Rapid separation of cannabinoid isomer sets using differential mobility spectrometry and mass spectrometry.

With legalization and decriminalization of cannabis in many parts of the world comes the need for rapid separation and quantitation of the psychoactive ingredients. Here, we demonstrate the use of differential mobility spectrometry (DMS) mass spectrometry for the analysis of five cannabinoid molecules: the isomer set of Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabichromine (CBC), and the (-)-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA) isomer pair. Analytes were investigated under a variety of gas-phase environments to identify optimal separation conditions based on ion differential mobilities. Separation of the isomers was complicated by the formation of ion-solvent adducts during electrospray ionization (ESI). The observation of ion-solvent adducts correlated with calculated intermolecular binding energies. Introducing 1.5% (v/v) isopropyl alcohol into the N2 carrier gas resulted in strong clustering with the cannabinoid isomers, displacing ESI solvent from the adducts and enabling separation and quantitation of the cannabinoid isomer sets within seconds. Quantification of the carboxylated isomers in marijuana flower was performed to demonstrate analysis of cannabis samples.

UVPD Spectroscopy of Differential Mobility-Selected Prototropic Isomers of Rivaroxaban.

Two ion populations of protonated Rivaroxaban, [C19H18ClN3O5S + H]+, are separated under pure N2 conditions using differential mobility spectrometry prior to characterization in a hybrid triple quadrupole linear ion trap mass spectrometer. These populations are attributed to bare protonated Rivaroxaban and to a proton-bound Rivaroxaban-ammonia complex, which dissociates prior to mass-selecting the parent ion. Ultraviolet photodissociation (UVPD) and collision-induced dissociation (CID) studies indicate that both protonated Rivaroxaban ion populations are comprised of the computed global minimum prototropic isomer. Two ion populations are also observed when the collision environment is modified with 1.5% (v/v) acetonitrile. In this case, the protonated Rivaroxaban ion populations are produced by the dissociation of the ammonium complex and by the dissociation of a proton-bound Rivaroxaban-acetonitrile complex prior to mass selection. Again, both populations exhibit a similar CID behavior; however, UVPD spectra indicate that the two ion populations are associated with different prototropic isomers. The experimentally acquired spectra are compared with computed spectra and are assigned to two prototropic isomers that exhibit proton sharing between distal oxygen centers.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry.

The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (m/z: 86-683 Da and CCS 110-236 Å2) was measured in a N2 environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's m/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform.