The authors gratefully acknowledge a University at Albany-SUNY Presidential Initiatives Fund for Research and Scholarship in Forensic Science and Cybersecurity grant, a National Science Foundation grant (Grant #1310350) and a National Institute of Justice grant (Grant #2015-DN-BX-K057) to RAM. We also acknowledge Justine E. Giffen for taking the photographs of the plant materials.

1. Preparation of Plant Materials
<ol>
	<li>Kratom Fresh Leaf Material
	<ol>
		<li>Use a 6 mm diameter hole punch to create uniform chads of Kratom leaf material from M. speciosa plant. Repeat 5 times.</li>
	</ol>
	</li>
	<li>Kratom Powder Extraction
	<ol>
		<li>Mix 5 ml of ethanol and 5 ml of distilled water to create 1:1 solvent mixture for extraction.</li>
		<li>In a 1.5 ml microcentrifuge tube, suspend a small amount (~5 mg) of Kratom Bali powder in 1 ml of the 1:1 EtOH:H2O solvent mixture. Repeat 5 times.</li>
		<li>Sonicate the Kratom Bali powder extract samples in an ultrasonic bath for 30 min at ambient temperature.</li>
		<li>Centrifuge the Kratom Bali powder extract samples for 2 min at 750 x g at ambient temperature.</li>
		<li>Decant the solvent from residual powder for subsequent analysis.</li>
	</ol>
	</li>
	<li>Datura seed preparation
	<ol>
		<li>Slice a D. stramonium seed in half across the transverse plane using a razor blade. Repeat using 5 different seeds.</li>
		<li>Repeat for D. inoxia and D. ferox seeds.</li>
	</ol>
	</li>
</ol>
2. Direct Analysis in Real Time Ion Source Parameters
<ol>
	<li>Gas Heater Temperature
	<ol>
		<li>Set the gas heater temperature of the ion source to 350 &#176;C.</li>
	</ol>
	</li>
	<li>Ion Mode
	<ol>
		<li>Conduct the analysis in positive ion mode with grid voltage of 250 V.</li>
	</ol>
	</li>
	<li>Helium Gas Flow Rate
	<ol>
		<li>Set the helium gas flow rate to 2.0 L/sec.</li>
	</ol>
	</li>
</ol>
3. Time-of-flight Mass Spectrometer Parameters
<ol>
	<li>Orifice Voltages
	<ol>
		<li>Set the orifice 1 voltage to 20 V and the orifice 2 voltage to 5 V.</li>
	</ol>
	</li>
	<li>Ring Lens and Peak Voltage
	<ol>
		<li>Adjust the ring lens voltage to 5 V and change the peaks voltage to 600 V.</li>
	</ol>
	</li>
	<li>Mass Spectral Acquisition
	<ol>
		<li>Set the mass spectral acquisition rate to 1 spectrum per second over a mass range of m/z 60-800.</li>
	</ol>
	</li>
	<li>Mass Spectrometer Resolving Power
	<ol>
		<li>Set the resolving power of the mass spectrometer to 6000 FWHM.</li>
	</ol>
	</li>
</ol>
4. Analysis of Plant Materials
<ol>
	<li>Analysis of Kratom Leaf
	<ol>
		<li>Press &#34;Start Run&#34; in mass spectrometer control software. Suspend the chad of plant material between the ion source and mass spectrometer inlet (approximately 2 cm from the inlet) with tweezers until a spectrum is obtained. Repeat 5 times with separate chads of plant material.</li>
		<li>Calibrate the spectrum with polyethylene glycol 600 (PEG).
		<ol>
			<li>Dip the closed end of a melting point capillary tube into the PEG standard. Suspend the coated capillary between the ion source and the mass spectrometer inlet.</li>
		</ol>
		</li>
		<li>After analyzing the PEG standard, select the &#34;Stop&#34; button to end the analytical run.</li>
		<li>Press &#34;Start Run&#34; in mass spectrometer control software. Suspend a small amount of dried leaf material between the ion source and mass spectrometer inlet with tweezers until a spectrum is obtained. Repeat 5 times, analyzing new plant material each time.</li>
		<li>Calibrate the spectrum with PEG.
		<ol>
			<li>Dip the closed end of a capillary into the PEG standard. Suspend the coated capillary between the ion source and the mass spectrometer inlet.</li>
		</ol>
		</li>
		<li>After analyzing the PEG standard, select the &#34;Stop&#34; button to end the analytical run.</li>
	</ol>
	</li>
	<li>Analysis of Kratom Powder
	<ol>
		<li>Press &#34;Start Run&#34; in mass spectrometer control software. Dip the closed end of a melting point capillary into the Kratom powder.</li>
		<li>Suspend the coated capillary between the ion source and mass spectrometer inlet until a spectrum is obtained. Repeat the analysis 5 times with a new capillary each time.</li>
		<li>Calibrate the spectrum with PEG.
		<ol>
			<li>Dip the closed end of a capillary into the PEG standard. Suspend the coated capillary between the ion source and the mass spectrometer inlet.</li>
		</ol>
		</li>
		<li>After analyzing the PEG standard, select the &#34;Stop&#34; button to end the analytical run.</li>
	</ol>
	</li>
	<li>Analysis of Kratom Extract
	<ol>
		<li>Immerse the closed end of a capillary tube into the extract.</li>
		<li>Suspend the capillary tube in the 12-sample holder on the linear rail attached to the mass spectrometer. Repeat 5 times with a different extract each time.</li>
		<li>Press &#34;Start Run&#34; in mass spectrometer control software. Using the control panel, select the &#34;&#62;&#34; button to advance the linear rail through the ion stream at rate of 1 mm/sec to collect spectra.</li>
		<li>Calibrate the spectrum with PEG.
		<ol>
			<li>Dip the closed end of a capillary into the PEG standard. Suspend the coated capillary between the ion source and the mass spectrometer inlet.</li>
		</ol>
		</li>
		<li>After analyzing the PEG standard, select the &#34;Stop&#34; button to end the analytical run.</li>
	</ol>
	</li>
	<li>Analysis of Datura seeds
	<ol>
		<li>Press &#34;Start Run&#34; in mass spectrometer control software. Suspend the Datura seed half between the ion source and mass spectrometer inlet with tweezers until a spectrum is collected. Ensure that the cut side is oriented to face the ion source. Repeat 5 times, analyzing a new seed half each time.</li>
		<li>Calibrate the spectrum with PEG.
		<ol>
			<li>Dip the closed end of a capillary into the PEG standard. Suspend the coated capillary between the ion source and the mass spectrometer inlet.</li>
		</ol>
		</li>
		<li>After analyzing the PEG standard, select the &#34;Stop&#34; button to end the analytical run.</li>
		<li>Repeat steps 4.4.1-4.4.3 for each Datura species.</li>
	</ol>
	</li>
</ol>
5. Data Processing
<ol>
	<li>Translating Data Files
	<ol>
		<li>In the data processing software, select File, &#34;Translate DART Files&#34; with &#34;automatic calibration&#34; turned on, to create calibrated data files.</li>
		<li>Left click and drag a box around the first peak in the chromatogram and select &#34;Average&#34; to create an averaged spectrum.</li>
		<li>Right click and drag a box around an area where no sample was collected and select &#34;Average entire box as background&#34; to subtract background from the averaged spectrum.</li>
		<li>Save the mass spectrum as a .txt file.</li>
		<li>Repeat steps 5.1.1-5.1.4 for each peak in the chromatogram to create an averaged spectrum for each replicate in the file.</li>
		<li>Repeat steps 5.1.2-5.1.5 for each file collected.</li>
	</ol>
	</li>
</ol>
6. Statistical Analysis
<ol>
	<li>Principal Component Analysis
	<ol>
		<li>In the Classify section of the spectral analysis software (See List of Materials), under the &#34;Set up&#34; tab, create classes for data processing by selecting &#34;Add Class&#34;.</li>
		<li>Import the text files of data by selecting &#34;Add File(s)&#34;.</li>
		<li>Assign data files to the appropriate class of plant by selecting text files and &#34;Set Class for Selected Files&#34;.</li>
		<li>Select feature masses for discrimination from MS from Training Set and set Threshold % to 1%.</li>
		<li>Set a mass tolerance (mmu) to 10 and select &#34;Build Vectors from Data Files&#34;.</li>
		<li>In the &#34;Compute&#34; section, perform principal component analysis by checking the box for 3D PCA Graph and select &#34;Calculate&#34;.</li>
		<li>Perform leave-one-out cross validation by selecting &#34;Validate (SLOW!).&#34;</li>
	</ol>
	</li>
	<li>Generate Heat Map
	<ol>
		<li>In the Frequency Plot tab of the spectral analysis software, generate a heat map of data by selecting &#34;Heat Map.&#34;</li>
		<li>Select &#34;Threshold saved data&#34; to set abundance threshold to 1%.</li>
		<li>Export the heat map to a spreadsheet by selecting &#34;Save Heat Map to Excel.&#34;</li>
		<li>In the spreadsheet program, save the exported heat map as a .txt file.</li>
	</ol>
	</li>
	<li>Hierarchical Clustering Analysis
	<ol>
		<li>Import the heat map as a .txt file into Cluster 3.0 software.</li>
		<li>In the hierarchical tab of Cluster 3.0, under Genes and Arrays, check boxes &#34;Cluster&#34; and &#34;Calculate weights&#34;. Set cutoff at 0.1 and exponent to 1. Select single linkage clustering to perform analysis.</li>
		<li>View the generated .cdt data file in Java Treeview.</li>
	</ol>
	</li>
</ol>

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<li>Jansen, K., Prast, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ehtnopharmacology+of+Kratom+and+the+Mitragyna+alkaloids%5BTitle%5D)+AND+%22J.+Ethnopharmacol%22%5BJournal%5D)">Ehtnopharmacology of Kratom and the Mitragyna alkaloids.</a> J. Ethnopharmacol. 23, 115-119 (1988).</li>
<li>Matsumoto, K. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aMatsumoto%2C+K+%22Pharmacological+Studies+on+7-Hydroxymitragynine%2C+Isolated+from+the+Thai+Herbal+Medicine+Mitragyna+speciosa%3A+Discovery+of+an+Orally+Active+Opioid+Analgesic%22">Pharmacological Studies on 7-Hydroxymitragynine, Isolated from the Thai Herbal Medicine Mitragyna speciosa: Discovery of an Orally Active Opioid Analgesic</a>. , Chiba University. (2006).</li>
<li>Matsumoto, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Involvement+of+%C2%B5-opioid+receptors+in+antinociception+and+inhibition+of+gastrointestinal+transit+induced+by+7-hydroxymitragynine%2C+isolated+from+Thai+herbal+medicine+Mitragyna+speciosa%5BTitle%5D)+AND+%22Eur.+J.+Pharmacol%22%5BJournal%5D)">Involvement of µ-opioid receptors in antinociception and inhibition of gastrointestinal transit induced by 7-hydroxymitragynine, isolated from Thai herbal medicine Mitragyna speciosa.</a> Eur. J. Pharmacol. 549, (2006).</li>
<li>Matsumoto, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Antinociceptive+effect+of+7-hydroxymitragynine+in+mice%3A+Discovery+of+an+orally+active+opioid+analgesic+from+the+Thai+medicinal+herb+Mitragyna+speciosa%5BTitle%5D)+AND+%22Life+Sciences%22%5BJournal%5D)">Antinociceptive effect of 7-hydroxymitragynine in mice: Discovery of an orally active opioid analgesic from the Thai medicinal herb Mitragyna speciosa.</a> Life Sciences. 74, 2143-2155 (2004).</li>
<li>El Bazaoui, A., Stambouli, H., Bellimam, M. A., Soulaymani, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+tropane+alkaloids+in+seeds+of+Datura+stramonium+L.+by+GC%2FMS+and+LC%2FMS%5BTitle%5D)+AND+%22Ann.+Toxicol.+Anal%22%5BJournal%5D)">Determination of tropane alkaloids in seeds of Datura stramonium L. by GC/MS and LC/MS.</a> Ann. Toxicol. Anal. 21, 183-188 (2009).</li>
<li>Friedman, M., Levin, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Composition+of+Jimson+Weed+%28Datura+stramonium%29+seeds%5BTitle%5D)+AND+%22J.+Agr.+Food+Chem%22%5BJournal%5D)">Composition of Jimson Weed (Datura stramonium) seeds.</a> J. Agr. Food Chem. 37, 998-1005 (1989).</li>
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<li>Preissel, U., Preissel, H. -G. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aPreissel%2C+U+%22Brugmansia+and+Datura%3A+Angel%27s+Trumpets+and+Thorn+Apples%22">Brugmansia and Datura: Angel's Trumpets and Thorn Apples</a>. , Firefly Books. (2002).</li>
<li>Boumba, V. A., Mitselou, A., Vougiouklakis, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fatal+poisoning+from+ingestion+of+Datura+stramonium+seeds%5BTitle%5D)+AND+%22Vet.+Hum.+Toxicol%22%5BJournal%5D)">Fatal poisoning from ingestion of Datura stramonium seeds.</a> Vet. Hum. Toxicol. 46, 81-82 (2004).</li>
<li>Kronstrand, R., Roman, M., Thelander, G., Eriksson, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unintentional+Fatal+Intoxications+with+Mitragynine+and+O-Desmethyltramadol+from+the+Herbal+Blend+Krypton%5BTitle%5D)+AND+%22J.+Anal.+Toxicol%22%5BJournal%5D)">Unintentional Fatal Intoxications with Mitragynine and O-Desmethyltramadol from the Herbal Blend Krypton.</a> J. Anal. Toxicol. 35, 242-247 (2011).</li>
<li>Neerman, M., Frost, R., Deking, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+drug+fatality+involving+Kratom%5BTitle%5D)+AND+%22J.+Forensic+Sci%22%5BJournal%5D)">A drug fatality involving Kratom.</a> J. Forensic Sci. 58, 278-279 (2013).</li>
<li>Steenkamp, P. A., Harding, N. M., Van Heerden, F. R., Van Wyk, B. -E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fatal+Datura+poisoning%3A+Identification+of+atropine+and+scopolamine+by+high+performance+liquid+chromatography+%2F+photodiode+array+%2F+mass+spectrometry%5BTitle%5D)+AND+%22Forensic+Sci.+Int%22%5BJournal%5D)">Fatal Datura poisoning: Identification of atropine and scopolamine by high performance liquid chromatography / photodiode array / mass spectrometry.</a> Forensic Sci. Int. 145, 31-39 (2004).</li>
<li><a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22Scientific+Working+Group+for+the+Analysis+of+Seized+Drug+Recommendations%22">Scientific Working Group for the Analysis of Seized Drug Recommendations</a>. , Scientific Working Group for the Analysis of Seized Drugs. (2014).</li>
<li>Kikura-Hanajiri, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Simultaneous+analysis+of+mitragynine%2C+7-hydroxymitragynine%2C+and+other+alkaloids+in+the+psychotropic+plant+%22Kratom%22+%28Mitragyna+speciosa%29+by+LC-ESI-MS%5BTitle%5D)+AND+%22Forensic+Toxicol%22%5BJournal%5D)">Simultaneous analysis of mitragynine, 7-hydroxymitragynine, and other alkaloids in the psychotropic plant "Kratom" (Mitragyna speciosa) by LC-ESI-MS.</a> Forensic Toxicol. 27, 67-74 (2009).</li>
<li>Wang, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparison+of+three+chromatographic+techniques+for+the+detection+of+mitragynine+and+other+indole+and+oxindole+alkaloids+in+Mitragyna+speciosa+%28Kratom%29+plants%5BTitle%5D)+AND+%22J.+Separation+Sci%22%5BJournal%5D)">Comparison of three chromatographic techniques for the detection of mitragynine and other indole and oxindole alkaloids in Mitragyna speciosa (Kratom) plants.</a> J. Separation Sci. , (2014).</li>
<li>Cody, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Observation+of+molecular+ions+and+analysis+of+nonpolar+compounds+with+the+Direct+Analysis+in+Real+Time+ion+source%5BTitle%5D)+AND+%22Anal.+Chem%22%5BJournal%5D)">Observation of molecular ions and analysis of nonpolar compounds with the Direct Analysis in Real Time ion source.</a> Anal. Chem. 81, 1101-1107 (2009).</li>
<li>Cody, R., Laramee, J., Durst, H. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Versatile+new+ion+source+for+the+analysis+of+materials+in+open+air+under+ambient+conditions%5BTitle%5D)+AND+%22Anal.+Chem%22%5BJournal%5D)">Versatile new ion source for the analysis of materials in open air under ambient conditions.</a> Anal. Chem. 77, 2297-2302 (2005).</li>
<li>Musah, R. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+High+Throughput+Ambient+Mass+Spectrometric+Approach+to+Species+Identification+and+Classification+from+Chemical+Fingerprint+Signatures%5BTitle%5D)+AND+%22Sci.+Rep%22%5BJournal%5D)">A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures.</a> Sci. Rep. 5, (2015).</li>
<li>Lesiak, A. D., Cody, R. B., Dane, A. J., Musah, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Rapid+detection+by+direct+analysis+in+real+time-mass+spectrometry+%28DART-MS%29+of+psychoactive+plant+drugs+of+abuse%3A+The+case+of+Mitragyna+speciosa+aka+%22Kratom%22%5BTitle%5D)+AND+%22Forensic+Sci.+Int%22%5BJournal%5D)">Rapid detection by direct analysis in real time-mass spectrometry (DART-MS) of psychoactive plant drugs of abuse: The case of Mitragyna speciosa aka "Kratom".</a> Forensic Sci. Int. 242, 210-218 (2014).</li>
<li>Lesiak, A. D., Cody, R. B., Dane, A. J., Musah, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Plant+Seed+Species+Identification+from+Chemical+Fingerprints%3A+A+High-Throughput+Application+of+Direct+Analysis+in+Real+Time+Mass+Spectrometry%5BTitle%5D)+AND+%22Anal.+Chem%22%5BJournal%5D)">Plant Seed Species Identification from Chemical Fingerprints: A High-Throughput Application of Direct Analysis in Real Time Mass Spectrometry.</a> Anal. Chem. , (2015).</li>
<li>Espinoza, E. O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Distinguishing+wild+from+cultivated+agarwood+%28Aquilaria+spp.%29+using+direct+analysis+in+real+time+and+time+of-flight+mass+spectrometry%5BTitle%5D)+AND+%22Rapid+Commun.+Mass+Spectrom%22%5BJournal%5D)">Distinguishing wild from cultivated agarwood (Aquilaria spp.) using direct analysis in real time and time of-flight mass spectrometry.</a> Rapid Commun. Mass Spectrom. 28, 281-289 (2014).</li>
<li>Lancaster, C., Espinoza, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluating+agarwood+products+for+2-%282-phenylethyl%29chromones+using+direct+analysis+in+real+time+time-of-flight+mass+spectrometry%5BTitle%5D)+AND+%22Rapid+Commun.+Mass+Spectrom%22%5BJournal%5D)">Evaluating agarwood products for 2-(2-phenylethyl)chromones using direct analysis in real time time-of-flight mass spectrometry.</a> Rapid Commun. Mass Spectrom. 26, 2649-2656 (2012).</li>
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</ol>

The authors have no disclosures.

The ability to identify plant-based drugs of abuse is of increasing necessity due to the dramatic rise in the marketing, sale and consumption of unscheduled psychoactive substances.2 Traditional methods for identification of botanical material usually involve characterization of physical features coupled with analysis of the chemical constituents by hyphenated chromatographic-mass spectrometric methods. However, both of these approaches present challenges to streamlined analysis. Physical features of the plants are often destroyed when the plants are dried, pulverized or extracted during the manufacturing process and as such, it is often difficult to distinguish one type of plant-based psychotropic product from another based on physical features alone.23 Analysis by chromatographic-mass spectrometric methods can enable identification of the psychoactive compounds in plant matrices, but the sample preparation and method development is time and resource intensive, and the creation of new protocols for each class or species of plant-based drug of abuse is impractical in many forensic chemistry labs.
Direct analysis in real time-high resolution mass spectrometry circumvents some of these challenges, as complex matrices such as leaves, powders, extracts and seeds can be analyzed with little sample preparation. Despite the complex matrices of the materials sampled here, the psychoactive constituents were easily identifiable, even at nanogram concentrations,21 due to the high sensitivity of the mass spectrometer. Seeds, leaves and powders were demonstrated to be readily analyzed by direct analysis in real time-high resolution mass spectrometry, and a variety of other types of materials can also be sampled in the same manner, including TLC plates, currency, tablets, flowers, solid phase microextraction (SPME) fibers and even insect puparial casings.21-22 Through accurate mass analysis, elemental composition determination and isotope matching, biomarkers and compounds of interest can be identified, regardless of whether the compounds are contained in a leaf, spotted on a TLC plate or coated on a capillary tube.
Direct analysis in real time-high resolution mass spectrometry methodology can be used for streamlined analysis as there are very few parameters that need to be modified from experiment to experiment. Analysis can be performed in positive-ion or negative-ion mode, and molecules of up to 3,000 amu can be detected in both cases. Ionization in positive-ion mode occurs by proton transfer from activated water clusters,21 and any compound with a proton affinity higher than that of water will be ionized. Here, positive-ion mode was used because of the high proton affinity of alkaloids, which causes them to be readily ionized by protonation. Analysis in negative-ion mode can be used for the successful detection of hydrocarbons (as O2 adducts)21, explosive materials27 and organic acids such as artesunate in malarial medications.28 Due to the ionization method of proton-transfer and the inability to produce multiply charged ions, direct analysis in real time-high resolution mass spectrometry is limited mainly to the analysis of small molecules of up to 3,000 amu.
Other than ionization mode, the temperature of the ion source is an important parameter and the appropriate temperature largely depends on the sample being analyzed. For example, it is important to use lower temperatures (~250 &#176;C) for SPME fiber analysis to prevent destruction of the coating material on the fiber, while higher temperatures (~500 &#176;C) should be used for amino acid analysis for desorption and subsequent ionization. Here, plant material analyses were conducted at 350 &#176;C, as this allows for ionization of alkaloids and other compounds of interest without causing pyrolysis of compounds in the plant matrix.
Direct analysis in real time-high resolution mass spectrometry analysis not only enables identification of the psychoactive constituents of the plant material based on accurate masses, elemental composition determination and isotope matching, but it also produces unique chemical fingerprints that can be exploited for species identification using multivariate statistical analysis with highly reproducible results, even with smaller datasets. Multivariate statistical analysis has been applied to a wide variety of direct analysis in real time-high resolution mass spectrometry data, including that derived from wood, puparial casings, seeds, leaf material, and biodiesel fuelstocks, showcasing the versatility and reproducibility of the method.22-26 The high-throughput capabilities of direct analysis in real time-high resolution mass spectrometry enable the acquisition of large amounts of mass spectral data in a short time period, and the large number of replicates needed for statistical analysis are easily acquired using this method. The direct analysis in real time-high resolution mass spectrometry mass spectral dataset of Datura and Kratom was comprised of over 100 individual spectra that were collected with less than an hour of total time investment. To obtain the same number of spectra using GC-MS with an oven temperature program of 30 minutes would take approximately 50 hours, without consideration of the added time for sample preparation steps, such as extraction or derivatization.
Principal component analysis can be used to highlight variations between sets of plant substances based on the presence and intensity of selected feature masses. The statistical analysis processing provides species identification, as well as varietal information. Other methods of statistical analysis, such as hierarchical clustering analysis (HCA), can also be applied without the a priori selection of feature masses. The results of HCA of comprehensive chemical fingerprints show that unsupervised statistical analysis can be successfully applied for species identification of plant-based drugs of abuse.25
The species discrimination of forensic botanical material by direct analysis in real time-high resolution mass spectrometry was demonstrated using the identification of psychotropic compounds and other biomarkers in the soft-ionization mass spectra, and the application of multivariate statistical analysis. The application of two types of statistical analyses revealed not only that the class of a plant-based drug of abuse can be identified, but also that the variety and species of said drug can be determined based on the unique chemical fingerprints observed by direct analysis in real time-high resolution mass spectrometry. The method presented here enables the rapid, high-throughput identification of mind-altering substances in a manner that circumvents challenges encountered in conventional analytical methods, and provides forensic laboratories with a means to characterize and identify psychoactive plant material without time and resource intensive method development. This protocol can be extended to species differentiation of a variety of other plant-derived materials.22-26

For millennia, psychoactive natural products have been used in shamanic rituals, abused for their mind-altering attributes, and consumed for their medicinal properties. The ingestion of these plants and related plant-based substances can be significant in areas where they are endemic, and they have social and economic importance. Recently however, there has been a dramatic rise in the use of these &#34;natural&#34; drugs due to the ease of accessibility through internet commerce. The perception that these substances are safe to use, coupled with an increased crackdown on possession and use of more traditional drugs of abuse and synthetic substances, have contributed to the spike in abuse of plant-based drugs. It is generally difficult by visualization to distinguish between these products and harmless plant material, and therefore there is interest in developing methods that can be used identify these products. However, conventional analytical methods for plant species identification are time consuming and impractical to perform. Moreover, the methods development process is time and resource intensive. These factors have made the crafting of legislation to curb the use of these substances lag far behind the rate of escalation in their abuse. Thus, there are few laws that regulate the production, manufacture, sale and consumption of many of these natural psychoactives and as such, there are hundreds of plants of abuse available to users in thousands of different forms.1,2
Two such plant-based drugs of abuse are Mitragyna speciosa, commonly known as Kratom, and plants from the Datura genus, namely D. stramonium, D. ferox and D. inoxia. Kratom and Datura are unscheduled in the United States, but the Drug Enforcement Administration has listed both as drugs of concern.3,4 Kratom is characterized by the presence of the psychoactive compounds mitragynine and 7-hydroxymitragynine, as well as other non-psychoactive alkaloids including mitraphylline, paynantheine, corynoxeine, and rhynchophylline.4-8 The psychoactive properties of Datura spp. are attributed to atropine and scopolamine, but a variety of other tropane alkaloids have been identified in the plants.9-12 Both Kratom and Datura have been implicated in poisonings and fatalities, and their identification is increasingly necessary in both forensic and toxicological contexts, as the abuse of these products is on the rise.13-16
By and large, traditional methods used for the analysis of forensic drug material, such as color tests, microscopy, and Raman and infrared spectroscopy, are used in a rule-in/rule-out presumptive capacity. Hyphenated techniques such as GC-MS and liquid chromatography-mass spectrometry (LC-MS), are confirmatory analysis methods based on comparison of the profiles of detected analytes to Scientific Working Group on Analysis of Seized Drugs (SWGDRUG) library standards.17 The sample treatment steps that are performed prior to analysis including pulverization, extraction, derivatization and evaporation, can add hours to the run time and adulterate the sample,9,11,18,19 making analysis of botanical drugs less than straightforward compared to that for other traditional drugs of abuse like cocaine or heroin. Moreover, individual chromatographic programs need to be developed for every product of interest, which makes the implementation of standard operating protocols for each species or variety of plant-based drug of abuse highly impractical for routine casework.
Direct analysis in real time-high resolution mass spectrometry is an ambient ionization mass spectrometric technique that circumvents some of the challenges associated with conventional analytical methods. Gases, liquids, solids, powders, TLC plates and plant material can all be analyzed directly using direct analysis in real time-high resolution mass spectrometry, and both polar and non-polar compounds can be easily detected in complex matrices.20-22 Furthermore, studies have shown that psychoactive compounds can be rapidly identified in plant material by direct analysis in real time-high resolution mass spectrometry, and species-specific information can be gleaned from statistical processing of the mass spectral data.22-26
Here, we demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to quickly assess various plant materials (i.e., plants, powders, extracts and seeds) for their psychoactive components, and that the species and varieties of the plant-derived products can be determined in a rapid and high-throughput manner. The analysis of forensically relevant botanical material without the need for sample preparation steps or long chromatographic analysis run times, in addition to plant species identification is reported.

<table><tbody><tr><td>AccuTOF Mass Spectrometer</td><td>JEOL USA, Inc.</td><td></td><td></td></tr><tr><td>DART-SVP Ion Source</td><td>IonSense, Inc.</td><td>DART-SVP</td><td></td></tr><tr><td>Linear Rail System</td><td>IonSense, Inc.</td><td>HW-10029</td><td></td></tr><tr><td>Hole puncher (6 mm)</td><td>Swingline</td><td>A7074005</td><td></td></tr><tr><td>One-Pint Compact Ultrasonic Cleaner</td><td>Cole-Palmer</td><td>EQ-08849-00</td><td></td></tr><tr><td>1.5 ml Eppendorf Microcentrifuge tubes</td><td>Fisher Scientific</td><td>02-682-550</td><td></td></tr><tr><td>AccuSpin Micro 17R Centrifuge</td><td>Fisher Scientific</td><td>13-100676</td><td></td></tr><tr><td>#9 Stainless Steel Razor blade</td><td>Stanley</td><td>11-515</td><td></td></tr><tr><td>Dip-it Tip Holder</td><td>IonSense, Inc.</td><td>SCT-70003</td><td></td></tr><tr><td>Dip-it Tips</td><td>IonSense, Inc.</td><td>DPT-110</td><td></td></tr><tr><td>Melting Point Capillary</td><td>Krackeler Scientific</td><td>1-9530-3</td><td></td></tr><tr><td>Polyethylene glycol (600)</td><td>Sigma Aldrich</td><td>81180</td><td></td></tr><tr><td>Rifat Kratom Live Plant</td><td>World Seed Supply Kratom Collection</td><td>LIVEKRATOMPLANT</td><td></td></tr><tr><td>Bali Kratom Dried Leaf</td><td>The Kratom King</td><td>OZKRAPCOM</td><td></td></tr><tr><td>Bali Kratom Powder</td><td>The Kratom King</td><td>OZKRAPCOMPOW</td><td></td></tr><tr><td>&lt;em&gt;Datura stramonium&lt;/em&gt; seeds</td><td>Horizon Herbs LLC</td><td>PDATUJ</td><td></td></tr><tr><td>&lt;em&gt;Datura inoxia&lt;/em&gt; seeds</td><td>Horizon Herbs LLC</td><td>PDATUM</td><td></td></tr><tr><td>&lt;em&gt;Datura ferox&lt;/em&gt; seeds</td><td>Georgia Vines</td><td>255/737</td><td></td></tr><tr><td>Ethanol, anhydrous</td><td>Krackeler Scientific</td><td>1328-E402-4L</td><td></td></tr><tr><td>Mass Mountaineer Spectral Analysis Software</td><td>mass-spec-software.com</td><td>MM-20030-PCA-DVD</td><td></td></tr><tr><td>TSSPro3 Data Processing/Data Reduction Software</td><td>Shrader Labs</td><td></td><td></td></tr><tr><td>Cluster 3.0</td><td>http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm</td><td>Open Source Software</td><td></td></tr><tr><td>Java Treeview</td><td>http://jtreeview.sourceforge.net/</td><td></td><td>Open Source Software</td></tr></tbody></table>

rapid high-throughput species identification of botanical material using direct analysis in real time high resolution mass spectrometry

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, and that these chemical fingerprints can be used for plant species identification. The mass spectral data can be acquired rapidly and in a high throughput manner without the need for sample extraction, derivatization or pH adjustment steps. The use of this technique bypasses challenges presented by more conventional techniques including lengthy chromatography analysis times and resource intensive methods. The high throughput capabilities of the direct analysis in real time-high resolution mass spectrometry protocol, coupled with multivariate statistical analysis processing of the data, provide not only class characterization of plants, but also yield species and varietal information. Here, the technique is demonstrated with two psychoactive plant products, Mitragyna speciosa (Kratom) and Datura (Jimsonweed), which were subjected to direct analysis in real time-high resolution mass spectrometry followed by statistical analysis processing of the mass spectral data. The application of these tools in tandem enabled the plant materials to be rapidly identified at the level of variety and species.

Representative soft ionization positive-ion mode direct analysis in real time-high resolution mass spectrometry data of Kratom products and Datura seeds are shown in Figures 2 and 3. Various compounds previously isolated from M. speciosa, including mitragynine (C23H30N2O4 + H+, m/z 399.2284) and 7-hydroxymitragynine (C23H30N2O5 + H+, m/z 415.2233), were detected in all four samples and the corresponding mass measurement data are presented in Table 1.4-8 Representative Datura data are shown in Figure 3 and signature biomarkers including atropine (C17H23NO3 + H+, m/z 290.1756) and scopolamine (C17H21NO4 + H+, m/z 304.1549) were detected in the three species. Mass measurement data associated with Figure 3 are presented in Table 2.9-12 Compound identities were confirmed through elemental composition determination, isotope matching, and comparisons to reports in literature.23-24
Heat map renderings of the direct analysis in real time-high resolution mass spectrometry spectra of Kratom and Datura are illustrated in Figure 4. The data presented were used in principal component analysis (PCA) to differentiate between the two classes of plant-based drugs of abuse (Figure 5). The PCA plot was constructed using ten feature masses (listed in Table 3), with blue circles representing Kratom data and red squares representing Datura data. The feature masses selected corresponded to various alkaloids present in Datura or Mitragyna spp., including the psychoactive compounds atropine, scopolamine, mitragynine and 7-hydroxymitragynine.23-24 Three principal components accounted for 75.26% of the variance and leave-one-out cross validation (LOOCV) was 100%. The PCA plot clearly shows that the Kratom data and Datura data are well resolved from one another. PCA analysis also revealed that the individual varieties of Kratom and the different species of Datura could be identified and distinguished from one another (Figure 6). LOOCV was 94.29% with three principal components covering 75.26% of the variance. The two varieties of Kratom (Bali in blue circles and Rifat in red squares) cluster together, indicating that they belong to the species M. speciosa, but are resolved from one another, demonstrating that they represent different varieties. Furthermore, the Datura species group together and separated from the M. speciosa data, but each of the individual species of Datura (D. inoxia in green triangles, D. stramonium in pink squares and D. ferox in turquoise circles) are clearly differentiated. Despite a data point for D. stramonium appearing to be an outlier, the seed is correctly classified as D. stramonium and not D. inoxia using PCA. Most importantly, the difference in seed color between D. stramonium and D. inoxia confirms they are different species and that the data point in question cannot be D. inoxia.
Hierarchical clustering (Figure 7) was performed without the a priori selection of feature masses. Instead, the entire group of spectral data sets spanning a mass range of m/z 60-800 was imported into open source genomic clustering software and a dendrogram featuring this data was produced. The results of HCA also revealed class, species and variety differentiation solely based on direct analysis in real time-high resolution mass spectrometry derived data and confirmed those of the PCA analysis. The two classes of plant-based drugs of abuse, Kratom and Datura, were separated into individual clades of the dendrogram. Moreover, the Rifat and Bali varieties of Kratom were each isolated into individual sub-clades within the Kratom class. Similarly, D. inoxia, D. ferox and D. stramonium were resolved into their own clades by species within the Datura class.
<img alt="Figure 1" src="/files/ftp_upload/54197/54197fig1.jpg" /> 
Figure 1. Images of M. speciosa (Kratom) products and Datura spp. seeds. a: Bali Kratom dried leaf; b: Bali Kratom powder; c: Rifat Kratom live plant; d: D. stramonium seeds; e: D. inoxia seeds; f: D. ferox seeds. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54197/54197fig2.jpg" /> 
Figure 2. Direct analysis in real&#160;time-high&#160;resolution mass spectrometry positive-ion spectra of M. speciosa (Kratom) products. a: Rifat fresh leaf; b: Bali dried leaf; c: Bali powder; d: Bali powder extract. The mass measurement data associated with these spectra are shown in Table 1. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54197/54197fig3.jpg" /> 
Figure 3. Direct analysis in real&#160;time-high&#160;resolution&#160;mass spectrometry positive-ion spectra of Datura spp. seeds. a: D. ferox; b: D. inoxia; c: D. stramonium. The mass measurement data associated with these spectra are shown in Table 2. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54197/54197fig4.jpg" /> 
Figure 4. Heat map renderings of the direct analysis in real time-high resolution mass spectrometry spectra of Kratom and Datura plant materials. High intensity peaks are shown in dark red and lower intensity peaks are indicated in lighter shades. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54197/54197fig5.jpg" /> 
Figure 5. Principal component analysis (PCA) plot of Kratom and Datura products constructed using direct analysis in real time high resolution mass spectrometry-derived data. Three principal components (PCs) accounted for 75.26% of the variation, and the leave-one-out cross validation (LOOCV) was 100%. The feature masses used for the PCA are listed in Table 3. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/54197/54197fig6.jpg" /> 
Figure 6. Principal component analysis (PCA) plot of Kratom and Datura products using direct analysis in real time-high resolution mass spectrometry data. Class assignments were based on the variety (Kratom) or species (Datura) of the plant materials. Three principal components (PCs) accounted for 75.26% of the variation and the leave-one-out cross validation (LOOCV) was 94.29%. The feature masses used for PCA are listed in Table 3. <a href="https://www.jove.com/files/ftp_upload/54197/54197fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/54197/54197fig7.jpg" /> 
Figure 7. Hierarchical clustering results obtained using the direct analysis in real time-high resolution mass spectrometry-derived data from analysis of Kratom and Datura plant materials. The two classes of plants are clearly separated into two distinct branches in the dendrogram (shown in blue and red brackets for Kratom and Datura, respectively). The Datura seed species are also resolved from one another (shown in green, turquoise and pink dashed boxes for D. inoxia, D. ferox, and D. stramonium respectively). The Kratom plant materials are separated by variety (shown in red and blue dashed boxes for Rifat and Bali, respectively). <a href="https://www.jove.com/files/ftp_upload/54197/54197fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/54197/54197tbl1.jpg" /> 
Table 1. Mass measurement data associated with the soft ionization spectra of Kratom products presented in Figure 2. <a href="https://www.jove.com/files/ftp_upload/54197/54197tbl1large.jpg" target="_blank">Please click here to view a larger version of this table.</a>
<img alt="Table 2" src="/files/ftp_upload/54197/54197tbl2.jpg" /> 
Table 2. Mass measurement data associated with the soft ionization spectra of Datura seeds presented in Figure 3. <a href="https://www.jove.com/files/ftp_upload/54197/54197tbl2large.jpg" target="_blank">Please click here to view a larger version of this table.</a>
<img alt="Table 3" src="/files/ftp_upload/54197/54197tbl3.jpg" /> 
Table 3. Feature masses used for principal component analysis plot of Kratom and Datura products shown in Figures 5 and 6.

Watch this Scientific Journal Video about Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry at JoVE.com

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

A method for species identification of botanical material by direct analysis in real time-high resolution mass spectrometry and multivariate statistical analysis is presented.

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, ...

rapid-high-throughput-species-identification-botanical-material-using

Research

JoVE Journal

Chemistry

11.5K Views.  University at Albany-SUNY.  Een methode voor het soort identificatie van botanische materiaal door directe analyse in real time-hoge resolutie massaspectrometrie en multivariate statistische analyse wordt gepresenteerd. 

Video: Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. This article outlines a typical workflow utilized for non-targeted metabolite profiling of serum including sample organization and preparation, data acquisition, data analysis, quality control, and metabolite identification.

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to ...

Improved Polymerase Chain Reaction-restriction Fragment Length Polymorphism Genotyping of Toxic Pufferfish by Liquid Chromatography/Mass Spectrometry

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS) is described. DNA extraction is carried out using a silica membrane-based DNA extraction kit. After the PCR amplification using a detergent-free PCR buffer, restriction enzymes are added to the solution without purifying the reaction solution. A reverse-phase silica monolith column and a Fourier transform high resolution mass spectrometer having a modified Kingdon trap analyzer are employed for separation and detection, respectively. The mobile phase, consisting of 400 mM 1,1,1,3,3,3-hexafluoro-2-propanol, 15 mM triethylamine (pH 7.9) and methanol, is delivered at a flow rate of 0.4 ml/min. The cycle time for LC/ESI-MS analysis is 8 min including equilibration of the column. Deconvolution software having an isotope distribution model of the oligonucleotide is used to calculate the corresponding monoisotopic mass from the mass spectrum. For analysis of oligonucleotides (range 26-79 nucleotides), mass accuracy was 0.62 &#177; 0.74 ppm (n = 280) and excellent accuracy and precision were sustained for 180 hr without use of a lock mass standard.

An improved polymerase chain reaction-restriction fragment length polymorphism method for genotyping pufferfish species by liquid chromatography/mass spectrometry is described. A reverse-phase silica monolith column is employed for separating digested amplicons. This method can elucidate the monoisotopic masses of oligonucleotides, which is useful for identifying base composition.

An improved version of a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) method for genotyping toxic pufferfish species by ...

Genetics

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the use of non-renewable energy sources. In order to identify which plants, out of a diverse pool, have the desired chemical traits for downstream applications, attributes, such as cellulose and lignin content, or monomeric sugar release following an enzymatic saccharification, must be compared. The experimental and data analysis protocols of the standard methods of analysis can be time-consuming, thereby limiting the number of samples that can be measured. High-throughput (HTP) methods alleviate the shortcomings of the standard methods, and permit the rapid screening of available samples to isolate those possessing the desired traits. This study illustrates the HTP sugar release and pyrolysis-molecular beam mass spectrometry pipelines employed at the National Renewable Energy Lab. These pipelines have enabled the efficient assessment of thousands of plants while decreasing experimental time and costs through reductions in labor and consumables.

Plant cell wall structure and chemistry traits are evaluated to identify ideal feedstocks for biofuels and bio-materials. Standard methods have limitations when applied to large data sets. These high-throughput pretreatment, enzyme saccharification, and pyrolysis-molecular beam mass spectrometry methods compare large numbers of biomass samples with decreased experimental time and cost.

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the ...

Environment

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that belongs to the Direct-Injection Mass Spectrometric (DIMS) technologies. These techniques allow the rapid determination of volatile organic compounds (VOCs), assuring high sensitivity and accuracy. In general, PTR-MS requires neither sample preparation nor sample destruction, allowing real time and non-invasive analysis of samples. PTR-MS are exploited in many fields, from environmental and atmospheric chemistry to medical and biological sciences. More recently, we developed a methodology based on coupling PTR-ToF-MS with an automated sampler and tailored data analysis tools, to increase the degree of automation and, consequently, to enhance the potential of the technique. This approach allowed us to monitor bioprocesses (e.g. enzymatic oxidation, alcoholic fermentation), to screen large sample sets (e.g. different origins, entire germoplasms) and to analyze several experimental modes (e.g. different concentrations of a given ingredient, different intensities of a specific technological parameter) in terms of VOC content. Here, we report the experimental protocols exemplifying different possible applications of our methodology: i.e. the detection of VOCs released during lactic acid fermentation of yogurt (on-line bioprocess monitoring), the monitoring of VOCs associated with different apple cultivars (large-scale screening), and the in vivo study of retronasal VOC release during coffee drinking (nosespace analysis).

Proton Transfer Reaction Time of Flight Mass Spectrometry allows high-sensitivity, rapid and non-invasive analysis of volatile organic compounds. To demonstrate its potential, we give three examples: lactic acid fermentation of yogurt (on-line bioprocess monitoring), different apple genotypes (large-scale screening), and retronasal space after drinking coffee (nosespace analysis).

Proton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that ...

Leaf Spray Mass Spectrometry: A Rapid Ambient Ionization Technique to Directly Assess Metabolites from Plant Tissues

Plants produce thousands of small molecules that are diverse in their chemical properties. Mass spectrometry (MS) is a powerful technique for analyzing plant metabolites because it provides molecular weights with high sensitivity and specificity. Leaf spray MS is an ambient ionization technique where plant tissue is used for direct chemical analysis via electrospray, eliminating chromatography from the process. This approach to sampling metabolites allows for a wide range of chemical classes to be detected simultaneously from intact plant tissues, minimizing the amount of sample preparation needed. When used with a high-resolution, accurate mass MS, leaf spray MS facilitates the rapid detection of metabolites of interest. It is also possible to collect tandem mass fragmentation data with this technique to facilitate a compound identification. The combination of accurate mass measurements and fragmentation is beneficial in confirming compound identities. The leaf spray MS technique requires only minor modifications to a nanospray ionization source and is a useful tool to further expand the capabilities of a mass spectrometer. Here, fresh leaf tissue from Sceletium tortuosum (Aizoaceae), a traditional medicinal plant from South Africa, is analyzed; numerous mesembrine alkaloids are detected with leaf spray MS.

Leaf spray mass spectrometry is a direct chemical analysis technique that minimizes the sample preparation and eliminates chromatography, allowing for the rapid detection of small molecules from plant tissues.

Plants produce thousands of small molecules that are diverse in their chemical properties. Mass spectrometry (MS) is a powerful technique for analyzing ...

Biochemistry

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

Here, we present a protocol for the sequential targeted quantification and non-targeted analysis of fluorinated compounds in water by mass spectrometry. This methodology provides quantitative levels of known fluorochemical compounds and identifies unknown chemicals in related samples with semi-quantitative estimates of their abundance.

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the ...

Identifying Chemical Composition of Gynura bicolor by UPLC-TOF Mass Spectrometry

High-resolution Tandem Mass Spectrometry for Studying Chemical Constituents of Gynura bicolor DC

The separation and analysis of the desired chemical components are important subjects for the fundamental research of traditional Chinese medicine (TCM). Ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) has gradually become a leading technology for the identification of TCM ingredients. Gynura bicolor DC. (BFH), a perennial stemless herb used for medicine and food in China has medicinal effects such as clearing heat, moistening the lung, relieving cough, dispersing stasis, and relieving swelling. Polyphenols and flavonoids contain numerous isomers, which hinder the identification of the complex compounds in BFH. This paper presents a systematic protocol for studying chemical constituents of BFH based on solvent extraction and integrated data via UPLC-Q-TOF-MS.
The method described here includes systematic protocols for sample pretreatment, MS calibration, MS acquisition, data processing, and analysis of results. Sample pretreatment includes collection, cleaning, drying, crushing, and extraction. MS calibration consists of multipoint and single-point correction. Data processing includes data importing, method establishment, analysis processing, and result presentation. Representative results of the typical fragmentation pattern of phenolic acids, esters, and glycosides in Gynura bicolor DC. (BFH) are presented in this paper. In addition, organic solvent selection, extraction, data integration, collision energy selection, and method improvement are discussed in detail. This universal protocol can be widely used to identify complex compounds in TCM.

Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry

We describe a general protocol that integrates high-resolution mass spectrometry analysis and molecular docking in traditional Chinese medicine research.

The separation and analysis of the desired chemical components are important subjects for the fundamental research of traditional Chinese medicine (TCM). ...

Classification of Tropane Alkaloids from Plant Metabolites Using LC-MS/MS

Applications of Liquid-Chromatography Tandem Mass Spectrometry in Natural Products Research: Tropane Alkaloids as a Case Study

Although many drugs utilized today are synthetic in origin, natural products still provide a rich source of novel chemical diversity and bioactivity, and can yield promising leads for resistant or emerging diseases. The challenge, however, is twofold: not only must researchers find natural products and elucidate their structures, but they must also identify what is worth isolating and assaying (and what is already known - a process known as dereplication). With the advent of modern analytical instrumentation, the pace of natural product discovery and dereplication has accelerated. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become an especially valuable technique for identifying and classifying chemical structures. Tropane alkaloids (TAs) are plant-derived compounds of great medicinal and toxicological significance. In this study, we developed an LC-MS/MS-based screening workflow utilizing the multiple MS/MS configurations available on a triple-quadrupole (QQQ) mass spectrometer to annotate and classify TA structures based on their distinct fragmentation patterns. By using a combination of data-dependent (DD) product ion scans, precursor ion scans (PrIS), and neutral loss scans (NLS), we applied this method to TA-rich extracts of the nightshades Datura stramonium and Datura metel. This method is rapid, sensitive, and was successfully employed for both preliminary dereplication of complex TA-containing samples and for the discovery of a novel candidate for isolation, purification (and eventual bioassay).

Author Spotlight: Discovering New Alkaloids in Plants with Advanced Mass Spectrometry Techniques

We present a method for rapid mass spectrometry (MS)/mass spectrometry (MS)-based annotation and classification of tropane alkaloids, useful for both preliminary dereplication of tropane-containing samples and discovery of novel alkaloids for isolation.

Although many drugs utilized today are synthetic in origin, natural products still provide a rich source of novel chemical diversity and bioactivity, and ...

Field Identification of Matricaria chamomilla using a Portable qPCR System

Quality control in botanical products begins with the raw material supply. Traditionally, botanical identification is performed through morphological assessment and chemical analytical methods. However, the lack of availability of botanists, especially in recent years, coupled with the need to enhance quality control to combat the stresses on the supply chain brought by increasing consumer demand and climate change, necessitates alternative approaches. The goal of this protocol is to facilitate botanical species identification using a portable qPCR system on the field or in any setting, where access to laboratory equipment and expertise is limited. Target DNA is amplified using dye-based qPCR, with DNA extracted from botanical reference materials serving as a positive control. The target DNA is identified by its specific amplification and matching its melting peak against the positive control. A detailed description of the steps and parameters, from hands-on field sample collection, to DNA extraction, PCR amplification, followed by data interpretation, has been included to ensure that readers can replicate this protocol. The results produced align with traditional laboratory botanical identification methods. The protocol is easy to perform and cost-effective, enabling quality testing on raw materials as close to the point of origin of the supply chain as possible.

Field Identification of Matricaria chamomilla using a Portable qPCR System

Presented here is a protocol for field identification of Matricaria chamomilla using a portable qPCR system. This easy-to-perform protocol is ideal as a method to confirm the identity of a botanical species at locations where access to laboratory equipment and expertise is limited, such as farms and warehouses.

Quality control in botanical products begins with the raw material supply. Traditionally, botanical identification is performed through morphological ...

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

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