HIV-1 drug resistance mutations detection and HIV-1 subtype G report by using next-generation sequencing platform

2020 ◽  
Vol 146 ◽  
pp. 104221
Author(s):  
Mohammad Gholami ◽  
NeginHosseini Rouzbahani ◽  
SiamakMirab Samiee ◽  
Katayoun Tayeri ◽  
Khodayar Ghorban ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Resistance Mutations ◽  
Sequencing Platform ◽  
Drug Resistance Mutations ◽  
Next Generation Sequencing Platform ◽  
Generation Sequencing ◽  
Hiv 1

scholarly journals Correction: First evaluation of the Next-Generation Sequencing platform for the detection of HIV-1 drug resistance mutations in Belgium

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0211587
Author(s):  
Géraldine Dessilly ◽  
Léonie Goeminne ◽  
Anne-thérèse Vandenbroucke ◽  
François E. Dufrasne ◽  
Anandi Martin ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Resistance Mutations ◽  
Sequencing Platform ◽  
Drug Resistance Mutations ◽  
Next Generation Sequencing Platform ◽  
Generation Sequencing ◽  
Hiv 1

scholarly journals First evaluation of the Next-Generation Sequencing platform for the detection of HIV-1 drug resistance mutations in Belgium

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0209561 ◽  
Author(s):  
Géraldine Dessilly ◽  
Léonie Goeminne ◽  
Anne-thérèse Vandenbroucke ◽  
Francois E. Dufrasne ◽  
Anandi Martin ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Next Generation ◽  
Resistance Mutations ◽  
Sequencing Platform ◽  
Drug Resistance Mutations ◽  
Next Generation Sequencing Platform ◽  
Generation Sequencing ◽  
Hiv 1

scholarly journals HIV-DRLink: A tool for detecting linked HIV-1 drug resistance mutations in next generation sequencing data

2019 ◽  
Author(s):  
Wei Shao ◽  
Valerie F. Boltz ◽  
Junko Hattori ◽  
Michael J. Bale ◽  
Frank Maldarelli ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Genome Sequencing ◽  
Research Tool ◽  
Next Generation ◽  
Resistance Mutations ◽  
Drug Resistance Mutations ◽  
Single Genome ◽  
Generation Sequencing ◽  
Hiv 1

AbstractThe prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy (cART). Using Ultrasensitive Single-Genome Sequencing (uSGS), a next-generation method that avoids PCR bias and PCR recombination, a recent report showed that pre-existing dual-class drug resistance mutations linked on the same viral genomes were predictive of treatment failure while unlinked mutations were not. Because of the large numbers of sequences generated by uSGS and other next-generation sequencing methods, it is difficult to assess each sequence individually for linked resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large datasets but they provide no information on their linkage. Here, we report the HIV-DRLink program, a research tool that provides mutation frequencies in the total dataset as well as their linkage to other mutations conferring resistance to the same or different drug classes. The HIV-DRLink program should only be used on datasets generated by methods that eliminate artifacts due to PCR recombination, for example, standard Single-Genome Sequencing (SGS) or Ultrasensitive Single-Genome Sequencing (uSGS). HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

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

2018 ◽  
Vol 15 (8) ◽  
pp. 1697 ◽  
Author(s):  
Andrea Arias ◽  
Pablo López ◽  
Raphael Sánchez ◽  
Yasuhiro Yamamura ◽  
Vanessa Rivera-Amill
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
T Cell ◽  
Sanger Sequencing ◽  
Response To Therapy ◽  
Next Generation ◽  
Resistance Mutations ◽  
Drug Resistance Mutations ◽  
Generation Sequencing ◽  
Hiv 1

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.

scholarly journals HIV Drug Resistance Mutations Detection by Next-Generation Sequencing during Antiretroviral Therapy Interruption in China

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 264
Author(s):  
Miaomiao Li ◽  
Shujia Liang ◽  
Chao Zhou ◽  
Min Chen ◽  
Shu Liang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Antiretroviral Therapy ◽  
Detection Threshold ◽  
Next Generation ◽  
Resistance Mutations ◽  
Hiv Drug Resistance ◽  
Drug Resistance Mutations ◽  
Therapy Interruption ◽  
Generation Sequencing

Patients with antiretroviral therapy interruption have a high risk of virological failure when re-initiating antiretroviral therapy (ART), especially those with HIV drug resistance. Next-generation sequencing may provide close scrutiny on their minority drug resistance variant. A cross-sectional study was conducted in patients with ART interruption in five regions in China in 2016. Through Sanger and next-generation sequencing in parallel, HIV drug resistance was genotyped on their plasma samples. Rates of HIV drug resistance were compared by the McNemar tests. In total, 174 patients were included in this study, with a median 12 (interquartile range (IQR), 6–24) months of ART interruption. Most (86.2%) of them had received efavirenz (EFV)/nevirapine (NVP)-based first-line therapy for a median 16 (IQR, 7–26) months before ART interruption. Sixty-one (35.1%) patients had CRF07_BC HIV-1 strains, 58 (33.3%) CRF08_BC and 35 (20.1%) CRF01_AE. Thirty-four (19.5%) of the 174 patients were detected to harbor HIV drug-resistant variants on Sanger sequencing. Thirty-six (20.7%), 37 (21.3%), 42 (24.1%), 79 (45.4%) and 139 (79.9) patients were identified to have HIV drug resistance by next-generation sequencing at 20% (v.s. Sanger, p = 0.317), 10% (v.s. Sanger, p = 0.180), 5% (v.s. Sanger, p = 0.011), 2% (v.s. Sanger, p < 0.001) and 1% (v.s. Sanger, p < 0.001) of detection thresholds, respectively. K65R was the most common minority mutation, of 95.1% (58/61) and 93.1% (54/58) in CRF07_BC and CRF08_BC, respectively, when compared with 5.7% (2/35) in CRF01_AE (p < 0.001). In 49 patients that followed-up a median 10 months later, HIV drug resistance mutations at >20% frequency such as K103N, M184VI and P225H still existed, but with decreased frequencies. The prevalence of HIV drug resistance in ART interruption was higher than 15% in the survey. Next-generation sequencing was able to detect more minority drug resistance variants than Sanger. There was a sharp increase in minority drug resistance variants when the detection threshold was below 5%.

scholarly journals Coupling chemical mutagenesis to next generation sequencing for the identification of drug resistance mutations in Leishmania

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Arijit Bhattacharya ◽  
Philippe Leprohon ◽  
Sophia Bigot ◽  
Prasad Kottayil Padmanabhan ◽  
Angana Mukherjee ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Next Generation Sequencing ◽  
Chemical Mutagenesis ◽  
Next Generation ◽  
Resistance Mutations ◽  
Drug Resistance Mutations ◽  
Paromomycin Resistance ◽  
Allelic Replacement ◽  
Genome Wide ◽  
Generation Sequencing

AbstractCurrent genome-wide screens allow system-wide study of drug resistance but detecting small nucleotide variants (SNVs) is challenging. Here, we use chemical mutagenesis, drug selection and next generation sequencing to characterize miltefosine and paromomycin resistant clones of the parasite Leishmania. We highlight several genes involved in drug resistance by sequencing the genomes of 41 resistant clones and by concentrating on recurrent SNVs. We associate genes linked to lipid metabolism or to ribosome/translation functions with miltefosine or paromomycin resistance, respectively. We prove by allelic replacement and CRISPR-Cas9 gene-editing that the essential protein kinase CDPK1 is crucial for paromomycin resistance. We have linked CDPK1 in translation by functional interactome analysis, and provide evidence that CDPK1 contributes to antimonial resistance in the parasite. This screen is powerful in exploring networks of drug resistance in an organism with diploid to mosaic aneuploid genome, hence widening the scope of its applicability.

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