Journal of Clinical Microbiology, February 2007, p. 279-284, Vol. 45, No. 2
0095-1137/07/$08.00+0 doi:10.1128/JCM.01118-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.
Andrew J. Low,2,4,
Winnie Dong,2
Tobias Sing,3
Peter K. Cheung,2,4
Fabrizio Mammano,1,5 and
P. Richard Harrigan2,4*
INSERM U552 Recherche Antivirale, Paris, France,1 B.C. Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada,2 Max-Planck-Institute for Informatics, Saarbrücken, Germany,3 Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada,4 Faculté de Médecine, Université Denis Diderot Paris 7, Paris, France5
Received 31 May 2006/ Returned for modification 3 August 2006/ Accepted 13 November 2006
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2,500-bp ("Trofile" assay) or an
900-bp (TRT assay) fragment of the HIV envelope gp120. Population-based HIV envelope V3 loop sequences (
105 bp) were derived by automated sequence analysis. Genotypic coreceptor predictions were performed using a support vector machine model trained on a separate genotype-Trofile phenotype data set. HIV coreceptor usage was obtained from both phenotypic assays for 74 samples, with an overall 85.1% concordance. There was no evidence of a difference in sensitivity between the two phenotypic assays. A bioinformatic algorithm based on a support vector machine using HIV V3 genotype data was able to achieve 86.5% and 79.7% concordance with the Trofile and TRT assays, respectively, approaching the degree of agreement between the two phenotype assays. In most cases, the phenotype assays and the bioinformatic approach gave similar results. However, in cases where there were differences in the tropism results, it was not clear which of the assays was "correct." X4 (CXCR4-using) minority species in clinically derived samples likely complicate the interpretation of both phenotypic and genotypic assessments of HIV tropism. |
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Recently, with the development of coreceptor antagonists capable of blocking either the CCR5 (14, 18) or the CXCR4 (18, 20) coreceptor, the need for accurate HIV-phenotyping assays has increased. This is especially important in preliminary tests to screen patients for clinical trials of these agents and for monitoring the evolution of coreceptor usage under the pressure of CCR5 and/or CXCR4 antagonists (13).
Many, but not all, of the genetic determinants of coreceptor usage reside in the HIV envelope, in particular, the V3 loop (8, 10). Consequently, this region is highly useful for the training and development of computerized genotypic predictors of coreceptor usage, which have the potential to make the screening and testing of HIV-infected patients faster and more cost-effective. The simplest genotypic approach, known as the "11/25 rule" classifies a virus as X4 if positively charged amino acids (lysine or arginine) are present at positions 11 and/or 25 of the V3 loop (5, 7, 8). Evaluation of bioinformatics-based genotypic predictors, such as neural networks (17), position-specific scoring matrices (9), and support vector machines (SVMs), indicate that the coreceptor phenotypes may be accurately determined with genotypic predictors (19) when tested on clonally derived sequence data. However, both phenotypic assays and genotypic prediction methods are challenged when applied to heterogeneous sequence data obtained from actual clinical samples. If testing for HIV coreceptor usage becomes necessary for treatment with coreceptor inhibitors, it would be expected to be performed on clinically derived samples. Under these circumstances, a high level of reliability and repeatability should be expected.
Two previously validated recombinant phenotypic assays for HIV coreceptor use (the Trofile HIV Co-receptor Tropism Assay [formerly the PhenoSense HIV-Entry Assay] from Monogram Biosciences and the Tropism Recombinant Test [TRT], performed in the laboratory of Fabrizio Mammano at INSERM [to be available through Eurofins Viralliance Inc.]) were employed here, as well as genotypic analysis of the HIV V3 loop in 74 clinically derived HIV-1 samples in order to evaluate the concordance between phenotypic assays and to determine the ability of an SVM-based genotypic method to predict coreceptor usage.
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Assay methods. The two phenotypic assays (12, 21) use virus stocks pseudotyped with envelope sequences derived from patient plasma samples to infect cell lines engineered to express CCR5 or CXCR4. Some relevant differences in the phenotypic assays are highlighted in Table 1. The Trofile assay confirms coreceptor usage by verifying a decrease in relative light units (RLU) after the addition of a CCR5 or CXCR4 antagonist. The TRT assay did not perform this step at the time of these analyses. Note that the TRT assay was performed on PCR products amplified by our laboratory in British Columbia, Canada, and the Trofile assay was performed on the corresponding baseline plasma samples. More detailed information regarding the two phenotypic assays can be found in references 3, 4, and 12 (Trofile) and 4 and 21 (TRT).
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TABLE 1. Potentially relevant differences in phenotypic assays
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105 bp) of corresponding baseline plasma samples were obtained using previously described standard automated sequence analysis (1). Genotypic predictions of HIV coreceptor usage were performed using an SVM analysis of the sequenced HIV V3 loop (http://www.geno2pheno.org). Robust alignments of the envelope V3 region were obtained using the multiple-alignment software MUSCLE (6). SVMs were trained using all genotype-phenotype data from the HOMER cohort, determined using the Trofile assay, excluding the 74 samples compared here. Codon mixtures in sequence data are considered ambiguous with respect to sequence identity and were treated using an "X4-sensitive" strategy during training and a "combinatorial" strategy for prediction, as described previously (19). Briefly, in the combinatorial prediction strategy, nonambiguous V3 sequences are generated by random sampling from the ambiguous genotype, and a numeric score, indicating the probability of CXCR4 usage, is calculated for each of the nonambiguous sequences. The final score is taken as the 0.75 percentile of the individual scores. A cutoff of 0.4 on this score was chosen to predict X4 variants. This cutoff was determined by maximizing the area under the receiver operating characteristic (ROC) curve (AUC) for all matched genotype-phenotype samples in the HOMER cohort, excluding the 74 samples analyzed here.
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Overall, 85.1% concordance was observed between the two assays. Of the 74 samples, 42 (56.8%) were identified as R5 by both assays and 21 (28.4%) were identified as R5/X4 by both assays. An additional eight (10.8%) were identified as R5 by the Trofile assay but as R5/X4 by the TRT assay, and the remaining three (4.1%) were identified as R5/X4 by the Trofile assay but as R5 by the TRT assay. The Trofile assay characterized one sample as being pure X4. This sample was characterized as being R5/X4 by the TRT assay but for the purposes of our analysis was classified as being R5/X4 by the Trofile assay and was therefore treated as concordant.
We then investigated the clinical parameters of samples with concordant and discordant results (Table 2) . A low CD4 cell count has been shown to be predictive of CXCR4-using HIV (22), and as expected, the samples identified as R5 in both assays showed significantly higher median CD4 cell counts (P < 0.01) than those samples identified as R5/X4 in both assays, although the plasma viral loads were not significantly different (P > 0.1). Median R5 RLU (Trofile assay) and R5 optical-density (OD) (TRT assay) values were consistently high in both assays, regardless of whether they were identified as R5 or R5/X4, implying a high efficiency of replication in the R5 cell lines. Discordant results were observed where R5/X4 was detected in the Trofile assay and not in the TRT assay, and vice versa (shown individually in Table 3). When samples were grouped as "discordant" and "concordant," we observed no statistically significant differences between the viral loads or CD4 counts (P > 0.05). Also, when discordant groups were compared to each other, we observed no statistically significant differences between CD4 or viral loads (P >> 0.5; Wilcoxon rank sum test), although the small sample size of the discordant groups should be noted.
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TABLE 2. Summary of median baseline CD4 count and baseline viral load for samples categorized as either R5 or R5/X4 using the Trofile or TRT coreceptor usage assay
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TABLE 3. Characteristics of samples with discordant results from the Trofile or TRT entry coreceptor assay
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FIG. 1. Receiver operating characteristic curve of the Trofile HIV coreceptor assay versus the TRT coreceptor assay. The gray line uses the Trofile coreceptor results as the reference while varying the cutoff for the X4 ODSample/X4 ODCtrl data obtained from the TRT assay. The black line uses the TRT coreceptor results as the reference while varying the cutoff for the X4 RLU data obtained from the Trofile assay.
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1 codon of the HIV V3 loop were observed in 56 (75.7%) sequences. According to the "combinatorial" prediction strategy, mixture-containing sequences were expanded into all possible permutations (median, 2 permutations per isolate; range, 1 to 128), giving rise to multiple values for each sample, each falling between 0 (a low likelihood of being X4) and 1 (a high likelihood of being X4) (Fig. 2).
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FIG. 2. SVM-predicted probabilities of CXCR4 coreceptor usage. Each position on the x axis represents a sample from a single patient. Sequences containing amino acid mixtures were expanded into all possible permutations per sample, and each permutation was assigned a score based on its probability of harboring X4-containing virus (where 0 is low probability and 1 is high probability). Sample permutations were tested and scored individually, and the probability of being X4 is indicated on the y axis. Each individual sample permutation is represented by a single symbol, generating a series of vertically aligned symbols for each clinically derived sample. The samples were grouped along the x axis, labeled according to the results obtained from both phenotypic assays as "R5" or "R5/X4," and ordered by "Trofile assay/TRT assay." The solid triangles represent samples phenotyped as R5/X4 by both assays, open squares represent samples phenotyped as R5/X4 by the Trofile assay and as R5 by the TRT assay, solid diamonds represent samples phenotyped as R5 by the Trofile assay and as R5/X4 by the TRT assay, and open circles represent samples phenotyped as R5 by both assays. The dashed horizontal line represents the SVM cutoff, above which samples are classified as R5/X4.
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FIG. 3. Box plot summary of the predicted probability of CXCR4 coreceptor usage. Mixtures were separated into all possible permutations per sample. The samples were grouped and labeled according to the results obtained from both phenotypic assays as "R5" or "R5/X4" and ordered by "Trofile assay/TRT assay." The maximum score observed for each isolate was used to create the box plot. The boxes represent the interquartile range, and the solid line inside each box represents the median of the maxima of the group of samples. The box plot whiskers represent the range of the data in each category, and outliers are represented as open circles.
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FIG. 4. Concordances between phenotypic coreceptor assays and an SVM bioinformatic predictor. The black bars represent the concordances between the Trofile coreceptor assay (TF) and SVM, and the gray bars represent concordances between the TRT coreceptor assay and SVM. Percent discordances are represented by the white bars.
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Some potentially relevant differences between the two assays may account for many of the observed differences between coreceptor phenotypes observed here. These differences include the size of the viral RNA fragment excised and amplified, the cells used to express the coreceptors, and the reporter gene. While the Trofile HIV assay uses the entire gp160 gene fragment, approximately 2,500 base pairs, the TRT assay uses a 900-bp-long viral fragment that spans the V1-V3 region, including 150-bp-long extensions on each side to allow homologous recombination during transfection (21). One hypothesis that may require further investigation is whether amplification of a larger DNA fragment leads to a greater loss of minority species during PCR amplification. Other potential reasons for discordance between assay results have been reviewed by Coakley et al. (4), including the interaction between the viral vector Gag proteins and the patient-derived envelope proteins, which may affect pseudotyping efficiency and the usage of reporter cell lines. The use of different target cell lines could be another source of discrepancy between the assays, as the tropism assays made use of human malignant glioma cell lines (U87 and U373) engineered to express CD4 and various chemokine coreceptors on their surfaces. Previous studies have shown that coreceptor utilization may be influenced by the level of receptor expression and the ratio of the receptors to each other (16). However, results from at least one study suggest that coreceptor levels do not impact the ability to measure coreceptor usage (15).
Clinical samples contain a heterogeneous viral population. Studies of the detection of minority species within interindividual virus populations have shown that the limit of detection is in the range of 10 to 20% for the phenotypic coreceptor assays (4) while the limit of detection of conventional genotypic assays (consisting of reverse transcription (RT)-PCR, followed by population ["bulk"] sequencing) is approximately 25%. This is largely because low-level signals cannot be detected by conventional automated DNA sequencing, a factor that limits both the phenotypic coreceptor assays and genotypic predictors (SVM).
Developing a reliable genotypic predictor of coreceptor usage requires a well-validated phenotypic coreceptor assay to use as a reference. Although the "11/25" rule for determining tropism, which categorizes variants as syncytium inducing if they display positively charged residues at codons 11 and/or 25 within the V3 loop and non-syncytium inducing if they do not, is reasonably specific, it lacks sensitivity (<60%) for predicting coreceptor usage (9). SVM analysis of clinically derived sequences appears to correlate well with the results of phenotypic coreceptor assays and has higher sensitivity and specificity than other bioinformatic models for determining coreceptor usage from clonal data (19). However, the inability to consistently detect minority species in clinically derived sequence data presents difficulties both in using genotypic predictors and in training these predictors with sequence data phenotyped using assays that are also unable to consistently detect minority species.
In summary, the two phenotypic coreceptor assays tested here generated largely concordant results. However, in cases where there were differences in the assay results, it was not clear which of the assays was "correct." The discordances did not show significant trends that could be attributed to differences between the two phenotypic coreceptor assays or to patient characteristics. It is likely that the presence of heterogeneous viral populations in clinically derived isolates posed difficulties of detection for both phenotypic and genotypic/bioinformatic approaches for determining coreceptor use. For the purposes of determining coreceptor usage in a clinical setting, an understanding of the limitations of the test used is essential. Although genotypic predictive models have the potential to reduce the cost and time for determining the coreceptor usage of patient-derived isolates, validation of genotypic methods against a verified reference would be required before they can be adopted for clinical use.
Published ahead of print on 22 November 2006. ![]()
K.S. and A.J.L. contributed equally to this work. ![]()
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