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Journal of Clinical Microbiology, July 1999, p. 2291-2296, Vol. 37, No. 7
Department of Virology, University Hospital
Utrecht, Utrecht, The Netherlands1;
Infectious Diseases Unit, University of Rochester School of
Medicine and Dentistry, Rochester, New York2;
and National Institute of Child Health and Human Development,
Bethesda, Maryland3
Received 29 December 1998/Returned for modification 12 February
1999/Accepted 15 April 1999
A panel (ENVA-1) of well-defined blinded samples containing
wild-type and mutant human immunodeficiency virus type 1 (HIV-1) reverse transcriptase was analyzed by automated DNA sequencing in 23 laboratories worldwide. Drug resistance mutations at codons 41, 215, and 184 were present in the panel samples at different ratios to the
wild type. The presence of mutant genotypes was determined
qualitatively and quantitatively. All laboratories reported the
presence of sequence heterogeneities at codons 41, 215, and 184 in one
or more of the panel samples, though not all reported the correct codon
genotypes. Two laboratories reported a mutant genotype in samples
containing only the wild type, whereas two and three laboratories
failed to detect the mutant genotypes at codons 41 and 215, respectively, in a completely mutant DNA population. Mutations present
at relative concentrations of 25% of the total DNA population were
successfully identified by 13 of 23, 10 of 23, and 16 of 23 labs for
codons 41, 215, and 184Val, respectively. For more than 80% of those
laboratories that qualitatively detected the presence of a mutation
correctly, the estimated wild type/mutant ratio was less than 25%
different from the input ratio in those samples containing 25 to 50%
or 75% mutant input. This first multicenter study on the quality of
DNA sequencing approaches for identifying HIV-1 drug resistance
mutations revealed large interlaboratory differences in the quality of
the results. The application of these procedures in their current state
would in several cases lead to inaccurate or even incorrect diagnostic results. Therefore, proper quality control and standardization are
urgently needed.
The incomplete inhibition of human
immunodeficiency virus type 1 (HIV-1) replication may result in the
emergence of viral isolates with reduced susceptibility (resistance) to
an antiviral drug. For most drugs used in the treatment of
HIV-1-infected individuals to date, specific resistance-conferring
mutations have been identified (16). The determination of
these mutations in clinical isolates may serve as a surrogate for
laborious and time-consuming classical biological drug susceptibility
determinations (2, 6, 13, 17).
DNA sequencing, using various automated technologies, is widely applied
to identify drug resistance mutations (17). In addition to
enzymatic sequencing approaches used with most methodologies, an
innovative technology involving the differential hybridization of
nucleic acid sequences with short oligonucleotide arrays present on
microchips is currently under evaluation (9).
The high mutation rate of HIV results in continuous changes in the
composition of the viral population and the presence of sequence
heterogeneities (sequence mixtures) along the viral genome (3, 11,
12). Population-based sequencing approaches enable the genotypic
characterization of the predominant viral species in a patient. On the
other hand, analysis of multiple (individual) cloned genes provides a
detailed insight into the interactions of mutations present on the same
genome and also allows for a more reliable detection of minority
species. In general the sensitivities of various sequencing approaches
in the detection of minority virus populations are highly variable
(4).
At present, genotypic resistance determinations are performed mainly by
research laboratories, without any systematic interlaboratory standardization or quality control. However, genotypic resistance determinations are of increasing diagnostic value in a number of
clinical settings, including monitoring of patient resistance prior to
therapy initiation or at the time of therapy failure (1, 5,
14).
This study was conducted to investigate the quality and relative
sensitivity of DNA sequence analysis procedures in a large number of
laboratories worldwide. Using their standard laboratory methods and
technologies, participants analyzed a coded set of plasmid mixtures
containing nucleotide mixtures at several drug resistance codons and
reported the results of both qualitative and quantitative interpretation.
ENVA-1 panel.
A panel of nine plasmid mixtures at a
concentration of 100 pg/ml of water (approximately 20 × 106 DNA copies/ml) was distributed among participating
research and commercial laboratories in Europe and the United States.
Four different plasmid constructs harboring HIV-1 HxB2 reverse
transcriptase (RT) genes (amino acids 1 to 563) without flanking HIV
sequences were used to prepare the panel: one containing a completely
wild-type RT sequence, one containing zidovudine resistance mutations
at codons 41 (ATG
0095-1137/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Worldwide Evaluation of DNA Sequencing Approaches
for Identification of Drug Resistance Mutations in the Human
Immunodeficiency Virus Type 1 Reverse Transcriptase
,*
and
ABSTRACT
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
INTRODUCTION
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
MATERIALS AND METHODS
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
CTG) and 215 (ACCTAC), and two containing either the 184Ile (ATGATA) or 184Val (ATGGTG) mutation, conferring resistance to lamivudine. Mutations had been introduced into the wild-type HxB2 sequence via site-directed mutagenesis and confirmed by
sequence analysis of the complete RT genes (2). The
concentration of the source plasmids was determined
spectrophotometrically, and subsequently mixtures containing 25, 50, and 75% of the mutant genotype were prepared. The composition of these
mixtures was checked and confirmed by using a semiquantitative point
mutation assay (data not shown) (7, 19). Thereafter, the
source plasmids were mixed at different ratios to create a panel of
nine samples with wild-type and resistant genotypes at various relative
concentrations between 0 and 100% (Table
1). It should be noted that the mutations at codons 41 and 215 are present on the same source plasmid. Therefore, the amount of mutant codon 41 in a sample is always identical to the
amount of mutant codon 215 in that sample.
TABLE 1.
Composition of ENVA-1 panel
Genotypic analysis of the panel samples. The panel samples (ENVA-1 panel) were coded and sent to the participants at room temperature. Participants treated the material as purified DNA and performed the genotypic analysis starting from amplification, by using their standard in-house sequencing procedures. In addition, participants filled out a questionnaire requesting information on the technologies and analysis procedures applied.
Panel samples consisted of complete wild-type or mutant genotypes or a mixture of these. In all samples containing a mixed genotype the minority genotype was always present at a concentration of least 5% (Table 1). Participants were requested to perform sequence analysis on all the samples and report the interpreted nucleotide sequence between nucleotides 30 and 800 of RT (amino acids 10 to 265) for each of the samples. In addition, laboratories were requested to provide semiquantitative information (percentages) on the heterogeneic positions, based on the sequencing results for each of the mixed nucleotide positions.Data analysis. Data were collected on standard report forms and entered into a central database at the European Network for the Evaluation of New Antiviral Treatments (ENVA) headquarters. Information was collected on the sequence analysis procedures and technology, i.e., sequencing hardware, DNA labelling technology, and analysis of one or both strands. In addition, the obtained qualitative and quantitative results for each of the heterogeneous positions in the panel were collected, as well as all additional mutations reported by the participants. After being entered into the database, the blinded results were reviewed for data entry errors by each of the participants.
For each of the participants we calculated the so-called mutation score (M). M is the total number of positions at which the presence of a mutation was reported, irrespective of its concentration relative to that of the wild type. The total (cumulative) number of mutations present in the panel (i.e., codons harboring between 5 and 100% of the mutations) was 25, indicating that the maximal M that could be achieved was 25. Subsequent analyses focused on the determination of the sensitivities and accuracies of the methodologies in relation to the input mutant or wild-type concentration.| |
RESULTS |
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Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
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Participating laboratories and technologies used. Sequence analysis. A total of 23 laboratories participated on a voluntary basis in the study: 11 European and 12 U.S. labs. The European labs were ENVA collaborating laboratories studying HIV-1 drug resistance (eight), independent research labs (two), or commercial DNA sequencing laboratories (one). The U.S.-based laboratories were ACTG laboratories (ten), a biotechnology company laboratory (one), and a laboratory that performed sequence analysis on a contract basis for clinical trials (one).
As shown in Table 2, none of the labs used manual sequencing technologies for the analysis of the panel. Seventeen of 23 labs (74%) used Applied Biosystems International (ABI) (Foster City, Calif.) automated fluorescent sequencing technology (ABI models 310, 373, and 377). The remaining six laboratories used one of the other automated platforms, i.e., ALF or ALF-express (Pharmacia Upjohn, Uppsala, Sweden), Amersham Vistra (Amersham, Little Chalfont, United Kingdom), or Affymetrix gene chip technology (Santa Clara, Calif.). This distribution of sequencing hardware and sequencing technologies allowed a comparison of individual laboratory performance but did not provide sufficient data to assess the relative performance of the different technologies.
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Detection of resistance mutations.
The drug
resistance-conferring mutations were located at three amino acid and
four independent nucleotide positions, i.e., codon 41 (ATGCTG),
184Val (ATGGTG), 184Ile (ATGATA), and 215 (ACCTAC). The
nine panel samples encoded a complete wild-type genotype at 11 of these
nucleotide positions and a total of 25 positions at which a mutant
(drug-resistant) genotype was present in at least 5% of the RT
population. For each of the participating laboratories the total number
of positions was scored at which a mutant (resistant) genotype was
reported irrespective of its relative concentration (M) (Table 2). The
maximum M was 25. The highest score obtained was 22, whereas one of the
participants failed to detect a correct mutant genotype at any of the
25 positions. No differences in M were observed between labs that based
the results on sequence analysis of one strand compared to those which analyzed both strands.
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GTG) in 25% of the DNA population, its presence was
reported by 16 of the laboratories when in a background of 75%
wild-type methionine (ATG) and by 14 of the laboratories when present
in a background of 50% wild-type (ATG) and 25% codon 184 isoleucine
mutants (ATA; Table 4). The presence of a third nucleotide change
(ATGATA) in the sample harboring the three codon 184 genotypes (sample S-1) was detected by only nine laboratories, suggesting that
the sensitivities for the detection of different mutations may not be
equal for each of the mutations.
Mutations present in the panel at codons 41 and 215 originated from a
single plasmid. Therefore, by definition the input concentrations for
both mutations within a sample were identical. Concordance of the
results for these codons was checked for each of the participants that
had analyzed both codons and reported the correct wild-type and mutant
codons. For each panel sample, concordant results were obtained by 74 to 95% of the laboratories, with the lowest level of concordance
(79%) in the panel sample containing 25% mutant genotypes (Table 3).
Even in the samples containing a complete wild-type or mutant DNA
population, an incomplete concordance was observed at 90 and 95%, respectively.
Quantitative detection of sequence heterogeneities. In addition to the qualitative detection of the mutations in the panel samples, laboratories also reported their best estimates for the relative proportions of wild-type and mutant genotypes at the four mutation positions in each panel sample. The majority of laboratories that reported the presence of a sequence heterogeneity also estimated its proportion, in most cases based on the double-peak spectra at these nucleotide positions in the electropherograms. These results, as shown in Fig. 1, demonstrated extensive interlaboratory differences in the estimated proportions. For those laboratories that did detect the presence of the mutation and reported a quantitative estimate, we analyzed the variation in estimated output concentrations for samples containing mixed RT populations at an input of 25 to 75% mutant genotype (Table 5). The estimated proportions were less than 25% different from the input concentration for 83 to 100% of the laboratories. For 47 to 100% of the laboratories the accuracy of the estimated proportion mutant genotype in the samples was less than 10% different from the input concentration (Table 5).
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5%), an incorrect mutant codon was reported (
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DISCUSSION |
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Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
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This is the first large-scale study evaluating the quality of sequence analysis approaches for the identification of drug resistance mutations in the HIV-1 RT gene. Recent developments and improvements in genotyping technologies (9, 15, 17), a rapidly evolving understanding of the effects of resistance mutations on viral drug susceptibility, and the fact that biological drug susceptibility assays are costly, difficult to standardize, and extremely time-consuming (2, 6, 13) have led to an increasing use of genotypic drug resistance methods for HIV. At present these methods are mainly applied by research laboratories but are beginning to be implemented diagnostically. Most importantly, genotyping to determine the resistance profile in patients virologically showing treatment failure has recently been shown to be beneficial in selecting a salvage regimen (1, 5), and as such, sequencing results become of increasing importance in the clinical care of HIV-1-infected patients.
This first study evaluating the quality of HIV drug resistance genotyping protocols was based on the use of recombinant RT genes derived from a reference virus, into which mutations had been introduced via site-directed mutagenesis. This approach enabled a direct comparison of the reliability of DNA sequencing protocols in the absence of factors such as variation introduced by viral quasispecies, the nucleic acid extraction procedure, or the cDNA synthesis reactions. Participants used their standard sequencing hardware, procedures, and protocols to analyze the panel samples. Most of the participants used an ABI sequencer (17 of 23 labs); the remaining six labs used the additional available sequencing technologies. This distribution of technologies therefore did not allow the comparison of the results for each hardware technology. Moreover, the qualitative interpretation of the results demonstrated highly variable scores even between laboratories using the same sequencing technology, indicating that interlaboratory differences are extensive and may affect the results more than the differences between the technologies. The striking differences in the M values show that large differences exist in the quality of DNA sequencing results of laboratories dedicated to performing these types of analyses routinely on a research or even diagnostic basis.
The qualitative interpretation of the laboratory results for each of the panel samples demonstrated that none of the panel samples, including those containing only wild-type or mutant genotypes, was scored correctly by all of the laboratories. Incorrect codon calls, i.e., the detection of a codon sequence that did not reflect the wild-type or the mutant sequence, were reported for several of the panel samples, in particular for codons 41 and 184, independent of the mutant concentration. However, all these calls originated from three (13%) of the participants. No incorrect codons at the mutation sites were reported by any of the other participants.
In addition, the results for codons 41 and 215 demonstrated that some laboratories missed the presence of a resistance mutation, even in samples with a homogeneous genetic makeup, or in the opposite situation, the presence of a mutation was reported in samples containing a complete wild-type input. It is of note that the participant detecting the codon 41 mutation, when it was present at the level of 5%, also reported the presence of this mutation in the purely wild-type specimen. This suggests that the reported detection of the 5% minority species might result from a nonspecific sequencing reaction or sample contamination and does not necessarily reflect a highly sensitive and specific procedure.
Upon entry of the data into the database all participants reviewed the blinded results for data entry errors. It cannot be excluded that some errors may have been introduced somewhere in the entire multistep laboratory process or at the steps of data analysis, data reporting, and data entry into the central database. Since, except for data entry into a central database, all these procedures are part of the standard sample manipulation process in HIV-1 genotyping, the results may be a good reflection of the actual overall quality of these procedures in daily practice.
The analysis of the results did not include an evaluation of the quality of the sequence reaction, e.g., signal strength or peak heights, and its effect on the sequence interpretation. Since the decision to use the sequence results for interpretation was in the hands of the participants, without any predefined quality criteria, differences in the quality of the sequence reactions itself may partially explain the observed interlaboratory differences.
The results of this study indicate that before applying DNA sequencing diagnostically for the detection of drug resistance mutations, considerable improvements need to be made in the quality of the results and procedures. In order to achieve this and monitor the quality of these procedures on a continuous basis, the installation of proper quality control programs and the standardization of protocols are essential. A significant improvement in the overall quality may also come from the use of dedicated kits and procedures to perform HIV-1 drug resistance genotyping, as recently introduced by ABI and Visible Genetics (Toronto, Canada).
The sensitivity of detecting a mutant genotype when this was present at
a relative concentration of 25% was comparable for the mutations at
codons 41 and 215 and for the 184-valine mutation. Interestingly, a
much lower frequency was observed for the 184-isoleucine mutation. This
might be due to differences in the sensitivities of the sequencing
procedures to detect each of the nucleotide changes. The 184-isoleucine
mutation is the result of a GA mutation, whereas for all three other
codons at least one of the base changes is due to a mutation in which
the wild-type A nucleotide is replaced (codon 41, AG; codon 215, AT; and CA, codon 184Val AG). The relatively low sensitivity
for codon 184-isoleucine was specifically observed in a combination
with both the wild type and valine variant, indicating that the high
level of variation in the codon might have affected the interpretation
of the analyzed nucleotide sequence. Another explanation might be that
the codon 184-isoleucine mutation was unexpected by the participants,
since the mutation is rather infrequent in clinical isolates from
extensively lamivudine-treated patients (8, 10, 18).
As mentioned before, the inputs for codons 41 and 215 were identical, as the mutations were coupled on the source plasmid. The concordance of results for codons 41 and 215, based on the qualitative results, was high, though it was complete in none of the samples. The maximum variation, i.e., a 50% wild-type and mutant mixture, resulted in only 79% concordance, again suggesting mutation-specific differences in mutation detection sensitivities. Apart from possible explanations mentioned before, this difference might also be due to other factors such as the distance of the mutation from the sequencing primer, resulting in divergent signal strengths at the location of the mutations.
The quantitative determination of the mutations demonstrated that laboratories capable of detecting a mutation qualitatively generally estimated its relative concentration with 25% accuracy from the input concentration. This indicates that laboratories performing good quality sequencing should be able to differentiate relative mutant concentrations in strata of 25%.
This study demonstrates that extensive differences exist in the quality of DNA sequence analysis for the identification of HIV-1 drug resistance mutations. Although the capacity to determine mutations was analyzed only for the HIV-1 RT gene, there is no reason to assume that the quality of results would be different for the protease gene or other target genes and organisms. In summary, this first multicenter evaluation of DNA sequence analysis procedures for HIV-1 drug resistance demonstrates large differences in the overall quality of the results. Many of the laboratories generated moderate to good results, while none of the labs were perfect. A small number of laboratories demonstrated poor performance. Therefore, the clinical application of DNA sequencing results should be considered with care, and clinicians should be clearly educated about the current limitations of sequencing technology for HIV-1 drug resistance genotyping.
As an important step towards the improvement of the quality of the results, the development of quality control programs for genotyping is essential.
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ACKNOWLEDGMENTS |
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We thank all who contributed to the study: M. Arens, J. Albert, B. Clotet, R. Colgrove, D. Descamps, E. Fisher, D. Huang, V. Johnson, L. Johnston-Dow, D. de Jong, E. Lorenzo, S. Kaye, D. Kuritzkes, B. Masquelier, C. Nielsen, L. Perrin, S. Rasheed, R. Respess, R. Shafer, G. Sitbon, A. M. Vandamme, O. Weislow, and Y. Zhao. Furthermore, we thank A. M. van Loon for critically reading the manuscript. R. Tedder and S. Kaye are thanked for their help in the initial quality control of the source plasmids.
This study was supported by the Biomed-2 program of the European Commission (grant BMH4-CT96-0409).
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FOOTNOTES |
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* Corresponding author. Mailing address: Department of Virology, University Hospital Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Phone: 31 30 250 6526. Fax: 31 30 250 5426. E-mail: r.schuurman{at}lab.azu.nl.
On behalf of the European Network for the Virological Evaluation of
International Trials for New Anti-HIV Therapies.
On behalf of the Sequencing Working Group.
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Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
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Journal of Clinical Microbiology, July 1999, p. 2291-2296, Vol. 37, No. 7
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Copyright © 1999, American Society for Microbiology. All rights reserved.
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