Literature DB >> 32267869

Polymorphisms and drug resistance analysis of HIV-1 isolates from patients on first line antiretroviral therapy (ART) in South-eastern Nigeria.

Augustine O Udeze1,2, David O Olaleye1, Georgina N Odaibo1.   

Abstract

Acquisition of resistance mutations by HIV-1 isolates causes treatment failure among infected patients receiving antiretroviral therapy (ART). This study determined patterns of drug-resistance mutations (DRMs) among HIV-1 isolates from patients receiving first-line ART in South-eastern Nigeria. Blood samples were collected from HIV-1 infected patients accessing antiretroviral treatment centers at General Hospital Awo-Omamma, Imo state, State Hospital Asaba, Delta state and St Joseph's Catholic Hospital Adazi, Anambra state and used for HIV-1 DNA sequencing and phylogenetic analysis. DRMs were scored using combination of Stanford algorithm and the 2015 International Antiviral Society-USA list while drug susceptibility was predicted using Stanford algorithm. Twenty eight of the HIV-1 isolates were sequenced and identified as subtypes G (35.7%), CRF02_AG (57.1%) and unclassifiable, UG (7.1%). Major PI resistance-associated mutations were identified at two sites including M46L (16.7% of subtype G/UG) and V82L (6.3% of CRF02_AG). Minor PI resistance-associated mutations identified among subtype G/UG are L10V/I (8.3%) and K20I (100%) while L10V/I (50%), K20I (100%), L33F (6.3%) and N88D (6.3%) were identified among CRF02_AG. Other polymorphisms found include; I13V/A, E35Q, M36I/L, N37D/S/E/H, R57K/G, L63T/P/S/Q, C67E/S, H69K/R, K70R, V82I and L89M in the range of 28.6% to 100% among the different subtypes. Interpretation based on Stanford algorithm showed that Darunavir/ritonavir is the only regimen whose potency was not compromised by the circulating mutations. Identification of major and minor PI resistance mutations in this study underscores the need for drug resistance testing prior to initiation of second line antiretroviral therapy in Nigeria.

Entities:  

Year:  2020        PMID: 32267869      PMCID: PMC7141668          DOI: 10.1371/journal.pone.0231031

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Human immunodeficiency virus type-1 (HIV-1) is characterized by high level of genetic diversity with the distribution of the different variants varying by regions globally [1]. Due to the unstable nature of its genome, new variants continue to emerge especially in areas with circulating multiple subtypes [2]. Despite increasing availability of antiretroviral (ARV) drugs, the genetic diversity posed a major challenge to global management of HIV infection. The use of Highly Active Antiretroviral Therapy (HAART) proved highly effective yet treatment failure remains a common occurrence among patients. In addition to adherence issues [3], emergence of drug resistant variants has been identified as a major obstacle to the effectiveness of antiretroviral therapy (ART) and one of the leading causes of treatment failure [4]. Emergence of drug resistance variants of HIV-1 has been attributed to mutations within the HIV-1 pol genes that encode the molecular targets for major ARV drugs [5]. A number of factors are believed to contribute to the acquisition of drug resistance in Africa including; lack of plasma viral load monitoring [6], drug interactions [7], treatment interruptions due to drug stock-outs [8] and the use of substandard antiretroviral regimens [9]. Available data shows that effectiveness of ARV therapy is also influenced by both viral subtype and pre-existing mutations [10, 11]. Furthermore, it has been postulated that the pathways to drug resistance may be affected by pre-existing polymorphisms among different HIV-1 subtypes [12]. Most reports on HIV-1 drug resistance so far has focused on subtype B viruses which is prevalent in the Western world. There is however comparatively little available data from less developed countries where non-B subtypes predominate. In Nigeria where the epidemic is largely driven by non-B subtypes, reports on HIV drug resistance and polymorphisms [12-21] have primarily focused on resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) and nucleoside reverse transcriptase inhibitors (NRTIs) while resistance to Protease inhibitors (PI) remain understudied. Since the commencement of ART program in Nigeria in 2001, government has collaborated with some donor agencies such as Global Fund to Fight AIDS, Tuberculosis, and Malaria and US President’s Emergency Plan for AIDS Relief (PEPFAR) to scale up its ART clinics. With subsequent revision of the treatment guidelines by WHO first in 2010 [22], 2013 [23] and more recently in 2016 [24], initiation of ART for infected individuals is now recommended regardless of WHO clinical stage and at any CD4 cell count as against the previous ≤200 cells/mm3 during the pre-2010 era. This greatly increased the number of patients commencing first-line ART with anticipated increase in development of drug resistance. In Nigeria the recommended first line ARV drugs between 2010 and 2013 were AZT+3TC +EFV OR AZT+3TC+NVP OR TDF +3TC (or FTC) + EFV OR TDF +3TC (or FTC) + NVP. Patients failing first-line ARV treatments require switching to second-line regimens. Drug-regimens consist mostly of NNRTIs and NRTIs in the first-line with the addition of protease inhibitors (PIs) in the second-line. Adequate knowledge of drug resistance mutations and polymorphisms in protease gene of the circulating strains is therefore needed to help optimize the selection of second-line regimens for patients who are failing first-line regimens and limit the acquisition of cross-resistance. The aim of this study was to characterize and determine the polymorphisms and drug resistance mutations to PIs of HIV-1 isolates from first-line ART-experienced individuals in South-eastern Nigeria.

Materials and methods

Study participants and sample collection

The study participants included 28 HIV-1-infected individuals assessing therapy at HIV clinics located in General Hospital Awo-Omamma, Imo state; State Hospital Asaba, Delta state and St Joseph’s Catholic Hospital Adazi, Anambra state between February and May 2012. They consisted of 11 males and 17 females with mean age of 34.7 years (range: 25–50 years). HIV infected patients who are receiving treatment are included in the study while drug naïve patients are excluded. About 5ml of venous blood samples were collected from each participant for the study after informed consent. The study protocol was approved by University of Ibadan/UCH ethical review board (UI/EC/11/0178). Due to high level of patients with no formal education, option of verbal/oral consent was adopted as the ethics committee was not specific on mode.

DNA extraction, nested PCR, sequencing and phylogenetic analysis

Genomic DNA was extracted from the samples using modified phenol-chloroform extraction procedure and precipitated using ethanol. Nested polymerase chain reaction was used to amplify a 524-bp fragment of the pol gene from the extracted DNA. The first round PCR primers were OJ1 (5′-AAATGATGACAGCATGTCAGGGAG-3′; HXB2, 1823–1846) and OJ2 (5′- TATCTACTTGTTCATTTCCTCCAAT-3′; HXB2, 4173–4197) while the second round primers were OJ3 (5′-AGACAGGCTAATTTTTTAGGGA-3′; HXB2, 2074–2095) and OJ4 (5′-CATTCCTGGCTTTAATTTTACTGG-3′; HXB2, 2574–2597) [12]. The PCR products were separated by agarose gel electrophoresis. The amplicons were purified using WIZARD Purification Kit (Promega) according to manufacturer’s protocol. The protease gene was sequenced using Big Dye Terminator Cycle Sequencing Ready Reaction kit v3.1 (Applied Biosystems, Foster City, CA, USA) with primers OJ3 and OJ4 as sequencing primers. Sequences were generated using ABI Prism 3130 XL genetic analyzer (Applied Biosystems, California, USA). The sequences were aligned with HIV-1 protease reference sequences of various subtypes downloaded from the Los Alamos HIV Sequence Database (www.hiv.lanl.gov). Phylogenetic inferences were performed by the neighbour-joining method with 1,000 bootstrap replicates under Kimura’s two-parameter correction using MEGA 6.06. The evolutionary distances were computed using the Maximum Composite Likelihood method and are in the units of the number of base substitutions per site [25]. Sequences have been deposited in the GenBank with accession numbers MF458138- MF458165.

Drug resistance mutation analysis and prediction of susceptibility

The nucleotide sequences were translated to amino acid sequences using MEGA 6.06 software. The whole protease gene was analyzed to identify potential drug resistance mutations (DRMs), polymorphisms at DRM sites, and subtype-specific polymorphisms. DRMs were classified as minor or major base on the September 15, 2016 updated HIV drug resistance data base (http://hivdb.stanford.edu) and the latest definition of the International Antiviral Society (IAS-USA) mutation lists updated in 2015 [26]. Possible impact of the DRMs on the therapeutic response was predicted by use of Stanford drug-resistance algorithm.

Results

Phylogenetic analysis of the sequences

Phylogenetic analysis revealed that 10 (35.7%) and 16 (57.1%) of the virus isolates were HIV-1G and CRF02_AG respectively while 2 (7.1%) sequences were unclassifiable. Blast results of sequences of these two isolates from the Los Alamos HIV-1 sequence database also showed that the isolates had closest similarity to HIV-1 subtype G and are hereby referred to as unclassified subtype G (UG) (Fig 1).
Fig 1

Phylogenetic tree of study sequences aligned with sequences of reference subtypes from Los Alamos database.

Multiple sequences alignment and phylogenetic tree were constructed using ClustalW and neighbour-joining algorithm with Maximum Composite Likelihood model in MEGA 6.06 software. Statistical significance of the tree topology was tested by 1000 bootstrap replication. Only bootstrap values ˃70% are displayed at the nodes. Study sequences are marked with solid blocks.

Phylogenetic tree of study sequences aligned with sequences of reference subtypes from Los Alamos database.

Multiple sequences alignment and phylogenetic tree were constructed using ClustalW and neighbour-joining algorithm with Maximum Composite Likelihood model in MEGA 6.06 software. Statistical significance of the tree topology was tested by 1000 bootstrap replication. Only bootstrap values ˃70% are displayed at the nodes. Study sequences are marked with solid blocks.

Amino acid diversity of the protease region

The amino acid alignment of the samples with subtype B consensus (Cons B) is shown in Fig 2. The sequence analysis of the Protease showed total variation in 41 out of the 99 amino acid positions (41.4% of variation) when compared to Cons B. There were no insertions or deletions in the sequence. High variation was observed for amino acid positions I13(100.0%), K14(48.4%), K20(100.0%), E35(60.7%), M36(100.0%), R41(89.3%), R57(42.9%), L63(53.6%), C67(42.9%), H69(100.0%), V82(46.4%) and L89(100.0%) among the isolates in this study.
Fig 2

Alignment of protease amino acid sequences of the isolates compared with the subtype B consensus (cons B) sequence.

Amino acids are represented by the single-letter amino acid code. Each amino acid residue not differing from the reference sequence is represented by a dot.

Alignment of protease amino acid sequences of the isolates compared with the subtype B consensus (cons B) sequence.

Amino acids are represented by the single-letter amino acid code. Each amino acid residue not differing from the reference sequence is represented by a dot.

Mutations and polymorphisms at previously characterized drug resistance sites

Major drug resistance mutations were identified at two protease sites (M46L and V82L) previously characterized for drug resistance in three of the sequences (Table 1). Polymorphisms at known secondary mutation sites (K20I, M36I/L, H69K/R and L89M) were found in all the samples while L63T/P/S/Q was found in 83.3% (10/12) and 31.3% (5/16) of subtypes G/UG and CRF02_AG respectively. Furthermore, a polymorphism at a known primary mutation site (V82I) was found in all subtype G/UG samples. Other common mutations at positions not selected for drug resistance include; I13V/A which occurred in all the samples; C67E/S found in all subtypes G/UG; E35Q occurred in 91.7% of subtypes G/UG; N37D/S/E/H which occurred in 41.7% and 25.0% of subtypes G/UG and CRF02_AG respectively. Also R57K/G occurred in 83.3% (10/12) of subtypes G/UG and 12.5% (2/16) of CRF02_AG. The frequency of occurrence of the different mutations and/or polymorphisms is shown in Table 2. It is important to note that C67E/S, V82I and E35Q mutations were found only among the G/UG isolates.
Table 1

Protease mutations/polymorphisms detected among HIV isolates in South-Eastern Nigeria.

SampleSubtypeMutations/Polymorphisms
NG_AN.12_01GI13V, K14R, K20I, E35Q, M36I, R41K, K43R, M46L, R57K, Q61X, L63T, C67E, H69K, K70R, V82I, L89M
NG_AN.12_02GK20I, I13V, K14R, E35Q, M36I, R41K, K43R, M46L, R57K, L63T, C67E, H69K, K70R, V82I, L89M
NG_AN.12_03GI13V, K20I, E35Q, M36I, R41K, R57K, L63P, C67E, H69K, V82I, L89M
NG_AN.12_04CRF02_AGL10V, I13V, L19P, K20I, E35D, M36I, R41K, R59G, H69K, L89M, G94R, C95W, N98H
NG_AN.12_05GI13V, K20I, M36I, N37D, R41K, C67S, H69R, V82I, L89M
NG_AN.12_06GI13V, K14R, K20I, E35Q, M36I, N37S, R41K, K45R, R57K, L63S, C67E, H69K, V82I, L89M
NG_AN.12_07CRF02_AGI13A, K20I, M36I, R41K, H69K & L89M
NG_AN.12_08CRF02_AGL10V, I13V, L19P, K20I, E35D, M31I, R41K, H69K, K70R, L89M
NG_AN.12_09GL10M, I13V, K20I, E35Q, M36I, R41K, R57K, I62V, L63P, I64L, C67E, H69K, V82I, L89M
NG_AN.12_10CRF02_AGI13V, K20I, M36I, N37S, L63S, H69K, K70R, I72M, L89M
NG_DE.12_01CRF02_AGI13V, K14R, G16E, K20I, E35D, M36I, R41K, H69K, L89M
NG_DE.12_02CRF02_AGI13V, K14R, G16E, K20I, M36I, R41K, H69K, K70R, I72T, L89M
NG_DE.12_03GI13V, K20I, E35Q, M36I, R41K, R57K, L63P, C67E, H69K, V82I, L89M, Q92W
NG_DE.12_04CRF02_AGL10I, I13V, K14R, I15V, L19I, K20I, M36I, R41K, I64M, H69K, K70R, L89M
NG_DE.12_05CRF02_AGI13V, K20I, E35D, M36I, R41K, H69K, K70R, L89M, L97K, F99S
NG_DE.12_06CRF02_AGI13V, K14R, K20I, M36I, R41K, I64L, E65D, H69K, L89M
NG_DE.12_07CRF02_AGI13V, K14R, G17E, K20I, M36I, R41K, H69K, L89M
NG_DE.12_08GL10I, I13V, K14R, K20I, E35Q, M36I, R41K, R57K, L63Q, C67E, H69K, V82I, L89M
NG_DE.12_09UGI13V, K20I, E35Q, M36I, N37E, L63S, C67E, H69R, V82I, L89M
NG_DE.12_10CRF02_AGL10V, T12A, I13V, I15V, L19P, K20I, M36I, R41K, K43R, L63P, H69K, K70R, L89M
NG_IM.12_01CRF02_AGL10V, I13V, G16E, K20I, E35D, M36I, R41K, I64M, H69K & L89M
NG_IM.12_02GI13V, K14R, K20I, E35Q, M36I, N37D, R41K, R57K, C67E, H69R, V82I, L89M
NG_IM.12_03CRF02_AGI13V, K14R, K20I, M36I, R41K, I64L, H69K, L89M
NG_IM.12_04CRF02_AGI13V, K14R, K20I, E35D, M36I, N37S, R41K, L63S, H69K, L89M
NG_IM.12_05CRF02_AGI13V, L19P, K20I, L33F, M36L, N37H, L38I, R41K, K43R, R57K, L63P, H69K, L89M
NG_IM.12_06UGI13V, G17E, K20I, E35Q, M36I, N37E, R57K, L63S, C67E, H69R, V82I, L89M
NG_IM.12_07CRF02_AGL10I, I13V, K14R, K20I, M36I, N37S, R41K, L63S, H69K, I72V, P79S, V82L, G86L, R87L, N88D, L89M, T91C, Q92H, G94I, T96A, L97V, N98H
NG_IM.12_08GI13V, K20I, E35Q, M36I, R41K, K45R, R57K, L63P, C67E, H69K, V82I, L89M

Key: PI Major Resistance Mutations are in bold face, PI Minor Resistance Mutations are in italics, and other mutations are in regular face.

Table 2

Frequency of occurrence of mutations and/or polymorphisms in protease by HIV subtypes.

No. (%) of mutationsNo. (%) of mutations
MutationSubtype G & UG (n = 12)CRF02_AG (n = 16)MutationSubtype G & UG (n = 12)CRF02_AG (n = 16)
L10V/I1 (8.3)6(50.0)L63T/P/S/Q10(83.3)5 (31.3)
L10M1(8.3)-I64L/M1(8.3)4(25.0)
T12A-1(6.3)E65D-1(6.3)
I13V/A12(100.0)16(100.0)C67E/S12(100.0)-
K14R6(50.0)7(43.8)H69K/R12(100.0)16(100.0)
I15V-2(12.5)K70R2(16.7)6(37.5)
G16E-3(18.8)I72M/T/V-3(18.8)
G17E1(8.3)1(6.3)P79S-1(6.3)
L19P-5(31.3)V82I12(100.0)-
K20I12(100.0)16(100.0)V82L-1(6.3)
L33F-1(6.3)G86L-1(6.3)
E35Q11(91.7)-R87L-1(6.3)
E35D-6(37.5)N88D-1(6.3)
M36I/L12(100.0)16(100.0)L89M12(100.0)16(100.0)
N37D/S/E/H5(41.7)4 (25.0)T91C-1(6.3)
L38I-1(6.3)Q92W/H1(8.3)1 (6.3)
R41K10(83.3)15(93.8)G94R/I-2(12.5)
K43R2(16.7)2(12.5)C95W-1(6.3)
K45R2(16.7)-T96A-1(6.3)
M46L2(16.7)-L97K/V-`2(12.5)
R57K/G10(83.3)2(12.5)N98H-2(12.5)
I62V1(8.3)-F99S-1(6.3)

Keys: Numbers correspond to amino acid positions. The first letter corresponds to the wild-type amino acid; the substituted amino acid is coded by the last letter.

Key: PI Major Resistance Mutations are in bold face, PI Minor Resistance Mutations are in italics, and other mutations are in regular face. Keys: Numbers correspond to amino acid positions. The first letter corresponds to the wild-type amino acid; the substituted amino acid is coded by the last letter.

Drug resistance analysis

Major mutation that confers resistance to protease inhibitors, M46L was found in two out of the twelve (16.7%) subtypes G/ UG sequences while V82L, was present in one out of the sixteen (6.3%) CRF02_AG sequences. Minor PI mutations detected among the isolates include; L10I/V [7/28 (25.0%)], K20I [28/28 (100%)], L33F [1/28 (3.6%)] and N88D [1/28 (3.6%)]. The different PI-resistance mutations and the patterns of resistance to the different PIs are shown in Table 3.
Table 3

PI resistance patterns among the HIV isolates from South-eastern Nigeria.

SampleSubtypeMajor mutationMinor mutationATV/rDRV/rFPV/rIDV/rLPV/rNFVSQV/rTPV/r
NG_AN.12_01GM46LK20IPSPPPISP
NG_AN.12_02GM46LK20IPSPPPISP
NG_AN.12_03G-K20ISSSSSPSS
NG_AN.12_04CRF02_AG-L10V, K20ISSSSSPSS
NG_AN.12_05G-K20ISSSSSPSS
NG_AN.12_06G-K20ISSSSSPSS
NG_AN.12_07CRF02_AG-K20ISSSSSPSS
NG_AN.12_08CRF02_AG-L10V, K20ISSSSSPSS
NG_AN.12_09G-K20ISSSSSPSS
NG_AN.12_10CRF02_AG-K20ISSSSSPSS
NG_DE.12_01CRF02_AG-K20ISSSSSPSS
NG_DE.12_02CRF02_AG-K20ISSSSSPSS
NG_DE.12_03G-K20ISSSSSPSS
NG_DE.12_04CRF02_AG-L10I, K20ISSSSSPSS
NG_DE.12_05CRF02_AG-K20ISSSSSPSS
NG_DE.12_06CRF02_AG-K20ISSSSSPSS
NG_DE.12_07CRF02_AG-K20ISSSSSPSS
NG_DE.12_08G-L10I, K20ISSSSSPSS
NG_DE.12_09UG-K20ISSSSSPSS
NG_DE.12_10CRF02_AG-L10V, K20ISSSSSPSS
NG_IM.12_01CRF02_AG-L10V, K20ISSSSSPSS
NG_IM.12_02G-K20ISSSSSPSS
NG_IM.12_03CRF02_AG-K20ISSSSSPSS
NG_IM.12_04CRF02_AG-K20ISSSSSPSS
NG_IM.12_05CRF02_AG-K20I, L33FSSPSSLSP
NG_IM.12_06UG-K20ISSSSSPSS
NG_IM.12_07CRF02_AGV82LL10I, K20I N88DLSLPPILI
NG_IM.12_08G-K20ISSSSSPSS

ATV = Atazanavir; DRV = Darunavir; FPV = Fosamprenavir; IDV = Indinavir; LPV = Lopinavir; NFV = Nelfinavir; SQV = Saquinavir; TPV = Tipranavir; r = ritonavir; S, P, L and I indicate Susceptible, Potential low-level, Low-level and intermediate-level resistant to drugs respectively

ATV = Atazanavir; DRV = Darunavir; FPV = Fosamprenavir; IDV = Indinavir; LPV = Lopinavir; NFV = Nelfinavir; SQV = Saquinavir; TPV = Tipranavir; r = ritonavir; S, P, L and I indicate Susceptible, Potential low-level, Low-level and intermediate-level resistant to drugs respectively Fig 3 shows the frequency of occurrence of the predicted viral susceptibility of the isolates to PIs. Of these virus sequences harbouring ≥1 DRM, susceptibility to boosted Darunavir was maintained in all (100%) of the isolates. Reduced susceptibility was predicted for boosted Atazanavir, Indinavir and Lopinavir in about 11% of sequences, Saquinavir in 4%, Fosamprenavir and Tipranavir in 14%. Reduced HIV-1 susceptibility was predicted for the only non-boosted Nelfinavir in all (100%) of the sequences due to general presence of K20I.
Fig 3

Predicted susceptibility of the isolates to protease inhibitors (PIs).

ATV = Atazanavir, DRV = Darunavir, FPV = Fosamprenavir, IDV = Indinavir, LPV = Lopinavir, NFV = Nelfinavir, SQV = Saquinavir, TPV = Tipranavir, r = Ritonavir.

Predicted susceptibility of the isolates to protease inhibitors (PIs).

ATV = Atazanavir, DRV = Darunavir, FPV = Fosamprenavir, IDV = Indinavir, LPV = Lopinavir, NFV = Nelfinavir, SQV = Saquinavir, TPV = Tipranavir, r = Ritonavir.

Discussion

The frequency of occurrence (10.7%) of major PI resistance mutations, M46L and V82L, obtained in this study is somewhat lower than the 39.1% recorded in a similar study conducted by Odaibo et al. [17] on pattern of HIV-1 drug resistance among adults on ART in Nigeria. However, some other studies conducted in different parts of the country on both drug naïve and experienced patients reported no major PI resistance mutations [18, 19]. Acquisition of PI resistance is known to be cumulative in nature requiring sequential accumulation of mutations in the setting of on-going exposure to non-suppressive PI-based ART [27, 28]), therefore the appreciable level of IAS PR mutation detected among the patients in our study is a serious cause for concern as it places them at increased risk of accumulating additional PI resistance mutations. M46I/L is a nonpolymorphic PI-selected mutation that reduces susceptibility to indinavir (IDV), nelfinavir (NFV), fosamprenavir (FPV), lopinavir (LPV) and atazanavir (ATV) when present with other mutations. M46L also reduces susceptibility to tipranavir (TPV). This mutation which occurred at a frequency of 7.14% among all the isolates and frequency of 16.7% among the subtype G isolates accounted for over 66.0% of all the major PI resistance mutations identified in this study. Again, this is also similar to the report of Odaibo et al. [17] which reported this mutation at a frequency of 55.6%. Although our study did not determine the phenotypic resistance pattern in the infected individuals (a limitation of the study), analysis according to the Stanford algorithm showed that M46L mutation confers potential low-level resistance to ATV/r, FPV/r, IDV/r, LPV/r, TPV/r and intermediate-level resistance to NFV to isolates in this study as shown in Table 3. Mutations at positions 82 and 88 generally co-exist and result in contraindication to many PIs particularly NFV [29]. In line with this, the only isolate with V82L mutation in this study, NG_IM.12_07, also harbours N88D mutation in addition to L10I and K20I mutations. This V82L mutation is shown to confer low-level resistance to ATV/r, FPV/r and SQV/r as well as potential low-level resistance to IDV/r and LPV/r while it confers intermediate-level resistance to NFV and TPV/r. All the patients had preserved susceptibility to DRV/r since it is the only PI drug analysed that was not selected by any resistance mutation. Similar observations had been reported in a more widespread study in Nigeria which examined the impact of maintaining patients on failing second line ART on the accumulation of PR mutations [30]. Isolates in this study also showed high level of susceptibility (96.4%) to SQV/r. The only isolate with intermediate-level resistance to these drugs had V82L major PI resistance mutation as well as L10I and N88D minor PI resistance mutations. V82L is an uncommon non-polymorphic substrate-cleft mutation known to reduce susceptibility to TPV. This mutation was reported at a frequency of 22.2% in a similar study by Odaibo et al. [17]. The different degrees of resistance mutations to the second-line PI drugs in isolates from patients still on first-line ART is worrisome as this is a prelude to treatment failure even before switching to second-line ART. This further limits the choice of treatment regimen available for patients failing first-line therapy when the need arises. Our study also revealed very high frequencies of minor mutations in the protease gene of the isolates with the predominant mutations found at positions L10I/V and K20I. Similar finding was reported in Jos, North-Central Nigeria among isolates from ART-naïve patients [16]. Although the presence of these minor mutations do not lead to high level resistance when occurring alone, they have to be taken into account by physicians before making treatment decisions as they may play a role in improving viral fitness or increasing the drug resistance level in the presence of major PI mutations [31-34]. Pol gene polymorphisms usually occur in non-B HIV-1 strains as genetic fingerprints that lowers their susceptibility to ARV compounds [35-37]. Other mutations/polymorphisms that occurred at very high frequencies among patients in this study include; I13V/A, K20I, E35Q, M36I/L, R41K, R57K/G, L63T/P/S/Q, C67E/S, H69K/R, V82I and L89M. Similar mutations/polymorphic substitutions in the protease region had been reported earlier for some Nigerian isolates [13]. I13V/A, K20I, M36I/L, R41K, H69K/R and L89M are the consensus mutations identified for subtypes G, UG and CRF02_AG while E35Q, R57K/G, C67E/S and V82I are the consensus mutations for G and UG in this study. A study on PI-naive Nigerian HIV-patients have earlier identified I13V, M36I and H69K as wild-type consensus mutations for HIV-1 subtypes G′, G, CRF02_AG, CRF06_cpx, and A. The same study also identified K20I as consensus for G′, G, CRF02_AG, and CRF06_cpx while V82I was identified as the consensus for G′ and G [14]. Although our study utilized samples from first-line drug experienced individuals, the findings are consistent with these earlier reports from drug naïve individuals. In addition, the mutations K14R, N37D/S/E/H and L63T/P/S/Q occurred in ≥ 25% of subtype G, UG and CRF02_AG patients, at a proportion that is significantly greater than in subtype B. Similarly, mutations L10V/I, L19P, E35D, I64L/M and K70R occurred in ≥ 25% of CRF02_AG patients at a proportion that is significantly greater than in subtype B in this study. There is already a concern that treatment of non-subtype B infected persons with PI could be less effective as a result of higher frequency of polymorphism in the protease gene of non-B isolates including positions 20, 36, 63 and 82 [10]. The limitation of this study however is the small sample size (28 samples) analysed. A larger sample size would have showed a clearer picture of the situation. In conclusion, we have shown that major and minor PI drug resistance mutations occur in significant proportions of non-B HIV-1 strains circulating among first-line drug experienced individuals in south-eastern Nigeria. This study also demonstrated differences in the distribution pattern of these mutations between subtypes G and CRF02_AG isolates. The high level of these drug resistance mutations will not augur well for PI treatment interventions. This result therefore underscores the need for periodic genotypic DR testing of patients on ART and prior to second-line ART switch for early detection of DR mutations and selection of appropriate treatment regimens. The only challenge however is the high cost of carrying out these tests which may limit its implementation in resource limited settings. 4 Sep 2019 PONE-D-19-17545 Polymorphisms and drug resistance analysis of HIV-1 isolates from patients on first line antiretroviral therapy (ART) in South-eastern Nigeria PLOS ONE Dear Dr. Odaibo, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. We would appreciate receiving your revised manuscript by Oct 19 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. 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The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Our internal editors have looked over your manuscript and determined that it is within the scope of our Antimicrobial Resistance call for papers. This collection of papers is headed by a team of Guest Editors for PLOS ONE: Kathryn Holt (Monash University and London School of Hygiene and Tropical Medicine), Alison H. Holmes (Imperial College London), Alessandro Cassini (WHO Infection Prevention and Control Global Unit), Jaap A. Wagenaar (Utrecht University). The Collection will encompass a diverse range of research articles; additional information can be found on our announcement page: https://collections.plos.org/s/antimicrobial-resistance. If you would like your manuscript to be considered for this collection, please let us know in your cover letter and we will ensure that your paper is treated as if you were responding to this call. If you would prefer to remove your manuscript from collection consideration, please specify this in the cover letter. 3. Please specify in your ethics statement: 1) whether the ethics committee approved the verbal/oral consent procedure, 2) why written consent could not be obtained, and 3) how verbal/oral consent was recorded.” Do not ping with follow up unless there are questions, in which case, ping me. Additional Editor Comments (if provided): This a cross-sectional of HIV drug resistance in persons on first-line ART in Nigeria. While 3 study sites were include, the overall population size is modest.  It is unclear why only a very short study period (February to May 2012) was included. Have the authors explored the two “unclassifiable” sequences in more detail?  What are the closest hits in a Blast search? For Table 2, were there any statistically significant differences in mutations when the data are stratified by subtype? If the point of Figure 2 is to show polymorphism at particular amino acid sites, creating a WebLogo for this region would better illustrate this. It is unclear from the introduction what specific antiretroviral therapies were available in this region of Nigeria during the 2012 study period. Limitations of the current study should be described in more detail in the Discussion. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Partly ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: N/A Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: ART use has greatly reduced morbidity and mortality among people living with HIV, and subsequently improved life expectancy and quality of life. However, genetic diversity and specific genetic resistance pathways could impair these individual and community ART benefits in resource-limited settings. This study aimed to describe resistance patterns to PIs of HIV isolates from first-line drug experienced individual in Imo state (Nigeria). This study was conducted on 28 HIV-1 infected patient enrolled between February and may 2012 in a general hospital. Mains results of this study highlighted a significant polymorphism in HIV protease resistance gene. According to the Stanford drug-resistance algorithm, in this study, all the PIs excepted darunavir were affected by this important polymorphism and two non-polymorphic mutation M46L and V82L. Two HIV-1 non B subtypes G and CRF02_AG were described with differences in the pattern of these polymorphic mutations. Overall, this study reported the genetic diversity of HIV-1 in Nigeria and assessed the prevalence of the PIs drug resistance mutation in first ART first line experience individuals. PIs regimen outcomes in resource-limited settings can be impacted by the high prevalence of the genetic diversity and point out the necessity of genotypic resistance assays before switching to second-line ART. Strengths and weaknesses The research was conducted in ethical and sound research background. This paper is well organized and followed the manuscript guidelines of the journal to a large extent. This study confirms that in resource-limited west African countries, HIV-1 non-B subtypes are majority and have significant polymorphism on protease resistance codons, as described by several authors. The inclusion criteria should be more detailed, especially on the therapeutic aspects (patients being treated). The number of samples included should be explained. Details on the choice of the DNA matrix would be important additional information for the article understanding Please mention primers used reference. Reviewer #2: The study reported on PI drug resistance mutations that were present at first line failure in a cohort of patients from 3 states in south-eastern Nigeria. The study highlights the fact that major and minor PI mutations were found before the initiation of a PI-inclusive 2nd-line, with DRV the only fully active PI available. While the data does contribute to the knowledge of circulating subtypes in the region, a short-coming of the study is that the samples size is very small, especially since it is meant to be representative of the south-eastern region. The study would therefore benefit from an increased sample size. In addition, the naturally occurring polymorphisms in protease that are reported are already known for these subtypes. Specific comments: Line 117-118: Informed consent was already mentioned in line 116. Is this meant to be different? Line 148-150: it is not clear why these older versions of the drug resistance lists are cited here. Line 179: should be "L89 (100%)" Line 194: The V82I mutation is already known to occur in subtype G isolates. Line 324: "high level" is misleading as this occurs in only 2 isolates. Generally there are grammatical throughout the paper an would benefit from a language editor. Some are listed below. Line 55: should read "....multiple circulating subtypes." Line 67: "...ARV therapy..." Line 136: should read "...downloaded from the Los Alamos...." Line 146: should read "...protease gene..." Line 325: cause not "course" Line 327: should read "M46I/L is a nonpolymorphic PI-selected mutation that reduces...." Line 344: should read "....PI drug analysed …resistance mutation." Line 345 "observations" Line 354: "switching to..." ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step. 27 Dec 2019 Reviewer #1 Comment: The inclusion criteria should be more detailed, especially on the therapeutic aspects (patients being treated). Response: Done (lines 112-113) Comment: Please mention primers used reference. Response: Done (line 127) Submitted filename: Imo 3 (1).jpg Click here for additional data file. 16 Mar 2020 Polymorphisms and drug resistance analysis of HIV-1 isolates from patients on first line antiretroviral therapy (ART) in South-eastern Nigeria PONE-D-19-17545R1 Dear Dr. Odaibo, We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements. Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication. Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. With kind regards, Jason Blackard, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): None Reviewers' comments: None Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: All comments have been addressed specially on sample size, the method and the therapeutic regimen. The paper is good for publication. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No 23 Mar 2020 PONE-D-19-17545R1 Polymorphisms and drug resistance analysis of HIV-1 isolates from patients on first line antiretroviral therapy (ART) in South-eastern Nigeria Dear Dr. Odaibo: I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. For any other questions or concerns, please email plosone@plos.org. Thank you for submitting your work to PLOS ONE. With kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Jason Blackard Academic Editor PLOS ONE
  29 in total

1.  Increased fitness of drug resistant HIV-1 protease as a result of acquisition of compensatory mutations during suboptimal therapy.

Authors:  M Nijhuis; R Schuurman; D de Jong; J Erickson; E Gustchina; J Albert; P Schipper; S Gulnik; C A Boucher
Journal:  AIDS       Date:  1999-12-03       Impact factor: 4.177

Review 2.  Preventing and managing antiretroviral drug resistance.

Authors:  Daniel R Kuritzkes
Journal:  AIDS Patient Care STDS       Date:  2004-05       Impact factor: 5.078

3.  Selection of resistance in protease inhibitor-experienced, human immunodeficiency virus type 1-infected subjects failing lopinavir- and ritonavir-based therapy: mutation patterns and baseline correlates.

Authors:  Hongmei Mo; Martin S King; Kathryn King; Akhteruzzaman Molla; Scott Brun; Dale J Kempf
Journal:  J Virol       Date:  2005-03       Impact factor: 5.103

4.  Subtype-specific patterns in HIV Type 1 reverse transcriptase and protease in Oyo State, Nigeria: implications for drug resistance and host response.

Authors:  Akinyemi I Ojesina; Jean-Louis Sankalé; Georgina Odaibo; Stanley Langevin; Seema T Meloni; Abdoulaye Dieng Sarr; David Olaleye; Phyllis J Kanki
Journal:  AIDS Res Hum Retroviruses       Date:  2006-08       Impact factor: 2.205

5.  An increase in viral replicative capacity drives the evolution of protease inhibitor-resistant human immunodeficiency virus type 1 in the absence of drugs.

Authors:  Noortje M van Maarseveen; Dorien de Jong; Charles A B Boucher; Monique Nijhuis
Journal:  J Acquir Immune Defic Syndr       Date:  2006-06       Impact factor: 3.731

6.  Global and regional distribution of HIV-1 genetic subtypes and recombinants in 2004.

Authors:  Joris Hemelaar; Eleanor Gouws; Peter D Ghys; Saladin Osmanov
Journal:  AIDS       Date:  2006-10-24       Impact factor: 4.177

7.  Virological response and HIV drug resistance 12 months after antiretroviral therapy initiation at 2 clinics in Nigeria.

Authors:  Richard Ugbena; John Aberle-Grasse; Karidia Diallo; Orji Bassey; Tapdiyel Jelpe; Erin Rottinghaus; Aderemi Azeez; Raphael Akpan; Mukhtar Muhammad; Vedapuri Shanmugam; Satvinder Singh; Chunfu Yang
Journal:  Clin Infect Dis       Date:  2012-05       Impact factor: 9.079

Review 8.  Drug resistance in non-subtype B HIV-1.

Authors:  Rami Kantor; David Katzenstein
Journal:  J Clin Virol       Date:  2004-03       Impact factor: 3.168

9.  Short communication: Transmitted HIV drug resistance in antiretroviral-naive pregnant women in north central Nigeria.

Authors:  Godwin E Imade; Atiene S Sagay; Beth Chaplin; Philippe Chebu; Jonah Musa; Jonathan Okpokwu; Donald J Hamel; Ishaya C Pam; Oche Agbaji; Jay Samuels; Seema Meloni; Jean-Louis Sankale; Prosper Okonkwo; Phyllis Kanki
Journal:  AIDS Res Hum Retroviruses       Date:  2013-11-22       Impact factor: 2.205

10.  High levels of pre-treatment HIV drug resistance and treatment failure in Nigerian children.

Authors:  Ragna S Boerma; T Sonia Boender; Kim C E Sigaloff; Tobias F Rinke de Wit; Michael Boele van Hensbroek; Nicaise Ndembi; Titilope Adeyemo; Edamisan O Temiye; Akin Osibogun; Pascale Ondoa; Job C Calis; Alani Sulaimon Akanmu
Journal:  J Int AIDS Soc       Date:  2016-11-10       Impact factor: 5.396

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  1 in total

1.  Antiretroviral therapy resistance mutations among HIV infected people in Kazakhstan.

Authors:  Ainur Mukhatayeva; Aidana Mustafa; Natalya Dzissyuk; Alpamys Issanov; Zhussipbek Mukhatayev; Bauyrzhan Bayserkin; Sten H Vermund; Syed Ali
Journal:  Sci Rep       Date:  2022-10-13       Impact factor: 4.996

  1 in total

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