Dissecting the Mechanism of Antifungal Drug Action by GC/Q-TOF
Posters | 2012 | Agilent TechnologiesInstrumentation
Understanding how antifungal agents interfere with the biosynthesis of ergosterol is essential for the development of more effective treatments against pathogenic fungi. Yeast Saccharomyces cerevisiae serves as a well‐characterized model for dissecting drug action, enabling both genetic and metabolic approaches to pinpoint enzymatic targets. High‐resolution GC/Q-TOF mass spectrometry enhances sensitivity and specificity in profiling sterol metabolites, offering insights into drug mechanism of action and potential resistance pathways.
High‐resolution GC/Q-TOF metabolic profiling of yeast sterols, supported by MS/MS structural confirmation and multivariate analysis, effectively delineates the mechanisms of existing and novel antifungal agents. This platform bridges genetic screening and analytical chemistry, driving targeted drug development and enhancing our understanding of sterol metabolism in fungal biology.
GC/MSD, GC/MS/MS, GC/HRMS, GC/Q-TOF
IndustriesMetabolomics, Clinical Research
ManufacturerAgilent Technologies
Summary
Significance of the Topic
Understanding how antifungal agents interfere with the biosynthesis of ergosterol is essential for the development of more effective treatments against pathogenic fungi. Yeast Saccharomyces cerevisiae serves as a well‐characterized model for dissecting drug action, enabling both genetic and metabolic approaches to pinpoint enzymatic targets. High‐resolution GC/Q-TOF mass spectrometry enhances sensitivity and specificity in profiling sterol metabolites, offering insights into drug mechanism of action and potential resistance pathways.
Objectives and Study Overview
- Validate a combined targeted and untargeted GC/Q-TOF workflow to profile yeast sterols.
- Apply the method to known antifungal drugs (terbinafine, fluconazole) and novel compounds (Totarol, NCE 1181-0519).
- Identify accumulation or depletion of pathway intermediates to infer specific enzyme inhibition.
- Use MS/MS accurate mass data and computational tools to confirm structures of unexpected metabolites.
Methodology and Instrumentation
- Sample Preparation: Wild‐type S. cerevisiae cultures treated with drug concentrations causing ~10% growth inhibition. Lipids extracted by Folch method; sterols derivatized via oximation (hydroxyamine HCl) and silylation (MSTFA + 1% TMCS).
- GC/Q-TOF Analysis: Agilent 7890 GC coupled to 7200 series Quadrupole-TOF. HP-5 MS UI column (30 m × 0.25 mm, 0.25 µm), EI full‐scan (50–600 m/z), 5 Hz acquisition in centroid and profile modes.
- Data Processing: Chromatographic deconvolution with MassHunter Unknowns; targeted quantitation with MassHunter Quantitative; untargeted multivariate analysis with Mass Profiler Professional; structure prediction using Molecular Structure Correlator (MSC) and NIST11 library.
Main Results and Discussion
- Terbinafine treatment led to pronounced accumulation of squalene and depletion of downstream intermediates, confirming inhibition of squalene epoxidase (Erg1).
- Fluconazole induced lanosterol buildup and reduction of demethylated sterols, consistent with block of 14α‐demethylase (Erg11).
- Untargeted analysis uncovered unexpected 14α-methylated sterols (e.g., 4,4-dimethyl-8,24-cholestadienol) accumulating under NCE 1181-0519, pointing to Erg25 inhibition.
- Totarol treatment specifically elevated 4α-carboxy-4β-methyl-5α-cholesta-8,24-dienol, implicating Erg26 as its molecular target.
- MS/MS accurate mass fragments and MSC scoring confirmed the structures of novel intermediates not present in spectral libraries.
Benefits and Practical Applications
- Combining targeted and untargeted GC/Q-TOF profiling provides comprehensive coverage of sterol pathway alterations.
- Rapid identification of drug targets accelerates lead optimization in antifungal drug discovery.
- High‐resolution MS/MS data enable confident structural assignment of trace metabolites and detection of off‐target effects.
- The approach can be extended to study resistance mechanisms and screen compound libraries in a high‐throughput manner.
Future Trends and Potential Applications
- Integration with genetic screens (e.g., HaploInsufficiency Profiling) for multi‐omics target validation.
- Development of automated workflows combining GC/Q-TOF with machine learning for real-time mechanism prediction.
- Expansion to pathogenic fungal species and direct analysis of clinical isolates.
- Application to other lipid pathways and natural product screening for novel bioactive compounds.
Conclusion
High‐resolution GC/Q-TOF metabolic profiling of yeast sterols, supported by MS/MS structural confirmation and multivariate analysis, effectively delineates the mechanisms of existing and novel antifungal agents. This platform bridges genetic screening and analytical chemistry, driving targeted drug development and enhancing our understanding of sterol metabolism in fungal biology.
References
- Folch J., Lees M., Sloane Stanley G.H. Extraction and purification of total lipids from animal tissues. J Biol Chem, 1957;226:497–509.
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