Jannik Fonager1, Jonas T Larsson2, Christian Hussing3, Frederik Neess Engsig4, Claus Nielsen3, Thea Kølsen Fischer3. 1. Department of Microbiological Diagnostics and Virology, Statens Serum Institut, Copenhagen, Denmark. Electronic address: FON@ssi.dk. 2. Department of Microbiology and Infection Control, Statens Serum Institut, Copenhagen, Denmark. 3. Department of Microbiological Diagnostics and Virology, Statens Serum Institut, Copenhagen, Denmark. 4. Department of Infectious Diseases, Copenhagen University Hospital, Hvidovre, Denmark.
Abstract
BACKGROUND: The current widely applied standard method to screen for HIV-1 genotypic resistance is based on Sanger population sequencing (Sseq), which does not allow for the identification of minority variants (MVs) below the limit of detection for the Sseq-method in patients receiving integrase strand-transfer inhibitors (INSTI). Next generation sequencing (NGS) has facilitated the detection of MVs at a much deeper level than Sseq. OBJECTIVES: Here, we compared Illumina MiSeq and Sseq approaches to evaluate the detection of MVs involved in resistance to the three commonly used INSTI: raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG). STUDY DESIGN: NGS and Sseq were used to analyze RT-PCR products of the HIV-1 integrase coding region from six patients and in serial samples from two patients. NGS sequences were assembled and analyzed using the low frequency variant detection (LFVDT) tool in CLC genomic workbench. RESULTS: Sseq detected INSTI resistance and accessory mutations in three of the patients (called INSTI Res+), while no resistance or accessory mutations were detected in the remaining three patients (called INSTI Res-). Additional INSTI resistance and/or accessory mutations were detected by NGS analysis of integrase sequences from all three INSTI Res+ and one INSTI Res- patient. CONCLUSION: Our observations suggested that NGS demonstrated a higher sensitivity than sSEQ in the identification of INSTI relevant MVs both in patients at treatment baseline and in patients receiving INSTI therapy. Thus NGS can be a valuable tool in monitoring of antiretroviral minority resistance in patients receiving INSTI therapy.
BACKGROUND: The current widely applied standard method to screen for HIV-1 genotypic resistance is based on Sanger population sequencing (Sseq), which does not allow for the identification of minority variants (MVs) below the limit of detection for the Sseq-method in patients receiving integrase strand-transfer inhibitors (INSTI). Next generation sequencing (NGS) has facilitated the detection of MVs at a much deeper level than Sseq. OBJECTIVES: Here, we compared Illumina MiSeq and Sseq approaches to evaluate the detection of MVs involved in resistance to the three commonly used INSTI: raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG). STUDY DESIGN: NGS and Sseq were used to analyze RT-PCR products of the HIV-1 integrase coding region from six patients and in serial samples from two patients. NGS sequences were assembled and analyzed using the low frequency variant detection (LFVDT) tool in CLC genomic workbench. RESULTS: Sseq detected INSTI resistance and accessory mutations in three of the patients (called INSTI Res+), while no resistance or accessory mutations were detected in the remaining three patients (called INSTI Res-). Additional INSTI resistance and/or accessory mutations were detected by NGS analysis of integrase sequences from all three INSTI Res+ and one INSTI Res- patient. CONCLUSION: Our observations suggested that NGS demonstrated a higher sensitivity than sSEQ in the identification of INSTI relevant MVs both in patients at treatment baseline and in patients receiving INSTI therapy. Thus NGS can be a valuable tool in monitoring of antiretroviral minority resistance in patients receiving INSTI therapy.
Authors: Ronit R Dalmat; Negar Makhsous; Gregory G Pepper; Amalia Magaret; Keith R Jerome; Anna Wald; Alexander L Greninger Journal: J Clin Microbiol Date: 2018-11-27 Impact factor: 5.948
Authors: Keylie M Gibson; Margaret C Steiner; Uzma Rentia; Matthew L Bendall; Marcos Pérez-Losada; Keith A Crandall Journal: Viruses Date: 2020-07-14 Impact factor: 5.048