Stéphanie Raymond1, Florence Nicot2, Florence Abravanel3, Luce Minier2, Romain Carcenac2, Caroline Lefebvre2, Agnès Harter2, Guillaume Martin-Blondel4, Pierre Delobel4, Jacques Izopet3. 1. INSERM U1043, CNRS UMR 5282, Toulouse University Paul Sabatier, CPTP, Toulouse, F-31300 France; CHU de Toulouse, Hôpital Purpan, Laboratoire de Virologie, Toulouse, F-31300 France. Electronic address: raymond.s@chu-toulouse.fr. 2. CHU de Toulouse, Hôpital Purpan, Laboratoire de Virologie, Toulouse, F-31300 France. 3. INSERM U1043, CNRS UMR 5282, Toulouse University Paul Sabatier, CPTP, Toulouse, F-31300 France; CHU de Toulouse, Hôpital Purpan, Laboratoire de Virologie, Toulouse, F-31300 France. 4. INSERM U1043, CNRS UMR 5282, Toulouse University Paul Sabatier, CPTP, Toulouse, F-31300 France; CHU de Toulouse, Hôpital Purpan, Service des Maladies Infectieuses et Tropicales, Toulouse, F-31300 France.
Abstract
BACKGROUND: Patients on antiretroviral therapy could benefit from HIV-1 DNA resistance genotyping for exploring virological failure with low viral load or to guide treatment simplification. Few new generation sequencing data are available. OBJECTIVE: To check that the automated deep sequencing Sentosa platform (Vela DX) detected minority resistant variants well enough for HIV DNA genotyping. STUDY DESIGN: We evaluated the Sentosa SQ HIV genotyping assay with automated extraction on 40 DNA longitudinal samples from treatment-experienced patients by comparison with Sanger sequencing. HIV drug resistance was interpreted using the ANRS algorithm (v29) at the threshold of 20 % and 3 %. RESULTS: The Sentosa SQ HIV genotyping assay was 100 % successful to amplify and sequence PR and RT and 86 % to amplify and sequence IN when the HIV DNA load was >2.5 log copies/million cells. The Sentosa and Sanger sequencing were concordant for predicting PR-RT resistance at the threshold of 20 % in 14/18 samples successfully sequenced. A higher level of resistance was predicted by Sentosa in three samples and by Sanger in one sample. The prevalence of resistance was 7 % to PI, 59 % to NRTI, 31 % to NNRTI and 20 % to integrase inhibitors using the Sentosa SQ genotyping assay at the threshold of 3 %. Seven additional mutations <20 % were detected using the Sentosa assay. CONCLUSION: Automated DNA extraction and sequencing using the Sentosa SQ HIV genotyping assay accurately predicted HIV DNA drug resistance by comparison with Sanger. Prospective studies are needed to evaluate the clinical interest of HIV DNA genotyping.
BACKGROUND:Patients on antiretroviral therapy could benefit from HIV-1 DNA resistance genotyping for exploring virological failure with low viral load or to guide treatment simplification. Few new generation sequencing data are available. OBJECTIVE: To check that the automated deep sequencing Sentosa platform (Vela DX) detected minority resistant variants well enough for HIV DNA genotyping. STUDY DESIGN: We evaluated the Sentosa SQ HIV genotyping assay with automated extraction on 40 DNA longitudinal samples from treatment-experienced patients by comparison with Sanger sequencing. HIV drug resistance was interpreted using the ANRS algorithm (v29) at the threshold of 20 % and 3 %. RESULTS: The Sentosa SQ HIV genotyping assay was 100 % successful to amplify and sequence PR and RT and 86 % to amplify and sequence IN when the HIV DNA load was >2.5 log copies/million cells. The Sentosa and Sanger sequencing were concordant for predicting PR-RT resistance at the threshold of 20 % in 14/18 samples successfully sequenced. A higher level of resistance was predicted by Sentosa in three samples and by Sanger in one sample. The prevalence of resistance was 7 % to PI, 59 % to NRTI, 31 % to NNRTI and 20 % to integrase inhibitors using the Sentosa SQ genotyping assay at the threshold of 3 %. Seven additional mutations <20 % were detected using the Sentosa assay. CONCLUSION: Automated DNA extraction and sequencing using the Sentosa SQ HIV genotyping assay accurately predicted HIV DNA drug resistance by comparison with Sanger. Prospective studies are needed to evaluate the clinical interest of HIV DNA genotyping.
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: Hezhao Ji; Paul Sandstrom; Roger Paredes; P Richard Harrigan; Chanson J Brumme; Santiago Avila Rios; Marc Noguera-Julian; Neil Parkin; Rami Kantor Journal: Viruses Date: 2020-05-27 Impact factor: 5.048