The Journal of antimicrobial chemotherapy · 2026
Antibiotic resistance of Pseudomonas aeruginosa strains-intracellular metabolomics analysis.
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Mielko-Niziałek Karolina Anna, Jabłoński Sławomir, Wiśniewski Jerzy, Milczewska Justyna, Sands Dorota, Łukaszewicz Marcin, Młynarz Piotr
Аннотация
OBJECTIVES: Pseudomonas aeruginosa (Pa) stands as a dangerous multidrug-resistant human pathogen, and the associated antibiotic resistance mechanisms, governed by diverse molecular processes, present a persistent challenge in eradicating bacterial infections, especially in patients with cystic fibrosis. The search for novel antibiotic resistance markers has led researchers to explore the field of metabolomics. This study aims to discern alterations in metabolite levels resulting from varied antibiotic resistance profiles in Pa strains isolated from clinical patients.
METHODS: In-depth analysis of intracellular metabolites from Pa strains was conducted. Following bacterial cultivation and extraction, LC-MS measurements were performed, and subsequent data analysis used a combination of statistical and chemometric methodologies.
RESULTS: A total of 45 metabolites were identified under positive ionization mode. Statistically significant variations were discerned across all comparisons involving the 14 antibiotics investigated, primarily manifesting as alterations in amino acid pathways and their derivatives. The chemometric outcomes revealed a distinct clustering of samples corresponding to the specific antibiotics tested.
CONCLUSION: The presented findings show noteworthy shifts in bacterial metabolic pathways, laying the groundwork for further investigations. These initial insights promise to delineate avenues towards comprehensive explorations into antibiotic resistance in bacteria. This study provides a foundation for future investigations aimed at unravelling the intricate dynamics of antibiotic resistance in Pa.
METHODS: In-depth analysis of intracellular metabolites from Pa strains was conducted. Following bacterial cultivation and extraction, LC-MS measurements were performed, and subsequent data analysis used a combination of statistical and chemometric methodologies.
RESULTS: A total of 45 metabolites were identified under positive ionization mode. Statistically significant variations were discerned across all comparisons involving the 14 antibiotics investigated, primarily manifesting as alterations in amino acid pathways and their derivatives. The chemometric outcomes revealed a distinct clustering of samples corresponding to the specific antibiotics tested.
CONCLUSION: The presented findings show noteworthy shifts in bacterial metabolic pathways, laying the groundwork for further investigations. These initial insights promise to delineate avenues towards comprehensive explorations into antibiotic resistance in bacteria. This study provides a foundation for future investigations aimed at unravelling the intricate dynamics of antibiotic resistance in Pa.