ArticlePLoS computational biology2012
Stochastic simulations suggest that HIV-1 survives close to its error threshold.
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.
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Who cites it
10 citing papers in PubMed, 35 citations in OpenAlex.
- Modelling HIV-1 control and remission.NPJ systems biology and applications · 2024Review
- An Evolutionary Paradigm Favoring Cross Talk between Bacterial Two-Component Signaling Systems.mSystems · 2022Article
- Increased B Cell Selection Stringency In Germinal Centers Can Explain Improved COVID-19 Vaccine Efficacies With Low Dose Prime or Delayed Boost.Frontiers in immunology · 2021Article
- Pre-existing resistance in the latent reservoir can compromise VRC01 therapy during chronic HIV-1 infection.PLoS computational biology · 2020Article
- Becoming a Selfish Clan: Recombination Associated to Reverse-Transcription in LTR Retrotransposons.Genome biology and evolution · 2019Review
- Mutational pathway maps and founder effects define the within-host spectrum of hepatitis C virus mutants resistant to drugs.PLoS pathogens · 2019Article
- An analog of camptothecin inactive against Topoisomerase I is broadly neutralizing of HIV-1 through inhibition of Vif-dependent APOBEC3G degradation.Antiviral research · 2016Article
- Recombination Enhances HIV-1 Envelope Diversity by Facilitating the Survival of Latent Genomic Fragments in the Plasma Virus Population.PLoS computational biology · 2015Article
- Statistical Mechanics and Thermodynamics of Viral Evolution.PloS one · 2015Article
- Tautomerism provides a molecular explanation for the mutagenic properties of the anti-HIV nucleoside 5-aza-5,6-dihydro-2'-deoxycytidine.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
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.
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