Evidence map›Paper›PMID 23856772›Full record

ArticleAntimicrobial agents and chemotherapy2013

Basis for early and preferential selection of the E138K mutation in HIV-1 reverse transcriptase.

Matthew McCallum, Maureen Oliveira, Ruxandra-Ilinca Ibanescu, Victor G Kramer, Daniela Moisi, Eugene L Asahchop, Bluma G Brenner, P Richard Harrigan, Hongtao Xu, Mark A Wainberg

Abstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Matthew McCallumMcGill University AIDS Centre, Lady Davis Institute of Medical Research, Jewish General Hospital, Montreal, Quebec, Canada.
Maureen Oliveira
Ruxandra-Ilinca Ibanescu
Victor G Kramer
Daniela Moisi
Eugene L Asahchop
Bluma G Brenner
P Richard Harrigan
Hongtao Xu
Mark A Wainberg

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

E138K, a G→A mutation in HIV-1 reverse transcriptase (RT), is preferentially selected by etravirine (ETR) and rilpivirine over other substitutions at position E138 that offer greater drug resistance. We hypothesized that there was a mutational bias for the E138K substitution and designed an allele-specific PCR to monitor the emergence of E138A/G/K/Q/R/V during ETR selection experiments. We also performed competition experiments using mutated viruses and quantified the prevalence of E138 minority species in drug-naive patients. E138K, as well as E138G, consistently emerged first during ETR selection experiments, followed by E138A and E138Q; E138R was never selected. Surprisingly, E138K was identified as a tiny minority in 23% of drug-naive subtype B patients, a result confirmed by ultradeep sequencing (UDS). This result could reflect a low fitness cost of E138K; however, E138K was one of the least fit substitutions at codon E138, even after taking into account the deoxynucleoside triphosphate pools of the cells used in competition experiments. Further UDS analysis revealed other minority species in a pattern consistent with the mutational bias of HIV RT. There was no evidence of APOBEC3-hypermutation in these selection experiments or in patients. Our results confirm the mutational bias of HIV-1 in patients and highlight the importance of G→A mutations in HIV-1 drug resistance evolution.

Indexed as

Anti-HIV AgentsCell LineCodonHIV Reverse TranscriptaseHumansMutationNitrilesPyridazinesPyrimidinesAnti-HIV AgentsCodonetravirineHIV Reverse TranscriptaseNitrilesPyridazinesPyrimidinesreverse transcriptase, Human immunodeficiency virus 1

Identifiers

PMID23856772
PMCPMC3811420

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.