The early metabolic stages in the evolution of antimicrobial resistance

Project Information

MetEvoAMR

Grant agreement ID: 101069111

DOI

10.3030/101069111

Project closed

EC signature date 9 June 2022

Start date 1 March 2023

End date 30 June 2026

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 179 373,76

Coordinated by

CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Germany

Periodic Reporting for period 1 - MetEvoAMR (The early metabolic stages in the evolution of antimicrobial resistance)

Reporting period: 2023-03-01 to 2026-06-30

Summary of the context and overall objectives of the project

Antimicrobial resistance is one of the most urgent global health challenges, threatening the effectiveness of current treatments and increasing the risk of untreatable infections. This project addresses an important gap in our understanding of how pathogenic bacteria survive the first, critical phase of antibiotic exposure before true genetic resistance appears. It focuses on Pseudomonas aeruginosa and Acinetobacter baumannii, two priority pathogens that cause hard-to-treat infections and are increasingly difficult to eliminate with existing drugs.

The overall objective is to identify the metabolic and stress-response mechanisms that allow small subpopulations of bacterial cells to tolerate antimicrobial treatment and persist long enough to acquire resistance. By studying bacteria in infection-like conditions and combining high-throughput phenotyping with proteomics, metabolomics, and evolutionary genetics, the project will reveal how the local metabolic environment shapes treatment survival. In the long term, this knowledge could support better treatment strategies, help slow the emergence of resistance, and contribute to the development of new combination therapies and screening tools aligned with EU priorities on antimicrobial resistance.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the reporting period, the project established and optimized the experimental and analytical framework for investigating antimicrobial tolerance in Pseudomonas aeruginosa and Acinetobacter baumannii under infection-mimicking conditions. Parallelized phenotyping workflows were implemented to assess bacterial growth and survival across clinically relevant antimicrobial classes and media resembling host-associated environments. In parallel, the conditions required to capture early stress responses were developed, including the separation of tolerant subpopulations and the preparation of samples for downstream omics analyses.

A major achievement was the generation of high-dimensional datasets linking antimicrobial exposure, growth behaviour, and metabolic state. These data revealed treatment- and environment-dependent differences in bacterial stress responses, including signatures consistent with metabolic adaptation during early survival. In addition, the technical basis for proteomic and metabolomic profiling of tolerant cells was established, enabling comparison of response networks across antimicrobial compounds, growth conditions, and species.
Collectively, these activities provided the experimental foundation for linking metabolic reprogramming to antimicrobial tolerance and for identifying mechanisms that may precede the emergence of stable resistance.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The project advanced understanding of antimicrobial tolerance beyond the current state of the art by shifting the focus from permanent resistance mutations to the early survival strategies that allow bacterial subpopulations to withstand treatment. By combining infection-mimicking growth conditions with high-throughput phenotyping and omics-based analyses, the work generated a more physiologically relevant view of how Pseudomonas aeruginosa and Acinetobacter baumannii respond to antimicrobial stress. This approach revealed that the metabolic environment and early stress-response programmes can strongly influence survival, highlighting mechanisms that are not captured by conventional susceptibility testing. The project also identified environmental and metabolic conditions that lead to highly altered antimicrobial treatment regimes in order to inhibit pathogen growth. These findings are very translatable to the clinic by informing clinicians about the changes in resistance testing when considering the growth environment.

The project also delivered new experimental and analytical workflows for studying tolerance at scale. These included parallelized assays for growth and survival, strategies for isolating tolerant subpopulations, and pipelines for proteomic and metabolomic profiling under clinically relevant conditions. Together, these results provide a stronger basis for linking phenotype, metabolism, and genetic adaptation in priority pathogens.

The main potential impact is improved understanding of how antimicrobial tolerance arises before stable resistance becomes established. This knowledge can support the development of better treatment strategies, including combination therapies or interventions that target metabolic buffering mechanisms. Further uptake and success will depend on continued validation of candidate pathways, extension of the workflows to additional pathogens and antimicrobial classes, and effective translation of the findings into broadly usable screening and therapeutic concepts. If relevant for later exploitation, additional support may also be needed for data integration, intellectual property assessment, and future collaboration with translational or industrial partners.