作者非常感谢一个大学奥尔巴尼分校，纽约州立大学的总统倡议基金研究和法医学和网络安全拨款，美国国家科学基金会的资助（资助＃1310350）和国家司法研究所的资助（资助＃2015-DN-BX-奖学金K057）到RAM。我们也承认贾斯汀E.吉芬采取植物材料的照片。

1.植物材料的制备<ol><li> Kratom鲜叶原料 <ol><li>使用6毫米直径的打孔器创建M. Kratom叶材料的均匀纸屑桐厂。重复5次。 </li></ol></li><li> Kratom粉提取 <ol><li>混合5ml乙醇和5ml蒸馏水创造1:萃取1溶剂混合物。 </li><li>在1.5ml微量离心管中，暂停少量在1ml的1 Kratom巴厘岛粉末（〜5毫克）:1乙醇:H 2 O溶剂混合物。重复5次。 </li><li>超声处理的Kratom巴厘岛粉末提取物样品在超声浴中在环境温度下30分钟。 </li><li>离心Kratom巴厘岛粉提取物样品2分钟，在室温下750 XG。 </li><li>从倒出为后续分析残粉溶剂。 </li></ol></li><li> 曼陀罗种子准备 <ol><li>一个切片D. STRAM在半鎓种子横跨横向平面用刀片。重复使用5个不同的种子。 </li><li>重复D. inoxia和D.芡种子。 </li></ol></li></ol> 2.直接分析实时离子源参数<ol><li> 燃气取暖器温度 <ol><li>设置离子源至350℃的气体加热器的温度。 </li></ol></li><li> 离子模式 <ol><li>进行正离子模式分析与250伏的栅极电压</li></ol></li><li> 氦气流量 <ol><li>设置氦的气体流速为2.0升/秒。 </li></ol></li></ol> 3.时间飞行质谱仪参数<ol><li> 孔板电压 <ol><li>设置孔1电压到20V和孔口2电压到5 V. </li></ol></li><li> 环镜头和峰值电压 <ol><li>调整环镜头电压5V和峰值电压改变为600V。 </li></ol></li><li> 质谱采集 <ol><li>设置质谱采集速率为每秒1光谱的经M / Z 60-800的质量数范围。 </li></ol></li><li> 质谱仪分辨能力 <ol><li>设置的质谱仪的分辨能力，以6000 FWHM。 </li></ol></li></ol> 4.植物材料的分析<ol><li> Kratom叶分析 <ol><li>按"开始→运行"，在质谱仪控制软件。暂停与镊子离子源和质谱仪的入口（从入口约2厘米）之间的植物材料的碎屑直到获得光谱。与植物材料分离纸屑重复5次。 </li><li>校准用聚乙二醇600（PEG）的频谱。 <ol><li>浸熔点毛细管的封闭端进入的PEG标准。暂停涂层毛细管betwEEN离子源和质谱仪的入口。 </li></ol></li><li>分析PEG标准后，选择"停止"按钮，结束分析运行。 </li><li>按"开始→运行"，在质谱仪控制软件。暂停离子源和质谱仪的入口之间的干叶材料的少量用镊子直至获得光谱。重复5次，每次分析新的植物材料。 </li><li>校准与PEG的频谱。 <ol><li>蘸毛细管导入PEG标准的封闭端。暂停离子源和质谱仪的入口之间的涂覆的毛细管中。 </li></ol></li><li>分析PEG标准后，选择"停止"按钮，结束分析运行。 </li></ol></li><li> Kratom粉末分析 <ol><li>按"开始→运行"，在质谱仪控制软件。浸熔点毛细管导入Kratom粉末的封闭端。 </li><li> Suspend被获得的离子源和质谱仪的入口，直到光谱之间的涂覆的毛细管中。用一个新的毛细管每次重复分析的5倍。 </li><li>校准与PEG的频谱。 <ol><li>蘸毛细管导入PEG标准的封闭端。暂停离子源和质谱仪的入口之间的涂覆的毛细管中。 </li></ol></li><li>分析PEG标准后，选择"停止"按钮，结束分析运行。 </li></ol></li><li> Kratom提取物的分析 <ol><li>浸入毛细管进入提取的封闭端。 </li><li>暂停在附着到质谱仪的直线导轨12的样品保持器的毛细管。每次重复5次用不同的提取物。 </li><li>按"开始→运行"，在质谱仪控制软件。使用控制面板，选择"&gt;"按钮，在1毫米/秒的速度通过离子流来推进直线导轨收集光谱。 </li><li>校准与PEG的频谱。 <ol><li>蘸毛细管导入PEG标准的封闭端。暂停离子源和质谱仪的入口之间的涂覆的毛细管中。 </li></ol></li><li>分析PEG标准后，选择"停止"按钮，结束分析运行。 </li></ol></li><li> 曼陀罗种子分析 <ol><li>按"开始→运行"，在质谱仪控制软件。直到频谱被收集暂停离子源和质谱仪的入口之间的曼陀罗种子半用镊子。确保该切口侧被定向成面对所述离子源。重复5次，每次半时间分析新的种子。 </li><li>校准与PEG的频谱。 <ol><li>蘸毛细管导入PEG标准的封闭端。暂停离子源和质谱仪的入口之间的涂覆的毛细管中。 </li></ol></li><li>分析PEG标准后，选择"停止"按钮，结束分析运行。 </li><li>重复步骤4.4.1-4.4.3每个曼陀罗物种。 </li></ol></li></ol> 5.数据处理<ol><li> 翻译数据文件 <ol><li>在数据处理软件中，选择文件，"翻译DART文件"和"自动校准"打开，创建校准数据文件。 </li><li>左键单击并拖动色谱周围的框的第一个高峰，然后选择"平均值"来创建一个平均光谱。 </li><li>右键单击并拖动那里收集样品没有一个地区一个框，然后选择"平均值整个箱体为背景"，从平均光谱减去背景。 </li><li>保存质谱为.txt文件。 </li><li>重复步骤5.1.1-5.1.4为色谱图中每个峰的每个文件中的复制来创建平均光谱。 </li><li>重复步骤5.1.2-5.1.5所收集的每个文件。 </li></OL&gt; </li></ol> 6.统计分析<ol><li> 主成分分析 <ol><li>在频谱分析软件的分类段（参见材料清单），在"设置"选项卡下，选择"添加类"创建用于数据处理的类。 </li><li>选择"添加文件（S）"导入数据的文本文件。 </li><li>通过选择文本文件指定的数据文件到相应的类厂和"设置班选定的文件"。 </li><li>选择功能群众从MS从训练集歧视和设置的阈％至1％。 </li><li>设置质量偏差（MMU）10，选择"建立从数据文件的载体。" </li><li>在"计算"一节中，通过检查3D图形PCA框进行主成分分析，并选择"计算"。 </li><li>通过选择执行留一交叉验证"验证（慢！）。" </li></ol></li><li><strong&gt;的生成热图<ol><li>在频谱分析软件的频率图选项卡，选择生成数据的热图"热图"。 </li><li>选择"门槛保存的数据"，以丰富的阈值设置为1％。 </li><li>通过选择导出的热量地图到电子表格中"保存热图到Excel。" </li><li>在电子表格程序，保存导出的热量地图为.txt文件。 </li></ol></li><li> 分层聚类分析 <ol><li>导入热图为.txt文件到Cluster 3.0软件。 </li><li>在群集3.0的分级选项卡，在基因和阵列，复选框"集群"和"计算权重"。 0.1截止设置和指数为1。选择单机联动聚类进行分析。 </li><li>查看Java的树状视图生成.cdt数据文件。 </li></ol></li></ol>

<ol>
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The authors have no disclosures.

识别滥用植物药物的能力是越来越多的必要性，由于在营销，销售急剧上升和消费不定期精神活性物质。2植物药材鉴定传统方法通常涉及再加上分析物理特性表征由复姓色谱 - 质谱方法的化学成分。但是，这两种方法来简化分析当前面临的挑战。当将植物干燥，粉碎或在制造过程中提取的，因此，它往往很难仅根据物理特性区分不同类型的基于植物的精神产物的植物的物理特性往往被破坏。23分析由色谱 - 质谱方法可以使植物基质的精神化合物鉴定，但样品制备和方法开发的时间ND资源密集，并且为每个类或虐待的植物为基础的药物品种新协议是建立在许多法医化学实验室不切实际的。 实时高分辨率质谱直接分析规避一些挑战，因为复杂的基质如叶，粉末，提取物和种子可以用小的样品制备进行分析。尽管在此采样的材料的复杂的基质中，精神成分为易于识别，即使在纳克浓度，21由于质谱仪的高灵敏度。种子，叶和粉末被证明通过实时高分辨率质谱直接分析可以容易地进行分析，以及各种其它类型的材料也可以以同样的方式采样，包括TLC板，货币，片剂，花，固相微萃取（SPME）纤维，甚至昆虫puparial肠衣21-22通过精确质量ANA裂解，元素组成测定和同位素匹配，生物标记物和感兴趣的化合物可以被识别，而不管是否包含在叶的化合物中，点样在TLC板或涂覆在毛细管。 实时高分辨率质谱法直接分析可用于简化分析，因为有其需要从实验改性实验很少的参数。分析可以在正离子或负离子模式下进行，并且可以在这两种情况下被检测到3000 amu的分子。电离在正离子模式由从活化水簇，21质子转移和与质子亲和力比水将被电离更高任何化合物发生。在此，使用因生物碱的高的质子亲和力，这使得它们通过质子化容易地离子化的正离子模式。分析在负离子模式可以用于成功检测HYDROCARB的项（如O 2加合物）21，爆炸材料27和由于质子转移的电离方法和无法产生多电荷的离子，在实时高分辨率质谱直接分析有机酸如青蒿琥酯在疟疾的药物。28法主要限于高达3000阿拉伯马格里布联盟的小分子的分析。 除了电离模式中，离子源的温度是重要的参数和相应的温度在很大程度上取决于被分析的样品。例如，使用较低的温度（〜250℃）进行固相微萃取纤维分析，以防止涂层材料的破坏的纤维，而较高的温度（〜500℃）应当用于氨基酸分析为解吸是很重要的，并随后电离。这里，植物材料的分析在350℃下进行的，因为这允许对生物碱和其它感兴趣的化合物的电离出在植物基质引起化合物的热分解。 实时高分辨率质谱分析直接分析不仅能够基于精确质量，元素组成测定和同位素匹配的植物材料的精神成分的鉴别，但它也产生了可为物种鉴定使用被利用独特的化学指纹多元统计分析具有高度可重复性的结果，即使是更小的数据集。多元统计分析已被应用到实时高分辨率质谱数据各种各样直接分析的，包括从木材，puparial肠衣，种子，叶材料，和生物柴油fuelstocks衍生，展示了该方法的通用性和可重复性。 22-26实时高分辨率质谱直接分析的高通量功能可获取大量质量SPECTR的在很短的时间内人数据，以及大量需要进行统计分析重复的很容易用这种方法获得的。在曼陀罗和Kratom的实时高分辨率质谱质谱数据集的直接分析包括收集与小于总时间投资的一个小时以上100个单独的光谱。以获得相同的编号使用GC-MS以30分钟的烘箱温度程序将需要大约50个小时的光谱，没有考虑对于样品制备步骤如萃取或衍生的附加时间。 主成分分析可以用于突出显示基于所选特征群众的存在和强度套植物物质之间的变化。统计分析处理提供品种鉴定，以及品种信息。统计分析的其它方法，如分级聚类分析（HCA），也可以是应用无功能群众的先验选择。综合化学指纹图谱HCA的结果表明，可以成功地应用于用于虐待的植物为基础的药物种类鉴定无监督的统计分析。25 通过实时高分辨率质谱直接分析法医学植物材料的种类判别，使用精神的化合物和在软电离质谱其他生物标志物的鉴定，和多元统计分析的应用证明。两种类型的统计分析中的应用表明不仅该类滥用的基于植物的药物的可被识别，而且该品种和所述能够根据通过直接分析中观察到的独特的化学指纹来确定药物种类实时高分辨率质谱。这里介绍的方法使英里的快速，高通量鉴定ND-改变物质在规避传统的分析方法所遇到的挑战，并提供了法医实验室与表征和精神鉴定植物材料不受时间和资源密集型的方法发展的手段的方式。该协议可以扩展到多种其他植物衍生的材料的物种分化22-26

几千年来，精神自然产品已在萨满教的仪式中，滥用他们的心态改变属性，消耗他们的药性。这些植物以及相关的植物为基础的物质的摄入可以在他们流行地区显著，他们有社会和经济的重要性。然而，最近出现了使用这些"天然"药物急剧上升，由于通过互联网电子商务的方便可及性。人们认为这些物质是安全的使用，再加上拥有和使用的滥用和人工合成物质的更传统的药物增加的打击，不得不在植物药物滥用秒杀作出了贡献。其通常难以通过可视化这些产品和无害的植物材料来区分，因此有在显影，可用于识别这些产品的方法的兴趣。然而，对于植物常规分析方法物种鉴定耗时，且不能执行。此外，该方法的开发过程是时间和资源密集型。这些因素使立法来遏制这些物质的使用远远落后升级其滥用率各具特色。因此，存在调节许多这些天然psychoactives的生产，制造，销售和消费，因此，有数百数千不同的形式提供给用户滥用的植物数的法律。1,2- 滥用的两个这样的基于植物的药物是帽柱木桐，俗称Kratom，并从曼陀罗属，即D.植物曼陀罗，D芡和D. inoxia。Kratom和曼陀罗是在美国计划外，但缉毒局列出了既作为关注的药品。3,4 Kratom为特征的精神化合物存在一个帽柱木碱第二7- hydroxymitragynine，以及其他非精神生物碱包括mitraphylline，paynantheine，corynoxeine和钩藤4-8 曼陀罗属的精神性质。归因于阿托品和东莨菪碱，但其他各种莨菪烷类生物碱的植物已经确定的9-12双方Kratom和曼陀罗有牵连中毒和死亡，而他们的身份是在这两个法医和毒理学环境越来越有必要，因为这些产品的滥用正在上升13-16 通过与用于法医药物物质的分析大，传统的方法，如色测试，显微镜和拉曼和红外光谱，在一个规则中/规则出假定容量使用。联用技术如GC-MS和液相色谱 - 质谱（LC-MS）是根据检测到的分析物的轮廓比较确证分析方法17科学工作组缉获的毒品分析（SWGDRUG）库的标准。这在分析前进行的样品处理步骤，包括粉碎，提取，衍生化和蒸发，可以加个小时的运行时间和掺假样品，9,11 ，植物药小于直截了当相比，滥用可卡因一样海洛因或其他毒品的传统制作18,19分析。此外，个别色谱程序需要为每个感兴趣的产品，这使得每个物种或滥用各种例行个案极不现实的植物类药物的标准作业协议的实施进行开发。 实时高分辨率质谱直接分析是一种环境电离质谱技术，避开了与常规的分析方法有关的挑战。气体，液体，固体，粉末，TLC板和植物脑膜胶质都可以实时高分辨率质谱使用直接分析直接分析，并且可以在复杂基质容易地检测极性和非极性化合物20-22此外，研究显示，精神化合物可以被快速识别通过实时高分辨率质谱直接分析，和特定种类信息的植物材料可以从质谱数据的统计处理来收集。22-26 这里，我们表明，在实时高分辨率质谱直接分析可以用来快速地评估各种植物材料（ 即，植物，粉末，提取物和种子），用于其精神的组件，且该植物-的物种和品种衍生产品可以以快速和高通量的方式来确定。法医相关植物药材，而不需要进行样品制备步骤或长色谱分析分析运行时间，除了植物物种鉴定报告。

<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

我们表明，在实时高分辨率质谱直接分析可以用于生产植物材料的质谱型材，并且这些化学指纹可用于植物物种鉴定。质谱数据可以迅速且以高通量的方式，而不需要样品提取，衍生化或pH调整步骤来获取。使用这种技术的旁路通过多种常规的技术，包括冗长色谱分析时间和资源密集的方法提出了挑战。实时高分辨率质谱协议直接分析的高吞吐量能力，再加上数据的多元统计分析处理，提供植物不仅类表征，而且还产生物种和品种的信息。在这里，技术表现出两个精神植物产品， 帽柱木桐 （Kratom）和曼陀罗（曼陀罗），这是在实时高分辨率质谱后跟质谱数据的统计分析处理进行直接分析。的串联这些工具的应用使植物材料在品种和种类的水平迅速识别。

在Kratom产品和曼陀罗种子实时高分辨率质谱数据代表软电离正离子模式直接分析示于图2和3。各种化合物先前从隔离M.桐 ，包括帽柱木碱（C 23 H 30 N 2 O 4 + H +，M / Z 399.2284）和7-hydroxymitragynine（C 23 H 30 N 2 O 5 + H +， 男ž415.2233 /），是在所有四个检测样品和相应的质量的测量数据在表1中。4-8代表曼陀罗数据示于图3和签名的生物标志物包括阿托品（C 17 H 23 NO 3 + H +，M / Z 290.1756）和东莨菪碱（C 17 H 21 NO 4 + H + </sup&gt;，M / Z 304.1549）在这三个物种进行检测。与图3相关联的质量测量数据在表2中给出。9-12化合物的身份是通过元素组成确定，同位素匹配，并在文献中报道的比较证实23-24 在Kratom和曼陀罗实时高分辨率质谱光谱直接分析的热地图效果在图4中示出。显示的数据是在主成分分析（PCA）中使用的两个类的植物药物以区分滥用（ 图5）。在PCA情节被使用10个功能块（在表3中列出），与代表Kratom数据和表示曼陀罗数据红色正方形蓝色圆圈构成。选择的特征群众符合各种生物碱存在曼陀罗或帽柱木属，包括精神化合物阿托品，东莨菪碱，帽柱木碱和7- hydroxymitragynine 23-24三个主要成分占方差的75.26％和留一法交叉验证（LOOCV）为100％。在PCA情节清楚地表明，Kratom数据和曼陀罗数据是公彼此解决。主成分分析还显示，Kratom的个别品种和曼陀罗的不同种类可以被确定并且彼此（ 图6）可分辨。 LOOCV为94.29％与3个主成分覆盖方差的75.26％。两品种Kratom的（巴厘岛蓝色圆圈，并在瑞法特红色方块）聚集在一起，表明它们属于物种M.桐 ，但彼此解决，这表明它们代表不同的品种。此外， 曼陀罗物种组一起从分枝分离SPeciosa数据，但每个曼陀罗 （D. inoxia绿色三角形， 四曼陀罗粉红色广场和D.绿松石圈芡 ）的个别品种有明显区分。尽管为D.数据点曼陀罗看来是离群值，种子被正确地分类为D.陀罗 ，而不是D. inoxia采用PCA，最重要的是，D之间种子颜色差异陀罗和D. inoxia证实它们是不同的物种和有问题的数据点不能D. inoxia。 无功能群众的先验选择进行聚类（ 图7）。相反，光谱数据集涵盖M / Z 60-800的质量范围在整个组导入开源基因组集群软件和树形图的特色这个数据产生的。结果Ø˚FHCA还透露仅基于实时高分辨率质谱获得的数据直接分析类，种类和品种分化并确认那些主成分分析的。这两个类的滥用，Kratom和曼陀罗植物为基础的药物，被分成树状图的各个分支。此外，瑞法特和巴厘岛品种Kratom的分别隔离成Kratom类中各个子分支。同样，D. inoxia，D芡和D.曼陀罗是由曼陀罗类中的物种解析到自己的分支。 <img alt="图1" src="/files/ftp_upload/54197/54197fig1.jpg" /> 图1. M.图像桐 （Kratom）产品和曼陀罗属种子 :巴厘岛Kratom干叶; B:巴厘岛Kratom粉末; C:瑞法特Kratom活植物; <strong&gt; D:D。曼陀罗种子; E:D. inoxia种子; F:D。芡种子。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/54197/54197fig2.jpg" /> 图2. 实时高M.分辨率质谱正离子光谱直接分析桐 （Kratom） 产品 :瑞法特鲜叶; B:巴厘岛的干叶; C:巴厘岛粉末; D:巴厘岛粉提取物。与这些光谱相关的海量测量数据如表1所示。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/54197/54197fig3.jpg" /> 图3.在 曼陀罗属 实时高分辨率 质谱正离子谱 直接分析 。 。 种子 :D芡 ; B:D. inoxia; C:D。陀罗。与这些光谱相关的海量测量数据如表2所示。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图4" src="/files/ftp_upload/54197/54197fig4.jpg" /> 图4.实时高的Kratom和曼陀罗植物材料分辨率质谱光谱直接分析的热图效果图。嗨GH强度峰在暗红色和较低强度峰显示在较浅的颜色表示。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图5" src="/files/ftp_upload/54197/54197fig5.jpg" /> 使用实时高分辨质谱派生的数据直接分析构建了Kratom和曼陀罗产品图5.主成分分析（PCA）的情节。三个主成分（PC）的占变异的75.26％，而请假，单交叉验证（LOOCV）为100％。用于PCA的特征群众如表3所示。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig5large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 实时高分辨率质谱数据使用直接分析 的Kratom和 曼陀罗 制品 图6 的主成分分析（PCA）曲线图 。类分配是基于植物材料的品种（Kratom）或种（ 曼陀罗 ）。 3个主成分（PC）的占比的变化和留一交叉验证（LOOCV）的75.26％，94.29是％。用于PCA特征群众如表3所示。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig6large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图7" src="/files/ftp_upload/54197/54197fig7.jpg" /> 图7.分层聚类结果使用真正的TI直接分析得到从Kratom和曼陀罗植物材料分析箱高分辨率质谱衍生数据。这两个类植物的明确（分别为Kratom和曼陀罗蓝色和红色括号中所示，）分为两个不同的分支的树形图。 曼陀罗种子品种也从另一个解决（绿色，绿松石色显示和粉红色的虚线分别盒D. inoxia，D芡，和D曼陀罗 ）。 （红色和蓝色虚线框的瑞法特和巴厘岛，分别显示）Kratom植物材料是由多种分开。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197fig7large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="表格1" src="/files/ftp_upload/54197/54197tbl1.jpg" /> 与Kratom机生产线的软电离光谱相关表1.海量测量数据图2中所示的CTS， <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197tbl1large.jpg" target="_blank">请点击这里查看此表的放大版本。</a> <img alt="表2" src="/files/ftp_upload/54197/54197tbl2.jpg" /> 表2与图3所示 曼陀罗种子的软电离光谱相关海量测量数据。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54197/54197tbl2large.jpg" target="_blank">请点击这里查看此表的放大版本。</a> <img alt="表3" src="/files/ftp_upload/54197/54197tbl3.jpg" /> 用于在图5和6所示Kratom和曼陀罗产品主成分分析图表3.功能块。

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

提出一种用于物种鉴定植物材料的通过实时高分辨率质谱和多元统计分析直接分析方法。

植物材料的快速高通量物种鉴定实时高分辨质谱法直接分析

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

Universidad San Sebastian

Research

JoVE Journal

Chemistry

11.5K 次观看.  University at Albany-SUNY. 提出一种用于物种鉴定植物材料的通过实时高分辨率质谱和多元统计分析直接分析方法。 

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

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.

不相关的代谢组学，生物源使用超高效液相色谱 - 高分辨质谱（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 ...

科研

化学

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

植物标本标本的鲁棒 DNA 分离与高通量测序库建设

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

遗传学

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).

PTR-ToF-MS结合自动采样系统和食品研究定制数据分析:生物过程监测，筛选和鼻空间分析

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.

叶喷雾质谱: 一种快速的环境电离技术直接评价植物组织中的代谢产物

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

生物化学

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.

用于表征复杂天然有机物混合物的单吞吐量互补高分辨率分析技术

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

环境科学

<meta charset="utf8"></head><body>药用植物的 DNA 条形码：鉴定和系统发育分析

Application of DNA Barcoding to Identify Medicinal Plants

Medicinal plants are valuable resources globally and are used worldwide to maintain health and treat disease; however, the presence of adulteration obstructs their development. DNA barcoding, a technique for species identification by standard DNA regions, facilitates prompt and accurate identification of traditional medicinal plants. The process of DNA barcoding entails six basic steps: 1) processing the medicinal plants, 2) extracting high-quality total DNA from the medicinal plants using centrifugal column method, 3) amplifying target DNA region internal transcribed spacer 2 (ITS2) with universal primers of plants and performing Sanger sequencing, 4) splicing and aligning sequence to obtain the target sequence, 5) matching the barcode sequence against the barcode library for identification, 6) aligning sequence, comparing intraspecific and interspecific variation, constructing phylogenetic neighbor-joining tree. As shown in the results, the universal primer can amplify the target region. Basic Local Alignment Search Tool (BLAST) demonstrates the percentage identified was 100%, and the neighbor-joining tree demonstrates that the splicing sequences were clustered with the A. sinensis OR879715.1 clade, and the clade support value is 100. This protocol provides a reference for applying DNA barcoding technology as an effective method to identify medicinal plants and adulterants.

<meta charset="utf8"></head><body>作者聚焦：利用 DNA 条形码技术提高药用植物鉴定的效率

The present protocol describes the use of DNA barcoding technology to authenticate plant-based medicinal materials, and the medicinal plant Angelica sinensis (Oliv.) Diels was identified as an example.

DNA 条形码在药用植物鉴定中的应用

Medicinal plants are valuable resources globally and are used worldwide to maintain health and treat disease; however, the presence of adulteration ...

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Fast detection of cyanobacteria and cyanotoxins is achieved using a Fast Detection Strategy (FDS). Only 24 h are needed to unravel the presence of cyanobacteria and related cyanotoxins in water samples and in an organic matrix, such as bivalve extracts. FDS combines remote/proximal sensing techniques with analytical/bioinformatics analyses. Sampling spots are chosen through multi-disciplinary, multi-scale, and multi-parametric monitoring in a three-dimensional physical space, including remote sensing. Microscopic observation and taxonomic analysis of the samples are performed in the laboratory setting, which allows for the identification of cyanobacterial species. Samples are then extracted with organic solvents and processed with LC-MS/MS. Data obtained by MS/MS are analyzed using a bioinformatic approach using the online platform Global Natural Products Social (GNPS) to create a network of molecules. These networks are analyzed to detect and identify toxins, comparing data of the fragmentation spectra obtained by mass spectrometry with the GNPS library. This allows for the detection of known toxins and unknown analogues that appear related in the same molecular network.

A fast-multidisciplinarystrategy for early detection of cyanobacterial blooms and associated cyanotoxins is described here. It allows for the detection of cyanobacteria and related cyanotoxins in water samples and in organic matrices, such as bivalve samples, in 24 h.

使用快速检测策略早期检测蓝藻花和相关氰毒素

Fast detection of cyanobacteria and cyanotoxins is achieved using a Fast Detection Strategy (FDS). Only 24 h are needed to unravel the presence of ...

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Untargeted metabolomics techniques are being widely used in recent years. However, the rapidly increasing throughput and number of samples create an enormous amount of spectra, setting challenges for quality control of the mass spectrometry spectra. To reduce the false positives, false discovery rate (FDR) quality control is necessary. Recently, we developed a software for FDR control of untargeted metabolome identification that is based on a Target-Decoy strategy named XY-Meta. Here, we demonstrated a complete analysis pipeline that integrates XY-Meta and metaX together. This protocol shows how to use XY-meta to generate a decoy database from an existing reference database and perform FDR control using the Target-Decoy strategy for large-scale metabolome identification on an open-access dataset. The differential analysis and metabolites annotation were performed after running metaX for metabolites peaks detection and quantitation. In order to help more researchers, we also developed a user-friendly cloud-based analysis platform for these analyses, without the need for bioinformatics skills or any computer languages.

We constructed an untargeted metabolomic workflow that integrated XY-Meta and metaX together. In this protocol, we displayed how to use XY-Meta to generate a decoy spectral library from open access spectra reference, and then performed FDR control and used the metaX to quantitate the metabolites after identifying the metabolomics spectra.

基于FDR对照的非靶向代谢组的鉴定和定量集成工作流程

Untargeted metabolomics techniques are being widely used in recent years. However, the rapidly increasing throughput and number of samples create an ...

植物材料的快速高通量物种鉴定实时高分辨质谱法直接分析

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此视频中的章节

不相关的代谢组学，生物源使用超高效液相色谱 - 高分辨质谱（UPLC-HRMS）

植物标本标本的鲁棒 DNA 分离与高通量测序库建设

PTR-ToF-MS结合自动采样系统和食品研究定制数据分析:生物过程监测，筛选和鼻空间分析

叶喷雾质谱: 一种快速的环境电离技术直接评价植物组织中的代谢产物

用于表征复杂天然有机物混合物的单吞吐量互补高分辨率分析技术

DNA 条形码在药用植物鉴定中的应用

DNA 条形码在药用植物鉴定中的应用

DNA 条形码在药用植物鉴定中的应用

使用快速检测策略早期检测蓝藻花和相关氰毒素

基于FDR对照的非靶向代谢组的鉴定和定量集成工作流程