaranteeing the detection of a minor variant present at least at 1% of the population [48].
All 109 plasma samples from both cohorts of patients (St. George's and NHS Lothian) were originally analyzed using standard Sanger-based HIV-1 genotyping in the respective clinical laboratories. Altogether a total of 157 mutations (129 and 28 in St. George's and NHS Lothian cohorts, respectively) in positions associated with drug resistance were detected by Sanger sequencing (i.e., 44 in the protease, 93 in the RT, and 20 in the integrase) (Fig. 2a). As expected, all the drug resistance mutations identified by Sanger sequencing were also detected using DEEPGEN ™ , while 280 additional drug resistance mutations (120 and 160 in the St. George's and NHS Lothian cohorts, respectively) were detected only by deep sequencing (i.e., 80 in the protease, 168 in the RT, and 32 in the integrase) (Fig. 2a). This difference in the numbers of drug resistance mutations detected by Sanger and deep sequencing-in both institutions-was significant, even when the mutations were quantified by drug class, ranging from 1.4-to 12-fold additional mutations detected by deep sequencing compared to Sanger sequencing (Paired t test, p < 0.0001 to p = 0.029) (Fig. 2a).
Overall, a similar number of drug resistance mutations were identified using Sanger sequencing and DEEPGEN ™ with a mutation frequency threshold of ≥ 20%, resulting in comparable HIVdb mutation scores; however, the HIVdb scores were consistently higher for most antiretroviral drugs when DEEPGEN ™ was used with a mutation frequency of ≥ 1% (Fig. 2b). In fact, no significant differences were observed in the HIVdb scores determined by Sanger or DEEPGEN ™ using mutation frequencies ≥ 20% when all drug classes (PI, NRTI, NNRTI, and INSTI) were compared for both cohorts of patients (Fig. 2c). As expected, significantly higher HIVdb scores were obtained -for all antiretroviral drugs-using DEEP-GEN ™ with mutation frequencies ≥ 1% compared to Sanger or DEEPGEN ™ with mutation frequencies ≥ 20%, i.e., 26-and twofold (PI), 16-and sixfold (NRTI), fourand twofold (NNRTI), and four-and twofold (INSTI) for St. George's and NHS Lothian, respectively (Paired t test, p < 0.01 to p < 0.0001) (Fig. 2c).
Although the clinical significance of minority variants is still on debate, here we assumed equal impact on predicted drug resistance of a mutation detected by Sanger sequencing or DEEPGEN ™ with mutation frequency thresholds of ≥ 20%, ≥ 5%, or ≥ 1%, the HIVdb scores to infer the levels of susceptibility to the different antiretroviral drugs. As observed in Fig. 3, similar drug resistance profiles (susceptible, low-level/intermediate, or high-level resistance) were obtained using Sanger and DEEPGEN ™ with mutation frequencies ≥ 20%; however, a few additional mutations detected at frequencies between 5 and 20% increased the resistance level George's and NHS Lothian cohorts, respectively, showed some kind of resistance HIV-1 genotype (reduced susceptibility) determined by Sanger or DEEPGEN ™ with mutation frequencies ≥ 20%; however, these numbers increased to 44/59 (74.6%) and 42/50 (84%) using DEEPGEN ™ with mutation frequencies ≥ 1% (Fig. 3), which correlated with the antiretroviral drugs listed in their treatment histories (Supp . Tables 1 and 2). Finally, we used DEEPGEN ™ to quantify the frequency of CCR5-or CXCR4-tropic variants and determine HIV-1 coreceptor tropism in both cohorts of patients. HIV-1 tropism based on Sanger sequencing had been determined in six patients from St. George's, all classified as being infected with R5 viruses (Fig. 4). Interestingly, DEEPGEN ™ was able to corroborate the R5 tropism in 5/6 viruses while in one patient X4 HIV-1 variants were detected at low frequency (i.e., 5.1%), changing the tropism determination to dual-or mixed-tropic (D/Mtropic). Overall, 35% of the St. George's patients were infected with D/M-tropic viruses, with the frequency of X4 variants ranging from 5.1 to 100% within the HIV-1 population (Fig. 4). In the case of the NHS Lothian, only 16% (8/50) of the patients harbored D/M-tropic HIV-1 strains, with X4 variants ranging from 10.9 to 100% (Fig. 4).

Verifying DEEPGEN ™ in the United Kingdom
Following the implementation of DEEPGEN ™ in the clinical laboratories at St. George's and NHS Lothian, and the successful test of 59 and 50 clinical HIV-1 samples in the respective institutions, 32 of these samples (16 from each group) were sent to the University Hospitals Translational Laboratory (UHTL, Cleveland, Ohio, USA) to complete the verification of the assay in the U.K. laboratories. After testing all 32 samples with DEEPGEN ™ in the UHTL, we quantified the number of mutations -and their frequency in the population-determined in the UHTL and compared them to the values obtained in the U.K. (St. George's and NHS Lothian). As expected, strong significant correlations were observed when the two sets of 16 sequences were compared, even after segregating the mutations per drug class, with r values ranging from 0.995 to 0.999 (p < 0.0001, Pearson coefficient correlation) (Fig. 5a). We next quantified the number of drug resistance mutations detected using different mutation frequency thresholds for DEEPGEN ™ (≥ 1%, ≥ 5%, or ≥ 20%) in all three laboratories. With the exception of a slight difference between St. George's and UHTL in the number of drug resistance mutations quantified at ≥ 1% (mean 4.1 vs. 6.2 mutations, p = 0.029, Mann-Whitney), no significant differences were observed when the number of mutations associated with drug resistance were quantified in the U.S. or in the U.K. (Fig. 5b). More importantly, no difference was observed in the drug resistance profiles determined using the HIVdb algorithm (Fig. 5c). Finally, a perfect agreement (100% concordance, κ = 1) was observed comparing HIV-1 coreceptor tropism determinations based on V3 sequences obtained in the U.K. (St. George's and NHS Lothian) and in the U.S. (UHTL) (Fig. 5d).
Phylogenetic and diversity analysis using deep sequencing As described above, DEEPGEN ™ is based on deep sequencing viral RNA extracted from plasma samples and optimized to accurately detect minority HIV-1 variants above a 1% frequency level in the HIV-1 population [19]. Moreover, this methodology is capable of generating over 10,000 HIV-1 sequences (reads) per patient that can be used to analyze inter-and intra-patient HIV-1 genetic diversity [11,41,49]. Phylogenetic analyses confirmed the HIV-1 subtype initially determined for each patientderived virus with the DEEPGEN ™ Software Tool Suite v2 and Geno2Pheno. HIV-1 subtyping classification varied slightly depending on the HIV-1 genomic region analyzed (pol or C2V3); however, based on the most broadly used C2V3 region [19,50,51], the HIV-1 subtypes identified in these patients included: A1 (20), B (15), C (7), CFR02_ AG (6) Table S1, Additional file 2: Table S2).
As expected, mean inter-patient genetic distances calculated with the consensus C2V3 sequences were higher than those calculated with the PR/RT and INT sequences (Fig. 7b). Viruses from St. George's patients were significantly more diverse than viruses from NHS Lothian's individuals comparing C2V3 (mean 0.265 vs. 0.215 substitutions per site, p < 0.0001 unpaired t test) and PR/RT (0.111 vs. 0.098 s/site, p < 0.0001 unpaired t test) sequences but not when comparing INT sequences (0.084 vs. 0.081 s/site, p = 0.082 unpaired t test), respectively (Fig. 7b). Finally, intra-patient HIV-1 diversity was also determined using all three PR/RT-, INT-, and C2V3-coding regions based on the p-distance model as described for deep sequencing [46]. Although slightly higher in patients from NHS Lothian compared with viruses from St. George's individuals, no significant difference was observed in the HIV-1 quasispecies diversity of these patients, i.e., PR/RT (1.212 vs. 0.968), INT (1.013 vs. 0.817), and C2V3 (2.761 vs. 2.446), respectively (Fig. 7c).

Association of DEEPGEN ™ -based HIV-1 genotyping with clinical parameters
Given the considerable amount of data that we were able to accumulate from deep sequencing patient-derived HIV-1 sequences from these HIV-infected individuals, i.e., majority (frequency > 20%) and minority (frequency < 20% and > 1%) drug resistance mutations, susceptibility to antiretroviral drugs (HIVdb scores), coreceptor tropism, subtyping, inter-patient and intrapatient viral diversity, we decided to investigate potential associations among any of these metrics and clinical parameters, mainly plasma HIV RNA load, CD4 + T-cell counts, and antiretroviral therapy history. As expected, HIVdb scores determined using only majority, or including minority, drug resistance mutations correlated significantly with ART history in patients from St. George's (r = 0.51, p < 0.0001 or r = 0.58, p < 0.0001 Pearson coefficient correlation) and NHS Lothian (r = 0.37, p = 0.007 or r = 0.45, p = 0.001). On the other hand, no significant association was observed in most pairwise comparisons of the multiple virological metrics and clinical parameters studied (data not shown). For example, no significant correlation was observed between HIVdb scores determined using only majority (r = 0.13, p = 0.30 or r = 0.01, p = 0.98) or including minority (r = 0.12, p = 0.38 or r = 0.10, p = 0.47) drug resistance mutations, ART history

Discussion
Widespread HIV-1 drug resistance, usually associated with suboptimal virological suppression and poor clinical outcomes [52,53], is the natural byproduct of years of treating HIV-infected individuals with cART. Monitoring and detecting HIV-1 drug resistance, as soon as possible, does not only help control the infection and preserve the immunologic response in the individual but also limits the transmission of HIV-1 drug resistant variants, restricting the increasing prevalence of pretreatment resistance [53,54]. Deep sequencing-based HIV-1 genotyping assays have the intrinsic capability of detecting minority HIV-1 drug resistant variants before they become majority members of the HIV-1 quasispecies, which may lead to virologic failure [11,19,39,55,56]. Thus, the use of these highly sensitive assays should help controlling HIV-1 drug resistance both at the individual (patient) and population (epidemic) levels. In this study, we evaluated the use of DEEPGEN ™ , a deep sequencing-based HIV-1 genotyping and coreceptor tropism assay implemented in the clinical setting in the United States since 2013 [19] and in Uganda since 2017 [41], in two clinical laboratories in the U.K. i.e., St. George's University Hospitals Healthcare NHS Foundation Trust (London) and at NHS Lothian (Edinburgh). As expected, DEEPGEN ™ was able to accurately detect a series of drug resistance-associated mutations not identified using standard Sanger sequencing-based tests, correlating significantly with the patient's cART history and providing a more accurate characterization of drug resistant HIV-1 infections in these clinical institutions.
Adapting and implementing deep sequencing-based methodologies has become much easier and accessible since its inception in the early 2000s [11]. A multitude of deep sequencing-based tests have been developed and are being offered in clinical laboratories aimed to asses genomic, cancer, or infectious diseases related conditions [11,[57][58][59] and HIV/AIDS is not the exception. Still, while numerous groups have used these methodologies in research studies, only a few deep sequencing-based Each dot represents a patient-derived consensus sequence. b HIV-1 inter-patient genetic distances determined using the Maximum Composite Likelihood model with bootstrap as the variance estimation method (1000 replicates) within MEGA 6.06 [45]. c Intra-patient HIV-1 quasispecies diversity determined using all three PR/RT-, INT-, and C2V3-coding regions based on the p-distance model as described for deep sequencing [46]. Means ± standard deviations and statistically significant differences between both cohorts of patients (unpaired t test) are marked by ****(p < 0.0001), ***(p < 0.001), **(p < 0.01), *(p < 0.05), and n.s.   [19,41,49,61], DEEP-GEN ™ detected all the drug resistance mutations, in all 109 patients, originally identified in each laboratory using Sanger sequencing. More importantly, a total of 280 additional drug resistance mutations were identified in both cohorts of HIV-infected individuals, i.e., mutations below the limit of detection of Sanger sequencing (~ 20%) [14][15][16][17][18] and only detectable using deep sequencing, therefore modifying the Sanger-based HIVdb scores and overall resistance interpretation. The kind, number, and frequency of the minority drug resistance mutations identified matched the cART history of the patients, the most common being M46I/L and I50 V (PIs), K65R, D67 N, L74I, M184 V/I, and K219Q (NRTIs), and L100I (NNR-TIs). A few minority INSTI-resistance mutations were observed in the 109 HIV-infected individuals, reflecting the limited number of patients being treated with INSTIs at the time of the study (23/109). Most of these mutations have also been detected as minority variants in cohorts of patients failing first-or second-line cART [10,40,41,49,55,[61][62][63][64] or in antiretroviral-naïve patients [10,[65][66][67][68][69], including a study from the U.K. [3]. As expected, drug resistance profiles based on Sanger sequencing correlated significantly with cART history; however, the correlation was stronger when minority mutations were included in the analysis, suggesting that the presence of drug resistant minority variants as part of the HIV-1 quasispecies is a direct consequence of the antiretroviral drug pressure. Interestingly, minority drug resistant variants were observed in both antiretroviral-experienced and antiretroviral-naïve individuals, some of them associated with the current cART of each patient but others not related nor conferring cross-resistance to any particular drug in the respective regimens. These minority variants may be lurking in the population, waiting for the proper conditions to be selected [20,22]. However, based on our cross-sectional analysis, it is difficult to discern whether the increase in drug resistance (mutations, HIVdb scores, resistance profiles) due to the detection of minority variants at the time the plasma samples were obtained will result in an increase in plasma viremia and subsequent immunologic decline.
It is important to highlight that DEEPGEN ™ , in addition to determining HIV-1 drug resistance and coreceptor tropism, was also designed to evaluate subtyping, inter-patient and intra-patient HIV-1 diversity based on pol and env genes [19]. Here we were able to assess all these viral parameters for all 109 HIV-infected individuals. Interestingly, while 44% (48/109) of the patients in this study were infected with subtype B HIV-1 strains (66% in NHS Lothian's patients), several non-B HIV-1 strains were detected in these individuals, including A1, A2, C, D, F1, G, CRF02_AG, and CRF01_AE. Most of these non-B HIV-1 subtypes have been previously reported in the U.K. [4,[70][71][72]; however, it is important to highlight the presence of three individuals infected with subtype F1 HIV-1 strains. Prevalence of subtype F1 viruses has been increasing in North East Spain, particularly among men who have sex with men [73,74]. Since response to cART seems to be impaired in patients infected with F1 viruses [74,75], it will be important to monitor the circulation of this HIV-1 subtype in the U.K., particularly with the recent increase in chemsex among MSM living with HIV-1 in the country [76].
As described above, a number of studies -including some from the U.K.-have shown that deep sequencing assays are excellent tools to increase the detection of drug resistance mutations [19,34,40,41,62,63,65,67], monitor transmission of HIV-1 drug resistance [3,19,33,41,49,61,63,65,68,69,[77][78][79][80][81][82], and potentially determine the relevance of detecting minority drug resistance mutations in the clinical setting [10,11,31,40,55,83,84]. Are these minority drug resistant HIV-1 variants going to be selected as majority members of the quasispecies, eventually contributing to elevated plasma viremia and leading to virologic failure? What is the real importance and/or clinical significance of these minority variants? A multitude of studies have attempted to address these questions, adding to the controversy [29-33, 40, 41]. Although it may seem logical that, under the right (drug) pressure, these drug resistant minority variants will become majority members of the HIV-1 population, only a few studies have been able to clearly demonstrate that pre-existent minority variants contribute to a negative clinical outcome [33,41,62,69,85]. It is clear that further studies based on larger and well-characterized cohorts of patients, and using clinically validated deep sequencingbased HIV-1 genotyping assays such as DEEPGEN ™ , will be needed to determine whether drug resistant minority variants contribute to virologic failure.
In summary, to our knowledge, this is the first study evaluating the transition, training, and implementation of DEEPGEN ™ , a deep sequencing-based HIV-1 genotyping assay, between three clinical laboratories in two different countries (we are in the process of publishing the establishment of DEEPGEN ™ in Uganda). 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 109 individuals from the United Kingdom, providing valuable information to help control the HIV/AIDS epidemic in the country. This study provides a rigorous basis for basing clinical decisions on highly sensitive and cost-effective deep sequencingbased HIV-1 genotyping assays. Moreover, our work is an example of a verification study of a fully validated deep sequencing-based HIV-1 genotyping assay, which can replace Sanger sequencing assays and improve the HIV-1 drug resistant profiles of HIV-infected patients. DEEPGEN ™ can be effectively implemented into nationally accredited clinical and molecular pathology laboratories in the U.K., supporting local HIV-1 treatment services and contributing to public health programs that monitor the emergence and transmission of HIV-1 drug resistance quasispecies in the country.