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Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments
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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122037/ https://www.ncbi.nlm.nih.gov/pubmed/30096879 http://dx.doi.org/10.3390/ijerph15081697 |
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author | Arias, Andrea López, Pablo Sánchez, Raphael Yamamura, Yasuhiro Rivera-Amill, Vanessa |
author_facet | Arias, Andrea López, Pablo Sánchez, Raphael Yamamura, Yasuhiro Rivera-Amill, Vanessa |
author_sort | Arias, Andrea |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6122037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61220372018-09-07 Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments Arias, Andrea López, Pablo Sánchez, Raphael Yamamura, Yasuhiro Rivera-Amill, Vanessa Int J Environ Res Public Health Brief Report 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. MDPI 2018-08-09 2018-08 /pmc/articles/PMC6122037/ /pubmed/30096879 http://dx.doi.org/10.3390/ijerph15081697 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Brief Report Arias, Andrea López, Pablo Sánchez, Raphael Yamamura, Yasuhiro Rivera-Amill, Vanessa Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title | Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title_full | Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title_fullStr | Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title_full_unstemmed | Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title_short | Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments |
title_sort | sanger and next generation sequencing approaches to evaluate hiv-1 virus in blood compartments |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122037/ https://www.ncbi.nlm.nih.gov/pubmed/30096879 http://dx.doi.org/10.3390/ijerph15081697 |
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