Characterization of HIV-1 reverse transcriptase drug resistance connection subdomain mutation N348I

2011 ◽  
Author(s):  
Matthew M. Schuckmann
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Hiv 1

Genetic Diversity and Drug Resistance of HIV-1 CRF55_01B in Guangdong, China

2020 ◽  
Vol 18 (3) ◽  
pp. 210-218
Author(s):  
Guolong Yu ◽  
Yan Li ◽  
Xuhe Huang ◽  
Pingping Zhou ◽  
Jin Yan ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Phylogenetic Analyses ◽  
Resistance Mutations ◽  
Protease Inhibition ◽  
Subtype B ◽  
Primary Drug Resistance ◽  
Hiv 1 ◽  
Primary Drug

Background: HIV-1 CRF55_01B was first reported in 2013. At present, no report is available regarding this new clade’s polymorphisms in its functionally critical regions protease and reverse transcriptase. Objective: To identify the diversity difference in protease and reverse transcriptase between CRF55_01B and its parental clades CRF01_AE and subtype B; and to investigate CRF55_01B’s drug resistance mutations associated with the protease inhibition and reverse transcriptase inhibition. Methods: HIV-1 RNA was extracted from plasma derived from a MSM population. The reverse transcription and nested PCR amplification were performed following our in-house PCR procedure. Genotyping and drug resistant-associated mutations and polymorphisms were identified based on polygenetic analyses and the usage of the HIV Drug Resistance Database, respectively. Results: A total of 9.24 % of the identified CRF55_01B sequences bear the primary drug resistance. CRF55_01B contains polymorphisms I13I/V, G16E and E35D that differ from those in CRF01_AE. Among the 11 polymorphisms in the RT region, seven were statistically different from CRF01_AE’s. Another three polymorphisms, R211K (98.3%), F214L (98.3%), and V245A/E (98.3 %.), were identified in the RT region and they all were statistically different with that of the subtype B. The V179E/D mutation, responsible for 100% potential low-level drug resistance, was found in all CRF55_01B sequences. Lastly, the phylogenetic analyses demonstrated 18 distinct clusters that account for 35% of the samples. Conclusions: CRF55_01B’s pol has different genetic diversity comparing to its counterpart in CRF55_01B’s parental clades. CRF55_01B has a high primary drug resistance presence and the V179E/D mutation may confer more vulnerability to drug resistance.

scholarly journals High-resolution view of HIV-1 reverse transcriptase initiation complexes and inhibition by NNRTI drugs

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Betty Ha ◽  
Kevin P. Larsen ◽  
Jingji Zhang ◽  
Ziao Fu ◽  
Elizabeth Montabana ◽  
...  
Keyword(s):  
Reverse Transcriptase ◽  
Viral Entry ◽  
Reverse Transcription ◽  
Molecular Mechanisms ◽  
Dissociation Kinetics ◽  
Structural Mechanism ◽  
Medium Resolution ◽  
Kinetics Of ◽  
Hiv 1

AbstractReverse transcription of the HIV-1 viral RNA genome (vRNA) is an integral step in virus replication. Upon viral entry, HIV-1 reverse transcriptase (RT) initiates from a host tRNALys3 primer bound to the vRNA genome and is the target of key antivirals, such as non-nucleoside reverse transcriptase inhibitors (NNRTIs). Initiation proceeds slowly with discrete pausing events along the vRNA template. Despite prior medium-resolution structural characterization of reverse transcriptase initiation complexes (RTICs), higher-resolution structures of the RTIC are needed to understand the molecular mechanisms that underlie initiation. Here we report cryo-EM structures of the core RTIC, RTIC–nevirapine, and RTIC–efavirenz complexes at 2.8, 3.1, and 2.9 Å, respectively. In combination with biochemical studies, these data suggest a basis for rapid dissociation kinetics of RT from the vRNA–tRNALys3 initiation complex and reveal a specific structural mechanism of nucleic acid conformational stabilization during initiation. Finally, our results show that NNRTIs inhibit the RTIC and exacerbate discrete pausing during early reverse transcription.

Characterization of drug resistance mutations in naïve and ART-treated patients infected with HIV-1 in Yaounde, Cameroon

2012 ◽  
Vol 84 (5) ◽  
pp. 721-727 ◽  
Author(s):  
Laura Ceccarelli ◽  
Romina Salpini ◽  
Sylvie Moudourou ◽  
Valeria Cento ◽  
Maria M. Santoro ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Resistance Mutations ◽  
Drug Resistance Mutations ◽  
Hiv 1

scholarly journals HIV-1 Phenotypic Reverse Transcriptase Inhibitor Drug Resistance Test Interpretation Is Not Dependent on the Subtype of the Virus Backbone

PLoS ONE ◽  
2012 ◽  
Vol 7 (4) ◽  
pp. e34708 ◽  
Author(s):  
Michelle Bronze ◽  
Kim Steegen ◽  
Carole L. Wallis ◽  
Hans De Wolf ◽  
Maria A. Papathanasopoulos ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Transcriptase Inhibitor ◽  
Resistance Test ◽  
Test Interpretation ◽  
Inhibitor Drug ◽  
Reverse Transcriptase Inhibitor ◽  
Hiv 1

Diversity of HIV-1 subtypes and transmitted drug-resistance mutations among minority HIV-1 variants in a Turkish cohort

2021 ◽  
Vol 19 ◽  
Author(s):  
Rabia Can Sarinoglu ◽  
Uluhan Sili ◽  
Ufuk Hasdemir ◽  
Burak Aksu ◽  
Guner Soyletir ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Transcriptase Inhibitor ◽  
Transmitted Drug Resistance ◽  
Resistance Mutations ◽  
Drug Resistance Mutations ◽  
Subtype B ◽  
Treatment Naïve ◽  
Reverse Transcriptase Inhibitor ◽  
Hiv 1

Background: The World Health Organization (WHO) recommends the surveillance of transmitted drug resistance mutations (TDRMs) to ensure the effectiveness and sustainability of HIV treatment programs. Objective: Our aim was to determine the TDRMs and evaluate the distribution of HIV-1 subtypes using and compared next-generation sequencing (NGS) and Sanger-based sequencing (SBS) in a cohort of 44 antiretroviral treatment-naïve patients. Methods: All samples that were referred to the microbiology laboratory for HIV drug resistance analysis between December 2016 and February 2018 were included in the study. After exclusions, 44 treatment-naive adult patients with a viral load of >1000 copies/mL were analyzed. DNA sequencing for reverse transcriptase and protease regions was performed using both DeepChek ABL single round kit and Sanger-based ViroSeq HIV-1 Genotyping System. The mutations and HIV-1 subtypes were analyzed using the Stanford HIVdb version 8.6.1 Genotypic Resistance software, and TDRMs were assessed using the WHO surveillance drug-resistance mutation database. HIV-1 subtypes were confirmed by constructing a maximum-likelihood phylogenetic tree using Los Alamos IQ-Tree software. Results: NGS identified nucleos(t)ide reverse transcriptase inhibitor (NRTI)-TDRMs in 9.1% of the patients, non-nucleos(t)ide reverse transcriptase inhibitor (NNRTI)-TDRMs in 6.8% of the patients, and protease inhibitor (PI)-TDRMs in 18.2% of the patients at a detection threshold of ≥1%. Using SBS, 2.3% and 6.8% of the patients were found to have NRTI- and NNRTI-TDRMs, respectively, but no major PI mutations were detected. M41L, L74I, K65R, M184V, and M184I related to NRTI, K103N to NNRTI, and N83D, M46I, I84V, V82A, L24I, L90M, I54V to the PI sites were identified using NGS. Most mutations were found in low-abundance (frequency range: 1.0% - 4.7%) HIV-1 variants, except M41L and K103N. The subtypes of the isolates were found as follows; 61.4% subtype B, 18.2% subtype B/CRF02_AG recombinant, 13.6% subtype A, 4.5% CRF43_02G, and 2.3% CRF02_AG. All TDRMs, except K65R, were detected in HIV-1 subtype B isolates.. Conclusion: The high diversity of protease site TDRMs in the minority HIV-1 variants and prevalence of CRFs were remarkable in this study. All minority HIV-1 variants were missed by conventional sequencing. TDRM prevalence among minority variants appears to be decreasing over time at our center.

Development and evaluation of an assay for HIV-1 protease and reverse transcriptase drug resistance genotyping of all major group-M subtypes

2012 ◽  
Vol 54 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Susan C. Aitken ◽  
Aletta Kliphuis ◽  
Carole L. Wallis ◽  
Mei Ling Chu ◽  
Quirine Fillekes ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Major Group ◽  
Drug Resistance Genotyping ◽  
Hiv 1

scholarly journals Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors

2010 ◽  
Vol 4 ◽  
pp. BBI.S6247 ◽  
Author(s):  
Marcin Kierczak ◽  
Michał Dramiński ◽  
Jacek Koronacki ◽  
Jan Komorowski
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Molecular Interaction ◽  
3D Structure ◽  
Resistance Mechanisms ◽  
Interaction Networks ◽  
Resistance Level ◽  
Molecular Interaction Networks ◽  
Monte Carlo Feature Selection ◽  
Hiv 1

Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. Results We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. Availability A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm .

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