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Record W2937781871 · doi:10.1016/j.heliyon.2019.e01498

Role of co-expressed APOBEC3F and APOBEC3G in inducing HIV-1 drug resistance

2019· article· en· W2937781871 on OpenAlexafffund
Robin P. Love, Richard M. Gibson, Eric J. Arts, Art F. Y. Poon, Linda Chelico

Bibliographic record

VenueHeliyon · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsWestern UniversityUniversity of Saskatchewan
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsAPOBEC3GHuman immunodeficiency virus (HIV)Drug resistanceDrugHIV drug resistanceVirologyPharmacologyMedicineBiologyMicrobiologyVirusViral loadViral replicationAntiretroviral therapy

Abstract

fetched live from OpenAlex

The APOBEC3 enzymes can induce mutagenesis of HIV-1 proviral DNA through the deamination of cytosine. HIV-1 overcomes this restriction through the viral protein Vif that induces APOBEC3 proteasomal degradation. Within this dynamic host-pathogen relationship, the APOBEC3 enzymes have been found to be beneficial, neutral, or detrimental to HIV-1 biology. Here, we assessed the ability of co-expressed APOBEC3F and APOBEC3G to induce HIV-1 resistance to antiviral drugs. We found that co-expression of APOBEC3F and APOBEC3G enabled partial resistance of APOBEC3F to Vif-mediated degradation with a corresponding increase in APOBEC3F-induced deaminations in the presence of Vif, in addition to APOBEC3G-induced deaminations. We recovered HIV-1 drug resistant variants resulting from APOBEC3-induced mutagenesis, but these variants were less able to replicate than drug resistant viruses derived from RT-induced mutations alone. The data support a model in which APOBEC3 enzymes cooperate to restrict HIV-1, promoting viral inactivation over evolution to drug resistance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations19
Published2019
Admission routes2
Has abstractyes

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