The Evolution of Resistance to Synergistic Multi-drug Combinations is More Complex Than Evolving Resistance to Each Individual Drug Component

Overview

Journal Evol Appl

Specialty Biology

Date 2023 Dec 25

PMID 38143903

Authors

Natalie Ann Lozano-Huntelman

Austin Bullivant

Jonathan Chacon-Barahona

Alondra Valencia

Nick Ida

April Zhou

Pooneh Kalhori

Gladys Bello

Carolyn Xue

Sada Boyd

Colin Kremer

Pamela J Yeh

Affiliations

Soon will be listed here.

Abstract

Multidrug antibiotic resistance is an urgent public health concern. Multiple strategies have been suggested to alleviate this problem, including the use of antibiotic combinations and cyclic therapies. We examine how adaptation to (1) combinations of drugs affects resistance to individual drugs, and to (2) individual drugs alters responses to drug combinations. To evaluate this, we evolved multiple strains of drug resistant in the lab. We show that evolving resistance to four highly synergistic combinations does not result in cross-resistance to all of their components. Likewise, prior resistance to one antibiotic in a combination does not guarantee survival when exposed to the combination. We also identify four 3-step and four 2-step treatments that inhibit bacterial growth and confer collateral sensitivity with each step, impeding the development of multidrug resistance. This study highlights the importance of considering higher-order drug combinations in sequential therapies and how antibiotic interactions can influence the evolutionary trajectory of bacterial populations.

Citing Articles

Laboratory Evolution of Antimicrobial Resistance in Bacteria to Develop Rational Treatment Strategies.

Maeda T, Furusawa C Antibiotics (Basel). 2024; 13(1).

PMID: 38247653 PMC: 10812413. DOI: 10.3390/antibiotics13010094.

The evolution of resistance to synergistic multi-drug combinations is more complex than evolving resistance to each individual drug component.

Lozano-Huntelman N, Bullivant A, Chacon-Barahona J, Valencia A, Ida N, Zhou A Evol Appl. 2023; 16(12):1901-1920.

PMID: 38143903 PMC: 10739078. DOI: 10.1111/eva.13608.

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