Name
Title | ||
|---|---|---|
Genotypic tropism testing by massively parallel sequencing: qualitative and quantitative analysis. |
Abstract | ||
|---|---|---|
Inferring viral tropism from genotype is a fast and inexpensive alternative to phenotypic testing. While being highly predictive when performed on clonal samples, sensitivity of predicting CXCR4-using (X4) variants drops substantially in clinical isolates. This is mainly attributed to minor variants not detected by standard bulk-sequencing. Massively parallel sequencing (MPS) detects single clones thereby being much more sensitive. Using this technology we wanted to improve genotypic prediction of coreceptor usage.Plasma samples from 55 antiretroviral-treated patients tested for coreceptor usage with the Monogram Trofile Assay were sequenced with standard population-based approaches. Fourteen of these samples were selected for further analysis with MPS. Tropism was predicted from each sequence with geno2pheno[coreceptor].Prediction based on bulk-sequencing yielded 59.1% sensitivity and 90.9% specificity compared to the trofile assay. With MPS, 7600 reads were generated on average per isolate. Minorities of sequences with high confidence in CXCR4-usage were found in all samples, irrespective of phenotype. When using the default false-positive-rate of geno2pheno[coreceptor] (10%), and defining a minority cutoff of 5%, the results were concordant in all but one isolate.The combination of MPS and coreceptor usage prediction results in a fast and accurate alternative to phenotypic assays. The detection of X4-viruses in all isolates suggests that coreceptor usage as well as fitness of minorities is important for therapy outcome. The high sensitivity of this technology in combination with a quantitative description of the viral population may allow implementing meaningful cutoffs for predicting response to CCR5-antagonists in the presence of X4-minorities. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1186/1472-6947-11-30 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
phenotype,false positive rate,health informatics,viral tropism,genotype | Massive parallel sequencing,Tropism,Data mining,Genotype,Maraviroc,Tissue tropism,Computational biology,Virology,Medicine | Journal |
Volume | Issue | ISSN |
11 | 1 | 1472-6947 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Däumer | 1 | 88 | 15.64 |
| Rolf Kaiser | 2 | 213 | 47.27 |
| Rolf Klein | 3 | 0 | 0.34 |
| Thomas Lengauer | 4 | 3155 | 605.03 |
| Bernhard Thiele | 5 | 0 | 0.34 |
| Alexander Thielen | 6 | 11 | 1.51 |