MétaCan
Menu
Back to cohort
Record W2046122324 · doi:10.1128/jvi.00947-14

Effect of HIV-1 Integrase Resistance Mutations When Introduced into SIVmac239 on Susceptibility to Integrase Strand Transfer Inhibitors

2014· article· en· W2046122324 on OpenAlexafffund
Said Hassounah, Thibault Mésplède, Peter K. Quashie, Maureen Oliveira, Paul Sandstrom, Mark A. Wainberg

Bibliographic record

VenueJournal of Virology · 2014
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsPublic Health Agency of CanadaMcGill UniversityJewish General Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsIntegraseBiologyIntegrase inhibitorVirologyGeneticsHuman immunodeficiency virus (HIV)MutationLentivirusAntiretroviral therapyViral loadGeneViral disease

Abstract

fetched live from OpenAlex

UNLABELLED: Studies on the in vitro susceptibility of SIV to integrase strand transfer inhibitors (INSTIs) have been rare. In order to determine the susceptibility of SIVmac239 to INSTIs and characterize the genetic pathways that might lead to drug resistance, we inserted various integrase (IN) mutations that had been selected with HIV under drug pressure with raltegravir (RAL), elvitegravir (EVG), and dolutegravir (DTG) into the IN gene of SIV. We evaluated the effects of these mutations on SIV susceptibility to INSTIs and on viral infectivity. Sequence alignments of SIVmac239 IN with various HIV-1 isolates showed a high degree of homology and conservation of each of the catalytic triad and the key residues involved in drug resistance. Each of the G118R, Y143R, Q148R, R263K, and G140S/Q148R mutations, when introduced into SIV, impaired infectiousness and replication fitness compared to wild-type virus. Using TZM-bl cells, we demonstrated that the Q148R and N155H mutational pathways conferred resistance to EVG (36- and 62-fold, respectively), whereas R263K also displayed moderate resistance to EVG (12-fold). In contrast, Y143R, Q148R, and N155H all yielded low levels of resistance to RAL. The combination of G140S/Q148R conferred high-level resistance to both RAL and EVG (>300- and 286-fold, respectively). DTG remained fully effective against all site-directed mutants except G118R and R263K. Thus, HIV INSTI mutations, when inserted into SIV, resulted in a similar phenotype. These findings suggest that SIV and HIV may share similar resistance pathways profiles and that SIVmac239 could be a useful nonhuman primate model for studies of HIV resistance to INSTIs. IMPORTANCE: The goal of our project was to establish whether drug resistance against integrase inhibitors in SIV are likely to be the same as those responsible for drug resistance in HIV. Our data answer this question in the affirmative and show that SIV can probably serve as a good animal model for studies of INSTIs and as an early indicator for possible emergent mutations that may cause treatment failure. An SIV-primate model remains an invaluable tool for investigating questions related to the potential role of INSTIs in HIV therapy, transmission, and pathogenesis, and the present study will facilitate each of the above.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.269
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of VirologySame topicHIV/AIDS drug development and treatmentFrench-language works237,207