Periodic Reporting for period 1 - PROBYDE (Probing the bypassability of genetic constraints in drug-resistance enzymes)
Okres sprawozdawczy: 2021-07-01 do 2023-06-30
Antibiotic resistance is estimated to account yearly for 35,000 deaths and a cost of >€1.5 billion in the European Union alone, according to the European Commission. With the slow development of new antibiotics, much recent interest is directed towards evolutionary-based strategies to prevent resistance evolution to preserve the existing arsenal of drugs, mostly by anticipating and curtailing the selective opportunity of drug-resistant mutants. In this spirit, we evolved in the laboratory clinically relevant drug-resistance enzymes and identified the most probable evolutionary paths towards resistance. As a result, our results contribute insights into both fundamental and applied questions about the reproducibility of antibiotic resistance evolution, an aspiration with the potential to improve therapeutic practice ultimately contributing to secure human well-being and to reduce the cost of EU’s healthcare systems. Finally, I should note that the results of this proposal are not amenable to be affected by gender dimension.
In brief, we uncovered the potential adaptive pathways available via single step mutations for several drug-resistance enzymes to improve their activity. This information enabled making predictions about antibiotic resistance evolution based on single-gene (in-vitro) observations of repeatability. I also conducted experimental adaptation to antibiotics with a model of E. coli clinical strain carrying the different drug-resistance enzymes. Comparison of the potential versus realized adaptive pathways provided insight into the bypassability of genetic constraints in the drug-resistance enzymes and into the role of mutation biases and GC content in this process. If we were able to predict the most probable new mutants, we could anticipate evolution and design new antimicrobials or inhibitors to tackle the expected new variants.
In brief, we uncovered the potential adaptive pathways available via single step mutations for several drug-resistance enzymes to improve their activity. This information enabled making predictions about antibiotic resistance evolution based on single-gene (in-vitro) observations of repeatability. I also conducted experimental adaptation to antibiotics with a model of E. coli clinical strain carrying the different drug-resistance enzymes. Comparison of the potential versus realized adaptive pathways provided insight into the bypassability of genetic constraints in the drug-resistance enzymes and into the role of mutation biases and GC content in this process. If we were able to predict the most probable new mutants, we could anticipate evolution and design new antimicrobials or inhibitors to tackle the expected new variants.
I followed an in-vitro Directed Evolution protocol using two clinically-relevant carbapenemases. We recovered several mutations commonly observed in clinical settings, but also previously unknown large-effect ones. Importantly, strong epistatic constraints largely determined evolutionary outcomes in this system: we uncover at least four distinct adaptive pathways in which the identity of the first mutation markedly affected the identity of subsequent adaptive steps (see Figure 1). These independent pathways most probably representing different solutions to the activity-stability trade-off, which we are in the process of verifying through protein purification, kinetic parameters and stability assay. Furthermore, using the 6 most prevalent mutations observed in the random in-vitro evolution step, we created all their possible 64 combinations via site directed mutagenesis. Then, the resistance profile was evaluated by minimal inhibitory concentration with the aim of defining epistatic constrains. Despite all mutations being beneficial in the ancestral background, the highest value of MIC was obtained with only the combination of two mutations. Most of the combination of the mutations conferred a beneficial or neutral effect, while a few of the combination represent a deleterious effect. Taken together, our results illustrate how strong epistasis imposes a high degree of contingency in the evolutionary pathways of two important carbapenemases, and that its evolution can be predictable based on the identity of the few first-step, beneficial mutations.
During the three-month secondment, I conducted directed mutagenesis experiments on the chromosome expressed penicillin binding protein PBP3, a protein essential for cell growth and division and are therefore critical targets for β-lactam antibiotics. Several mutations in PBP3 conferring resistance to cephalosporins were described previously. Our objective was to evaluate if there were presented epistatic constrains in the mutations controlling the system. Using CRISPR/Cas9-mediated error prone genome editing methodology (CREPE), a technique that allows the high-throughput generation of mutants, I generated a library of mutants within a targeted gene in its native genomic context. Moreover, I performed reconstruction experiments demonstrating selective effects of candidate mutations separately and in combination.
During the three-month secondment, I conducted directed mutagenesis experiments on the chromosome expressed penicillin binding protein PBP3, a protein essential for cell growth and division and are therefore critical targets for β-lactam antibiotics. Several mutations in PBP3 conferring resistance to cephalosporins were described previously. Our objective was to evaluate if there were presented epistatic constrains in the mutations controlling the system. Using CRISPR/Cas9-mediated error prone genome editing methodology (CREPE), a technique that allows the high-throughput generation of mutants, I generated a library of mutants within a targeted gene in its native genomic context. Moreover, I performed reconstruction experiments demonstrating selective effects of candidate mutations separately and in combination.
The proposal was inserted within the cutting-edge wave of studies that aim at gaining empirical understanding of evolutionary reproducibility. Predicting the evolution of antibiotic resistance enzymes could not be more timely. With the slow development of new antibiotics, much recent interest is directed towards evolutionary-based strategies to prevent resistance evolution to preserve the existing arsenal of drugs, mostly by anticipating and curtailing the selective opportunity of drug-resistant mutants (e.g. drug cycling and combination therapies, stewardship programs). As the major outcome of this proposal, we deeply characterized the evolvability of a highly relevant antibiotic resistance enzyme, shedding light on the potential routes it may follow in clinical settings, where many different aspects influence the outcomes (e.g. other mutations, host species, different antibiotics). Overall, this project contributes important insights into both fundamental and applied questions about the reproducibility of antibiotic resistance evolution, aspiring to improve therapeutic practice ultimately contributing to secure human well-being and to reduce the cost of EU’s healthcare systems.