title: Recombination increases human immunodeficiency virus fitness, but not necessarily diversity.
abstract: Recombination can facilitate the accumulation of mutations and accelerate the emergence of resistance to current antiretroviral therapies for human immunodeficiency virus (HIV) infection. Yet, since recombination can also dissociate favourable combinations of mutations, the benefit of recombination to HIV remains in question. The confounding effects of mutation, multiple infections of cells, random genetic drift and fitness selection that underlie HIV evolution render the influence of recombination difficult to unravel. We developed computer simulations that mimic the genomic diversification of HIV within an infected individual and elucidate the influence of recombination. We find, interestingly, that when the effective population size of HIV is small, recombination increases both the diversity and the mean fitness of the viral population. When the effective population size is large, recombination increases viral fitness but decreases diversity. In effect, recombination enhances (lowers) the likelihood of the existence of multi-drug resistant strains of HIV in infected individuals prior to the onset of therapy when the effective population size is small (large). Our simulations are consistent with several recent experimental observations, including the evolution of HIV diversity and divergence in vivo. The intriguing dependencies on the effective population size appear due to the subtle interplay of drift, selection and epistasis, which we discuss in the light of modern population genetics theories. Current estimates of the effective population size of HIV have large discrepancies. Our simulations present an avenue for accurate determination of the effective population size of HIV in vivo and facilitate establishment of the benefit of recombination to HIV.
authors.affiliation: Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, India.
authors.forename: N N V
authors.initials: NNV
authors.lastname: Vijay
authors.affiliation: Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, India.
authors.lastname: Vasantika
authors.affiliation: Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
authors.forename: Rahul
authors.initials: R
authors.lastname: Ajmani
authors.affiliation: Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
authors.forename: Alan S
authors.initials: AS
authors.lastname: Perelson
authors.affiliation: Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, India.
authors.forename: Narendra M
authors.initials: NM
authors.lastname: Dixit
mesh_terms: D003198:Computer Simulation; D019143:Evolution, Molecular; D014644:Genetic Variation; D006678:HIV / Q000235:genetics*; D015658:HIV Infections / Q000821:virology; D006801:Humans; D008957:Models, Genetic; D011995:Recombination, Genetic