title: Stochastic simulations suggest that HIV-1 survives close to its error threshold.
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.
authors.affiliation: Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.
authors.forename: Kushal
authors.initials: K
authors.lastname: Tripathi
authors.forename: Rajesh
authors.initials: R
authors.lastname: Balagam
authors.forename: Nisheeth K
authors.initials: NK
authors.lastname: Vishnoi
authors.forename: Narendra M
authors.initials: NM
authors.lastname: Dixit
mesh_terms: D002470:Cell Survival; D003198:Computer Simulation; D004056:Differential Threshold; D005828:Genetics, Population; D015497:HIV-1 / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation / Q000235:genetics*; D011995:Recombination, Genetic / Q000235:genetics*; D013269:Stochastic Processes; D014779:Virus Replication / Q000235:genetics*