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AIDS:
doi: 10.1097/QAD.0000000000000267
Clinical Science

Comparison of ultra-deep versus Sanger sequencing detection of minority mutations on the HIV-1 drug resistance interpretations after virological failure

Mohamed, Sofianea,d; Penaranda, Guillaumea; Gonzalez, Dimitrib; Camus, Clairea; Khiri, Hacènea; Boulmé, Ronanb; Sayada, Chalomb; Philibert, Patrickc; Olive, Danield; Halfon, Philippea,c

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Abstract

Objective:

Drug-resistance mutations are routinely detected using standard Sanger sequencing, which does not detect minor variants with a frequency below 20%. The impact of detecting minor variants generated by ultra-deep sequencing (UDS) on HIV drug-resistance interpretations has not yet been studied.

Design:

Fifty HIV-1 patients who experienced virological failure were included in this retrospective study.

Methods:

The HIV-1 UDS protocol allowed the detection and quantification of HIV-1 protease and reverse transcriptase variants related to genotypes A, B, C, F and G. DeepChek-HIV simplified drug-resistance interpretation software was used to compare Sanger sequencing and UDS.

Results:

The total time required for the UDS protocol was found to be approximately three times longer than Sanger sequencing with equivalent reagent costs. UDS detected all of the mutations found by population sequencing and identified additional resistance variants in all patients. An analysis of drug resistance revealed a total of 643 and 224 clinically relevant mutations by UDS and Sanger sequencing, respectively. Three resistance mutations with more than 20% prevalence were detected solely by UDS: A98S (23%), E138A (21%) and V179I (25%). A significant difference in the drug-resistance interpretations for 19 antiretroviral drugs was observed between the UDS and Sanger sequencing methods. Y181C and T215Y were the most frequent mutations associated with interpretation differences.

Conclusion:

A combination of UDS and DeepChek software for the interpretation of drug resistance results would help clinicians provide suitable treatments. A cut-off of 1% allowed a better characterization of the viral population by identifying additional resistance mutations and improving the drug-resistance interpretation.

© 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

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