Biomedical subjects

Hauke Walter

Publications and source records attributed to Hauke Walter.

16 recordsLinked to original sources

PubMed2007

Persistence of lamivudine-sensitive HIV-1 quasispecies in the presence of lamivudine in vitro and in vivo.

The establishment of persistent infection is one of the major obstacles facing the eradication of HIV-1. To improve our understanding of the mechanisms of viral persistence, we investigated the fate of defined viral quasispecies under conditions that might favor their eradication. We retrospectively analyzed changes in viral populations in HIV-1-infected patients treated with zidovudine/lamivudine and subsequently failing therapy within months in the years 1996 to 1997. Furthermore, we developed an in vitro model based on simultaneous infection of T cells with 2 or more different viral variants. Changes in minority quasispecies of drug-sensitive and drug-resistant HIV-1 variants based on lamivudine and the corresponding lamivudine-resistant viruses carrying the M184I or M184V mutation were investigated using an allele-specific real-time polymerase chain reaction assay. We demonstrate that lamivudine-sensitive and lamivudine-resistant HIV-1 variants are able to persist despite highly unfavorable conditions in vivo and in vitro and that selective advantages of viral variants can vary depending on the complexity of other simultaneously replicating viral variants.

Anti-HIV Agents↗

PubMed2007

Dual selection pressure by drugs and HLA class I-restricted immune responses on human immunodeficiency virus type 1 protease.

To determine the influence of human immunodeficiency virus type 1 (HIV-1)-specific CD8+ T cells on the development of drug resistance mutations in the HIV-1 protease, we analyzed protease sequences from viruses from a human leukocyte antigen class I (HLA class I)-typed cohort of 94 HIV-1-positive individuals. In univariate statistical analyses (Fisher's exact test), minor and major drug resistance mutations as well as drug-associated polymorphisms showed associations with HLA class I alleles. All correlations with P values of 0.05 or less were considered to be relevant without corrections for multiple tests. A subset of these observed correlations was experimentally validated by enzyme-linked immunospot assays, allowing the definition of 10 new epitopes recognized by CD8+ T cells from patients with the appropriate HLA class I type. Several drug resistance-associated mutations in the protease acted as escape mutations; however, cells from many patients were still able to generate CD8+ T cells targeting the escape mutants. This result presumably indicates the usage of different T-cell receptors by CD8+ T cells targeting these epitopes in these patients. Our results support a fundamental role for HLA class I-restricted immune responses in shaping the sequence of the HIV-1 protease in vivo. This role may have important clinical implications both for the understanding of drug resistance pathways and for the design of therapeutic vaccines targeting drug-resistant HIV-1.

Alleles↗

PubMed2006

Superiority of infectivity-based over particle-based methods for quantitation of drug resistant HIV-1 as inocula for cell cultures.

Performance of phenotypic assays and replication capacity assays require normalization of virus input. Therefore, quantitation of HIV-1 in supernatants to inoculate cell cultures is an important step. Since the gold standard for the determination of infectivity, the tissue culture infectious dose 50% (TCID50) is time-consuming, several other methods are in use. This study evaluated methods for the quantitation of drug resistant viruses in cell culture supernatants. The compared methods were based on the detection of viral structural components like genomic RNA or p24 antigen (CA-p24) (particle-based), the determination of reverse transcriptase (RT) activity, and methods based on the detection of viral infectivity like LTR-induced beta-galactosidase (beta-gal) activity and the TCID50 (infectivity-based). Significant correlations were observed between beta-gal activity and TCID50, and between CA-p24 and viral RNA. RT activity did not correlate with any other method. However, RT activity correlated significantly with infectivity when non-resistant subtype-B isolates were analyzed. In contrast to viral infectivity, CA-p24 exhibited a long half life and accumulated in cell culture, resulting in decreasing ratios of infectious virions to CA-p24 over time. As a consequence, relative replication capacities of drug resistant viruses were only determined reliably if the input virus was normalized according to infectivity. In conclusion, RT activity seems to be feasible for non-resistant subtype-B viruses but may be of limited use for non-B subtypes and for drug resistant viruses. Methods determining infectivity are most suitable for quantitation of cell culture inocula, whereas particle-based assays are more appropriate for quantitation of virus production during an experiment.

Anti-HIV Agents↗

PubMed2006

Antiviral activity of Arthrospira-derived spirulan-like substances.

Natural substances offer interesting pharmacological perspectives for antiviral drug development in regard to broad-spectrum antiviral properties and novel modes of action. In this study we analyzed polysaccharide fractions isolated from Arthrospira platensis. Fractions containing intracellular or extracellular spirulan-like molecules showed a pronounced antiviral activity in the absence of cytotoxic effects. Using specific assays for the quantification of viral replication in vitro, these substances exhibited strong inhibition of human cytomegalovirus, herpes simplex virus type 1, human herpesvirus type 6 and human immunodeficiency virus type 1, while only weak or no inhibition was noted for Epstein-Barr virus and influenza A virus. Considering herpesviruses, antiviral effects were most pronounced when the cells were preincubated with the substances prior to the addition of virus, indicating that antiviral action may be primarily targeted to virus entry. However, an inspection of the inhibition of human cytomegalovirus protein synthesis clearly demonstrated that intracellular steps also contributed to the antiviral effect. In the case of human immunodeficiency virus, inhibition occurred at a stage later than viral entry. Thus, spirulan-like substances possess a marked antiherpesviral and anti-HIVactivity based on different modes of action. Further development of these substances might yield novel candidates of broad-spectrum antiviral drugs.

Antiviral Agents↗

PubMed2005

Detection of minor populations of drug-resistant HIV-1 in acute seroconverters.

OBJECTIVE: The transmission of drug-resistant HIV-1 is a major health concern. To date, most clinical studies have relied on sequencing techniques for genotypic analyses which do not allow quantification of minority viral populations below 25%. As minor populations of drug-resistant HIV-1 could impact the efficiency of antiretroviral therapy, this study was performed to determine the prevalence of minor populations of drug-resistant HIV-1 in acute seroconverters. DESIGN AND METHODS: Forty-nine acute seroconverters from two clinical centers in Germany were included in the study. Individuals were identified between June 1999 and March 2003, and none had received antiretroviral therapy prior to sampling. Minor populations of drug-resistant variants were detected by quantitative real-time polymerase chain reaction using allele-discriminating oligonucleotides for three key resistance mutations: L90M (protease), K103N and M184V (reverse transcriptase). The approximate discriminative power was between 0.01 and 0.2%. RESULTS: Drug-resistant variants were detected in 10 of 49 patients (20.4%). The L90M mutation was found in one of 49 (2%), the K103N mutation in five of 49 (10.2%) and the M184V mutation in six of 49 (12.2%) patients, respectively. In five of the 10 individuals with detectable drug-resistant virus (50%), the detected population represented a minor viral quasi-species (< 25% of viruses) and was not detected by direct sequencing. CONCLUSIONS: The prevalence of minor populations of drug-resistant HIV-1 in acute seroconverters can be frequently detected and may impact the success of antiretroviral therapy.

Acute Disease↗

PubMed2005

Computational methods for the design of effective therapies against drug resistant HIV strains.

The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data.

Database Management Systems↗

PubMed2003

Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes.

Therapeutic success of anti-HIV therapies is limited by the development of drug resistant viruses. These genetic variants display complex mutational patterns in their pol gene, which codes for protease and reverse transcriptase, the molecular targets of current antiretroviral therapy. Genotypic resistance testing depends on the ability to interpret such sequence data, whereas phenotypic resistance testing directly measures relative in vitro susceptibility to a drug. From a set of 650 matched genotype-phenotype pairs we construct regression models for the prediction of phenotypic drug resistance from genotypes. Since the range of resistance factors varies considerably between different drugs, two scoring functions are derived from different sets of predicted phenotypes. Firstly, we compare predicted values to those of samples derived from 178 treatment-naive patients and report the relative deviance. Secondly, estimation of the probability density of 2000 predicted phenotypes gives rise to an intrinsic definition of a susceptible and a resistant subpopulation. Thus, for a predicted phenotype, we calculate the probability of membership in the resistant subpopulation. Both scores provide standardized measures of resistance that can be calculated from the genotype and are comparable between drugs. The geno2pheno system makes these genotype interpretations available via the Internet (http://www.genafor.org/).

Anti-HIV Agents↗

PubMed2003

Distinct cross-resistance profiles of the new protease inhibitors amprenavir, lopinavir, and atazanavir in a panel of clinical samples.

A panel of 245 clinical samples with known treatment histories was retrospectively evaluated for cross-resistance to new protease inhibitors (PI). Samples with resistance to previously approved PI displayed high cross-resistance to atazanavir, whereas cross-resistance to amprenavir was considerably lower. A similar cross-resistance profile was observed for lopinavir, if a higher cut-off for resistance (9.5-fold) was applied. The enhanced efficacy of boosted PI is discussed with respect to clinically relevant cut-offs for drug resistance.

Atazanavir Sulfate↗

PubMed2003

Methods for optimizing antiviral combination therapies.

MOTIVATION: Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging. RESULTS: To estimate the activity of a drug combination against a particular viral strain, we develop a scoring function whose independent variables describe a set of antiviral agents and viral DNA sequences coding for the molecular targets of the respective drugs. The construction of this activity score involves (1) predicting phenotypic drug resistance from genotypes for each drug individually, (2) probabilistic modeling of predicted resistance values and integration into a score for drug combinations, and (3) searching through the mutational neighborhood of the considered strain in order to estimate activity on nearby mutants. For a clinical data set, we determine the optimal search depth and show that the scoring scheme is predictive of therapeutic outcome. Properties of the activity score and applications are discussed.

Algorithms↗

PubMed2003

Tenofovir resistance and resensitization.

Human immunodeficiency viruses in 321 samples from tenofovir-naïve patients were retrospectively evaluated for resistance to this nucleotide analogue. All virus strains with insertions between amino acids 67 and 70 of the reverse transcriptase (n = 6) were highly resistant. Virus strains with the Q151M mutation were divided into susceptible (n = 12) and highly resistant (n = 8) viruses. This difference was due to the absence or presence of the K65R mutation, which was confirmed by site-directed mutagenesis. Viral clones with various combinations of the mutations M41L, K70R, L210W, and T215F or T215Y were analyzed for cross-resistance induced by thymidine analogue mutations (TAMs). The levels of increased resistance induced by single, double, and triple mutations at the indicated positions could be ranked as follows: for mutants with single mutations, mutations at positions 41 > 215 > 70; for mutants with double mutations, mutations at positions 41 and 215 > 70 and 215 = 210 and 215 > 41 and 70; for mutants with triple mutations, mutations at positions 41, 210, and 215 > 41, 70, and 215. Viral clones with M184V or M184I exhibited slightly increased susceptibilities to tenofovir (0.7-fold). Almost all clones with TAM-induced resistance were resensitized when M184V was present (P < 0.001). Among the viruses in the clinical samples, the rate of tenofovir resistance significantly increased with the number of TAMs both in the samples with 184M and in those with 184V (P = 0.005 and P = 0.003, respectively). A resensitizing effect of M184V was confirmed for all samples exhibiting at least one TAM (P = 0.03). However, accumulation of at least two TAMs resulted in more than 2.0-fold reduced susceptibility to tenofovir, irrespective of the presence of M184V. Decision tree building, a classical machine learning technique, was used to generate models for the interpretation of mutations with respect to tenofovir resistance. The application of previously proposed cutoffs for a reduced response to therapy and treatment failure demonstrated the central roles of positions 215 and 65 for 1.5- and 4.0-fold reduced susceptibilities, respectively. Thus, clinically relevant resistance may be conferred by the accumulation of TAMs, and the resensitizing effect of M184V should be considered only minor.

Adenine↗

PubMed2003

Quality control trial for human immunodeficiency virus type 1 drug resistance testing using clinical samples reveals problems with detecting minority species and interpretation of test results.

Between January and March 2000, a quality control panel for human immunodeficiency virus (HIV) drug resistance testing was analyzed by 20 laboratories in five countries. The panel consisted of three clinical samples with different drug resistance genotypes and phenotypes and one HIV-negative plasma. Participants were asked to report the methods used for amplification and sequencing, a list of drug resistance-associated mutations that were detected in the protease and reverse transcriptase of each sample, and an interpretation concerning the susceptibility or resistance to 14 antiretroviral drugs. A total of 22 genotypic data sets were generated, which showed an overall good technical quality except for three participants, who failed to report key mutations for drug resistance. Problems were encountered in three respects: (i). resistant minorities of L90M in the protease, which were determined to about 12% by real-time amplification, were only detected by one-fourth of the participants; (ii). newly described resistance mutations were frequently not reported; and (iii). interpretations of drug resistance-associated mutations varied widely, in particular for protease inhibitors. In some cases, different interpretations were caused by differences in the detection of resistant minorities, but even for the same genotypic profile, interpretations varied considerably. Similar discrepancies were revealed if current Web-based interpretation systems were used to predict drug resistance for samples of the proficiency panel. This indicates that a consensus for the interpretation of drug resistance-associated mutations is urgently needed.

Antiviral Agents↗

PubMed2002

No evidence for persistence of multidrug-resistant viral strains after a 7-month treatment interruption in an HIV-1-infected individual.

The number of HIV-1-infected patients harboring multidrug-resistant viruses is increasing. Since new antiretroviral drugs with favorable resistance profiles are limited, innovative strategies are urgently needed. Treatment interruptions can lead to a loss in HIV resistance followed by improved response to reinitiated therapy. The authors report the case of a patient with sustained antiretroviral response for 3.5 years after a 7-month treatment interruption. Concomitant with an increase in replication capacity, multidrug-resistant viruses gradually disappeared during treatment interruption. Resistance to protease inhibitors (PI) was completely lost, and resistance to reverse transcriptase inhibitors was still present when therapy was reinitiated. PI-resistant variants were not detected at four time points after treatment reinitiation. The alignment of the nucleic acid sequences from all different time points suggested that the viruses obtained after treatment reinitiation evolved from less-resistant variants prior to treatment interruption. This was supported by in vitro propagation of the viral plasma population and an individual clone derived from the time point of treatment interruption. This is consistent with a model favoring reversible binding of HIV-1 to reservoirs, as has recently been proposed for follicular dendritic cells. Understanding of this process could help to exploit the reduced fitness of drug-resistant viruses for treatment interruptions.

Adult↗

PubMed2002

Diversity and complexity of HIV-1 drug resistance: a bioinformatics approach to predicting phenotype from genotype.

Drug resistance testing has been shown to be beneficial for clinical management of HIV type 1 infected patients. Whereas phenotypic assays directly measure drug resistance, the commonly used genotypic assays provide only indirect evidence of drug resistance, the major challenge being the interpretation of the sequence information. We analyzed the significance of sequence variations in the protease and reverse transcriptase genes for drug resistance and derived models that predict phenotypic resistance from genotypes. For 14 antiretroviral drugs, both genotypic and phenotypic resistance data from 471 clinical isolates were analyzed with a machine learning approach. Information profiles were obtained that quantify the statistical significance of each sequence position for drug resistance. For the different drugs, patterns of varying complexity were observed, including between one and nine sequence positions with substantial information content. Based on these information profiles, decision tree classifiers were generated to identify genotypic patterns characteristic of resistance or susceptibility to the different drugs. We obtained concise and easily interpretable models to predict drug resistance from sequence information. The prediction quality of the models was assessed in leave-one-out experiments in terms of the prediction error. We found prediction errors of 9.6-15.5% for all drugs except for zalcitabine, didanosine, and stavudine, with prediction errors between 25.4% and 32.0%. A prediction service is freely available at http://cartan.gmd.de/geno2pheno.html.

Computational Biology↗

PubMed2002

Prediction of abacavir resistance from genotypic data: impact of zidovudine and lamivudine resistance in vitro and in vivo.

Abacavir is frequently used in antiretroviral combination therapies as a potent nucleoside reverse transcriptase inhibitor (NRTI). Four mutations are selected for by abacavir in vitro and in vivo: K65R, L74V, Y115F, and M184V. Abacavir resistance has also been observed in NRTI multidrug-resistant samples. Furthermore, abacavir resistance has been described in the context of zidovudine resistance. To evaluate the genetic basis of abacavir resistance, the viral genotype and phenotypic resistance were analyzed for 307 patient samples. Low- and high-level resistances were defined as 2.5- to 5.5-fold- and >5.5-fold-reduced susceptibility, respectively. If all samples with abacavir-selected and NRTI multidrug resistance-associated mutations were scored as resistant, 27.6% of the samples were misclassified, mainly due to samples falsely scored as susceptible. Therefore, the relative frequencies of other mutations were evaluated. Mutations at codons 44 and 118 were rarely detected in abacavir-susceptible samples but were overrepresented in resistant samples. Site-directed mutagenesis of E44D, V118I, and M184V resulted in low-level resistance for the double mutant 44/184 and the triple mutant. Low-level abacavir resistance was also detected for a viral clone carrying zidovudine mutations only. Additional insertion of M184V into the zidovudine background doubled the resistance, whereas 44/118 did not lead to a further increase. Incorporating combinations of zidovudine mutations and M184V into the scoring system markedly reduced the number of misclassified samples, whereas 44/118 did not improve the prediction. In conclusion, the combination of M184V with zidovudine mutations gives rise to high-level abacavir resistance, which may be clinically relevant. Thus, options for useful sequential combinations of NRTI are limited.

Algorithms↗

PubMedDate not supplied

Technologies for measuring HIV-1 drug resistance.

Drug resistance testing significantly improves response to antiretroviral treatment in HIV-1-infected patients, therefore it has recently been implemented into current guidelines for the management of antiretroviral therapy. Knowledge about technologies for measuring drug resistance is important for several reasons: (a) differences exist between different technologies and also between assays based on the same technology; (b) the results of resistance testing are strongly dependent on the reliability and precision of the technology used; and (c) technical aspects have to be considered for a clinically relevant interpretation of drug resistance. The spectrum of genotypic and phenotypic technologies as well as the technical quality is increasing, which shifts the emphasis to the interpretation of resistance profiles. The interpretation is based on the knowledge of drug resistance-associated mutations as well as correlations between genotype and phenotype and clinical response, which are incorporated into rules-based systems. Bioinformatic techniques are used to generate mathematical models for the prediction of drug resistance from genotype. Both approaches are converging toward the prediction of clinical response. Because therapy response is dependent on many additional variables, further efforts are required for the generation of a large clinical database. This will be the basis of a prediction system that will optimize the antiretroviral therapy for each individual patient.

Anti-HIV Agents↗

PubMedDate not supplied

Genotypic drug resistance interpretation systems--the cutting edge of antiretroviral therapy.

The technical quality of genotypic and phenotypic drug resistance testing has considerably improved, and therefore the major challenge now lies in the interpretation of drug resistance. This is due to several facts: (i) in times of combination therapy, the effect of drug resistance-associated mutations cannot be considered independently, (ii) many additive and subtractive interactions between mutations exist, and resistant strains may exhibit varying degrees of cross-resistance, (iii) the phenotype cannot adequately determine slight, but clinically relevant, differences for those drugs with a narrow range of resistance, and (iv) pharmacokinetic interactions may shift relevant levels of drug resistance. Genotypic drug resistance interpretation systems are designed to solve these problems. Rule-based systems incorporate current knowledge about correlations between genotype, phenotype and clinical response. Database-driven systems use the information provided by paired geno- and phenotypic data, applying database matching search or bioinformatic approaches. For detailed comparison, 11 interpretation systems were selected which present a comprehensive system for most of the available drugs, can easily be accessed via the Internet and are regularly updated. The systems were characterized for the source data, access, input, output, and availability of clinical studies. For further comparison, existing clinical databases should be merged into one large database to allow competition between the systems. This may also solve the burning problem of clinically relevant cut-offs. Head-to-head comparisons of interpretation systems require large prospective randomized trials in which only the interpretation system is different between groups, before a consensus can be achieved for the best antiretroviral therapy of the individual patient.

Algorithms↗