Reaction Kinetic Models of Antibiotic Heteroresistance

• Published in: International journal of molecular sciences Vol. 20; no. 16; p. 3965
• Main Authors: Martinecz, Antal, Clarelli, Fabrizio, Abel, Sören, Abel Zur Wiesch, Pia
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.08.2019; MDPI
• Subjects: Algorithms; Anti-Bacterial Agents - pharmacology; antibiotic resistance; Antibiotics; Bacteria; bacterial persistence; Basale medisinske, odontologiske og veterinærmedisinske fag: 710; Basic medical, dental and veterinary science disciplines: 710; Drug resistance; Drug Resistance, Bacterial; Efflux; Gillespie algorithm; Intracellular; Kinetics; Mathematical models; Medical disciplines: 700; Medisinske Fag: 700; Microbial Sensitivity Tests; Mutation; pharmacodynamics; Population; Reaction kinetics; stochastic simulation; VDP; reaction kinetics; antibiotic resistance; pharmacodynamics; bacterial persistence; stochastic simulation; antibiotics; Gillespie algorithm
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms20163965

Bacterial heteroresistance (i.e., the co-existence of several subpopulations with different antibiotic susceptibilities) can delay the clearance of bacteria even with long antibiotic exposure. Some proposed mechanisms have been successfully described with mathematical models of drug-target binding where the mechanism's downstream of drug-target binding are not explicitly modeled and subsumed in an empirical function, connecting target occupancy to antibiotic action. However, with current approaches it is difficult to model mechanisms that involve multi-step reactions that lead to bacterial killing. Here, we have a dual aim: first, to establish pharmacodynamic models that include multi-step reaction pathways, and second, to model heteroresistance and investigate which molecular heterogeneities can lead to delayed bacterial killing. We show that simulations based on Gillespie algorithms, which have been employed to model reaction kinetics for decades, can be useful tools to model antibiotic action via multi-step reactions. We highlight the strengths and weaknesses of current models and Gillespie simulations. Finally, we show that in our models, slight normally distributed variances in the rates of any event leading to bacterial death can (depending on parameter choices) lead to delayed bacterial killing (i.e., heteroresistance). This means that a slowly declining residual bacterial population due to heteroresistance is most likely the default scenario and should be taken into account when planning treatment length.