Metabolomics Analysis of Tuberculosis Drug Activity Using an Agilent 6545 Q-TOF LC/MS

Importance of the topic

Tuberculosis (TB) continues to be a major global health challenge, claiming more lives than any other infectious disease. Pyrazinamide (PZA) is a frontline anti-TB drug with a poorly understood mechanism of action, and emerging resistance threatens treatment success. A comprehensive metabolomic approach can reveal drug-specific biochemical effects and guide the development of new therapeutic strategies.

Study objectives and overview

This work aimed to develop and apply a robust ion-pairing reversed-phase (IP-RP) Q-TOF LC/MS workflow to profile PZA-induced metabolic alterations in Mycobacterium tuberculosis. By integrating chromatographic optimization, the Agilent 6545 Q-TOF with SWARM Autotune and JetStream (AJS) technologies, and software pipelines (Profinder and Mass Profiler Professional), the study evaluated PZA effects under bacteriostatic (pH 6.6) and bactericidal (pH 5.5) conditions.

Methodology and instrumentation

Sample preparation:

• Cultures of M. tuberculosis were grown on hydrophilic filters and treated with PZA under defined pH conditions.
• Metabolism was quenched in cold acetonitrile:methanol:water, followed by bead-beating lysis and sterile filtration.
• Extracts were snap-frozen and injected (5 µL) in duplicate on the LC/MS system.

Chromatography and mass spectrometry:

• Agilent 1290 Infinity II UHPLC equipped with a ZORBAX Extend C18 column and C8 guard, employing tributylamine/acetic acid ion pairing for negative-mode separations.
• A modified gradient ensured elution of coenzyme A species and other polar metabolites.
• Agilent 6545 Q-TOF run in negative mode with Dual ESI or AJS sources, using SWARM Autotune to optimize ion optics across m/z ranges for enhanced sensitivity.
• AJS thermal gradient focusing was applied to boost signals of stable and phosphorylated metabolites.
• Acquisition spanned 60–1,600 m/z with continuous reference-mass infusion, yielding mass accuracies <±1 ppm and reliable isotope ratios.

Main results and discussion

• SWARM Autotune identified fragile‐ion tuning in the 50–750 m/z range as optimal for small, labile metabolites.
• AJS source delivered a 5–15× sensitivity increase over conventional ESI, with sheath gas temperature adjustments tailored to metabolite classes.
• The 6545 Q-TOF consistently achieved sub-1 ppm mass error across diverse tuning modes and maintained isotope ratio errors within ±10% over a broad intensity range.
• Profinder batch-targeted feature extraction detected 73 of 111 targeted metabolites in TB extracts, streamlining subsequent analyses.
• PCA in MPP distinguished treatment groups by pH and PZA exposure; volcano plots revealed 25–54 statistically significant metabolites (p < 0.05, fold change > 1.5) under bactericidal conditions.
• Hierarchical clustering differentiated PZA effects at pH 5.5 from control and pH 6.6 samples.
• Pathway Architect mapping highlighted 15 differential metabolites in the pantothenate and CoA biosynthesis pathway, implicating cofactor metabolism in PZA activity.

Benefits and practical applications of the method

This integrated IP-RP Q-TOF LC/MS workflow delivers high sensitivity, reproducibility, and broad coverage of labile and phosphorylated metabolites. Automated tuning and real-time calibration ensure data quality, while Profinder and MPP streamline targeted and pathway-driven analyses. The approach is well suited for drug mechanism elucidation, resistance profiling, and high-throughput screening in pharmaceutical research.

Future trends and potential applications

Expanding to untargeted metabolomics, integrating with proteomic and transcriptomic datasets, and applying advanced statistical or machine-learning methods will deepen mechanistic insights. Adapting the workflow for other pathogens and clinical samples could accelerate personalized treatment strategies and novel drug discovery.

Conclusion

The described IP-RP Q-TOF LC/MS platform, enhanced by SWARM Autotune and AJS technologies and supported by Profinder and MPP software, successfully captured PZA-specific metabolic signatures in Mycobacterium tuberculosis. Notably, alterations in pantothenate and CoA metabolism were identified under bactericidal conditions, offering new perspectives on PZA action and demonstrating a powerful tool for metabolome-based drug profiling.

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