Drug Resistance Mutations for Surveillance of Transmitted HIV-1 Drug-Resistance: 2009 Update

Bennett, Diane; Camacho, Ricardo Jorge; Oțelea, Dan; Kuritzkes, Daniel R.; Fleury, Hervé; Kiuchi, Mark; Heneine, Walid; Kantor, Rami; Jordan, Michael R.; Schapiro, Jonathan; Vandamme, Anne‐Mieke; Sandstrom, Paul; Boucher, Charles A.; Vijver, David van de; Rhee, Soo-Yon; Liu, Tommy F.; Pillay, Deenan; Shafer, Robert W.

doi:10.1371/journal.pone.0004724

Cited by 865 publications

(855 citation statements)

References 22 publications

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“…The results indicate that as with the adjoining residue 97 80 , changes at residue 98 81 were not well tolerated by FIV, and further change improved viral fitness and infectivity. Interestingly, the two corresponding HIV-1 PR residues, T80 and P81 at the tip of the 80s loop in HIV-1 PR, are conserved, and no drug resistance mutations have been reported at these sites (7,24). Our results suggest that these two conserved residues at the tip of the 80s loop in HIV-1 PR (corresponding to the "90s loop" of FIV PR) may be a valuable target for new drug design.…”

Section: Discussionmentioning

confidence: 99%

“…In spite of the success of drug development and chemotherapy, however, the continuous selection and emergence of viral variants resistant to these inhibitors and the generation of cross-resistant mutants remain major challenges to drug development. More than 70 mutations in 38 residues of HIV-1 PR have been identified in association with drug resistance to PR inhibitors (7,24). Given this extreme plasticity in PR, new strategies are required for designing a new generation of drugs against these drug-resistant mutants.…”

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confidence: 99%

“…1B). The clinical drugs against HIV-1 PR are very poor inhibitors for wild-type (WT) FIV PR, and interestingly, eight of the drug resistance mutations in HIV-1 PR mentioned above, namely, V11I, K20I, V32I, I50V, I62V, A71I, N88D, and L90M, are already present in the structurally equivalent positions of FIV PR (16 11 I, 25 20 I, 37 32 I, 59 50 V, 71 62 V, 85 71 I, 105 88 D, and 107 90 M [FIV numbering is given, with equivalent HIV-1 numbering in superscript]) (7,24).…”

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confidence: 99%

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Generation of Infectious Feline Immunodeficiency Virus (FIV) Encoding FIV/Human Immunodeficiency Virus Chimeric Protease

Lin¹,

Torbett

Elder³

2010

J Virol

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Feline immunodeficiency virus (FIV) and human immunodeficiency virus type 1 (HIV-1) proteases (PRs)share only 23% amino acid identity and exhibit distinct specificities yet have very similar 3-dimensional structures. Chimeric PRs in which HIV residues were substituted in structurally equivalent positions in FIV PR were prepared in order to study the molecular basis of PR specificity. Previous in vitro analyses showed that such substitutions dramatically altered the inhibitor specificity of mutant PRs but changed the rate and specificity of Gag cleavage so that chimeric FIVs were not infectious. Chimeric PRs encoding combinations of the I37V, N55M, M56I, V59I, L97T, I98P, Q99V, and P100N mutations were cloned into FIV Gag-Pol, and those constructs that best approximated the temporal cleavage pattern generated by wild-type FIV PR, while maintaining HIV-like inhibitor specificity, were selected. Two mutations, M56I and L97T, were intolerant to change and caused inefficient cleavage at NC-p2. However, a mutant PR with six substitutions (I37V, N55M, V59I, I98P, Q99V, and P100N) was selected and placed in the context of full-length FIV-34TF10. This virus, termed YCL6, had low-level infectivity ex vivo, and after passage, progeny that exhibited a higher growth rate emerged. The residue at the position of one of the six mutations, I98P, further mutated on passage to either P98H or P98S. Both PRs were sensitive to the HIV-1 PR inhibitors lopinavir (LPV) and darunavir (DRV), as well as to the broad-based inhibitor TL-3, with 50% inhibitory concentrations (IC 50 ) of 30 to 40 nM, consistent with ex vivo results obtained using mutant FIVs. The chimeras offer an infectivity system with which to screen compounds for potential as broad-based PR inhibitors, define structural parameters that dictate specificity, and investigate pathways for drug resistance development.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Generation of Infectious Feline Immunodeficiency Virus (FIV) Encoding FIV/Human Immunodeficiency Virus Chimeric Protease

Lin¹,

Torbett

Elder³

2010

J Virol

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“…We first aligned all sequences to the reference sequence for the pol gene of HIV subtype-B. We then masked known drug resistant sites, as specified in the Stanford database of HIV drug resistance (Bennett et al 2009). We used the program HyPhy (Pond et al 2005) to identify the type of each sequence and then excluded recombinant sequences and nonsubtype-B sequences.…”

Section: Data Analysis Methods: the Sequence Datamentioning

confidence: 99%

Infectious Disease Dynamics Inferred from Genetic Data via Sequential Monte Carlo

Smith

Ionides

King

2016

Preprint

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Genetic sequences from pathogens can provide information about infectious disease dynamics that may supplement or replace information from other epidemiological observations. Most currently available methods first estimate phylogenetic trees from sequence data, then estimate a transmission model conditional on these phylogenies. Outside limited classes of models, existing methods are unable to enforce logical consistency between the model of transmission and that underlying the phylogenetic reconstruction. Such conflicts in assumptions can lead to bias in the resulting inferences. Here, we develop a general, statistically efficient, plug-and-play method to jointly estimate both disease transmission and phylogeny using genetic data and, if desired, other epidemiological observations. This method explicitly connects the model of transmission and the model of phylogeny so as to avoid the aforementioned inconsistency. We demonstrate the feasibility of our approach through simulation and apply it to estimate stage-specific infectiousness in a subepidemic of human immunodeficiency virus in Detroit, Michigan. In a supplement, we prove that our approach is a valid sequential Monte Carlo algorithm. While we focus on how these methods may be applied to population-level models of infectious disease, their scope is more general. These methods may be applied in other biological systems where one seeks to infer population dynamics from genetic sequences, and they may also find application for evolutionary models with phenotypic rather than genotypic data.

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“…Highly Active Antiretroviral Therapy (HAART) has radically changed the clinical outcome of has been accompanied with development of drug resistance that has resulted in limited treatment success. A survey performed in Kampala showed a prevalence of transmitted drug resistance at 8.6% [5].…”

Section: Introductionmentioning

confidence: 99%

Drug Resistance Testing in HIV Infected Individuals on Treatment and Naive: Implications on Treatment Outcome

Cheriro¹,

Kikuvi²,

Mining³

et al. 2015

J HIV Clin Sci Res

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Background: The Government of Kenya started offering ART in the public sector since 2003. Despite the dramatic reduction in AIDS related morbidity and mortality, the emergence and spread of drug resistance (DR) threatens to negatively impact on treatment regimens and compromise efforts to control the epidemic. Therefore, there is a need for information on the situation of DR Mutations (DRMS) and their implications on treatment. Objectives:To evaluate DRMS and their implications on treatment in HIV infected individuals attending Moi Teaching and Referral Hospital (MTRH) clinics. Method:In 2009, we consecutively collected plasma samples from two groups of HIV infected individuals, antiretroviral (ARV) naive and ARV experienced for more than 12 months and failing therapy according to world health organisation (WHO) guidelines. We performed genotypic DR using well established in-house Sanger sequencing methods. We then followed up the patients and compared the DRMS in relation to their drug regimens at the time of sample collection and16 months later. Results:We successfully extracted and sequenced 75 samples. Median age was 36.7 years. Out of 41 drug naive individuals only 3 had DRMS. Out of the 34 ARV experienced, 29 had DRMS to nucleoside reverse transcriptase inhibitor (NRTI), and 31 to non NRTI (NNRTI). After 16 months from sample collection date, 20/31(64%) ARV experienced patients with DRMS had not been changed therapy and only 5/20(25%) were susceptible to primary ARV while 12/14 changed were susceptible to new ARV. Conclusion:The information obtained in our study can serve as an indicator of ARV program efficiency in patients still on treatment, those who are to start treatment and those who are to be changed therapy due to failure. DR testing would be necessary before initiating and /or changing ART in order to achieve optimal clinical outcome.HIV, leading to decreased mortality and morbidity. Development of HIV drug resistance is inevitable in patients on ART. Increase in antiretroviral therapy (ART) in resource-limited settings (RLS) will successfully reduce HIV-related morbidity and mortality [1]. The increase in ART coverage is expected to lead to an increase in drug-resistant strains among experienced patients. Improved access to alternative combinations of antiretroviral drugs in sub-Saharan Africa is warranted [2].As the rollout of ART in Kenya is on the rise, there is a need to monitor the patients on ART [3]. The use of Cluster of Differentiation (CD4) and viral load measurements is important in monitoring HIV patients both immunologically and virologically. Though virological and immunological monitoring is important, there is a need to provide HIVDR testing services for patients who are starting therapy and those who are suspected to be failing treatment before they are switched to a different regimen [4]. A public-health approach based on standardized, affordable drug regimens and limited laboratory monitoring is crucial in scale up efforts. The ever-expanding rollout of antiretroviral ...

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Drug Resistance Mutations for Surveillance of Transmitted HIV-1 Drug-Resistance: 2009 Update

Cited by 865 publications

References 22 publications

Generation of Infectious Feline Immunodeficiency Virus (FIV) Encoding FIV/Human Immunodeficiency Virus Chimeric Protease

Generation of Infectious Feline Immunodeficiency Virus (FIV) Encoding FIV/Human Immunodeficiency Virus Chimeric Protease

Infectious Disease Dynamics Inferred from Genetic Data via Sequential Monte Carlo

Drug Resistance Testing in HIV Infected Individuals on Treatment and Naive: Implications on Treatment Outcome

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