Evidence map›Paper›PMID 23028282›Full record

ArticlePLoS computational biology2012

Stochastic simulations suggest that HIV-1 survives close to its error threshold.

Kushal Tripathi, Rajesh Balagam, Nisheeth K Vishnoi, Narendra M Dixit

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

10 citing papers in PubMed, 35 citations in OpenAlex.

  1. Modelling HIV-1 control and remission.NPJ systems biology and applications · 2024
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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

4 authors at 2 institutions in 2 countries.

Kushal TripathiDepartment of Chemical Engineering, Indian Institute of Science, Bangalore, India.
Rajesh Balagam
Nisheeth K Vishnoi
Narendra M Dixit
Indian Institute of Science Bangalore · INMicrosoft (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of mutagenic drugs to drive HIV-1 past its error threshold presents a novel intervention strategy, as suggested by the quasispecies theory, that may be less susceptible to failure via viral mutation-induced emergence of drug resistance than current strategies. The error threshold of HIV-1, μ c, however, is not known. Application of the quasispecies theory to determine μ c poses significant challenges: Whereas the quasispecies theory considers the asexual reproduction of an infinitely large population of haploid individuals, HIV-1 is diploid, undergoes recombination, and is estimated to have a small effective population size in vivo. We performed population genetics-based stochastic simulations of the within-host evolution of HIV-1 and estimated the structure of the HIV-1 quasispecies and μ c. We found that with small mutation rates, the quasispecies was dominated by genomes with few mutations. Upon increasing the mutation rate, a sharp error catastrophe occurred where the quasispecies became delocalized in sequence space. Using parameter values that quantitatively captured data of viral diversification in HIV-1 patients, we estimated μ c to be 7 x 10(-5)-1 x 10(-4) substitutions/site/replication, ≈ 2-6 fold higher than the natural mutation rate of HIV-1, suggesting that HIV-1 survives close to its error threshold and may be readily susceptible to mutagenic drugs. The latter estimate was weakly dependent on the within-host effective population size of HIV-1. With large population sizes and in the absence of recombination, our simulations converged to the quasispecies theory, bridging the gap between quasispecies theory and population genetics-based approaches to describing HIV-1 evolution. Further, μ c increased with the recombination rate, rendering HIV-1 less susceptible to error catastrophe, thus elucidating an added benefit of recombination to HIV-1. Our estimate of μ c may serve as a quantitative guideline for the use of mutagenic drugs against HIV-1.

Indexed as

Genetics, PopulationModels, GeneticCell SurvivalComputer SimulationDifferential ThresholdHIV-1Models, StatisticalMutationRecombination, GeneticStochastic ProcessesVirus Replication

Identifiers

PMID23028282
PMCPMC3441496
OpenAlexW2007441249

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.