Presented by Rabi A. Musah, Ph.D. (Louisiana State University)
Studies of Cannabis have revealed that its metabolome is comprised of over 500 compounds, hundreds of which appear in the parts of the plant that are smoked. While it is apparent that users would be exposed to these molecules, the range of compounds ingested by a smoker must also include their pyrolysis products. However, few studies have investigated the products formed from the pyrolysis of the major cannabinoids in Cannabis. As a part of a comprehensive study of the pyrolysis of Cannabis metabolome constituents, the goal of this work is to determine the products formed when the prominent cannabinoid Δ9-tetrahydrocannabinol (Δ9-THC), undergoes pyrolysis.
Milligram quantities of Δ9-THC were analyzed using a Frontier Labs micro-furnace pyrolyzer (Frontier Labs, New Ulm, MN). The samples were pyrolyzed at 400 ºC, 500 ºC, 600 ºC, 700 ºC, and 800 ºC. The micro-furnace pyrolyzer system was coupled to an Agilent 8890 GC system (Agilent, Santa Clara, CA) and a JMS-T2000GC AccuTOF™ GC-Alpha Time-of-Flight Mass Spectrometer (JEOL USA, Inc., Peabody, MA). Both 1D- and 2D- GC analyses were performed. After 30 seconds of pyrolysis, the gaseous Δ9-THC pyrolysis products were assessed by GC-MS. The data were processed using msFine Analysis software (JEOL USA, Inc., Peabody, MA) to generate a temperature-dependent profile of the Δ9-THC pyrolysis products.
The 1D-GC analysis of Δ9-THC pyrolysis products resulted in chromatograms whose complexity varied as a function of temperature. A wide variety of compounds representing classes such as alkanes, alkenes, aromatic hydrocarbons, and heterocycles were detected. Notably, low molecular weight cracking products were observed at higher temperatures. The 2D-GC data revealed a greater range of compounds that were not readily apparent by 1D-GC analysis, with hundreds of pyrolysis products observed, depending on temperature. The complexity of the chromatograms increased at elevated temperatures. With the AccuTOF™ GC-Alpha, the availability of multiple soft ionization modes including FI, PI, and CI facilitated the extraction of molecular weight information, particularly in cases where EI fragmentation resulted in minimal to no signal for the molecular ion. Many of the detected compounds appear to be novel. Determination of candidate structures was greatly facilitated using msFineAnalysis AI software. For unknown compounds not registered in a library database, msFineAnalysis algorithms automatically suggested molecular formulas, and enabled automatic prediction of structures for all detected components. Furthermore, the chromatographic peak deconvolution feature enabled detection of trace components that were not obvious in the total ion current chromatogram due to the coelution of several components. The results amplify our understanding of the range of molecules produced on pyrolysis of a major cannabinoid, alert us to a broader range of pyrolysis products than were previously known, and provide insights into the implications for human health for individuals exposed to both known and new molecules through inhalation of burned Cannabis.
Rabi A. Musah, Ph.D.
Distinguished Professor of Chemistry,
Patrick F. Taylor Chair in Environmental Chemistry – Louisiana State University
Dr. Rabi Musah is a Distinguished Professor of Chemistry at Louisiana State University and holds the Patrick F. Taylor Chair in Environmental Chemistry. Her research spans forensic science, environmental chemistry, plant volatile emissions, and the development of diagnostic tools from unconventional biological matrices. Her work on psychoactive plants, environmental forensics, and illegal species trafficking has been widely recognized, including features in PBS NOVA, Scientific American, The New Scientist, and Forensic Magazine.
Dr. Musah has also been a leading innovator in STEM education, previously serving at the State University of New York at Albany as both a professor and an institutional leader in student success initiatives.
Presented by Masaaki Ubukata, Ph.D. (JEOL LTD.)
Gas chromatography–mass spectrometry (GC-MS) is a powerful tool for comprehensive metabolomics, especially for the analysis of volatile and semi-volatile compounds. However, qualitative analysis using GC-MS remains challenging. The identification of unknown compounds often requires deep expertise in mass spectrometry, advanced spectral interpretation skills, and considerable time. To address these challenges, we are developing an AI-based solution. In this presentation, we will introduce msFineAnalysisAI version 3, an advanced software platform scheduled for release in summer 2025. It will feature a predicted EI mass spectral library containing approximately 200 million compounds, including around 100 million TMS-derivatized compounds commonly encountered in metabolomics. When combined with GC-HRTOFMS, this solution enables faster and more accurate metabolite identification in complex biological samples.
Masaaki Ubukata, Ph. D.
Manager of the Application Department at JEOL Ltd.
Masaaki Ubukata is a Manager of the Application Department at JEOL Ltd., with over 20 years of experience in mass spectrometry, particularly GC-MS and high-resolution mass spectrometry. His career has been centered around materials chemistry, while also contributing to applications in metabolomics, food analysis, and environmental sciences. He holds a Ph.D. in Engineering from Yokohama National University. After completing his doctoral studies, he worked at JEOL USA, where he facilitated international collaborations and promoted advanced MS solutions to a global audience. Currently, he leads efforts to integrate AI technologies into analytical workflows, aiming to accelerate and improve the identification of unknown compounds in complex matrices.
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