Metabolic response of Klebsiella oxytoca to ciprofloxacin exposure: a metabolomics approach.

Introduction: Rapid detection and identification of pathogens and antimicrobial susceptibility is essential for guiding appropriate antimicrobial therapy and reducing morbidity and mortality associated with sepsis.

Objectives: The metabolic response of clinical isolates of Klebsiella oxytoca exposed to different concentrations of ciprofloxacin (the second generation of quinolones antibiotics) were studied in order to investigate underlying mechanisms associated with antimicrobial resistance (AMR).

Methods: Metabolomics investigations were performed using Fourier-transform infrared (FT-IR) spectroscopy as a metabolic fingerprinting approach combined with gas chromatography-mass spectrometry (GC-MS) for metabolic profiling.

Application of infrared spectroscopy to study carbon-deuterium kinetics and isotopic spectral shifts at the single-cell level.

Microbial communities play crucial roles in shaping natural ecosystems, impacting human well-being, and driving advancements in industrial biotechnology. However, associating specific metabolic functions with bacteria proves challenging due to the vast diversity of microorganisms within these communities. In the past decades stable isotope probing (SIP) approaches, coupled with vibrational spectroscopy, have emerged as a novel method for revealing microbial metabolic roles and interactions in complex communities.

Rapid Classification and Differentiation of Sepsis-Related Pathogens Using FT-IR Spectroscopy.

Sepsis is a life-threatening condition arising from a dysregulated host immune response to infection, leading to a substantial global health burden. The accurate identification of bacterial pathogens in sepsis is essential for guiding effective antimicrobial therapy and optimising patient outcomes. Traditional culture-based bacterial typing methods present inherent limitations, necessitating the exploration of alternative diagnostic approaches.

Bacterial discrimination by Fourier transform infrared spectroscopy, MALDI-mass spectrometry and whole-genome sequencing.

Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. 104 pathogenic isolates of , , and were analyzed. Overall prediction accuracy was 99.