Theoretical Considerations and Empirical Predictions of the Pharmaco- and Population Dynamics of Heteroresistance

• Type of Material: Article
• Authors: Bruce Levin, Emory University; Brandon Berryhill, Emory University; TERESA GIL GIL, Emory University; Joshua Manuel, Emory University; Andrew Smith, Emory University; Jake Choby, Emory University; Dan I. Andersson, Uppsala University; David S Weiss, Emory University; Fernando Baquero, Hospital Universitario Ramón y Cajal
• Language: English
• Date: 2023-10-24
• Publisher: NIH
• Publication Version: Preprint (Prior to Peer Review)
• Copyright Statement: The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
• Final Published Version (URL): https://doi.org/10.1101/2023.09.21.558832
• Title of Journal or Parent Work: bioRxiv
• Grant/Funding Information: BRL, DAA, and DSW thank the U.S. National Institute of General Medical Sciences for their funding support via R35GM136407, the U.S. National Institute of Allergy and Infectious Diseases for their funding support via U19AI158080-02, and the Emory University Antibiotic Resistance Center. FB acknowledges the support of CIBERESP (CB06/02/0053) from the Carlos III Institute of Health of Spain.
• Keywords: Antibiotic Resistance; Heteroresistance; Mathematical Modeling; Pharmacodynamics; Microbiology
• Research Categories: Health Sciences, Pharmacology; Health Sciences, Public Health; Biology, Microbiology

Abstract

Antibiotics are considered one of the most important contributions to clinical medicine in the last 100 years. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulations models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend the definition of heteroresistance should include a consideration of the rate of return to susceptibility.