Metabolic Analyses Revealed Time-Dependent Synergistic Killing by Colistin and Aztreonam Combination Against Multidrug-Resistant Acinetobacter baumannii

代谢分析揭示粘菌素和氨曲南联合用药对多重耐药鲍曼不动杆菌具有时间依赖性协同杀菌作用

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Abstract

Background: Polymyxins are a last-line class of antibiotics against multidrug-resistant Acinetobacter baumannii; however, polymyxin resistance can emerge with monotherapy. Therefore, synergistic combination therapy is a crucial strategy to reduce polymyxin resistance. Methods: This study conducted untargeted metabolomics to investigate metabolic responses of a multidrug-resistant (MDR) A. baumannii clinical isolate, AB090342, to colistin and aztreonam alone, and their combination at 1, 4, and 24 h. Metabolomics data were analyzed using univariate and multivariate statistics; metabolites showing ≥ 2-fold changes were subjected to bioinformatics analysis. Results: The synergistic action of colistin-aztreonam combination was initially driven by colistin via significant disruption of bacterial cell envelope, with decreased phospholipid and fatty acid levels at 1 h. Cell wall biosynthesis was inhibited at 4 and 24 h by aztreonam alone and the combination as shown by the decreased levels of two amino sugars, UDP-N-acetylglucosamine and UDP-N-acetylmuramate; these results suggested that aztreonam was primarily responsible for the synergistic killing at later time points. Moreover, aztreonam alone and the combination significantly depleted pentose phosphate pathway, amino acid, peptide and nucleotide metabolism, but elevated fatty acid and key phospholipid levels. Collectively, the combination synergy between colistin and aztreonam was mainly due to the inhibition of cell envelope biosynthesis via different metabolic perturbations. Conclusion: This metabolomics study is the first to elucidate multiple cellular pathways associated with the time-dependent synergistic action of colistin-aztreonam combination against MDR A. baumannii. Our results provide important mechanistic insights into optimizing synergistic colistin combinations in patients.

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