Previous Article | Next Article ![]()
Journal of Clinical Microbiology, July 2003, p. 2900-2907, Vol. 41, No. 7
0095-1137/03/$08.00+0 DOI: 10.1128/JCM.41.7.2900-2907.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.
BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada V6Z 1Y6
Received 25 September 2002/ Returned for modification 4 March 2003/ Accepted 28 March 2003
|
|
|---|
|
|
|---|
Despite these advances, there are currently no specific standards for either genotypic or phenotypic testing for HIV drug resistance. Consequently, aspects such as technical laboratory expertise, assay performance characteristics and quality control, diversity of patient populations, and drug resistance interpretation algorithms may produce variability of resistance testing results. Previous studies (16, 17) have shown a high degree of interlaboratory differences in results of sequence-based resistance testing methods mainly through the use of predefined mixtures of HIV DNA clones. Other studies have shown that interlaboratory concordance can be quite high (19, 20), particularly when laboratories with high levels of sequencing experience are using similar methods. Studies comparing different commercial and in-house sequencing methods for resistance testing in clinical samples have found that concordance across methods at key mutation sites can range from 80 to 99% (6, 7, 9). Since genotypic tests are relatively complex to perform, careful attention to performance consistency and quality control are necessary to ensure reliable results (6, 7, 9, 16, 17). Routine use of quality measures to assess PCR contamination, instrument performance, and raw sequence data can minimize methodological variability (10).
With the increasing use of resistance testing in clinical practice, the reproducibility of detection of drug resistance mutations is critical for accurate assessment of antiretroviral drug resistance in the individual patient. In the present study, we determined the intralaboratory reproducibility and inter-rater concordance of an in-house sequencing method for HIV drug resistance testing with plasma samples obtained from antiretroviral-experienced HIV patients. Furthermore, we attempted to identify the methodological source of the greatest variation in sequencing results. The consistency of the whole genotyping process was also assessed by using multiple replicates of a single positive control. Finally, as a function of the reproducibility of the in-house resistance testing algorithm, we assessed the long-term genetic stability of virus populations in sequential plasma samples collected from a cohort of 22 HIV patients with detectable levels of predominantly wild type virus.
|
|
|---|
Additionally, sequence data determined by four different staff members from 103 replicates of a single plasma draw, used as a positive control over 9 months, were analyzed for variability.
To assess the biological stability of HIV sequence in plasma samples collected longitudinally, 168 PR and RT sequences were obtained from 22 patients enrolled in the British Columbia HIV Drug Treatment Program. These patients each provided a minimum of four sequential samples over an analysis period ranging from 6 to 55 months. All samples had detectable plasma viral loads (>500 HIV RNA copies/ml) and no detectable key resistance-associated mutations throughout the analysis. No attempt was made to control for therapy regimen or adherence.
HIV RNA extraction. RNA was extracted from 220 µl of single stored aliquots of plasma by using the QIAamp 96 Viral RNA Extraction kit (Qiagen, Valencia, Calif.) on a Qiagen BioRobot 9600 according to the manufacturer's instructions. For the purposes of this study, only a single RNA extract for each sample was used for replicate amplification. The potential impact of plasma HIV-1 RNA extraction on reproducibility, particularly in samples with low plasma HIV-1 RNA levels, was therefore not assessed. At plasma viral load levels of 100 to 1,000 HIV RNA copies/ml, the average amplification and sequencing success rate of our assay is 80%. At levels above 1,000 copies/ml, the success rate is >95%. In our study, the lowest plasma viral load of any sample was 1,500 copies/ml.
RT-PCR. PR and RT cDNAs were generated from RNA extracts with Expand Reverse Transcriptase (Expand High Fidelity PCR system; Roche Diagnostics GmbH, Mannheim, Germany) on GeneAmp PCR system 9600 and 9700 thermocyclers. First-round RT-PCR yielded a 2.2-kb product of the HIV-1 polymerase gene encompassing the entire PR region and most of the RT coding regions. This first-round product was then amplified with nested PCR primers in a second round to obtain the1.8-kb PCR products used in the study. The replicate testing algorithm used for the 46 cross-sectional samples is shown in Fig. 1. RT-PCR and first-round PCR were performed in duplicate (identified as A and B). Nested PCR was then performed in duplicate (identified as A1, A2, B1, and B2) from each first-round RT-PCR. The yield and purity of the PCR products were evaluated by agarose gel electrophoresis standardized to a DNA ladder with known molecular sizes. Similar extraction, PCR, and sequencing procedures were used for the 103 replicate control and 168 longitudinal samples.
![]() View larger version (17K): [in a new window] |
FIG. 1. Replicate testing algorithm. This algorithm depicts the replicate testing of RNA extracts from the 46 HIV-positive cross-sectional samples.
|
Sequence data analysis. In the cross-sectional study, final sequences for all replicate samples were compared to each other for complete and partial nucleotide discordances. Overall amino acid differences resulting from nucleotide discordance between the replicates and variance at key resistance mutation sites were also assessed to determine the source of greatest variability. Nucleotide mismatches were analyzed for statistical significance according to distribution and frequency patterns, as well as for trends in nucleotide bases in 5' and 3' directions from the mismatches. To assess inter-rater concordance, sequences from all A1 samples (Fig. 1) were reanalyzed using normal procedures by a different technical staff member of the same laboratory. Neighbor-joining trees were created by phylogeny using Clustal X, version 1.8 (21), to detect potential contamination with other samples.
For the longitudinal samples, intrapatient HIV sequence variability was assessed by comparing full and partial nucleotide changes in sequential samples with the index sequence determined from the first sample for each patient. For control sample replicates, sequences determined and analyzed over a 9-month period were compared to the initial sequence of the sample.
Definitions. A partial nucleotide discordance was considered to be present when one sequence position had a nucleotide mixture and its replicate had one of the mixture's components. For example, one sequence had an R (the International Union of Biochemistry and Molecular Biology code for A plus G), and its replicate had either an A or a G. A complete nucleotide discordance was considered to be present when a sequence and its replicate had different nonambiguous nucleotides at the same position. For example, one sequence had a C and its replicate had a T. Mutations were defined as amino acid differences between a patient sequence and the HIV-1 HXB2R sequence (accession no. AF033819; Los Alamos National Laboratory, Los Alamos, N.Mex.). Mutations were considered to be present if they were detected as part of a mixture (together with a wild-type allele) or in pure form. The following codons were considered "key" drug resistance-associated sites in genotypic comparisons: PR codons 30, 32, 48, 50, 82, 84, and 90; RT codons 41, 62, 65, 67, 69, 70, 74, 75, 77, 103, 106, 108, 115, 116, 151, 181, 184, 188, 190, 210, 215, 219, and 236 (11).
|
|
|---|
Nucleotide differences. A total of 68,862 nucleotides (1,497 bases each from 46 sequences) were analyzed from independent RT-PCR amplifications A1 and B1 (Table 1 and Fig. 2). Four hundred forty nucleic acid discordances were identified between first-round PCR products A1 and B1 (99.4% concordance). The mismatches were scattered throughout the genome at >300 different positions. Only two nucleotide positions (PR codon 79 and RT codon 271) had as many as four mismatches in the 46 samples. Neither of these codons is known to be associated with drug resistance. Concordance increased to 99.8% by using the same first-round PCR products but different second-round PCR products (A1 versus A2 and B1 versus B2) and to 99.9% by comparing the same first- and second-round PCR products (A2 versus A3 and B2 versus B3). The total number of nucleotide differences after second-round PCR (arm A, 127; arm B, 120) was significantly lower than that after first-round PCR (440 differences) (P < 0.001). Seventy-five percent of the nucleotide differences between arms A and B of the PCR were partial differences resulting from different calling of mixtures of bases at a single position (such as a call of A for one sequence and R for another; see "Definitions" above). More ambiguous base calls were observed in A1 sequences (from arm A) than in B1 sequences (from arm B) for both RT and PR (Fig. 2), despite the fact that these were duplicates. For the same first- and second- round PCR replicates, partial discordances accounted for 96.7% (arm A) and 98% (arm B) of the total nucleotide differences. Multiple mismatches at drug resistance-associated codons occurred at only three PR codons and one RT codon, respectively. A-to-G, A-R, and G-R mismatches were significantly more common than other mismatched base pairs (P < 0.001) (Fig. 3A). More than half (52%) of all mismatches involved A or G (or R, a mixture of A and G). We compared the proportion of bases immediately preceding the mismatches in both the 5' and 3' directions to the overall proportion of the respective bases within the 46 cohort samples. The proportion of A 5' to the mismatch was significantly higher than the total prevalence of A in the samples (P < 0.001) (Fig. 3B). The proportions of T (P = 0.002) and C (P = 0.02) 3' to the mismatch were significantly higher than the respective proportions within the cohort samples (Fig. 3C).
|
View this table: [in a new window] |
TABLE 1. Reproducibility of sequencing of replicate PCR products from single RNA extracts from 46 samples
|
![]() View larger version (70K): [in a new window] |
FIG. 2. Nucleotide sequence concordances and discordances. The matrices show the numbers of nucleotide sequence concordances and discordances between the two main arms (A1 and B1) for RT (A) and PR (B). Numbers of complete matches are shown along the diagonal. Numbers of complete discordances are boldfaced, and numbers of partial discordances are shaded. Blank cells indicate zero. International Union of Biochemistry and Molecular Biology ambiguity codes are as follows: R, A plus G; Y, C plus T; W, A plus T; M, A plus C; K, G plus T; S, G plus C. Data for sequence calls B, H, V, D, or N are not shown.
|
![]() View larger version (32K): [in a new window] |
FIG. 3. Relative frequency of sequence base mismatches and distribution of flanking nucleotides in 46 cross-sectional samples. (A) Distribution of complete and partial base pair mismatches expressed as percentages of the total mismatches within the cohort (n = 440). Nucleotide base pair mismatches A-G, A-R, and G-R showed significantly higher prevalences in the 46 samples than other mismatches (P < 0.001). (B) Relative proportion of bases immediately preceding the mismatches in the 5' direction compared to the overall proportion of these bases within the cohort. N, ambiguous nucleotides. P < 0.001 for A; P = 0.05 for C; P < 0.001 for G; P = 0.27 for T. (C) Proportion of bases preceding the mismatches in the 3' direction compared to the overall proportion of these bases within the cohort. P = 0.01 for A; P = 0.02 for C; P = 0.04 for G; P = 0.002 for T.
|
Inter-rater concordance. The inter-rater concordance for replicates of the 46 samples was 99.9% or greater for nucleotides as well as amino acids (Table 1). Additionally, a routine control sample was extracted and subjected to RT-PCR and nested PCR followed by sequencing for a total of 103 replicates over 9 months. The sequences were analyzed independently by four different, highly experienced staff members during this period. This process consistently gave highly reproducible sequences throughout the testing period (median, 0.04% nucleotide discordances; range, 0 to 0.2%).
Identification of resistance mutations and impact on resistance calls. A total of 265 drug resistance mutations were identified in the 46 isolates (Table 2); of these, 242 (91.3%) were complete matches. The distributions of amino acids at PR and RT codons associated with drug resistance are shown in Tables 3 and 4, respectively. Of the complete mismatches at RT codons, three were located at key RT resistance mutation sites (D67, K70, and T215) and one was located at V118 (a mutation associated with resistance in some genetic backgrounds [15]) (Table 3). There was only one complete mismatch at a key PR resistance codon (L90), although other mismatches were observed at the secondary PR resistance codons M46 and N88 and at codon L10 (Table 4). There were no complete mismatches at any key codons associated with resistance to nonnucleoside reverse transcriptase inhibitors (data not shown). Partial mismatches that could affect resistance calls occurred once at PR position 82 and once at RT positions 44, 69, 74, 184, and 219.
|
View this table: [in a new window] |
TABLE 2. Number and characteristics of drug resistance mutations observed in 46 plasma samples
|
|
View this table: [in a new window] |
TABLE 3. Distribution of amino acids at HIV RT positions associated with drug resistance in 46 plasma samples
|
|
View this table: [in a new window] |
TABLE 4. Distribution of amino acids at HIV PR positions associated with drug resistance
|
Plasma viral load. There was no obvious correlation between plasma viral load and the number of nucleotide, amino acid, or drug resistance mutation discordances in replicate sequences. At plasma viral loads below 4 log units (10,000 HIV RNA copies/ml) (n = 9), the mean number of full and partial nucleotide discordances between duplicates was 5 (range, 0 to 11); at plasma viral loads between 10,000 and 100,000 HIV RNA copies/ml (n = 10), the mean was 14 discordances (range, 0 to 22); and at plasma viral loads of >100,000 copies/ml (n = 16), the mean was 7 (range, 0 to 19).
|
|
|---|
In this study, the overall nucleotide concordance for the 276 replicate sequences from 46 cross-sectional clinical samples was >99%. Since not all nucleotide differences code for amino acid changes, we also demonstrated an amino acid concordance of >99% for the same study samples. Of note, significantly more nucleotide and amino acid differences occurred as a result of the first-round RT-PCR than during the second-round nested PCR (P < 0.001), indicating that most discordances are likely to result from initial RT-PCR sampling of the predominant HIV-1 plasma population rather than from technical variation (21) or operator performance (17). Despite the high concordance between sequence replicates, a total of 14 partial and 9 complete nucleotide mismatches occurred in the 265 total key and secondary resistance mutations observed in the study population. A portion of these mismatches would affect resistance interpretations, indicating that inaccuracies affecting resistance calls can occur at low prevalence even in highly controlled assay situations. Due to the relatively small numbers of cases with low viral loads, any impact of plasma viral load would have been difficult to detect in these experiments.
More than half of all mismatches involved nucleotide A or G, with significant prevalences of A-to-G, A-to-R (a mixture of A and G), and G-to-R mismatches relative to other combinations (P < 0.001). Furthermore, mismatches were context dependentdepending on flanking basesbut not location dependent, since nucleotide discrepancies occurred scattered throughout the genome. These data indicate a systematic rather than a random contribution to the variability of the sequences obtained.
As reported by others (19, 20), most nucleotide and amino acid discordances were the results of mixtures. The reduced ability to detect minor variants either by genotyping or by phenotyping methods should be a recognized limitation of clinical antiretroviral drug resistance testing (4, 14). If this is accepted, along with the relatively low prevalence of mixtures in clinical samples, the use of predefined mixtures of HIV DNA clones in external quality assessment (EQA) panels to assess variability (16, 17) may not be appropriate. The use of DNA clones in EQA panels would not allow assessment of the contribution of the extraction or the reverse transcription step to sequence variability. As concluded by this study, the reverse transcription step is potentially a source of significant variability, and the extraction step may also contribute to failure in some cases. Since DNA clones would not be directly amplified through RT-PCR, their use in quality assessment panels may not provide true performance assessment of all steps in an RT-PCR-containing assay. Until the reliability of resistance testing assays for detection of minority species in plasma is improved, consistency and reproducibility remain primary targets for control of day-to-day assay performance. Clinical trials (1, 5, 8, 18) have illustrated that genotyping can be a good prognostic marker when performed longitudinally. A key laboratory contribution to this prognostic capability is to demonstrate that minimal intrapatient sequence variation is achievable in sequential samples tested over time in the absence of significant viral evolution. In our study of 168 sequences from 22 antiretroviral-experienced patients with predominantly wild type HIV in plasma, sequence concordance with the initial sample for each patient remained high (96.5 to 100%) for the entire sampling period (ranging from 6 to 55 months). Although patients with no mutations at key resistance-associated sites were selected for this cohort, mutations at other sites were consistently detected in sequential samples from the same patient. These results suggest that the inherent biological variability of HIV-1 sequences is relatively small.
Interoperator variability was minimal in this study, which may be expected due to the high level of experience of the laboratory staff. In a direct comparison of 46 sequences analyzed by two different staff members using the same procedure, nucleotide and amino acid concordances were >99.9%. Furthermore, for 103 replicates of a single clinical plasma sample analyzed by as many as four different laboratory staff members over a 9-month period, concordance with the initial sequence averaged 99.9%, with nucleotide differences ranging from 0 to 3 per 1,497-base sequence. However, this isolate contained few nucleotide mixtures.
In summary, most of the variation observed in replicate cross-sectional or longitudinal samples in this study was likely due to the first-round RT-PCR, apparently resulting from systematic variations in nucleotide incorporation. Technical assay performance issues did not impact on the observed variance. These results confirm that carefully controlled sequence-based genotyping can be a precise and reliable tool for monitoring HIV drug resistance, and they suggest that efforts to reduce variability should focus on the RT-PCR step of the assay algorithm. These efforts could involve, but are not limited to, studies on RT enzyme fidelity, primer sequences, and the number of amplification cycles of RT-PCR.
|
|
|---|
This article has been cited by other articles:
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Copyright © 2009 by the American Society for Microbiology. For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»