Non-Targeted Profiling of Nepeta Cataria Using Multidimensional Gas Chromatography and High-Performance Time-of-Flight Mass Spectrometry

Significance of the Topic

Nepeta cataria, commonly known as catnip, produces a complex mixture of bioactive metabolites, including iridoid terpenes and aroma compounds. Its traditional use in medicine and its effect on feline behavior highlight the importance of detailed chemical profiling. Comprehensive analytical approaches support quality control, product standardization, and investigation of biological activities.

Study Objectives and Overview

• Perform non-targeted phytochemical profiling of catnip products focusing on nepetalactones and aroma terpenes using GC-TOFMS and GC×GC-HRTOFMS.
• Annotate key compounds responsible for differences among commercial and unbranded samples.
• Demonstrate enhanced annotation confidence through high-resolution time-of-flight mass spectrometry.

Methodology and Instrumentation

• Sample preparation: 100–200 mg of dried catnip mixed with saturated NaCl and extracted by headspace SPME using a DVB/Carbon WR/PDMS fiber (10 min incubation, 30 min extraction at 60 °C).
• GC×GC separation: LECO GC×GC QuadJet thermal modulator; primary column Rxi-5ms (30 m×0.25 mm×0.25 µm), secondary column Rxi-17Sil ms (0.60 m×0.25 mm×0.25 µm); oven program 40 °C (1 min) to 300 °C (10 °C/min, hold 13 min); modulation period 2 s at +15 °C above secondary oven.
• Mass spectrometry: LECO Pegasus BTX (resolution >1 100, mass delta 0.05 Da, EI) and Pegasus HRT+ (resolution up to 50 000, mass accuracy 1 ppm, EI/PCI/NCI) at 10 spectra/s (GC) or 200 spectra/s (GC×GC).
• Data processing: ChromaTOF software for peak finding, deconvolution, spectral database matching, retention index filtering, and mass delta calculations to assign formulas.

Main Findings and Discussion

• Identification of major nepetalactones, such as α-dihydronepetalactone, with high-confidence EI spectra and complementary PCI data improving molecular formula determination.
• Detection of diverse terpenes including hexahydrofarnesyl acetone and heterocyclic compounds; their relative abundances varied substantially between samples.
• Chemometric analysis (PCA) effectively distinguished samples labeled A–D from unbranded sample U based on non-targeted volatile profiles.
• Discovery of discriminating features like 2,6-dichlorotoluene and classes such as linear alcohols, aldehydes, and ketones contributing to sample differentiation.

Benefits and Practical Applications

• Supports quality assessment and batch consistency of catnip products in nutraceutical and veterinary applications.
• Enables detection of adulteration and verification of botanical provenance.
• Informs breeding and cultivation strategies by profiling bioactive compound variation.
• Provides valuable data for fragrance, flavor, and pharmaceutical industries exploring catnip’s olfactory and therapeutic properties.

Future Trends and Potential Applications

• Integration with high-throughput LC-MS and other hyphenated techniques for comprehensive multi-omics plant analysis.
• Application of machine learning for automated feature annotation and pattern recognition in complex datasets.
• Expansion of high-resolution spectral libraries to include novel plant metabolites and rare iridoids.
• Development of portable GC×GC-MS systems for rapid in-field screening and real-time quality control.

Conclusion

Non-targeted GC×GC-TOFMS combined with high-resolution TOFMS offers a robust strategy for detailed chemical profiling of Nepeta cataria. This approach delivers high-confidence compound annotation, clear sample differentiation, and underpins advanced quality control and research applications across various industries.

References

• Alonso DE, Hayes J, Humston-Fulmer E, Binkley JE. Non-Targeted Profiling of Nepeta cataria Using Multidimensional Gas Chromatography and High-Performance Time-of-Flight Mass Spectrometry. LECO Corporation; Saint Joseph, MI; Year n.d.