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.
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-1patients 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.
Authors: Dana S Clutter; Gelareh Mazarei; Ruma Sinha; Justen Manasa; Janin Nouhin; Ellen LaPrade; Sara Bolouki; Philip L Tzou; Jessica Hannita-Hui; Malaya K Sahoo; Peter Kuimelis; Robert G Kuimelis; Benjamin A Pinsky; Gary K Schoolnik; Arjang Hassibi; Robert W Shafer Journal: J Mol Diagn Date: 2019-04-23 Impact factor: 5.568
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Authors: Dario A Dilernia; Jung-Ting Chien; Daniela C Monaco; Michael P S Brown; Zachary Ende; Martin J Deymier; Ling Yue; Ellen E Paxinos; Susan Allen; Alfredo Tirado-Ramos; Eric Hunter Journal: Nucleic Acids Res Date: 2015-06-22 Impact factor: 16.971
Authors: Michael T Pyne; Keith E Simmon; Melanie A Mallory; Weston C Hymas; Jeffery Stevenson; Adam P Barker; David R Hillyard Journal: J Clin Microbiol Date: 2022-06-14 Impact factor: 11.677
Authors: Ivo N SahBandar; Genesis Samonte; Elizabeth Telan; Nalyn Siripong; Mahdi Belcaid; David Schanzenbach; Susan Leano; Haorile Chagan-Yasutan; Toshio Hattori; Cecilia M Shikuma; Lishomwa C Ndhlovu Journal: AIDS Res Hum Retroviruses Date: 2017-07-05 Impact factor: 2.205
Authors: Jenna Weber; Ilona Volkova; Malaya K Sahoo; Philip L Tzou; Robert W Shafer; Benjamin A Pinsky Journal: J Mol Diagn Date: 2019-08-02 Impact factor: 5.568
Authors: Bram Vrancken; Nídia Sequeira Trovão; Guy Baele; Eric van Wijngaerden; Anne-Mieke Vandamme; Kristel van Laethem; Philippe Lemey Journal: Viruses Date: 2016-01-07 Impact factor: 5.048