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Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold

Overview of attention for article published in PLoS Computational Biology, September 2012
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Title
Stochastic Simulations Suggest that HIV-1 Survives Close to Its Error Threshold
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002684
Pubmed ID
Authors

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

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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Geographical breakdown

Country Count As %
United Kingdom 1 2%
India 1 2%
Portugal 1 2%
Canada 1 2%
Unknown 43 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Ph. D. Student 8 17%
Professor 5 11%
Student > Bachelor 4 9%
Professor > Associate Professor 4 9%
Other 9 19%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 21%
Biochemistry, Genetics and Molecular Biology 8 17%
Physics and Astronomy 5 11%
Chemical Engineering 4 9%
Mathematics 4 9%
Other 10 21%
Unknown 6 13%