Rational Design of Antibiotic Treatment Plans: A Treatment Strategy for Managing Evolution and Reversing Resistance

Abstract

The development of reliable methods for restoring susceptibility after antibiotic resistance arises has proven elusive. A greater understanding of the relationship between antibiotic administration and the evolution of resistance is key to overcoming this challenge. Here we present a data-driven mathematical approach for developing antibiotic treatment plans that can reverse the evolution of antibiotic resistance determinants. We have generated adaptive landscapes for 16 genotypes of the TEM β-lactamase that vary from the wild type genotype “TEM-1” through all combinations of four amino acid substitutions. We determined the growth rate of each genotype when treated with each of 15 β-lactam antibiotics. By using growth rates as a measure of fitness, we computed the probability of each amino acid substitution in each β-lactam treatment using two different models named the Correlated Probability Model (CPM) and the Equal Probability Model (EPM). We then performed an exhaustive search through the 15 treatments for substitution paths leading from each of the 16 genotypes back to the wild type TEM-1. We identified optimized treatment paths that returned the highest probabilities of selecting for reversions of amino acid substitutions and returning TEM to the wild type state. For the CPM model, the optimized probabilities ranged between 0.6 and 1.0. For the EPM model, the optimized probabilities ranged between 0.38 and 1.0. For cyclical CPM treatment plans in which the starting and ending genotype was the wild type, the probabilities were between 0.62 and 0.7. Overall this study shows that there is promise for reversing the evolution of resistance through antibiotic treatment plans.

Environment changes epistasis to alter trade‐offs along alternative evolutionary paths

“…Exploiting environment dependent epistasis has been identified as a general strategy to combat the persistence of antibiotic resistance (Mira et al 2015;Nichol et al 2015). Local interactions, that is, those that depend on specific mutation combinations, can be important in determining whether environmental specialists or generalists evolve, or whether genotypes show cross-resistance to different chemotherapeutic drugs .…”

“…Similar differences also underlie a local fitness peak that allows evolution of populations toward a resistant genotype in the presence of a drug but prevents reversion to the wild-type genotype, the global fitness peak in a drug-free environment, once the drug is removed . Exploiting environment dependent epistasis has been identified as a general strategy to combat the persistence of antibiotic resistance (Mira et al 2015;Nichol et al 2015).…”

Functionally redundant forms of extended-spectrum beta-lactamases and aminoglycoside-modifying enzymes drive the evolution of two distinct multidrug resistance gene clusters in clinical populations of EXPEC

“…The discovery of specific complementarity groups and the functional redundancy they represent has significant implications for monitoring and controlling the spread of drug resistance. For example, functional redundancy greatly complicates the rational design of antibiotic therapeutic regimens aimed at maintaining the population sensitive (Mira et al 2015).…”

Antibiotic resistance and virulence: Understanding the link and its consequences for prophylaxis and therapy

“…As in Goulart et al, they focused on beta‐lactam resistance caused by TEM beta‐lactamases. From 16 TEM genotypes, they determined the antibiotic combinations leading to the reversal or stabilization of the infections caused by resistant organisms . Other studies also reported that mixing antibiotics could be effective for preventing the selection for MDR bacterial infections.…”