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Genotypic and phenotypic adaptation is the consequence of ongoing natural selection in populations and is key to predicting and preventing drug resistance. Whereas classic antibiotic persistence is all-or-nothing, here we demonstrate that an antibiotic resistance gene displays linear dose-responsive selection for increased expression in proportion to rising antibiotic concentration in growing E. coli populations. Furthermore, we report the potentially wide-spread nature of this form of emergent gene expression by instantaneous phenotypic selection process under bactericidal and bacteriostatic antxibiotic treatment, as well as an amino acid synthesis pathway enzyme under a range of auxotrophic conditions. We propose an analogy to Ohm’s law in electricity (V=IR) where selection pressure acts similarly to voltage (V), gene expression to current (I), and resistance (R) to cellular machinery constraints and costs. Lastly, mathematical modelling using agent-based models of stochastic gene expression in growing populations and Bayesian model selection reveal that the emergent gene expression mechanism requires variability in gene expression within an isogenic population, and a cellular ‘memory’ from positive feedbacks between growth and expression of any fitness-conferring gene. Finally, we discuss the connection of the observed phenomenon to a previously described general fluctuation-response relationship in biology.
Genotypic and phenotypic adaptation is the consequence of ongoing natural selection in populations and is key to predicting and preventing drug resistance. Whereas classic antibiotic persistence is all-or-nothing, here we demonstrate that an antibiotic resistance gene displays linear dose-responsive selection for increased expression in proportion to rising antibiotic concentration in growing E. coli populations. Furthermore, we report the potentially wide-spread nature of this form of emergent gene expression by instantaneous phenotypic selection process under bactericidal and bacteriostatic antxibiotic treatment, as well as an amino acid synthesis pathway enzyme under a range of auxotrophic conditions. We propose an analogy to Ohm’s law in electricity (V=IR) where selection pressure acts similarly to voltage (V), gene expression to current (I), and resistance (R) to cellular machinery constraints and costs. Lastly, mathematical modelling using agent-based models of stochastic gene expression in growing populations and Bayesian model selection reveal that the emergent gene expression mechanism requires variability in gene expression within an isogenic population, and a cellular ‘memory’ from positive feedbacks between growth and expression of any fitness-conferring gene. Finally, we discuss the connection of the observed phenomenon to a previously described general fluctuation-response relationship in biology.
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