Drug-resistant Escherichia coli metabolomics via pseudo-targeted SWATH/IDA-MRM: Bridging high coverage and precision.

Introduction: Metabolic reprogramming plays a significant role in the emergence, progression, and response to antibiotic pressure in bacterial resistance. Current metabolomics approaches face significant limitations: untargeted methods lack quantitative precision, while targeted analyses suffer from limited coverage. These technical constraints hinder comprehensive evaluation of metabolic contributions to antibiotic activity and resistance evolution, creating a critical knowledge gap in understanding treatment outcomes for resistant bacteria.

Objective: To establish a metabolomics method with comprehensive coverage, excellent reproducibility, high sensitivity, and wide dynamic range for elucidating the dynamic relationships between bacterial metabolic reprogramming, antibiotic activity, and resistance phenotype development.

Methods: We employed a complementary liquid chromatography system incorporating reverse-phase liquid chromatography, hydrophilic interaction liquid chromatography, and metal-sensitive liquid chromatography. Coupled with high-resolution mass spectrometry and utilizing three complementary data acquisition modes - full scan, information-dependent acquisition (IDA), and sequential window acquisition of all theoretical mass spectra (SWATH) - we developed a novel pseudo-targeted metabolomics approach based on triple quadrupole mass spectrometry, designated as SWATH/IDA-MRM. This optimized method was subsequently applied to investigate metabolic reprogramming in Escherichia coli strains harboring the resistance genes mcr-1, bla, bla, and the dual combination mcr-1 + bla.

Results: Our analytical platform successfully identified 3,529 metabolic features using six complementary chromatographic separation conditions, achieving broader metabolite coverage than conventional targeted metabolomics. Comparative evaluation against untargeted approaches revealed marked improvements in analytical performance, including enhanced linearity, reproducibility, detection sensitivity, and dynamic range, along with superior capacity for discriminating metabolic profiles between sample groups. Application to antibiotic-resistant E. coli strains revealed substantial metabolic flux alterations in resistant versus susceptible strains, with predominant perturbations in nucleotide metabolism, amino acid metabolism, energy metabolism, lipid metabolism, and redox balance pathways.

Conclusion: The developed SWATH/IDA-MRM platform represents a significant methodological advancement for investigating the complex interplay between microbial metabolic adaptation and antimicrobial responses. This integrated analytical approach enables systematic characterization of resistance-associated metabolic reprogramming, thereby establishing a framework for developing targeted therapeutic strategies against pathogen-specific metabolic vulnerabilities.