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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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 border="0" cellpadding="0" cellspacing="0" width="879">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:324px;">AccuTOF Mass Spectrometer</td>
			<td style="width:273px;">JEOL USA, Inc.</td>
			<td style="width:135px;"></td>
			<td style="width:147px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DART-SVP Ion Source</td>
			<td>IonSense, Inc.</td>
			<td>DART-SVP</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Linear Rail System</td>
			<td>IonSense, Inc.</td>
			<td>HW-10029</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Hole puncher (6 mm)</td>
			<td>Swingline</td>
			<td>A7074005</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">One-Pint Compact Ultrasonic Cleaner</td>
			<td>Cole-Palmer</td>
			<td>EQ-08849-00</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1.5 mL Eppendorf Microcentrifuge tubes</td>
			<td>Fisher Scientific</td>
			<td>02-682-550</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">AccuSpin Micro 17R Centrifuge</td>
			<td>Fisher Scientific</td>
			<td>13-100676</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">#9 Stainless Steel Razor blade</td>
			<td>Stanley</td>
			<td>11-515</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dip-it Tip Holder</td>
			<td>IonSense, Inc.</td>
			<td>SCT-70003</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dip-it Tips</td>
			<td>IonSense, Inc.</td>
			<td>DPT-110</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Melting Point Capillary</td>
			<td>Krackeler Scientific</td>
			<td>1-9530-3</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Polyethylene glycol (600)</td>
			<td>Sigma Aldrich</td>
			<td>81180</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Rifat Kratom Live Plant</td>
			<td>World Seed Supply Kratom Collection</td>
			<td>LIVEKRATOMPLANT</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Bali Kratom Dried Leaf</td>
			<td>The Kratom King</td>
			<td>OZKRAPCOM</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Bali Kratom Powder</td>
			<td>The Kratom King</td>
			<td>OZKRAPCOMPOW</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Datura stramonium seeds</td>
			<td>Horizon Herbs LLC</td>
			<td>PDATUJ</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Datura inoxia seeds</td>
			<td>Horizon Herbs LLC</td>
			<td>PDATUM</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Datura ferox seeds</td>
			<td>Georgia Vines</td>
			<td>255/737</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ethanol, anhydrous</td>
			<td>Krackeler Scientific</td>
			<td>1328-E402-4L</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Mass Mountaineer Spectral Analysis Software</td>
			<td>mass-spec-software.com</td>
			<td>MM-20030-PCA-DVD</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TSSPro3 Data Processing/Data Reduction Software</td>
			<td>Shrader Labs</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Cluster 3.0</td>
			<td colspan="2">http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm</td>
			<td>Open Source Software</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">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

Nanyang Technological University

Research

JoVE Journal

Chemistry

11.5K Views.  University at Albany-SUNY. A method for species identification of botanical material by direct analysis in real time-high resolution mass spectrometry and multivariate statistical analysis is presented.

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

Rapid High Throughput Amylose Determination in Freeze Dried Potato Tuber Samples

This protocol describes a high through put colorimetric method that relies on the formation of a complex between iodine and chains of glucose molecules in starch. Iodine forms complexes with both amylose and long chains within amylopectin. After the addition of iodine to a starch sample, the maximum absorption of amylose and amylopectin occurs at 620 and 550 nm, respectively. The amylose/amylopectin ratio can be estimated from the ratio of the 620 and 550 nm absorbance values and comparing them to a standard curve in which specific known concentrations are plotted against absorption values. This high throughput, inexpensive method is reliable and reproducible, allowing the evaluation of large populations of potato clones.&#160;

This protocol describes a high through put colorimetric method that relies on the formation of a complex between iodine and chains of glucose molecules in ...

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted metabolomics provides a hypothesis generating snapshot of a metabolic profile. This protocol will demonstrate the extraction and analysis of metabolites from cells, serum, or tissue. A range of metabolites are surveyed using liquid-liquid phase extraction, microflow ultraperformance liquid chromatography/high-resolution mass spectrometry (UPLC-HRMS) coupled to differential analysis software.

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first ...

A High-throughput-compatible FRET-based Platform for Identification and Characterization of Botulinum Neurotoxin Light Chain Modulators

Botulinum neurotoxin (BoNT) is a potent and potentially lethal bacterial toxin that binds to host motor neurons, is internalized into the cell, and cleaves intracellular proteins that are essential for neurotransmitter release. BoNT is comprised of a heavy chain (HC), which mediates host cell binding and internalization, and a light chain (LC), which cleaves intracellular host proteins essential for acetylcholine release. While therapies that inhibit toxin binding/internalization have a small time window of administration, compounds that target intracellular LC activity have a much larger time window of administrations, particularly relevant given the extremely long half-life of the toxin. In recent years, small molecules have been heavily analyzed as potential LC inhibitors based on their increased cellular permeability relative to larger therapeutics (peptides, aptamers, etc.). Lead identification often involves high-throughput screening (HTS), where large libraries of small molecules are screened based on their ability to modulate therapeutic target function. Here we describe a FRET-based assay with a commercial BoNT/A LC substrate and recombinant LC that can be automated for HTS of potential BoNT inhibitors. Moreover, we describe a manual technique that can be used for follow-up secondary screening, or for comparing the potency of several candidate compounds.

The botulinum neurotoxin type A light chain (BoNT/A LC) is a metalloprotease that enters motor neurons, cleaves its substrate SNAP-25, and disrupts neurotransmission, thereby resulting in flaccid paralysis. Utilizing a high-throughput-compatible FRET-based assay, large libraries of small molecules can be screened for their impact on BoNT/A LC enzymatic activity.

Botulinum neurotoxin (BoNT) is a potent and potentially lethal bacterial toxin that binds to host motor neurons, is internalized into the cell, and ...

Sequencing of Plant Wall Heteroxylans Using Enzymic, Chemical (Methylation) and Physical (Mass Spectrometry, Nuclear Magnetic Resonance) Techniques

This protocol describes the specific techniques used for the characterization of reducing end (RE) and internal region glycosyl sequence(s) of heteroxylans. De-starched wheat endosperm cell walls were isolated as an alcohol-insoluble residue (AIR)1 and sequentially extracted with water (W-sol Fr) and 1 M KOH containing 1% NaBH4 (KOH-sol Fr) as described by Ratnayake et al. (2014)2. Two different approaches (see summary in Figure 1) are adopted. In the first, intact W-sol AXs are treated with 2AB to tag the original RE backbone chain sugar residue and then treated with an endoxylanase to generate a mixture of 2AB-labelled RE and internal region reducing oligosaccharides, respectively. In a second approach, the KOH-sol Fr is hydrolyzed with endoxylanase to first generate a mixture of oligosaccharides which are subsequently labelled with 2AB. The enzymically released ((un)tagged) oligosaccharides from both W- and KOH-sol Frs are then methylated and the detailed structural analysis of both the native and methylated oligosaccharides is performed using a combination of MALDI-TOF-MS, RP-HPLC-ESI-QTOF-MS and ESI-MSn. Endoxylanase digested KOH-sol AXs are also characterized by nuclear magnetic resonance (NMR) that also provides information on the anomeric configuration. These techniques can be applied to other classes of polysaccharides using the appropriate endo-hydrolases.

Sequencing of Plant Wall Heteroxylans Using Enzymic, Chemical Methylation and Physical Mass Spectrometry, Nuclear Magnetic Resonance Techniques

This protocol describes the specific techniques used for the structural characterization of reducing end (RE) and internal region glycosyl sequence(s) of heteroxylans by tagging the RE with 2 aminobenzamide prior to enzymatic (endoxylanase) hydrolysis and then analysis of the resultant oligosaccharides using mass spectrometry (MS) and nuclear magnetic resonance (NMR).

This protocol describes the specific techniques used for the characterization of reducing end (RE) and internal region glycosyl sequence(s) of ...

Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry

Exhaled volatile organic compounds (VOCs) have aroused considerable interest, since they can serve as biomarkers for disease diagnosis and environmental exposure in a non-invasive manner. In this work, we present a protocol to characterize the exhaled VOCs in real time by using secondary nanoelectrospray ionization coupled to high resolution mass spectrometry (Sec-nanoESI-HRMS). The homemade Sec-nanoESI source was readily set up based on a commercial nanoESI source. Hundreds of peaks were observed in the background-subtracted mass spectra of exhaled breath, and the mass accuracy values are -4.0-13.5 ppm and -20.3-1.3 ppm in the positive and negative ion detection modes, respectively. The peaks were assigned with accurate elemental composition according to the accurate mass and isotopic pattern. Less than 30 s is used for one exhalation measurement, and it takes approximately 7 min for six replicated measurements.

A protocol for characterizing chemical composition of exhaled breath in real time by using secondary nanoelectrospray ionization coupled to high resolution mass spectrometry is demonstrated.

Exhaled volatile organic compounds (VOCs) have aroused considerable interest, since they can serve as biomarkers for disease diagnosis and environmental ...

Synthesis and Mass Spectrometry Analysis of Oligo-peptoids

Peptoids are sequence-controlled peptide-mimicking oligomers consisting of N-alkylated glycine units. Among many potential applications, peptoids have been thought of as a type of molecular information storage. Mass spectrometry analysis has been considered the method of choice for sequencing peptoids. Peptoids can be synthesized via solid phase chemistry using a repeating two-step reaction cycle. Here we present a method to manually synthesize oligo-peptoids and to analyze the sequence of the peptoids using tandem mass spectrometry (MS/MS) techniques. The sample peptoid is a nonamer consisting of alternating N-(2-methyloxyethyl)glycine (Nme) and N-(2-phenylethyl)glycine (Npe), as well as an N-(2-aminoethyl)glycine (Nae) at the N-terminus. The sequence formula of the peptoid is Ac-Nae-(Npe-Nme)4-NH2, where Ac is the acetyl group. The synthesis takes place in a commercially available solid-phase reaction vessel. The rink amide resin is used as the solid support to yield the peptoid with an amide group at the C-terminus. The resulting peptoid product is subjected to sequence analysis using a triple-quadrupole mass spectrometer coupled to an electrospray ionization source. The MS/MS measurement produces a spectrum of fragment ions resulting from the dissociation of charged peptoid. The fragment ions are sorted out based on the values of their mass-to-charge ratio (m/z). The m/z values of the fragment ions are compared against the nominal masses of theoretically predicted fragment ions, according to the scheme of peptoid fragmentation. The analysis generates a fragmentation pattern of the charged peptoid. The fragmentation pattern is correlated to the monomer sequence of the neutral peptoid. In this regard, MS analysis reads out the sequence information of the peptoids.

A protocol is described for the manual synthesis of oligo-peptoids followed by sequence analysis by mass spectrometry.

Peptoids are sequence-controlled peptide-mimicking oligomers consisting of N-alkylated glycine units. Among many potential applications, peptoids have ...

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

New analytical methods are urgently needed to enable high-throughput, yet comprehensive drug screening, given an alarming opioid and prescription drug crisis in public health. Conventional urine drug testing based on a two-tier immunoassay screen followed by a gas chromatography-tandem mass spectrometry (GC-MS/MS) or liquid chromatography-tandem mass spectrometry (LC-MS/MS) method are expensive and prone to bias while being limited to targeted panels of known drugs of abuse (DoA). Herein, we outline an improved method for drug surveillance that allows for the resolution and detection of an expanded panel of DoA and their metabolites when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Multiplexed separations of ten urine samples with a quality control by CE (&lt; 3 min/sample) in conjunction with full-scan data acquisition using a time-of-flight mass spectrometer (TOF-MS) under positive ion mode detection allows for the identification and quantification of DoA above recommended cut-off levels. An excellent resolution of drug isomers and isobars, including background interferences, are achieved when using MSI-CE-MS with an electrokinetic spacer between sample segments, where accurate mass/molecular formula together with the comigration of a matching deuterated internal standard and the detection of one or more bio-transformed metabolites facilitate DoA identification over a wider detection window. Additionally, urine samples can be analyzed directly without enzyme deconjugation for the rapid screening without complicated sample workup. MSI-CE-MS enables the surveillance of a broad spectrum of DoA that is required for the treatment monitoring of high-risk patients, including confirming prescribed drug adherence, revealing illicit drug use/substitution, and evaluating optimal dosage regimes as required for new advances in precision medicine.

Here we describe a high-throughput method for comprehensive drug surveillance that allows for the improved resolution and detection of large panels of drugs of abuse and their metabolites, with quality control based on multisegment injection-capillary electrophoresis-mass spectrometry.

New analytical methods are urgently needed to enable high-throughput, yet comprehensive drug screening, given an alarming opioid and prescription drug ...

Imaging Corrosion at the Metal-Paint Interface Using Time-of-Flight Secondary Ion Mass Spectrometry

Corrosion developed at the paint and aluminum (Al) metal-paint interface of an aluminum alloy is analyzed using time-of-flight secondary ion mass spectrometry (ToF-SIMS), illustrating that SIMS is a suitable technique to study the chemical distribution at a metal-paint interface. The painted Al alloy coupons are immersed in a salt solution or exposed to air only. SIMS provides chemical mapping and 2D molecular imaging of the interface, allowing direct visualization of the morphology of the corrosion products formed at the metal-paint interface and mapping of the chemical after corrosion occurs. The experimental procedure of this method is presented to provide technical details to facilitate similar research and highlight pitfalls that may be encountered during such experiments.

Time-of-flight secondary ion mass spectrometry is applied to demonstrate the chemical mapping and corrosion morphology at the metal-paint interface of an aluminum alloy after being exposed to a salt solution compared with a specimen exposed to air.

Corrosion developed at the paint and aluminum (Al) metal-paint interface of an aluminum alloy is analyzed using time-of-flight secondary ion mass ...

Dose Uptake of Platinum- and Ruthenium-based Compound Exposure in Zebrafish by Inductively Coupled Plasma Mass Spectrometry with Broader Applications

Metals and metal-based compounds comprise multifarious pharmaco-active and toxicological xenobiotics. From heavy metal toxicity to chemotherapeutics, the toxicokinetics of these compounds have both historical and modern-day relevance. Zebrafish have become an attractive model organism in elucidating pharmaco- and toxicokinetics in environmental exposure and clinical translation studies. Although zebrafish studies have the benefit of being higher-throughput than rodent models, there are several significant constraints to the model.
One such limitation is inherent in the waterborne dosing regimen. Water concentrations from these studies cannot be extrapolated to provide reliable internal dosages. Direct measurements of the metal-based compounds allow for a better correlation with compound-related molecular and biological responses. To overcome this limitation for metals and metal-based compounds, a technique was developed to digest zebrafish larval tissue after exposure and quantify metal concentrations within tissue samples by inductively coupled plasma mass spectrometry (ICPMS).
ICPMS methods were used to determine the metal concentrations of platinum (Pt) from cisplatin and ruthenium (Ru) from several novel Ru-based chemotherapeutics in zebrafish tissue. Additionally, this protocol distinguished concentrations of Pt that were sequestered in the chorion of the larval compared with the zebrafish tissue. These results indicate that this method can be applied to quantitate the metal dose present in larval tissues. Further, this method may be adjusted to identify specific metals or metal-based compounds in a broad range of exposure and dosing studies.

The increased rate of pharmaco- and toxicokinetic analyses of metals and metal-based compounds in zebrafish can be advantageous for environmental and clinical translation studies. The limitation of unknown waterborne exposure uptake was overcome by conducting trace metal analysis on digested zebrafish tissue using inductively coupled plasma mass spectrometry.

Metals and metal-based compounds comprise multifarious pharmaco-active and toxicological xenobiotics. From heavy metal toxicity to chemotherapeutics, the ...

Characterizing RNA Modifications in Single Neurons Using Mass Spectrometry

Post-transcriptional modifications (PTMs) of RNA represent an understudied mechanism involved in the regulation of translation in the central nervous system (CNS). Recent evidence has linked specific neuronal RNA modifications to learning and memory paradigms. Unfortunately, conventional methods for the detection of these epitranscriptomic features are only capable of characterizing highly abundant RNA modifications in bulk tissues, precluding the assessment of unique PTM profiles that may exist for individual neurons within the activated behavioral circuits. In this protocol, an approach is described&#8212;single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS)&#8212;to simultaneously detect and quantify numerous modified ribonucleosides in single neurons. The approach is validated using individual neurons of the marine mollusk, Aplysia californica, beginning with surgical isolation and enzymatic treatment of major CNS ganglia to expose neuron cell bodies, followed by manual single-neuron isolation using sharp needles and a micropipette. Next, mechanical and thermal treatment of the sample in a small volume of buffer is done to liberate RNA from an individual cell for subsequent RNA digestion. Modified nucleosides are then identified and quantified using an optimized liquid chromatography-mass spectrometry method. SNRMA-MS is employed to establish RNA modification patterns for single, identified neurons from A. californica that have known morphologies and functions. Examples of qualitative and quantitative SNRMA-MS are presented that highlight the heterogeneous distribution of RNA modifications across individual neurons in neuronal networks.

Post-transcriptional modifications of RNA represent an understudied layer of translation regulation that has recently been linked to central nervous system plasticity. Here, sample preparation and liquid chromatography-tandem mass spectrometry approach is described for simultaneous characterization of numerous RNA modifications in single neurons.

Post-transcriptional modifications (PTMs) of RNA represent an understudied mechanism involved in the regulation of translation in the central nervous ...