Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments

Andrea Arias, Pablo López, Raphael Sánchez, Yasuhiro Yamamura and Vanessa Rivera-Amill
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Andrea Arias: AIDS Research Infrastructure Program, Ponce Health Sciences University-Ponce Research Institute, Puerto Rico 00716-2348, USA
Pablo López: AIDS Research Infrastructure Program, Ponce Health Sciences University-Ponce Research Institute, Puerto Rico 00716-2348, USA
Raphael Sánchez: AIDS Research Infrastructure Program, Ponce Health Sciences University-Ponce Research Institute, Puerto Rico 00716-2348, USA
Yasuhiro Yamamura: AIDS Research Infrastructure Program, Ponce Health Sciences University-Ponce Research Institute, Puerto Rico 00716-2348, USA
Vanessa Rivera-Amill: AIDS Research Infrastructure Program, Ponce Health Sciences University-Ponce Research Institute, Puerto Rico 00716-2348, USA

IJERPH, 2018, vol. 15, issue 8, 1-10

Abstract: The implementation of antiretroviral treatment combined with the monitoring of drug resistance mutations improves the quality of life of HIV-1 positive patients. The drug resistance mutation patterns and viral genotypes are currently analyzed by DNA sequencing of the virus in the plasma of patients. However, the virus compartmentalizes, and different T cell subsets may harbor distinct viral subsets. In this study, we compared the patterns of HIV distribution in cell-free (blood plasma) and cell-associated viruses (peripheral blood mononuclear cells, PBMCs) derived from ART-treated patients by using Sanger sequencing- and Next-Generation sequencing-based HIV assay. CD4 + CD45RA − RO + memory T-cells were isolated from PBMCs using a BD FACSAria instrument. HIV pol (protease and reverse transcriptase) was RT-PCR or PCR amplified from the plasma and the T-cell subset, respectively. Sequences were obtained using Sanger sequencing and Next-Generation Sequencing (NGS). Sanger sequences were aligned and edited using RECall software (beta v3.03). The Stanford HIV database was used to evaluate drug resistance mutations. Illumina MiSeq platform and HyDRA Web were used to generate and analyze NGS data, respectively. Our results show a high correlation between Sanger sequencing and NGS results. However, some major and minor drug resistance mutations were only observed by NGS, albeit at different frequencies. Analysis of low-frequency drugs resistance mutations and virus distribution in the blood compartments may provide information to allow a more sustainable response to therapy and better disease management.

Keywords: HIV-1; blood compartment; plasma; PBMCs; memory CD4 + T-cells; Sanger Sequencing; Next-Generation Sequencing (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
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