Application of Ambient Ionization High Resolution Mass Spectrometry to Determination of the Botanical Provenance of the Constituents of Psychoactive Drug Mixtures

• NCJ Number: 255184
• Journal: Forensic Science International Volume: 266 Dated: September 2016 Pages: 271-280
• Author(s): Ashton D. Lesiak; Rabi A. Musah
• Date Published: September 2016
• Length: 10 pages
• Grant Number(s): 2015-DN-BX-K057
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description
• Award: Development of Ambient Ionization Mass Spectrometric and Multivariate Statistical Analysis Methods for Rapid High Throughput Analysis and Identification of Psychotropic Plant Species

Annotation

This article reports on a project that demonstrated the proof of principle that ambient ionization mass spectrometry, namely direct analysis in real time-high resolution mass spectrometry (DART-HRMS), and statistical analysis tools can be used to rapidly determine the individual components within a psychoactive brew (Ayahuasca) made from a mixture of botanicals.

Abstract

A continuing challenge in analytical chemistry is species-level determination of the constituents of mixtures that are made of a combination of plant species. There is an added urgency to identify components in botanical mixtures that have mind altering properties, due to the increasing global abuse of combinations of such plants. In the current study, five plant species used in Ayahuasca preparations were subjected to DART-HRMS analysis. The chemical fingerprint of each was reproducible but unique, thus enabling discrimination between them. The presence of important biomarkers, including N,N-dimethyltryptamine, harmaline and harmine, was confirmed using in-source collision-induced dissociation (CID). Six Ayahuasca brews made from combinations of various plant species were shown to possess a high level of similarity, despite having been made from different constituents. Nevertheless, the application of principal component analysis (PCA) was useful in distinguishing between each of the brews based on the botanical species used in the preparations. From a training set based on 900 individual analyses, three principal components covered 86.38 percent of the variance, and the leave-one-out cross validation was 98.88 percent. This is the first report of ambient ionization MS being successfully used for determination of the individual components of plant mixtures. (publisher abstract modified)