title: Dynamics of the emergence of genetic resistance to biocides among asexual and sexual organisms.
abstract: A stochastic, agent based, evolutionary algorithm, modeling mating, reproduction, genetic variation, phenotypic expression and selection was used to study the dynamic interactions affecting a multiple-gene system. The results suggest that strong irreversible constraints affect the evolution of resistance to biocides. Resistant genes evolve differently in asexual organisms compared with sexual ones in response to various patterns of biocide applications. Asexual populations (viruses and bacteria) are less likely to develop genetic resistance in response to multiple pesticides or if pesticides are used at low doses, whereas sexual populations (insects for example) are more likely to become resistant to pesticides if susceptibility to the pesticide relates to mate selection. The adaptation of genes not related to the emergence of resistance will affect the dynamics of the evolution of resistance. Increasing the number of pesticides reduces the probability of developing resistance to any of them in asexual organisms but much less so in sexual organisms. Sequential applications of toxins, were slightly less efficient in slowing emergence of resistance compared with simultaneous application of a mix in both sexual and asexual organisms. Targeting only one sex of the pest speeds the development of resistance. The findings are consistent to most of the published analytical models but are closer to known experimental results, showing that nonlinear, agent based simulation models are more powerful in explaining complex processes.
authors.affiliation: Departamento de Biologia de Organismos, Universidad Simon Bolivar, Apartado 89000, Caracas, Venezuela, 080A.
authors.forename: K
authors.initials: K
authors.lastname: Jaffe
authors.forename: S
authors.initials: S
authors.lastname: Issa
authors.forename: E
authors.initials: E
authors.lastname: Daniels
authors.forename: D
authors.initials: D
authors.lastname: Haile
mesh_terms: D000465:Algorithms; D000818:Animals; D001419:Bacteria / Q000235:genetics*; D004351:Drug Resistance / Q000235:genetics*; D004352:Drug Resistance, Microbial / Q000235:genetics; D007313:Insecta / Q000235:genetics; D008957:Models, Genetic; D012098:Reproduction; D012100:Reproduction, Asexual; D013269:Stochastic Processes; D014780:Viruses / Q000235:genetics*