Distinct chromosomal mutation associated with cefiderocol resistance in Acinetobacter baumannii: a combined bioinformatics and mass spectrometry approach to unveil and validate the in vivo-acquired chemoresistance

<i>Acinetobacter baumannii</i> is a significant public health concern due to the emergence of antibiotic-resistant strains. Cefiderocol (FDC), a novel siderophore cephalosporin, has shown promise as a last-line treatment for multidrug-resistant Gram-negative bacteria. However, the emergence of <i>in vivo</i>-acquired FDC-resistant <i>A. baumannii</i> strains highlights the need for advanced tools to identify resistance-associated genomic mutations and address the challenges of FDC susceptibility testing. This study aims to characterize a novel mutation responsible for FDC resistance in <i>A. baumannii</i> and to develop a workflow that integrates genomic and functional analyses for improved antimicrobial resistance monitoring. We examined two carbapenem-resistant <i>A. baumannii</i> isolates from bacteremia cases in two patients (<i>A. baumannii</i>_5406 from patient A and <i>A. baumannii</i>_5577 from patient B). Initial whole-genome sequence BLAST typing identified both as the same strain. However, a minimum inhibitory concentration (MIC) analysis showed that <i>A. baumannii</i>_5406 was resistant to FDC, while _5577 was not. Further variant calling analysis revealed a novel chromosomal mutation in a gene encoding a TonB-dependent receptor homolog, which is involved in ferric-siderophore and heme uptake. This mutation causes a premature stop codon, likely impairing the receptor's function. Mass spectrometry confirmed that the FDC-resistant strain exhibited reduced antibiotic uptake and intracellular accumulation. This study demonstrates the utility of combining genomic and functional analyses to detect emerging mutations associated with antibiotic resistance. The variant calling approach, together with LC-MS/MS technology, offers a valuable complement to traditional susceptibility testing in clinical settings, potentially improving the identification and monitoring of FDC resistance in <i>A. baumannii</i>. Additionally, this workflow could aid in the epidemiological tracking of resistant strains.