Determining the architecture of antibiotic resistance evolvability
Lead Research Organisation:
University of Manchester
Department Name: School of Biological Sciences
Abstract
The growing prevalence of antibiotic resistance is a major crisis for both public health and agriculture. Bacteria can dramatically vary in their ability to evolve resistance, but our ability to predict which ones will go on to evolve high-level resistance is currently limited. Understanding what contributes to the evolutionary potential for resistance will enable us to develop new interventions for suppressing antimicrobial resistance. It is therefore important to understand the genomic mechanisms that contribute to the 'evolvability' of resistance.
We will investigate how genome diversity contributes to the ability to evolve resistance. In contrast to other work that focuses on a single species of bacteria, we will investigate how between-species genome diversity contributes to the ability to evolve resistance. We will focus on Pseudomonas bacteria, an incredibly diverse genus that includes environmental, commensal and pathogenic organisms. Pseudomonas imposes a global economic burden that exceeds £150 billion GBP annually across health and agricultural sectors. Antibiotic resistance in Pseudomonas is increasing rapidly, and understanding what allows resistance to evolve to important anti-pseudomonal antibiotics is key to maintaining the ability to manage Pseudomonas. We will therefore determine how genome-level variation contributes to the evolvability of resistance to anti-pseudomonal antibiotics, including one recently come to market specifically designed to target pseudomonad physiology (cefiderocol).
Evidence from Pseudomonas suggests that even seemingly minor differences in genome content can have extensive consequences for the potential to evolve resistance. Previous work has shown that a single 'evolvability gene' can influence whether pseudomonads can evolve high-level resistance to the antibiotic ceftazidime. However, we currently do not know the extent to which such mechanisms generally operate. Specifically, little is known about (i) how resistance evolvability varies across diverse antibiotic classes, (ii) whether different evolvability mechanisms operate for single- and multi-drug resistance, and (iii) whether disrupting such genes can maintain or restore antibiotic sensitivity.
To address these questions, we will use a multi-disciplinary approach called 'comparative experimental evolution', a powerful technique able to investigate how species-level differences in genome content affect the ability for bacteria to evolve resistance. This approach combines high-throughput experimental evolution and bacterial phenotyping with whole genome sequencing and comparative genomics. We will evolve nearly 60,000 independent populations from eight Pseudomonas species under single- and multiple-antibiotic environments. We will connect differences in genome content to differences in mutations acquired by each species that confer high-level resistance. We will then use modern genome editing techniques to see if disrupting evolvability genes can constrain resistance, or restore sensitivity in already-resistant organisms. These massively parallel experiments will reveal the genomic basis for resistance evolvability, while also revealing the connection between high-level resistance and chromosomal mutations.
This project will advance our knowledge of what potentiates resistance evolution in these economically-important bacteria. It will also provide a framework from which we can identify genetic markers for predicting the risk of resistance evolution, allowing better targeted use of antimicrobials. Finally, it will provide a framework for testing anti-evolvability approaches to preventing resistance and restoring sensitivity.
We will investigate how genome diversity contributes to the ability to evolve resistance. In contrast to other work that focuses on a single species of bacteria, we will investigate how between-species genome diversity contributes to the ability to evolve resistance. We will focus on Pseudomonas bacteria, an incredibly diverse genus that includes environmental, commensal and pathogenic organisms. Pseudomonas imposes a global economic burden that exceeds £150 billion GBP annually across health and agricultural sectors. Antibiotic resistance in Pseudomonas is increasing rapidly, and understanding what allows resistance to evolve to important anti-pseudomonal antibiotics is key to maintaining the ability to manage Pseudomonas. We will therefore determine how genome-level variation contributes to the evolvability of resistance to anti-pseudomonal antibiotics, including one recently come to market specifically designed to target pseudomonad physiology (cefiderocol).
Evidence from Pseudomonas suggests that even seemingly minor differences in genome content can have extensive consequences for the potential to evolve resistance. Previous work has shown that a single 'evolvability gene' can influence whether pseudomonads can evolve high-level resistance to the antibiotic ceftazidime. However, we currently do not know the extent to which such mechanisms generally operate. Specifically, little is known about (i) how resistance evolvability varies across diverse antibiotic classes, (ii) whether different evolvability mechanisms operate for single- and multi-drug resistance, and (iii) whether disrupting such genes can maintain or restore antibiotic sensitivity.
To address these questions, we will use a multi-disciplinary approach called 'comparative experimental evolution', a powerful technique able to investigate how species-level differences in genome content affect the ability for bacteria to evolve resistance. This approach combines high-throughput experimental evolution and bacterial phenotyping with whole genome sequencing and comparative genomics. We will evolve nearly 60,000 independent populations from eight Pseudomonas species under single- and multiple-antibiotic environments. We will connect differences in genome content to differences in mutations acquired by each species that confer high-level resistance. We will then use modern genome editing techniques to see if disrupting evolvability genes can constrain resistance, or restore sensitivity in already-resistant organisms. These massively parallel experiments will reveal the genomic basis for resistance evolvability, while also revealing the connection between high-level resistance and chromosomal mutations.
This project will advance our knowledge of what potentiates resistance evolution in these economically-important bacteria. It will also provide a framework from which we can identify genetic markers for predicting the risk of resistance evolution, allowing better targeted use of antimicrobials. Finally, it will provide a framework for testing anti-evolvability approaches to preventing resistance and restoring sensitivity.
Technical Summary
Bacteria vary in their ability to evolve resistance, but our understanding of how the diversity in genome content among bacteria affects their ability to evolve resistance to antibiotics is currently severely limited. Identifying the genomic basis for this variation in 'evolvability' will provide novel ways to target antibiotic use, minimise the evolution of antibiotic resistance, and restore sensitivity in resistant organisms. We need to know how diversity in genome content at the species level affects the ability to evolve resistance to address these challenges.
Using 'comparative experimental evolution', we will identify how genome diversity affects resistance evolvability in the diverse bacterial genus Pseudomonas. This approach combines high-throughput experimental evolution with comparative genomics to understand what potentiates the evolution of resistance. Proof-of-concept for one antibiotic has demonstrated resistance evolvability can be contingent on a single gene. We will assess whether similar mechanisms operate across anti-pseudomonal drugs with diverse resistance mechanisms. Finally, we will use CRISPR-Cas9 based genome editing to determine if resistance evolvability can be constrained by disrupting key genes.
We will: i) identify mutations enabling resistance in different species to determine whether variation in gene content can affect resistance evolvability for particular antibiotics; ii) determine whether different evolvability mechanisms operate under single- and multi-drug environments; and iii) investigate the use of genome engineering to constrain resistance evolvability in sensitive strains and restore sensitivity in resistant strains.
This transformative approach to understanding resistance evolution across a broad taxonomic scale could open up a general principle by which resistance evolution can be understood and controlled, e.g. as genetic markers of 'resistance risk' or by providing targets for precision interventions.
Using 'comparative experimental evolution', we will identify how genome diversity affects resistance evolvability in the diverse bacterial genus Pseudomonas. This approach combines high-throughput experimental evolution with comparative genomics to understand what potentiates the evolution of resistance. Proof-of-concept for one antibiotic has demonstrated resistance evolvability can be contingent on a single gene. We will assess whether similar mechanisms operate across anti-pseudomonal drugs with diverse resistance mechanisms. Finally, we will use CRISPR-Cas9 based genome editing to determine if resistance evolvability can be constrained by disrupting key genes.
We will: i) identify mutations enabling resistance in different species to determine whether variation in gene content can affect resistance evolvability for particular antibiotics; ii) determine whether different evolvability mechanisms operate under single- and multi-drug environments; and iii) investigate the use of genome engineering to constrain resistance evolvability in sensitive strains and restore sensitivity in resistant strains.
This transformative approach to understanding resistance evolution across a broad taxonomic scale could open up a general principle by which resistance evolution can be understood and controlled, e.g. as genetic markers of 'resistance risk' or by providing targets for precision interventions.
