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Basic and Translational Science

HIV-1 Coreceptor Tropism in India

Increasing Proportion of X4-Tropism in Subtype C Strains Over Two Decades

Gupta, Soham MSc*,†; Neogi, Ujjwal MSc, PhD‡,§; Srinivasa, Hiresave MD; Banerjea, Akhil C. MSc, PhD; Shet, Anita MD*,¶,#

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: April 1, 2014 - Volume 65 - Issue 4 - p 397-404
doi: 10.1097/QAI.0000000000000046



The binding of HIV-1 to the host cell CD4 receptor is facilitated by a coreceptor, either C-C motif receptor 5 (CCR5) or C-X-C motif receptor 4. Based on the ability to use these coreceptors, the virus is classified either as R5-tropic (using CCR5), X4-tropic (using C-X-C motif receptor 4), or both.1–4 The initiation of HIV-1 infection mostly is caused by R5-tropic strains, which switches to more pathogenic X4-tropic strains during the later course of the disease. Although tropism switch from R5 to X4-tropic in later stages of the disease is reported to occur in 50% of subtype B strains, the phenomenon is thought to be rare in subtype C strains.5,6 In India, where subtype C strains dominates the epidemic, switch to X4-tropism was considered to be somewhat infrequent.6–8 However X4-tropism in subtype C strains may be more common than thought previously, as our group observed that switch to X4-tropism can occur with longer duration of infection and disease progression.9 Recent studies from Africa have also observed a higher prevalence of X4-tropism among HIV-1 subtype C strains compared with past years.10,11 But, there is very little information available on HIV-1 tropism in Indian subtype C strains and their growing prevalence over the years.

HIV-1 tropism can be assessed by phenotypic or genotypic methods.12–14 Compared with phenotypic tropism testing, genotypic tropism testing (GTT) is a feasible option because of its ease of performance, rapidity, and cost–effectiveness making it more suitable for routine clinical practice.12 GTT can be performed both in the plasma viral compartment and in the proviral compartment as was previously observed by us.15 GTT using whole blood DNA has an added advantage of easy collection and storage in remote areas and resource-limited settings.

The study of HIV-1 coreceptor tropism has thrown open avenues to study viral functionality, and associated therapeutic strategies, particularly, with the introduction of CCR5 inhibitor agents within the antiretroviral armamentarium. Maraviroc, a CCR5 antagonist approved by US Food and Drug Administration is active only against R5-tropic viruses and is also a potential therapeutic option for patients failing highly active antiretroviral therapy (ART).16 However, maraviroc fails to inhibit the entry of X4-tropic or dual tropic HIV-1 virus. R5-tropic strains can also escape from virological control by developing primary resistance to maraviroc. Both in vivo and in vitro studies have associated different sets of mutations with maraviroc resistance.17–19

In this study, we aim to characterize the predicted coreceptor tropism in clinical isolates obtained from 4 distant geographical regions of India along with sequences obtained from a secondary database. We also studied polymorphic patterns in the R5-tropic HIV-1 subtype C env V3 loop amino acid sequences, which are associated with maraviroc resistance. To the best of our knowledge, our study is the first to report the changing trends of genotypic coreceptor tropism over a period of more than 2 decades. These findings enhance our understanding of coreceptor tropism in Indian strains and provide contextual information useful for the consideration of CCR5-antagonist drugs in our setting.


Study Population

Peripheral blood samples were collected between 2007 and 2012 from 235 HIV-1–infected individuals hailing from different geographic locations of India; southern India (Karnataka, Andhra Pradesh, and Tamil Nadu; n = 130), northern India (Punjab and Haryana; n = 30), north-eastern India (Manipur; n = 50), and central India (Madhya Pradesh; n = 25). Ethical approval for the study was obtained from the St. John's Institutional Ethical Review Board. Written informed consent was obtained from all the participants or caregivers of the children. Patients' clinical and demographic information was noted from medical records.

Determination of Plasma Viral Load and CD4 Count

Plasma viral load (only from HIV-infected patients from southern India) was measured with Abbott m2000rt real-time polymerase chain reaction (PCR) (Abbott Molecular Diagnosis, Des Plaines, IL). CD4 count was determined using a dual-platform flow cytometer (FACSCalibur; Becton Dickinson Biosciences, San Jose, CA) or personal cell analyzer system (Guava Technologies Inc., Hayward, CA).

Database-Derived Sequences

Indian (n = 528) HIV-1 subtype C env V3 loop sequences tested in the period between 1991 and 2012 were downloaded from the Los Alamos database (accessed on 25th April 2012) after selecting 1 sequence per patient. Using the search interface of the Los Alamos database (accessed on 15th December 2012), only CCR5-tropic global subtype C (n = 308) and subtype B (n = 576) sequences from the sequence information system were selected and downloaded for assessing the presence of polymorphisms in the V3 loop.

Prediction of Genotypic Coreceptor Tropism

Genomic DNA from whole blood was extracted using a commercial kit (QIAamp Blood DNA kit; Qiagen, Hilden, Germany). The viral env gene encoding the V3–V4 region was amplified from whole-blood genomic DNA of all the patients using a nested PCR protocol as reported previously.20 Briefly, V3 region was enumerated using the nested PCR technology with the outer primers, ED5 (forward) 5′-ATGGGATCAAAGCCTAAAGCCATGTG-3′ (HXB2 nt 6556–6581) and ED12 (reverse) 5′-AGTGCTTCCTGCTGCTCCCAAGAACCCAAG-3′ (HXB2 nt 7822-7792), and inner primers were IN_ES7 (forward) 5′-CTGTTAAATGGCAGCCTAGC-3′ (HXB2 nt 7001–7020) and IN_ES8 (reverse) 5′-CACTTCTCCAATTGTCCCTCA-3′ (HXB2 nt7647-7667). The second round PCR amplicons were purified using QIAquick kit (Qiagen), followed by bidirectional population sequencing in 3730xl DNA analyzer (Applied Biosystems, Foster City, CA). The sequences thus generated were manually edited in Bio-Edit version, and the env V3 region was extracted for analysis. Tropism was determined using the bioinformatics software Geno2Pheno[coreceptor] (, which uses support vector machine technology. The false positive rate (FPR) output of the algorithm is defined as the probability of wrongly classifying an R5 strain as X4. The FPR value of 10% was used as threshold for X4 tropism determination in accordance with the European guidelines for tropism testing.13

Drug Resistance Genotyping

Drug resistance genotyping targeting reverse transcriptase (RT) region of the pol gene was performed on southern Indian samples showing treatment failure, using externally validated in-house methodology.21 The drug resistance–associated mutations documented because of selection pressure of antiretroviral drugs were analyzed and interpreted using International AIDS Society, US-updated drug resistance mutations in HIV-1 (IAS_2013), which includes 19 nucleoside reverse transcriptase inhibitor mutations in 16 positions (41, 62, 65, 67, 69, 70, 74, 75, 77, 115, 116, 151, 184, 210, 215, and 219) and 34 nonnucleoside reverse transcriptase inhibitor mutations in 16 positions (90, 98, 100, 101, 103, 106, 108, 138, 179, 181, 188, 190, 221, 225, 227, and 230) between amino acid residues 17–235 of RT region of Pol under study.22

HIV-1 Subtyping

HIV-1 subtyping was performed based on 2 genes as was described by us previously.20 We used the env gene sequences (V3–V4) and either pol (RT) or gag (p17) sequences of the clinical samples with reference sequences of different subtypes downloaded from Los Alamos database to construct maximum-likelihood phylogenetic tree using general time reversal substitution model and inverse gamma distribution (GTR + G + I) and 1000 bootstrapped data sets in MEGA 5.05.23 Any clinical samples showing clustering with non-C subtypes were further screened using Recombination Identification Program version 3 (RIP 3.0; available at:

Statistical Analysis

In this study, the age of patients, their duration of ART, CD4 count, and viral load in log10 copies, were described. Quantitative data were grouped into respective quartiles. The categorical variables were compared using Fisher exact test, and continuous variables were analyzed using the Mann–Whitney U nonparametric test.


Patients' Characteristics

Among the 235 samples from different regions of India, successful V3 loop amplification and sequencing was performed in 224 samples representing southern India (n = 126), northern India (n = 27), north-eastern India (n = 47), and central India (n = 24). These 224 patients were mostly men (n = 163; 72.8%) and ART-naive (n = 176; 78.6%) with a mean age of 35.5 ± 9.5 years (range, 5–60 years). According to the self-reported mode of transmission of HIV-1, 75.4% of the patients acquired the infection through heterosexual contact (n = 169), and 18.3% of the subjects hailing from Manipur (north-eastern India) were intravenous drug users (IDUs) (n = 41). Table S1 (see Supplemental Digital Content, shows the patients' available demographic and clinical characteristics.

HIV-1 Subtyping and Tropism

Based on env sequences, subtype C prevalence was noted at 88% (197/224); 27 samples (12%) were non-C subtype, which consisted of subtype B (n = 3), unique recombinant form BC (n = 18) and unique recombinant form A1C (n = 6). The majority of the non-C subtypes were contributed by the north-eastern Indian samples (36.2%) followed by north Indian samples (18.5%).

Using an FPR of 10% in Geno2Pheno, X4 tropism was predicted in 25 (11.2%) samples. Among the subtype C strains, the X4 tropism was noted at 10.2% (20/197) and in non-C subtypes at 18.5% (5/27), showing no significant difference (P = 0.2). The prevalence of X4 tropism in different regions of India is shown in Figure 1. The prevalence of X4 tropism in north-eastern India (19.1%) was higher compared with southern India (9.1%), central India (8.3%), and northern India (7.4%).

Distribution of R5 and X4-tropic strains in different geographic locations of India. Patient samples were obtained from the following regions: southern India [(Karnataka, Tamil Nadu, and Andhra Pradesh), northern (Punjab and Haryana), north-eastern (Manipur), and central India (Madhya Pradesh)]. The pie chart shows the percentage of R5-tropic and X4-tropic strains in the respective regions.

Association Between HIV-1 Coreceptor Tropism and Clinical Characteristics

The available clinical and demographic characteristics of patients harboring R5-tropic and X4-tropic virus are shown in Table 1. X4-tropic strains were present at a higher frequency in ART-experienced patients (18.8%) than in ART-naive patients (9.1%). No significant association was noted between HIV-1 tropism and age, gender, CD4 cell count, and plasma viral load. The median duration of infection was longer in patients with X4-tropic strains (23.5 months; interquartile range, 13.5–34.3) than with R5-tropic strains (10 months; interquartile range, 1–44). In univariate analysis, among X4-tropic strains (36%), IDU was the more common route of acquiring infection than in R5-tropic strains (16.1%) (P = 0.04).

Patients' Characteristics Based on Viral Tropism

Association Between HIV-1 Coreceptor Tropism With Drug-Resistant Mutations

Drug-resistant genotyping was performed for 41 patients hailing from southern India who were failing first-line ART. RT region of pol gene was successfully amplified in 39 samples. The presence of any nucleoside reverse transcriptase inhibitor/nonnucleoside reverse transcriptase inhibitor mutations was noted in 30 samples (R5 = 25; X4 = 5), and 9 patients harboring R5-tropic strains had no drug-resistant mutation. No significant association was observed between coreceptor tropism and the presence of any RT associated drug-resistant mutations. The frequency of drug-resistant mutations associated with R5 and X4-tropic strains is shown in Figure 2.

Frequency of drug-resistant mutations associated with RT inhibitor resistance in the R5 and X4-tropic strains of the HIV-1–infected patients (n = 37) of the southern Indian cohort failing first-line therapy. The bar diagram shows the frequency of X4-tropic and R5-tropic strains harboring drug resistance mutations either to NRTI (A) or to NNRTI drugs (B). There was no association noted between the coreceptor tropism and the presence of any RT associated drug-resistant mutations (P = 0.55) or with the number of drug resistance mutations associated with NRTI (P = 0.84) and NNRTI (P = 0.55). NRTI, nucleoside reverse transcriptase inhibitor; NNRTI, nonnucleoside reverse transcriptase inhibitor.

Temporal Trend of X4-Tropism in Indian Subtype C Strains 1991–2012

To identify specific trends in X4 tropism in Indian HIV-1 subtype C isolates reported over the past 2 decades, we included 528 Indian subtype C V3 loop database sequences (downloaded from Los Alamos Database accessed on 25th April 2012) along with 197 subtype C V3 loop sequences from our own cohort described above. In comparison with 10.2% X4 tropism observed in our own cohort sequences, the downloaded database Indian subtype C sequences showed a lower prevalence of X4 tropism at 4%. Overall, X4 tropism in Indian subtype C V3 loop sequences was noted at 5.7% and showed an increasing trend (Fig. 3). A significant increase in the frequency of X4 tropism between the years 2005 and 2012 (P < 0.05) was observed.

Prevalence trends of R5 and X4 tropism in Indian HIV-1 subtype C strains over 2 decades. The bar diagram shows the proportion of X4-tropism and R5-tropism in 5 time periods ranging between 1991 and 2012. This analysis revealed a significant increase in prevalence of X4 tropism over time. The sequences used were of primary sequences obtained from our clinical cohort (2007–2012), as well as Indian subtype C database sequences (1991–2010) downloaded from Los Alamos database.

Polymorphisms in the V3 Loop Associated With Maraviroc Resistance in Subtype C Strains

For this analysis, we included a total of 992 subtype C strains, which consisted of R5-tropic strains from the database and cohort sequences, as well as 576 subtype B V3 loop sequences showing R5-tropism. The 19S/T substitution in the V3 loop associated with in vitro maraviroc resistance19 was present at a frequency of 84.1% (19T: 83.3%; 19S: 0.8%) in R5-tropic subtype C strains. The 19S/T substitution was more frequently observed in our cohort (89.8%) and Indian database (90.7%) subtype C sequences than in Global database subtype C sequences (69.8%). The significantly higher prevalence of 19T substitution (83.3%) in subtype C sequences as compared with the frequency of subtype B sequences (8.2%), suggest that 19T may be a naturally occurring polymorphism in subtype C strains. However, this substitution in conjunction with 26V substitution, associated with high-level resistance to maraviroc, was observed to be present at a low frequency in both subtype C and subtype B (<5%). We observed a variable rate of polymorphisms associated with in vivo maraviroc resistance in subtype C and subtype B strains. A significantly higher frequency of 13S/H and 22T substitutions was found in subtype B strains (63.2% and 31.3%, respectively) compared with subtype C strains (0.2% and 0.9%, respectively) (P = 0.001). Several previously described maraviroc resistance–associated substitutions, such as 11S (frequency in subtype C: 97.5% and subtype B: 76.4%), 20F (subtype C: 98.7% and subtype B: 80.6%), and 25D (subtype C: 65.5% and subtype B: 41.1%), were common in both the subtypes, and thus their role in maraviroc resistance needs to be ascertained. Table 2 gives the detailed frequency of all the maraviroc resistance–associated substitutions as observed in in vitro and in vivo studies in both CCR5-tropic subtype C and subtype B.

Frequency of Mutational Patterns Associated With Maraviroc Resistance in the Study Population Harboring R5-Tropic Subtype C Strains, Global and Indian Database Sequences, and US Subtype B Database Sequences


This is the first study to provide a detailed analysis of X4-tropism in a large number of Indian HIV-1 subtype C strains collected from distinct geographical locations of India, along with database-derived sequences, over a period of 20 years. Our data show an increase in X4-tropism among these Indian HIV-1 subtype C strains over the 2-decade period. The results also highlight the significance of mutations in env V3 loop in these strains that previous studies have associated with maraviroc resistance in subtype B strains.

The increasing frequency of X4-tropism in Indian subtype C strains denotes an evolution in HIV-1 tropism over time. This is supported by recent studies showing high frequency of X4-tropic strains in African subtype C strains,10,11 which is an older epidemic as compared with India.20 Another study assessing X4 evolution in subtype C strains reported a significant increase in frequency of X4 tropism in samples collected after the year 2000 compared with strains obtained before the year 2000 (33% vs 8%).24

Considering all the sequences from 1991 to 2012, X4 tropism among the Indian subtype C population was observed at 5.6%. This is similar to the other previously published data (∼4%) from India.6–8 However, the prevalence of X4-tropism in the sampling time point from 2010 to 2012, which consisted predominantly of our own cohort sequences, was observed to be higher at a frequency of 10%. The length of the epidemic in India can explain the increase in frequency of X4-tropism. A recent study from our group has shown that the Indian HIV-1 subtype C epidemic is nearly 4 decades old, speculated to have originated in the early 1970's.20 Also, the same group had shown that there is linear correlation between X4 switch and length of the infection.9 Taken together, the older age of the epidemic and the longer survival of the patients in the ART era may explain the high prevalence of X4-tropic strains in recent years.

Other than the pre-existing population of the X4-tropic strains, resistance to maraviroc can also be manifested by certain amino acid changes in env V3 loop of the R5-tropic HIV-1 strains as was observed in vitro and in vivo studies. Previously, in an in vitro study by Westby et al19 performed on subtype B strain showed that substitutions 19T and 26V confer partial resistance and in combination (19T + 26V) confer full resistance. Previous studies of primary resistance to maraviroc in subtype B strains observed the presence of these mutations at a low level,17,18,25 which was similar to our finding in subtype B R5-tropic global database sequences. However our data indicate that the 19T substitution (∼90%) is inherently present as natural polymorphism in Indian subtype C strains. A previous study by Gonzalez et al26 on African subtype C strains also observed 19T (gp120 HXB2 316) substitution to be a natural polymorphism present in >65% of strains. This was similar to the 69.8% prevalence of 19T substitution in our data set of global sequences, which mostly comprised African strains. Similar to our findings, the presence of the 26V (gp120 HXB2 323) and combined 19T + 26V substitution in their study was also observed to be present at a low frequency (∼4%). Also intriguing to note was that certain single amino acid substitutions associated with maraviroc resistance (11S, 20F and 25D) in in vivo studies were frequently present in both R5-tropic subtype C and subtype B sequences of our study. Similar observation of high prevalence of 11S and 20F (75%) was also noted by other studies.17,18 These substitutions were identified based on observing stepwise accumulation of mutations in V3 loop in patients failing CCR5 antagonist regimen in clinical trials. In the absence of any guidelines or consensus on maraviroc resistant mutations, the role played by these substitutions in causing resistance to maraviroc is not clear, as other factors such as mutations outside V3 loop may also influence maraviroc resistance.27,28 Thus, it is important to ascertain the role of subtype-specific patterns of amino acid polymorphisms on the effectiveness of maraviroc.

A major strength of our study was having access to primary samples from 4 distinct geographical regions of India within a time range of 2007–2012. In accordance with previous studies, majority of our cohort subtype C strains were observed to be R5-tropic (89.7%). In subtype B population, earlier studies have even shown increased prevalence of X4 tropism in treatment-experienced patients.4,29–31 Among our study population that harbored mostly subtype C strains (88%), X4-tropism was observed to be more prevalent in ART-experienced patients than in ART-naive patients. Our results align well with another study reporting a minimally higher R5/X4 tropism among treatment-experienced patients (6%) compared with treatment-naive patients (3%) harboring HIV-1 subtype C strains.7 A study from West Africa reported 15% prevalence of X4 tropism among patients infected with subtype C in later stages of the disease, which was much less as compared with other subtypes.24 Studies from Africa on subtype C population have observed a significantly higher prevalence of X4 tropism among patients failing treatment than in treatment naive.30,32

HIV-1 coreceptor tropism is believed to have a differential disease progression, with X4-tropism being associated with lower CD4 count and longer duration of diagnosis.6 A previous study from our group on a pediatric population showed that coreceptor switch can occur with longer duration of infection.9 However, in our Indian cohort where 96% of samples were from adult patients, tropism was not observed to vary with the clinical characteristics like age, sex, CD4 count, viral load, duration since diagnosis as was also observed in previous studies.31,33,34 There was an association observed between X4-tropism and transmission through intravenous drug use. Individuals who reported to be IDU were predominantly from north-eastern India, which also showed the highest prevalence of X4-tropism among all the sampled regions. The distribution of tropism in intravenous drug use was observed at a same frequency as of an Italian study by Monno et al.35

Drug resistance mutations were also observed to be independent of the coreceptor tropism. Although occasional studies have associated drug resistance mutation with X4 tropism,36 most studies have not found any significant association between drug-resistant mutations and coreceptor usage.1,30,31,34,37

Variability of X4 tropism noticed globally may be due partially to the different methods applied in determining coreceptor usage. In our study, for coreceptor tropism prediction, we have used a support vector machine, Geno2Pheno using 10% FPR cutoffs as per the European guidelines.13 Geno2Pheno is the most widely used genotypic tropism prediction tool, which has been validated against different subtypes and also shows good concordance of GTT using proviral DNA with phenotypic methods.11,38,39

One of the limitations of our study was that we have used GTT, which is based on population-based V3 loop sequences using Geno2Pheno10% algorithm. This method cannot determine tropism in minor viral populations and thus can miss quasi-populations of X4-tropic strains. Because ours was a cross-sectional study where the baseline tropism for the ART-experienced group was not known, we could not ascertain whether the switch had occurred before the initiation of therapy or whether it was an effect of the ART. Additionally, we have used whole-blood DNA as the genetic material for GTT, which could have overestimated X4-tropism in our study population as previous studies have shown that X4-tropic strains are more frequent in proviral DNA than in plasma viral genetic material.40,41 However in a previous study, we have noted good concordance in GTT between plasma-viral RNA and proviral DNA.15

To conclude, although there is significant increase in the X4-tropic strains over a period of 2 decades, our findings indicate that over 90% of Indian patients harbor R5 strains and thus, failing patients may benefit from the use of CCR5-antagonist drugs such as maraviroc that can be included in salvage therapeutic regimens. Further studies with appropriate cell culture models are required to find out the efficacy of maraviroc drug under the influence of naturally occurring polymorphisms in HIV-1 subtype C V3 loop.


The authors are thankful to Ajay Wanchu, Post Graduate Institute of Medical Education and Research, Chandigarh, India, for providing patient samples from northern India; Ranbir L. Singh, Regional Institute of Medical Sciences, Imphal, India, for providing samples from north-eastern India; Vishal Diwan, R. D. Gardi Medical College, Ujjain, India, for providing samples from central India; and Maria L. Ekstrand, University of California, San Francisco, San Francisco, CA, for providing samples from southern Indian patients failing first-line of treatment. The authors also acknowledge the statistical inputs received from Karthika Armugam, St. John's Research Institute, Bangalore, India. The authors are grateful to the clinic staff of St. John's Medical College Hospital and Manipur Network for Positive People (MNP+), Imphal, for their extended support. The authors are also grateful to the patients who have consented to participate in the study.


1. Moyle GJ, Wildfire A, Mandalia S, et al.. Epidemiology and predictive factors for chemokine receptor use in HIV-1 infection. J Infect Dis. 2005;191:866–872.
2. Schuitemaker H, van 't Wout AB, Lusso P. Clinical significance of HIV-1 coreceptor usage. J Transl Med. 2011;9(suppl 1):S5.
3. Simon B, Grabmeier-Pfistershammer K, Rieger A, et al.. HIV coreceptor tropism in antiretroviral treatment-naive patients newly diagnosed at a late stage of HIV infection. AIDS. 2010;24:2051–2058.
4. Wilkin TJ, Su Z, Kuritzkes DR, et al.. HIV type 1 chemokine coreceptor use among antiretroviral-experienced patients screened for a clinical trial of a CCR5 inhibitor: AIDS Clinical Trial Group A5211. Clin Infect Dis. 2007;44:591–595.
5. Cilliers T, Nhlapo J, Coetzer M, et al.. The CCR5 and CXCR4 coreceptors are both used by human immunodeficiency virus type 1 primary isolates from subtype C. J Virol. 2003;77:4449–4456.
6. Neogi U, Prarthana SB, D'Souza G, et al.. Co-receptor tropism prediction among 1045 Indian HIV-1 subtype C sequences: therapeutic implications for India. AIDS Res Ther. 2010;7:24.
7. Ataher Q, Portsmouth S, Napolitano LA, et al.. The epidemiology and clinical correlates of HIV-1 co-receptor tropism in non-subtype B infections from India, Uganda and South Africa. J Int AIDS Soc. 2012;15:2.
8. Kandathil AJ, Kannangai R, Abraham OC, et al.. HIV-1 with predicted CXCR4 genotype identified in clade C from India. Mol Diagn Ther. 2009;13:19–24.
9. Neogi U, Sahoo PN, Arumugam K, et al.. Higher prevalence of predicted X4-tropic strains in perinatally infected older children with HIV-1 subtype C in India. J Acquir Immune Defic Syndr. 2012;59:347–353.
10. Connell BJ, Michler K, Capovilla A, et al.. Emergence of X4 usage among HIV-1 subtype C: evidence for an evolving epidemic in South Africa. AIDS. 2008;22:896–899.
11. Raymond S, Delobel P, Mavigner M, et al.. Prediction of HIV type 1 subtype C tropism by genotypic algorithms built from subtype B viruses. J Acquir Immune Defic Syndr. 2010;53:167–175.
12. Lengauer T, Sander O, Sierra S, et al.. Bioinformatics prediction of HIV coreceptor usage. Nat Biotechnol. 2007;25:1407–1410.
13. Vandekerckhove LP, Wensing AM, Kaiser R, et al.. European guidelines on the clinical management of HIV-1 tropism testing. Lancet Infect Dis. 2011;11:394–407.
14. Verhofstede C, Nijhuis M, Vandekerckhove L. Correlation of coreceptor usage and disease progression. Curr Opin HIV AIDS. 2012;7:432–439.
15. Gupta S, Neogi U, Srinivasa H, et al.. High concordance of genotypic coreceptor prediction in plasma-viral RNA and proviral DNA of HIV-1 subtype C: implications for use of whole blood DNA in resource-limited settings. J Antimicrob Chemother. 2013;68:2003–2006.
16. Llibre JM, Schapiro JM, Clotet B. Clinical implications of genotypic resistance to the newer antiretroviral drugs in HIV-1-infected patients with virological failure. Clin Infect Dis. 2010;50:872–881.
17. Saracino A, Monno L, Brindicci G, et al.. Are the proposed env mutations actually associated with resistance to maraviroc? J Acquir Immune Defic Syndr. 2010;53:550–552.
18. Seclen E, Gonzalez Mdel M, Lapaz M, et al.. Primary resistance to maraviroc in a large set of R5-V3 viral sequences from HIV-1-infected patients. J Antimicrob Chemother. 2010;65:2502–2504.
19. Westby M, Smith-Burchnell C, Mori J, et al.. Reduced maximal inhibition in phenotypic susceptibility assays indicates that viral strains resistant to the CCR5 antagonist maraviroc utilize inhibitor-bound receptor for entry. J Virol. 2007;81:2359–2371.
20. Neogi U, Bontell I, Shet A, et al.. Molecular epidemiology of HIV-1 subtypes in India: origin and evolutionary history of the predominant subtype C. PLoS One. 2012;7:e39819.
21. Neogi U, Prarthana BS, Gupta S, et al.. Naturally occurring polymorphisms and primary drug resistance profile among antiretroviral-naive individuals in Bangalore, India. AIDS Res Hum Retroviruses. 2010;26:1097–1101.
22. Johnson VA, Calvez V, Gunthard HF, et al.. 2011 update of the drug resistance mutations in HIV-1. Top Antivir Med. 2013;21:6–14.
23. Tamura K, Peterson D, Peterson N, et al.. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–2739.
24. Esbjornsson J, Mansson F, Martinez-Arias W, et al.. Frequent CXCR4 tropism of HIV-1 subtype A and CRF02_AG during late-stage disease–indication of an evolving epidemic in West Africa. Retrovirology. 2010;7:23.
25. Soulie C, Malet I, Lambert-Niclot S, et al.. Primary genotypic resistance of HIV-1 to CCR5 antagonists in CCR5 antagonist treatment-naive patients. AIDS. 2008;22:2212–2214.
26. Gonzalez S, Gondwe C, Tully DC, et al.. Short communication: antiretroviral therapy resistance mutations present in the HIV type 1 subtype C pol and env regions from therapy-naive patients in Zambia. AIDS Res Hum Retroviruses. 2010;26:795–803.
27. Ratcliff AN, Shi W, Arts EJ. HIV-1 resistance to maraviroc conferred by a CD4 binding site mutation in the envelope glycoprotein gp120. J Virol. 2013;87:923–934.
28. Soriano V, Geretti AM, Perno CF, et al.. Optimal use of maraviroc in clinical practice. AIDS. 2008;22:2231–2240.
29. Alencar CS, Nishiya AS, Ferreira S, et al.. Evaluation of primary resistance to HIV entry inhibitors among brazilian patients failing reverse transcriptase/protease inhibitors treatment reveal high prevalence of maraviroc resistance-related mutations. AIDS Res Hum Retroviruses. 2010;26:1267–1271.
30. Johnston ER, Zijenah LS, Mutetwa S, et al.. High frequency of syncytium-inducing and CXCR4-tropic viruses among human immunodeficiency virus type 1 subtype C-infected patients receiving antiretroviral treatment. J Virol. 2003;77:7682–7688.
31. Poveda E, Briz V, de Mendoza C, et al.. Prevalence of X4 tropic HIV-1 variants in patients with differences in disease stage and exposure to antiretroviral therapy. J Med Virol. 2007;79:1040–1046.
32. Singh A, Sunpath H, Green TN, et al.. Drug resistance and viral tropism in HIV-1 subtype C-infected patients in KwaZulu-Natal, South Africa: implications for future treatment options. J Acquir Immune Defic Syndr. 2011;58:233–240.
33. Chalmet K, Dauwe K, Foquet L, et al.. Presence of CXCR4-using HIV-1 in patients with recently diagnosed infection: correlates and evidence for transmission. J Infect Dis. 2012;205:174–184.
34. Parczewski M, Leszczyszyn-Pynka M, Urbanska A, et al.. Genotypic tropism of antiretroviral-treated patients with drug resistant HIV-1. J Med Virol. 2011;83:1869–1875.
35. Monno L, Scudeller L, Ladisa N, et al.. A greater prevalence of X4 viruses in HIV type 1 intravenous drug users reflects a “CD4+ effect”. AIDS Res Hum Retroviruses. 2011;27:1029–1031.
36. Wagner TA, Frenkel LM. Potential limitation of CCR5 antagonists: drug resistance more often linked to CXCR4-utilizing than to CCR5-utilizing HIV-1. AIDS. 2008;22:2393–2395.
37. Waters L, Mandalia S, Randell P, et al.. The impact of HIV tropism on decreases in CD4 cell count, clinical progression, and subsequent response to a first antiretroviral therapy regimen. Clin Infect Dis. 2008;46:1617–1623.
38. Santoro MM, Armenia D, Fabeni L, et al.. The lowest X4 Geno2Pheno false-positive rate is associated with greater CD4 depletion in HIV-1 infected patients. Clin Microbiol Infect. 2012;18:E289–E298.
39. Svicher V, Alteri C, Montano M, et al.. Performance of genotypic tropism testing on proviral DNA in clinical practice: results from the DIVA study group. New Microbiol. 2012;35:17–25.
40. Seclen E, Del Mar Gonzalez M, De Mendoza C, et al.. Dynamics of HIV tropism under suppressive antiretroviral therapy: implications for tropism testing in subjects with undetectable viraemia. J Antimicrob Chemother. 2010;65:1493–1496.
41. Verhofstede C, Vandekerckhove L, Eygen VV, et al.. CXCR4-using HIV type 1 variants are more commonly found in peripheral blood mononuclear cell DNA than in plasma RNA. J Acquir Immune Defic Syndr. 2009;50:126–136.

HIV-1 subtype C; coreceptor tropism; X4 tropism; maraviroc resistance; V3 loop polymorphism

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