A Center of Excellence for Biomedical Research and Training in Africa


HIV drug resistance testing among patients failing second line antiretroviral therapy. Validation of an in-house sequencing method

Benjamin Chimukangara,a Bhavini Varyani,a Tinei Shamu,b Junior Mutsvangwa,a Justen Manasa,c Elizabeth White,c Cleophas Chimbetete,b,d Ruedi Luethy,b David Katzensteinc

Department of Molecular Biology, Biomedical Training and Research Institute, Harare, Zimbabwe;

b Newlands Clinic, Newlands, Harare, Zimbabwe;

c Department of Medicine, Stanford University School of Medicine, Stanford, California, USA;

d Institute of Social and Preventive Medicine, University of Bern, Switzerland

E-mail addresses of authors:

BC: benjiechim@yahoo.com

BV: bhavinivaryani@gmail.com

TS: TineiS@newlandsclinic.org.zw

JM: Jnr.mutsvangwa@gmail.com,

JM: jmanasa@gmail.com,

EW: betsyjohn@aol.com,

CC: cleophasc@newlandsclinic.org.zw,

RL: RuediL@newlandsclinic.org.zw,

DK: davidkk@stanford.edu


Corresponding author:

Benjamin Chimukangara,

Africa Centre for Population Health,

Doris Duke Medical Research Institute,

Nelson Mandela School of Medicine, University of KwaZulu-Natal,

Durban, South Africa.



Abstract [Under Peer-review]

Introduction: Despite ART scale-up in low and middle-income countries (LMIC), HIV drug resistance testing by genotyping is often not available due to infrastructure requirements and cost. We developed local, lower cost sequencing “in house” in Harare with a Southern African Treatment and Resistance Network (SATuRN) protocol and compared the results to sequencing in California.

Methods: Remnant plasma samples from viral load tests of adults and children failing 2nd line ART at a clinic in Harare, Zimbabwe were accessed. HIV-1 viral RNA was extracted and reverse transcribed using SuperScript III. A nested PCR with Platinum Taq generated a 1.32kb amplicon spanning the protease and reverse transcriptase genes. Purified amplicons were sequenced at a commercial laboratory and in-house, on an ABI 3130xl genetic analyzer. Commercial sequences were analyzed at Stanford University. HIV drug resistance mutations were determined using the Stanford HIV drug resistance database. Phylogenetics and drug resistance analysis, were performed in parallel in Harare.

Results: 26 of 28 samples were successfully amplified and 25 were successfully genotyped. Both facilities successfully sequenced 24 samples each, of which one was unique for each lab. The average percent nucleotide and amino acid identities between the pairs successfully sequenced by both laboratories were 99.51 (±0.56) and 99.11 (±0.95) respectively. Comparable numbers of drug resistance mutations were detected between the in-house and commercial sequencing, 6.09 vs. 5.96 respectively (p=0.48). Of 19 samples with HIVDR mutations; 6 / 19 pairs had partially discordant mutations. All samples were unique subtype C HIV-1 by phylogenetics analysis.

Conclusions: Our results demonstrate a good quality in-house HIVDR testing method. Despite the few differences in mutations detected, the phenotypic predictions were not clinically significant, except in one sample where the local, in-house sequence was the more sensitive. Additionally, phylogenetic analysis illustrated that amplicons generated locally were of good quality thereby enabling sequencing by the post as an efficient external quality control for the in-house platform.


Keywords: HIV drug resistance, treatment failure, genotyping, validation, SATuRN, Zimbabwe

1.0 Introduction

Zimbabwe’s National antiretroviral treatment program began in 2004 [1]. As of 2014, antiretroviral treatment (ART) coverage had reached an estimated 77% of those eligible for treatment [2], after adapting World Health Organization (WHO) 2013 consolidated guidelines for ART initiation [3], i.e. patients with CD4 counts ≤500 cells/mm3, WHO clinical stages 3 or 4, or active TB disease. Currently, public health and donor funding provide WHO recommended first line ART [2] to over 920 000  recipients. The goal of ART is to suppress HIV to undetectable levels (<50 RNA copies/ml) using a combination of one non-nucleoside reverse transcriptase inhibitor (NNRTI) and two nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) as first line therapy, and a boosted protease inhibitor (PI) and two NRTIs for second line therapy [4].

The WHO 2015 ART guidelines for public health prevention and individual health benefits of ART extend ART to an additional 500 000 people. The beginning of the end of the HIV pandemic “Getting to zero new infections” is dependent upon >90% suppression of HIV RNA [5]. Viral load testing and adherence counseling to attain the “90 percent suppression” goal is critical [5] since drug resistance results in clinical failure and contributes to transmitted drug resistance. The Department of Health and Human Services (HHS) panel on ART guidelines for adults and adolescents recommends HIV drug resistance testing to guide ART when switching drug regimens for patients with virological failure (i.e. viral loads >1000 copies /ml) [6].

Access to drug resistance testing is limited by costs and laboratory infrastructure constraints. Strategies to provide drug resistance testing services for surveillance and management of patients on ART requires genotypic testing by sequencing of reverse transcriptase (RT) and protease (PR) genes to detect drug resistance mutations [7,8]. Genotyping may be performed by commercial systems (TruGene and ViroSeq) or more economical “home brew” assays [9]. Here we compared results from a commercial sequencing facility (MC Labs, California) and a 3130xl Genetic Analyzer in Harare using a Southern African Treatment Research Network (SATuRN) protocol [10] to obtain amplicons from HIV plasma RNA from complex, multidrug resistant samples.

2.0 Methods

Plasma samples (N=28) obtained from patients with virological failure (viral loads ≥1000 copies/ml) assessed using the COBAS AmpliPrep/ TaqMan48 HIV-1 Test, v2.0 (Roche Molecular Diagnostics) at Newlands Clinic in Harare, were genotyped for drug resistance mutations as part of routine patient care, to assist clinicians in choosing the appropriate third-line regimens. Samples were sequenced using two different methods (in-house and commercial sequencing), so as to validate the in-house sequencing method. In-house sequencing results were not used for patient management. The study was approved by the Biomedical Research and Training Institute (BRTI) Institutional Review Board (IRB), Ref: AP134/16.

2.1 Laboratory Methods

2.1.1 RNA extraction: Plasma samples stored at -80oC were thawed to room temperature prior to extraction. Plasma volumes used for pelleting the virus were based on the sample viral loads. For samples with viral loads ≥4.5 log10 copies/ml, 500µl of plasma was used. For samples with viral loads <4.5 log10 copies/ml, 1000µl – 1500µl of plasma was used. Respective volumes for each sample were centrifuged at 23 000 x g for 1 hour at 4oC to pellet the virus.

The supernatant was discarded leaving 200µl of pelleted sample for extraction. Viral RNA (vRNA) was extracted using a PureLink Viral RNA/ DNA Kit (Invitrogen, California, USA) according to manufacturer’s instructions. In summary, 25µl of proteinase K and 200µl of lysis buffer were added to 200µl of pelleted plasma sample, mixed by vortexing and incubated for 15 minutes at 56oC. Absolute ethanol (250µl) was added to the lysate, mixed by vortexing and incubated for 5 minutes at room temperature. The lysate was transferred to a viral spin column (Invitrogen, California, USA) and centrifuged at 6800 × for 1 minute. The column was washed twice using 500µl of wash buffer and spun at 6800 × for 1 minute discarding flow through. Viral RNA was eluted in 30µl of buffer and used immediately for reverse transcription.

2.1.2 Complimentary DNA (cDNA) synthesis: A dNTP/ primer mix was prepared by mixing 0.5µl of primer RT21 [5µM] and 0.5µl of dNTPs [10mM]. 6µl of RNA was mixed with the dNTP/ primer mix and placed in a PTC-100 programmable thermal controller (MJ Research, USA) at 65oC for 5 minutes, before rapidly cooling to 4oC for 2 minutes. With tubes held at 4oC, 5µl of enzyme mix containing 1µl of First Strand Buffer [10x], 2µl of MgCl[25mM], 1µl of DTT [0.1M], 0.5µl of RNaseOUT [40U/ml], and 0.5µl of 200U/ml Superscript III Reverse Transcriptase (Life Technologies), was added. The tubes were heated in the thermal cycler at 50°C for 60 minutes then at 85°C for 5 minutes, before cooling to 37oC. The thermal cycler was paused at 37oC and 0.5µl of RNAse H 
was added. The tubes were held at 37°C for 20 minutes and then cooled to 4°C. The cDNA was amplified immediately by nested PCR.

2.1.3 Nested PCR: The HIV protease (PR) and reverse transcriptase (RT) genes were amplified using SATuRN custom primers shown in Table 1. The first round primers were MAW26 and RT21 and second round primers were Pro1 and RT20. 2µl of cDNA was mixed with 23µl of PCR reagent mix containing 18.4µl of DEPC treated water, 2.5μl of buffer [10x], 1.0μl of MgCl2 [50mM], 0.5μl of dNTPs [10mM], 0.25μl of each primer [5µM],
and 0.1μl of 5U/μl Platinum Taq polymerase (Life Technologies).  Reagent volumes and PCR conditions for the 1st and 2nd rounds were as follows; 94oC for 2 minutes, followed by 30 cycles of 95oC for 30 seconds, 58oC for 20 seconds, 72oC for 2 minutes, and then 72oC for 10 minutes, before a final holding step at 4oC. The second round amplicon was 1.32kb as verified by gel electrophoresis on a 1% agarose gel [10].

2.1.4 Purification of PCR product: Amplicons were purified using a PureLink PCR purification kit (Invitrogen, Löhne, Germany) according to manufacturer’s instructions. Binding buffer High-Cutoff (B3) (4:1) was added to amplicon, which was transferred to a spin column (Invitrogen, Löhne, Germany), washed and centrifuged at >10 000 x g for 2 minutes. The purified amplicon was eluted in 30µl of elution buffer by centrifuging at 14 000 x g for 2 minutes.

The amplicon was divided into two 15µl volumes for commercial and in-house sequencing. DNA concentrations were determined using a NanoDrop Lite Spectrophotometer (ThermoScientific, location ?) and amplicons were stored at -20oC prior to sequencing.

An aliquot of each sample was sent for sequencing at Molecular Cloning Laboratory (MCLab) in California and the data were analyzed at Stanford University School of Medicine in the Division of Infectious Diseases. The duplicate aliquots were sequenced and analyzed in-house.

Table 1. PCR and sequencing SATuRN custom primers

Primer Sequence Direction HXB2 Stage
MAW-26 5’-TTGGAAATGTGGAAAGGAAGGAC-3’ Forward 2028-2050 1st round PCR
Pro-1 5’-TAGAGCCAACAGCCCCACCA-3’ Forward 2147-2166 2nd round PCR
RT-20 5’-CTGCCAATTCTAATTCTGCTTC-3’ Reverse 3462-3441
RTC1F 5’-ACCTACACCTGTCAACATAATTG-3’ Forward 2486-2508    Sequencing

HXB2, nucleotide position of HIV-1 reference sequence.

2.2 In-house Sequencing

2.2.1 Sequencing reaction: Big Dye Terminator v3.1 kit (Life Technologies) and four SATuRN custom sequencing primers (provided with the kit) shown in Table 1 were used. 1µl of the amplicon was mixed with 9µl of sequencing reaction mix containing 6.1µl of nuclease free water, 2µl of sequencing buffer (5X), 0.5µl of primer [3.2µM] (provided) and 0.4µl of Big Dye terminator sequencing mix. The sequencing reaction conditions were as follows; 96oC for 1 minute, followed by 35 cycles of 96oC for 10 seconds, 50oC for 5 seconds, 60oC for 4 minutes, and then a final holding step at 4oC.

2.2.2 Sequence reaction purification:
 The sequencing products were purified prior to capillary electrophoresis. In summary, 10µl of the sample was mixed with 80µl of freshly prepared 75% isopropanol. The tubes were mixed by vortexing and incubated in the dark for 15 minutes at room temperature. They were then centrifuged at >10 000 x g for 20 minutes. The isopropanol was aspirated and discarded taking care not to disturb the pellet. 200µl of freshly prepared 70% ethanol was added and mixed by vortexing. The tubes were centrifuged for 5 minutes and the ethanol was aspirated and discarded. This step was repeated followed by a quick spin to remove residual ethanol. The tubes were left open to dry in the dark for 10 minutes at room temperature. The pellet was re-suspended in 10µl of Hi-Di formamide and vortexed to mix.


2.2.3 Capillary Electrophoresis: Each sample was added to its respective position on a 96-well plate and covered with plate septa. Samples were denatured at 96oC for 2 minutes on a thermal cycler and immediately placed on ice for at least 2 minutes. The samples were loaded on the 3130xl Genetic Analyzer [Applied Biosystems] for capillary electrophoresis.


2.2.4 Sequence editing and analysis: Sequence editing was done in Sequencher v5.4 (Gene Codes Co.). Drug resistance mutations were detected using the Stanford University HIV drug resistance database (HIVdb) [11] and their significance was determined based on the International AIDS Society (IAS) mutation list [12]. Mutations were analyzed from both PR and RT genes spanning codons 1-99 and 1-238, respectively.


2.2.5 Phylogenetics: The qualities of sequences generated and edited in the two laboratories were analyzed by phylogenetic tree reconstruction in Geneious v.8.1.7. Phylogenetics analysis was done for 48 sequences, 23 sequence pairs and 2 sequences from either laboratory. HIV-1 reference sequences obtained from the Los Alamos Database (hiv.lanl.gov) were included. Sequences were aligned in Geneious R8 software [13] using ClustalW. Maximum likelihood tree reconstruction was carried out using the generalized time reversible model with proportion of invariable sites and gamma distribution (GTR+I+G). Internal node support with 1 000 bootstraps was done.


3.0 Results

3.1 Patient demographics, social and clinical characteristics

Twenty-eight plasma samples were submitted for genotyping. Over 50% of the patients had been on treatment for more than 6 years (Range: 6.5 – 10.8 years). Eighteen (64%) received a Tenofovir + Lamivudine + Atazanavir/ritonavir regimen.  Table 2 summarizes the demographic and clinical characteristics of the study subjects.

Table 2. Summary statistics of the 28 patients with treatment failure

                    Patients (n=28)
Characteristics No. %
          Male 16 57
          Female 12 43
Duration on ART
         < 1 year  1  4
          1 – 6 years 11 39
         > 6 years 16 57
Current Drug regimen
        ABC/3TC/ATV/r  3 11
        TDF/3TC/ATV/r 18 64
        TDF/3TC/ABC  1  4
        ABC/3TC/LPV/r  4 14
        AZT/3TC/ATV/r  1  4
        TDF/3TC/NVP  1  4
Clinical history/ Demographics Median IQR
      Age in years 20 18 – 34
      CD4 count, cells/mm3 595 436.5 – 659.3
      Log10 viral load, copies/ml 4.7 3.8 – 4.9
      Time on ART, years  7 5.4 – 8.4

ART, antiretroviral treatment; ABC, abacavir; 3TC, lamivudine; ATV/r, atazanavir + ritonavir; TDF, tenofovir; LPV/r, lopinavir + ritonavir; AZT, zidovudine; NVP, nevirapine; IQR, interquartile range

3.2 Viral load and amplification

Figure 1. Schematic amplification and sequencing success at the facilities used for sequencing.

Of the 28 samples, 26 (93%) were successfully amplified. The two samples that failed to amplify had relatively low viral loads, around the lower limit of the sensitivity of the assay, i.e., 1 247 and 901 copies/ml.

3.3 Drug resistance genotyping mutations

Of the 26 samples amplified, 25 were successfully sequenced by both sequencing facilities and 19 (76%) had at least one drug resistance mutation in either the protease and/or reverse transcriptase. The average percentage nucleotide and amino acid identities between the pairs were 99.51 (SD 0.56) and 99.11 (SD 0.95), respectively.

Table 3. Pairwise sequence identity analysis between the commercial and in-house sequences

  Commercial vs. In-house
Number of samples 23
Percentage nucleotide identity 99.51 (0.56)
Mean nucleotide identity 0.87 vs. 5.35 (p<0.05)
Percentage amino acid identity 99.11 (0.95)
Average number of drug resistance mutations 5.96 vs. 6.09 (p=0.4791)


Of the 23 samples genotyped in both laboratories 4 had no major drug resistance mutations. From the 19 pairs with drug resistance mutations, 13 were identical and 6 had partially discordant mutations. Consequently, 5 of the 6 had different phenotypic prediction results for certain drugs and one (NC14) was concordant despite mutation differences (Table 4).

Table 4. Samples with partially discordant drug resistance mutations and the consequent differences in predicted phenotypic resistance

Study ID Protease mutations Reverse transcriptase mutations Discordant Phenotypic predictions
Commercial In-house Commercial In-house Commercial In-house
NC1 M46L, I54V, V82A, L10V, L33F M46L, I50L*, I54V, V82A, L10V, L33F M41L, M184V, T215F, A98G, K103N M41L, M184V, L210LW*, T215F, A98G, K103N ABC: I






NC6 M46I, T74P


M46I, L24IL*, Q58EQ*, T74PT  D67N, K70E, M184V, K101E, V106I, G190A D67N, K70E, M184V,

K101E, V106I, G190A

LPV/r: I

SQV/r: L


LPV/r: H

SQV/r: I


NC7 L10F, L33I, Q58E, G73T


I54IV*, L10FI, L33I, Q58E, G73T


D67N, K70R, M184I, K219Q, V90I, K103N, Y181C D67N, K70R, M184I, K219Q, V90I, K103N, Y181C ATV/r: L

IDV/r: L

LPV/r: P

SQV/r: L

TPV/r: L

ATV/r: I

IDV/r:  I

LPV/r: L

SQV/r: I

TPV/r: I

NC14 None None A98G, V106M, Y181C, G190A A98G, V106M, Y181C, G190A, H221HY* EFV: H








NC22 None None G190A M184MV*, G190A 3TC:  S



3TC: H



NC28 None None M184V, V90I*, K103N, Y181C, Y188L*, H221Y* M184V, K103N, Y181C RPV: H RPV: I

Note: Alphanumeric characters in bold and with an asterisk* represent the discordant mutations.

ABC, abacavir; DDI, didanosine; TDF, tenofovir; LPV/r, lopinavir + ritonavir; SQV/r, saquinavir + ritonavir; ATV/r, atazanavir + ritonavir; IDV/r, indinavir + ritonavir; LPV/r, lopinavir + ritonavir; TPV/r, tipranavir + ritonavir; EFV, efavirenz; ETR, etravirine; NVP, nevirapine; RPV, rilpivirine; 3TC, lamivudine; FTC, emtricitabine; S, susceptible; P, potential low-level resistance; L, low-level resistance; I, intermediate resistance; H, high-level resistance.

3.4 Differences between in-house and commercial sequence resistance

Among three samples with differences in PI resistance mutations (NC1, NC6 and NC7 as shown in Table 4), in-house sequencing demonstrated protease drug resistance mutations that were not seen in the commercial sequence. In two cases this resulted in a modest increase in predicted resistance compared to commercial sequencing. In two samples, sample NC6 and NC7, the in-house sequencing detected minor variant protease inhibitor mixtures, L24IL and Q58EQ and an I54VI mixture (NC7) respectively.

The in-house assay was also more sensitive to mixtures and mutations at alleles associated with NRTI and NNRTI resistance. The NC7 in-house sequence demonstrated a thymidine mutation (TAM) L210W, associated with multi-NRTI resistance. Significantly, the in-house assay detected a mixture, M184MV in one sample (NC22) not found in the paired commercial sequence. In the one sequence pair, differences in the commercial sequence (NC28), detection of NNRTI mutations Y188L, H221Y led to a modest increase in predicted RPV resistance.

3.5 Phylogenetics

The phylogenetic tree for the samples showed good concordance between the two laboratories (bootstraps >70%). No contamination was observed. Samples sequenced commercially are labeled with SFD for Stanford, USA, and samples sequenced in-house are labeled with HRE for Harare, Zimbabwe. All samples clustered around the HIV-1C reference sequence. The sequences have been deposited in GenBank under accession numbers KU508549 – KU508596.

Figure 2. Phylogenetics tree of samples sequenced commercially (SFD) and in-house (HRE)

4.0 Discussion

Modern management of patients failing treatment and surveillance for transmitted drug resistance in resource-limited settings (RLS) has been constrained by lack of viral load monitoring and resistance testing capacity. In Zimbabwe we compared an in-house (“home-brew”) sequencing platform to a Virology Quality Assurance (VQA) accredited reference laboratory using a commercial facility for sequencing. Patient samples with multidrug failure from a tertiary treatment centre were assayed for IAS-USA drug resistance mutations from plasma RNA.

Of the 28 samples submitted for genotyping, 26 were successfully amplified; likely due to lower viral load in the two samples, i.e. viral loads of 1 247 and 901 copies/ml in samples NC18 and NC24 respectively. Of the 26 samples, 24 were successfully sequenced on each platform, and 23 were successfully sequenced in both laboratories. Nucleotide and amino acid identities between the 23 sequences were compared. Sequences between the in-house and commercial sequencing facility showed a 99.5% (0.56) nucleotide identity with a 0.87 vs. 5.35 (p-value <0.05) mean nucleotide identity, and a 99.11% (0.95) amino acid identity, demonstrating excellent inter-platform concordance. The results of our study are similar to a lower cost in-house genotype that was compared to ViroSeq Genotyping System 2.0 [9].

Of the 23 samples sequenced in both laboratories, 19 (83%) had drug resistance mutations. Thirteen of the 19 had concordant drug resistance mutations and 6 had partially discordant mutations as shown in Table 4. Of the 6 samples with discordant mutations, additional mutations were detected by the in-house assay which were not identified by commercial DNA sequencing. Five of the 6 demonstrated only a modest difference in the estimated resistance. The phenotypic predictions based on mutations showed resistance to the same PI and NNRTI drugs albeit with increased resistance, i.e. from Intermediate to High, based on additional within-class mutations (Table 4).

Acquired drug resistance to Lamivudine, Nevirapine and Efavirenz provided as first-line treatment in Zimbabwe leads to the predominance of significant transmitted drug resistance mutations [14]. Interestingly, we found that 18 of the 19 sequence pairs with mutations had one or more NNRTI resistance mutations, although only 2 were receiving NNRTI drugs in their current regimens. This provides evidence for the persistence of NNRTI mutations, which are estimated to recede, to undetectable levels in Sanger sequencing at a rate of about 10-20% annually [15]. However, they persist in about two thirds of patients despite NNRTI withdrawal probably because they are linked to other NRTI and PI resistance mutations, which are maintained under selective drug pressure of ART [16].

Although 24 of the samples were from patients reporting treatment with ATV/r (20) or LPV/r (4), drug resistance mutations associated with major PI resistance were detected in only 6 (25%), suggesting non-adherence rather than emergence of resistance as cause for virological failure.  In studies of boosted PI failure, drug resistance mutations to PI are reported in 10-40% [17]. Notably, in this study, none of the samples exhibited resistance to Darunavir. he presence of the M184V mutation in most of the samples is typical in first-line and second line failure [18]. Despite M184V/I mutations, Lamivudine (3TC) is usually retained as the M184V mutation reduces viral replicative capacity and may reverse AZT resistance caused by T215Y [19], delaying the emergence of thymidine analogue mutations (TAMs) [20], and increasing susceptibility to AZT and Tenofovir [21].

This study was limited to samples obtained from subjects with virologic failure (VL> 1000 copies/ml) and those close to the cut-off proved more difficult to sequence. Detection of drug resistance mutations is dependent on continued drug exposure and adherence [22,23] and thus we selected patients with virological failure, whilst on 2nd line ART, to compare the detection of mutations using two sequencing platforms. The discordances in PI and RT mutations largely resulted from detection of mixed variants in the in-house sequencing, illustrating the margin of error introduced by Sanger sequencing in the identification of minority variants. However, detection of mixtures did not significantly impact predicted phenotypic resistance.

Phylogenetics analysis showed good sequence quality between the commercial and in-house sequences, with all sequence pairs clustering on the same operational taxonomic units. All sequences clustered with the HIV-1 Subtype C sequences and there was no evidence of contamination.

5.0 Conclusion

We successfully demonstrated the feasibility of implementing HIV drug resistance testing in Zimbabwe with good quality results comparable to an accredited virology quality assurance certified facility at Stanford University. This warrants the adoption of the sequencing method for research and clinical resistance testing in Zimbabwe.

6.0 Competing interests

The authors declare that they have no competing interests.

7.0 Acknowledgements

We would like to thank Newlands Clinic for making available sample analytes and results available for this validation process.

8.0 Funding: This work was supported by the International, Clinical Operational and Health Services Research Training Award (ICOHRTA)

9.0 References

  1. Ministry of Health and Child Care. Report on the national HIV drug resistance prevention and assessment strategy: Zimbabwe, 2006-2008. 2008. 3-5 p.
  2. Global Aids Response Report. National AIDS Council, Zimbabwe. 2015.
  3. National Medicine and Therapeutics Policy Advisory Committee (NMTPAC): Ministry of Health and Child Welfare. Guidelines for Antiretroviral Therapy for the Prevention and Treatment of HIV in Zimbabwe. Harare; 2013.
  4. Bennett DE, Myatt M, Bertagnolio S, Sutherland D, Gilks CF. Recommendations for surveillance of transmitted HIV drug resistance in countries scaling up antiretroviral treatment. Antiviral Therapy. 2008. p. 25–36.
  5. WHO, UNAIDS. Global AIDS Response Progress Reporting 2015. Geneva; 2015.
  6. Panel on antiretroviral guidelines for adults and adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. US Department of Health and Human Services. [Internet]. 2014. Available from: http://aidsinfo.nih.gov/contentfiles/lvguidelines/ AA_Recommendations.pdf (Accessed 2014 Jan 12)
  7. Dybul M, Fauci AS, Bartlett JG, Kaplan JE, Pau AK, Mark Dybul John G. Bartlett, Jonathan E. Kaplan, Alice K. Pau, ASF. Guidelines for Using Antiretroviral Agents Among HIV-Infected Adults and Adolescents. Recommendations of the Panel on Clinical Practices for Treatment of HIV. 2002. p. 381–433.
  8. Vandamme A-M, Camacho RJ, Ceccherini-Silberstein F, de Luca A, Palmisano L, Paraskevis D, et al. European recommendations for the clinical use of HIV drug resistance testing: 2011 update. AIDS Rev. 2011;13:77–108.
  9. Chaturbhuj DN, Nirmalkar AP, Paranjape RS, Tripathy SP. Evaluation of a Cost Effective In-House Method for HIV-1 Drug Resistance Genotyping Using Plasma  Samples. Wainberg M, editor. PLoS One [Internet]. San Francisco, USA: Public Library of Science; 2014 Feb 12;9(2):e87441. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922725/
  10. Manasa J, Danaviah S, Pillay S, Padayachee P, Mthiyane H, Mkhize C, et al. An affordable HIV-1 drug resistance monitoring method for resource limited settings. J Vis Exp [Internet]. 2014;(85). Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4024245&tool=pmcentrez&rendertype=abstract
  11. Stanford HIV drug resistance database [Internet]. Palo Alto, California, USA; Available from: hivdb.stanford.edu (Accessed: 2015 Aug 13)
  12. Wensing AM, Calvez V, Günthard HF, Johnson VA, Paredes R, Pillay D, et al. Special Contribution 2014 Update of the Drug Resistance Mutations in HIV-1. Top Antivir Med [Internet]. 2014;22(3):642–50. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4392881/
  13. Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics [Internet]. 2012;28(12):1647–9. Available from: http://www.geneious.com
  14. Barth RE, Wensing AM, Tempelman HA, Moraba R, Schuurman R, Hoepelman AI. Rapid accumulation of nonnucleoside reverse transcriptase inhibitor-associated resistance: evidence of transmitted resistance in rural South Africa. AIDS. 2008;22(16):2210–2.
  15. Rhee S-Y, Blanco JL, Jordan MR, Taylor J, Lemey P, Varghese V, et al. Geographic and Temporal Trends in the Molecular Epidemiology and Genetic Mechanisms of Transmitted HIV-1 Drug Resistance: An Individual-Patient- and Sequence-Level Meta-Analysis. PLoS Med [Internet]. Public Library of Science; 2015 Apr 7;12(4):e1001810. Available from: http://dx.doi.org/10.1371%2Fjournal.pmed.1001810
  16. Joly V, Descamps D, Peytavin G, Touati F, Mentre F, Duval X, et al. Evolution of Human Immunodeficiency Virus Type 1 (HIV-1) Resistance Mutations in Nonnucleoside Reverse Transcriptase Inhibitors (NNRTIs) in HIV-1-Infected Patients Switched to Antiretroviral Therapy without NNRTIs. Antimicrob Agents Chemother. 2004;48:172–5.
  17. El-Khatib Z, Ekstrom AM, Ledwaba J, Mohapi L, Laher F, Karstaedt A, et al. Viremia and drug resistance among HIV-1 patients on antiretroviral treatment: a cross-sectional study in Soweto, South Africa. AIDS [Internet]. 2010/05/11 ed. 2010;24(11):1679–87. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20453629
  18. Hosseinipour MC, Gupta RK, Van Zyl G, Eron JJ, Nachega JB. Emergence of HIV Drug Resistance During First- and Second-Line Antiretroviral Therapy in Resource-Limited Settings. J Infect Dis [Internet]. Oxford University Press; 2013 Jun 15;207(Suppl 2):S49–56. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708738/
  19. Shafer RW, Kantor R, Gonzales MJ. The genetic basis of HIV-1 resistance to reverse transcriptase and protease inhibitors. AIDS Rev. 2000/01/01 ed. 2000;2(4):211–28.
  20. Johnson VA, Calvez V, Gunthard HF, Paredes R, Pillay D, Shafer RW, et al. Update of the drug resistance mutations in HIV-1: March 2013. Top Antivir Med. 2013/04/19 ed. 2013;21(1):6–14.
  21. Shafer RW. Genotypic testing for human immunodeficiency virus type 1 drug resistance. Clin Microbiol Rev. 2002/04/05 ed. 2002;15(2):247–77.
  22. Banks L, Gholamin S, White E, Zijenah L, Katzenstein DA. Comparing peripheral blood mononuclear cell DNA and circulating plasma viral RNA pol genotypes of subtype C HIV-1. J AIDS Clin Res. 2012/09/29 ed. 2012;3(2):141–7.
  23. Rossouw T, Lessells R, de Oliveira T. HIV & TB drug resistance & clinical management case book. South African Medical Research Council Press; 2013.



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With the contributions from a dedicated and professional staff complement, BRTI has achieved  20 years of continuing growth. From its inception in 1995, the BRTI has strived to become a a centre for excellence in health research and training in Africa. We are confident that the philosophy behind the formation of BRTI, that African scientists must take responsibility for improving their own working environment, was correct. We predict that, in spite of a degree of economic uncertainty in Zimbabwe, the gains that have been made during these years can be consolidated and expanded. We look forward to the future with confidence.

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