A Genotypic Test for HIV-1 Tropism Combining Sanger Sequencing with Ultradeep Sequencing Predicts Virologic Response in Treatment-Experienced Patients

Abstract

A tropism test is required prior to initiation of CCR5 antagonist therapy in HIV-1 infected individuals, as these agents are not effective in patients harboring CXCR4 (X4) coreceptor-using viral variants. We developed a clinical laboratory-based genotypic tropism test for detection of CCR5-using (R5) or X4 variants that utilizes triplicate population sequencing (TPS) followed by ultradeep sequencing (UDS) for samples classified as R5. Tropism was inferred using the bioinformatic algorithms geno2pheno[coreceptor] and PSSMx4r5. Virologic response as a function of tropism readout was retrospectively assessed using blinded samples from treatment-experienced subjects who received maraviroc (N = 327) in the MOTIVATE and A4001029 clinical trials. MOTIVATE patients were classified as R5 and A4001029 patients were classified as non-R5 by the original Trofile test. Virologic response was compared between the R5 and non-R5 groups determined by TPS, UDS alone, the reflex strategy and the Trofile Enhanced Sensitivity (TF-ES) test. UDS had greater sensitivity than TPS to detect minority non-R5 variants. The median log10 viral load change at week 8 was −2.4 for R5 subjects, regardless of the method used for classification; for subjects with non-R5 virus, median changes were −1.2 for TF-ES or the Reflex Test and −1.0 for UDS. The differences between R5 and non-R5 groups were highly significant in all 3 cases (p<0.0001). At week 8, the positive predictive value was 66% for TF-ES and 65% for both the Reflex test and UDS. Negative predictive values were 59% for TF-ES, 58% for the Reflex Test and 61% for UDS. In conclusion, genotypic tropism testing using UDS alone or a reflex strategy separated maraviroc responders and non-responders as well as a sensitive phenotypic test, and both assays showed improved performance compared to TPS alone. Genotypic tropism tests may provide an alternative to phenotypic testing with similar discriminating ability.

Deep Sequencing Reveals Mutagenic Effects of Ribavirin during Monotherapy of Hepatitis C Virus Genotype 1-Infected Patients

“…Nevertheless, it is critical to differentiate minor variants from technical errors associated with library preparation and the sequencing process. By sequencing a clonal fragment, we determined for the 454 platform and the Illumina platform error rates in good accordance with data from previous studies (39,41,43,45,55). Although specialized software for additional error correction exists (33,40), we refrained from employing it in this setting due to the risk of discarding genuine minority variants.…”

“…Sequencing reads and nucleotide distributions from this positive control were compared with the Sanger sequence corresponding to the clone, which also matched the consensus sequences generated from the 454 and Illumina reads. Sanger sequencing is commonly used as a comparator for the determination of deep sequencing errors (33,(40)(41)(42) and is expected to …”

“…The insert of one sequenced plasmid clone was excised from the vector with the restriction enzyme EcoRI and was deep sequenced in parallel with the other PCR amplicon samples. In accordance with other studies (33,(39)(40)(41)(42)(43), the technical error rate was calculated by counting all nucleotide variants of the plasmid reads in the alignment that did not correspond to the sequence of the clone determined by Sanger sequencing. While insertion errors were subject to automatic removal during the mapping of the sequencing reads to the HCV-J reference genome (34), deletions with respect to the reference sequence were detected during the mapping and quantified as errors but excluded from all further analyses.…”

Factors Influencing the Sensitivity and Specificity of Conventional Sequencing in Human Immunodeficiency Virus Type 1 Tropism Testing

“…Genotypic tropism inference can be achieved by sequencing of the V3 loop within the HIV-1 gp120 protein in conjunction with a bioinformatic algorithm (11)(12)(13)(14)(15)(16). Such genotypic methods can successfully predict non-R5 tropism (17), with predictive power equivalent to the original Trofile assay (a phenotypic tropism assay) (18). Next-generation deep sequencing, a powerful method which allows the sequencing of individual template molecules by physical separation (19), is also gaining widespread use.…”

“…Next-generation deep sequencing, a powerful method which allows the sequencing of individual template molecules by physical separation (19), is also gaining widespread use. Deep sequencing has improved sensitivity and viral tropism prediction over population-based sequencing, with sensitivities comparable to the latest phenotypic assay, the enhanced-sensitivity Trofile assay (17,20).…”