Determination of Terpenes in Traditional Chinese Medicine (TCM) by Comprehensive Two-Dimensional Gas Chromatography – Mass Spectrometry (GC × GC) Coupled to High-Resolution Quadrupole Time-of-Flight Mass Spectrometry (QTOFMS) with Orthogonal Partial Least Squares – Discrimination Analysis (OPLS-DA)

Abstract

With a variety of pharmacological effects, the genus Elsholtzia and Mosla of Lamiaceae contain volatile components, including monoterpenes, sesquiterpenes, and their oxygenated derivatives that are widely used in traditional Chinese medicine (TCM). In this work, the volatile terpenes were studied by a more efficient technique based on headspace solid-phase micro-extraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography and quadrupole time-of-flight mass spectrometry (GC × GC-QTOFMS). A total of 91 terpenes consisting of 7 monoterpenes, 34 monoterpene oxides, 39 sesquiterpenes, and 11 sesquiterpene oxides were identified. From the retention time, 4,8,8-trimethyl-2-methylene-4-vinylbicyclo[5.2.0] nonane was identified to be the dominant volatile component in E. blanda, M. chinensis for the first time with 8% prevalence, but further verification is needed. 10 volatile terpenes, including 2-isopropyl-5-methyl-3- cyclohexen-1-one, isoegomaketone, α-muurolene, linalool oxide, ethyl2-(5-methyl- 5-vinyltetrahydrofuran-2-yl)propan-2-ylcarbonate, perilla ketone, elsholtzia ketone, alloaromadendrene oxide, artemisia ketone, longifolene-(V4) were identified by multivariate orthogonal partial least-squares discrimination analysis (OPLS-DA). Because these terpenes have significant pharmacological effects, such as anti-anxiety, anti-oxidation, anti-bacteria, and anti-virus properties, the identification of these terpenes may result in new information related to their pharmacological activities.

Keywords:

• Comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC)
• Elsholtzia
• high-resolution quadrupole time-of-flight mass spectrometry (QTOFMS)
• Lamiaceae
• Mosla
• orthogonal partial least squares-discriminant analysis (OPLS-DA)
• volatile terpenes

Additional information

Funding

This work was supported by the GDAS' Project of Science and Technology Development (grants 2018GDASCX-0808 and 2019GDASYL-0105018).