This work is supported by the European Commission's 7th Framework Programme under Grant Agreement Number 287382. SY is a beneficiary of a European Commission's 7th Framework Programme Grant Agreement Number 287382. IK is a beneficiary of a FIRST doctoral school grant from the Fondazione Edmund Mach. For his work at University of Foggia, VC is supported by the Apulian Region in the framework of 'Future In Research' program (practice code 9OJ4W81).

该议定书遵循我们的人类研究伦理制度委员会的指导方针。 样品制备和自动进样器条件<ol><li> 在线生物过程监测:检测乳酸发酵过程中释放的挥发性有机酸 注意:本协议的这一部分代表了Benozzi 等报道的程序的一部分。 32 <ol><li>向每个小瓶（装有PTFE /硅胶隔片的20mL玻璃小瓶）中加入5mL巴氏灭菌牛奶。注意使用的牛奶类型，并将样品快速加热至45°C。将其转移到配有温度控制托盘（45°C）的多功能GC自动进样器。 </li><li>使用自动进样器的机器人手臂接种微生物发酵剂培养物（根据起始培养基生产商的规格）的小瓶。根据所需酸奶的类型和规格设定孵育时间由起始文化制造商报告。设置自动进样器以方便地分析一个样品，在酸奶制备过程中获得乳酸发酵的在线VOC监测。 </li></ol></li><li> 大规模筛选:监测与不同苹果基因型相关的VOC 注意:本协议的这一部分代表Farneti 等人报告的一部分程序。 33，36 <ol><li>在成熟/保存期望的阶段， 例如苹果（ 例如在商业收获阶段）。选择至少五个均匀的水果，每个克隆没有任何可见的损伤。将苹果在室温（25°C）或冷藏（4°C）下保存所需时间。 </li><li>用肉片采样器从每个苹果收集五个圆柱形盘（直径1.7厘米，厚1厘米）。包括一部分皮质组织，避免核心部分与种子。立即使样品均质并在液氮中冷冻。储存于-80°C直到分析。 </li><li>在分析前，将来自每个生物复制品的2.5g苹果样品的三次重复放入小瓶（装有PTFE /硅胶隔片的20mL玻璃小瓶）中。将样品与2.5mL去离子水，1g氯化钠，12.5mg抗坏血酸和12.5mg柠檬酸混合，并将样品保持在4℃直到分析（最多3天）。 </li><li>在40℃下孵育样品，然后设置自动进样器以自动分析VOC。 </li></ol></li><li> 空气分析:研究饮酒过程中VOC的深度释放 注意:该协议的这一部分代表Romano 等报道的程序的一部分。 28 <ol><li>从磨碎的咖啡样品中准备冲泡的咖啡。 <ol><li>使用咖啡机:报告水/粉比，所用矿泉水的种类，咖啡机的类型以及获得咖啡饮料所采用的程序（数量是咖啡机尺寸的函数）。 </li><li>使用六杯咖啡机，意大利知名的"moka"，使用450毫升水和30克咖啡粉。将煮过的咖啡放入容器中，并将其转移到恒温水浴（60°C）中。 </li></ol></li><li>对于每个咖啡冲泡，将7.5mL等分试样转移到具有塑料盖的聚苯乙烯杯（40mL）中。每个小组成员按照协议对饮料进行尝试:i）30秒的自由呼吸，ii）单次喝咖啡，然后快速吞咽，iii）3分钟的呼吸进入符合人体工程学的玻璃鼻梁28 。 </li><li>每天重复整个实验连续三天，随机抽取咖啡样本和小组成员的次序。 </li><li>通过将硅橡胶中的一次性符合人体工程学的喷嘴安装在小组成员的鼻子上进行采样。连接n通过仅在与面板主体接触的第一部分中不加热的PEEK管到PTR-ToF-MS，然后在110℃下在入口软管中加热，该入口软管将采样接口与PTR-MS连接仪器。 注意:在表2中，用Benozzi 等人报道的类似程序分析的产品列表。 32 ，Farneti et al。 33,36和Romano 等人 28报道。 </li></ol></li></ol><table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 食物矩阵 </td><td> 样品数量和种类 </td><td> 参考 </td></tr><tr><td>苹果</td><td>作者筛选了由新旧苹果品种组成的190个种质资源</td><td> 33 </td></tr><tr><td>酸奶</td><td>在酸乳酪乳酸发酵过程中释放的VOCs分析了四个起动器（A，FD-DVS YF-L812 Yo-Flex，Chr.Hansen; B，FD-DVS YC-380Yo-Flex，Chr.Hansen; C，FD -DVS YC-X11 Yo-Flex，Hansen; D，YO-MIX 883，Danisco） </td><td> 32 </td></tr><tr><td>咖啡</td><td>使用从单一纯阿拉比卡咖啡混合物获得的三种不同种类的研磨咖啡:中烤，黑烤和脱咖啡因培养基</td><td> 28 </td></tr></tbody></table> 表2:分析产品清单。通过与Benozzi 等人报道的类似程序分析的产品清单。 32 ，Farneti et al。 33,36和Romano 等人 28 2.实验设计与实践预防<ol><li>执行至少三个日间生物复制品每个都有三个技术重复，每个实验模式。 </li><li>在进行样品孵育和分析之前，每个小瓶以200sccm的清洁空气冲洗顶空1分钟。 </li><li>为每个实验模式准备一个空白，在相同的样品条件下孵育和分析空白。 </li><li>随机抽样/空白的顺序进行分析。 </li><li>与用于检测VOC的其他方法类似，在使用仪器之前，限制使用香水的个人护理产品以及口香糖和香烟。在实验室中紧密封住挥发性化学物质，并在测试期间尽可能多地控制气流。 </li></ol> 3. PTR-MS仪器优化与分析注意:工具条件在参考文献中有描述（ 例如 Makhoul 等人 27 ）。 <ol><li>用商品进行样品的顶空测量以PTR-ToF-MS装置为标准配置模式。 </li><li>直接将空气注入PTR-MS漂移管顶空，无需任何处理。样品空气通过PTR-MS连续流动，因此通过简单地将PTR-MS入口的末端插入样品顶部空间来实现注射。 </li><li>设置并不断验证漂移管中的以下电离条件:110°C漂移管温度，2.30 mbar漂移压力，550 V漂移电压。这导致约140Td（1Td = 10 -17cm 2 V - 1s - 1 ）的E / N比。入口管线由在110℃加热的PEEK毛细管（内径0.04英寸）组成。默认情况下，将入口流量设置为40sccm。 </li><li>将ToF采集通道的采样时间设置为0.1 ns，对于m / z = 400的质谱，共有35万个通道。每个单个频谱是大约28,600次采集的总和持续35每个μs，导致1秒的时间分辨率。 注意:然后连续存储光谱。光谱测量信号在几秒钟内（从入口管线中更换气体所需的时间）从背景水平增长到稳定值，并且仅在进一步分析后考虑采集的光谱。 </li></ol> 4.定制数据分析注意:使用MATLAB中的过程开发了量身定制的数据分析。 <ol><li>通过基于泊松统计的方法校正离子检测器死区时间造成的计数损失，如Cappellin 等人所述。 10 。 </li><li>根据Cappellin 等人描述的程序执行内部校准38达到良好的质量精度（高达0.001 Th）。 </li><li>进行复合注释比较获得的光谱数据与参考标准的碎片数据和数据r在科学文献中报道。 </li><li>根据Cappellin 等人进行降噪，基线去除和峰强度提取。 39 ，使用修改的高斯拟合峰。 </li><li>通过Lindinger 等人描述的公式计算峰值强度，单位为ppbv（以体积计） 。 5 ，当底层化合物未知时，使用适当的反应速率系数或反应速率系数（k = 2.10-9cm 3 s -1 ）的常数值。后者引入高达30％的系统误差，如果实际系数已知40则可以解释 。 </li><li>通过执行主成分分析，方差分析，Tukey的事后检验以及适应使用R开发的现有包装的其他统计测试/分析来挖掘数据（ 例如 Cappellin 等人 </ol>

The authors have nothing to disclose.

耦合飞行时间（ToF）质谱分析仪的质子转移反应 - 质谱（PTR-MS）代表了对挥发性有机化合物的鉴定和定量的需要以及快速分析分析的必要性之间的有效折中。表征ToF质量分析仪的高质量分辨率为相关灵敏度和质谱提供了相当大的信息内容。此外，PTR-ToF-MS与自动采样器的配合以及增加自动化程度的定制数据分析工具的应用，增强了这一技术的潜力。 在许多研究和技术领域，挥?...

直接注入质谱（DIMS）技术代表了一类分析仪器方法，具有高灵敏度和鲁棒性的相当大的质量和时间分辨率，可以快速检测和定量挥发性有机化合物（VOC） 1 。这些工具方法包括MS-e-noses，大气压力化学电离质谱（APCI-MS），质子转移反应质谱（PTR-MS）和选定离子流管质谱（ SIFT-MS） 1 。每种方法的优点和缺点取决于:样品注入的种类，前体离子的来源和控制，电离过程的控制以及质量分析仪1,2 。 质子转移反应质谱（PTR-MS）是二十多年前开发的，用于实时监测和检测在空气中的最低挥发性有机化合物（VOC）的低检测限（通常为几ppbv，体积百分之十）。目前PTR-MS的应用范围从医疗应用，食品控制到环境研究5,6 。该技术的主要特点是:快速连续测量的可能性，前体离子的强烈和纯净的来源，以及控制电离条件（压力，温度和漂移电压）的可能性。这些功能允许将多功能用途与高标准化组合1,4 。事实上，该方法是基于水合氢离子（H 3 O + ）的反应，其在大多数挥发性化合物（特别是以质子亲和力高于水的特征）中诱导非解离质子转移，质子化中性化合物（M）根据反应:H 3 O + + M→H 2 O + MH + 。与其他技术相比， 例如 APCI-MS，前体离子产生和样品电离分成两个不同的仪器室（ 图1中给出了PTR-MS仪器的示意图 ）。中空阴极离子源中的水蒸汽放电产生一束水合氢离子。在此阶段之后，离子穿过漂移管，其中VOC的电离发生7 。离子然后进入脉冲提取部分并加速到TOF部分。通过飞行时间，可以确定离子8的质荷比。每个提取脉冲导致所选m / z范围的完整质谱8 。离子光谱由快速数据采集系统7记录。一个完整的频谱是典型的在一秒钟内获得，尽管可以根据信号噪声水平实现更高的时间分辨率，并且即使没有校准，也可以提供VOC顶空浓度的定量估计9,10 。 <img alt="图1" src="/files/ftp_upload/54075/54075fig1.jpg" /> 图1: PTR-MS的示意图。 PTR-MS仪器的示意图。 HC:具有中空阴极的外部离子源; SD:源漂移;六，文丘里型入口; EM，电子倍增器; FC1-2，流量控制器。转载自Boschetti 等人的许可7 。 <a href="https://ecsource-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/54075/54075fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 11 。 PTR对环境，大气，食品，技术，医学和生物科学十分有兴趣12 。 与食品基质相关的挥发性有机化合物在食品科学和技术方面具有突出的兴趣，因为它们在与气味和风味感知相关的生物现象的分子基础中起重要作用，因此在食品接受度方面。因此，我们对VOC的实时和非侵入性检测的兴趣主要涉及食品的感官品质。此外，如果我们考虑通过释放的VOC 13检测腐败和致病微生物的可能性，和/或监测挥发性有机化合物作为标记物机翼技术过程（ 例如热处理中的美拉德副产品） 14 ，VOC识别和定量是食品质量管理中感兴趣的领域。几种近来PTR-MS技术用于快速监测和定量食品基质中VOCs的应用证明了这些分析方法的广泛应用（ 表1 ）。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 食物矩阵 </td><td> 种类适用 </td><td> 简要描述;简介 </td><td> 参考 </td></tr><tr><td>牛油</td><td>筛选/表征</td><td>欧洲的地理起源</td><td> 15 </td></tr><tr><td>酸奶</td><td>生物过程监控</td><td>乳酸过程中的进化心理状态</td><td> 16 </td></tr><tr><td>谷物酒吧</td><td> 体内测量</td><td>在食用不同糖成分的谷物酒的食物空间</td><td> 17 </td></tr><tr><td>液体模型系统</td><td>模拟口服条件</td><td>口腔压力和口腔状况的评估</td><td> 18 </td></tr><tr><td>苹果</td><td> 体内测量</td><td>消费苹果中的空白具有不同的遗传，结构和物理化学参数</td><td> 19 </td></tr><tr><td>咖啡</td><td>筛选/表征</td><td>专业咖啡的区别</td><td> 20 </td></tr><tr><td>葡萄必须</td><td>筛选/表征</td><td>烹饪过程的影响</td><td> 21 </td></tr><tr><td>调味糖果</td><td> 体内测量</td><td>决定使用不同的小组成员直接质谱法</td><td> 22 </td></tr><tr><td>火腿</td><td>筛选/表征</td><td>养猪系统的效果</td><td> 23 </td></tr><tr><td>面包</td><td>模拟口服条件</td><td>在咀嚼期间模拟面包香气</td><td> 24 </td></tr><tr><td>牛奶</td><td>筛选/表征</td><td>监测牛奶中光氧化诱导的动态变化</td><td> 25 </td></tr><tr><td>咖啡</td><td>筛选/表征</td><td>来自不同地理起源的烤咖啡的多样性</td><td> 26 </td></tr><tr><td>面包</td><td>生物过程监控</td><td>不同酵母起泡器在酒精发酵过程中的作用</td><td> 27 </td></tr><tr><td>咖啡</td><td> 体内测量</td><td>在消费不同的焙炒咖啡制品期间的空气</td><td> 28 </td></tr><tr><tD&gt;西红柿</td><td>筛选/表征</td><td>生产位置，生产系统和品种的影响</td><td> 29 </td></tr><tr><td>面包</td><td>生物过程监控</td><td>酒精发酵过程中面粉，酵母及其相互作用的影响</td><td>三十</td></tr><tr><td>蘑菇</td><td>筛选/表征</td><td>干燥的猪笼草蘑菇的保质期</td><td> 31 </td></tr><tr><td>酸奶</td><td>生物过程监控</td><td>不同发酵剂培养物在乳酸发酵过程中的作用</td><td> 32 </td></tr><tr><td>苹果</td><td>筛选/表征</td><td>苹果种质资源多样性</td><td> 33 </td></tr><tr><td>咖啡</td><td>筛选/表征</td><td>跟踪咖啡来源</td><td> 34 </td></tr><tr><td>咖啡</td><td> 体内测量</td><td>组合a动态感官方法和体内鼻子空间分析来了解咖啡感觉</td><td> 35 </td></tr></tbody></table> 表1:使用PTR-ToF-MS在食品行业的科学研究清单。使用基于PTR的方法在食品相关实验中监测VOC含量的科学研究非详尽列表。 在最近的研究中，我们报告了P​​TR-ToF-MS的应用以及自动采样系统和定制的数据分析工具，以提高采样自动化和可靠性，从而提高这种技术的潜力7,10,13。这允许我们在VOC含量方面筛选大样本集（ 例如具有许多重复的不同来源的食物，整个胚泡），以分析几种实验模式对VOC释放的影响（ 例如不同浓度特定技术参数的不同强度），并监测与给定生物过程相关的VOC（ 如酶氧化，酒精发酵）。在这里，为了说明PTR-ToF-MS在农业食品行业的潜力，我们提出了三种范式应用:检测由不同微生物启动子培养物诱导的酸奶乳酸发酵期间释放的VOC（在线生物过程监测），监测与不同苹果栽培品种（大规模筛选）相关的挥发性有机化合物（VOC），以及饮用咖啡时鼻内VOC释放的体内研究（鼻孔空间分析）。

<table><tbody><tr><td>PTR-TOF 8000 High-Resolution PTR-TOF-MS</td><td>Ionicon Analytik Ges.m.b.H.</td><td>PTR-TOF 8000</td><td>An detector for volatile organic compounds (VOCs) that allows for continuous VOC quantification with a very high mass resolution</td></tr><tr><td>GERSTEL&amp;nbsp;MPS 2XL</td><td>Gerstel</td><td></td><td>A multifunctional autosampler&amp;nbsp;</td></tr><tr><td>Gas Calibration Unit</td><td>Ionicon Analytik Ges.m.b.H.</td><td>GCU-s / GCU-a</td><td>A dynamic gas dilution system that provides variable but known quantities of different standard compounds in a carrier gas stream</td></tr><tr><td>TofDaq</td><td>Tofwerk AG</td><td>free available at http://soft.tofwerk.com/&amp;nbsp;&amp;nbsp;&amp;nbsp;</td><td>A data acquisition software&amp;nbsp;(for spectra&amp;nbsp; acquisition)</td></tr><tr><td>MATLAB&amp;nbsp;</td><td>MathWorks</td><td>http://it.mathworks.com/products/matlab/</td><td>A technical computing language and interactive environment for algorithm development, data visualization, and data analysis</td></tr><tr><td>R</td><td>The R Foundation</td><td>free available at https://cran.r-project.org/mirrors.html&amp;nbsp;&amp;nbsp;</td><td>A language and environment for statistical computing and graphics</td></tr></tbody></table>

ptr-tof-ms coupled with an automated sampling system and tailored data analysis for food studies: bioprocess monitoring, screening and nose-space analysis

质子转移反应（PTR），结合飞行时间（ToF）质谱（MS）是基于直接注入质谱（DIMS）技术的基于化学电离的分析方法。这些技术可以快速测定挥发性有机化合物（VOC），确保高灵敏度和准确度。一般来说，PTR-MS既不需要样品制备也不需要样品破坏，可以对样品进行实时和非侵入性分析。 PTR-MS在许多领域得到开发，从环境和大气化学到医学和生物科学。最近，我们开发了一种基于PTR-ToF-MS联合自动采样器和定制数据分析工具的方法，以增加自动化程度，从而提高该技术的潜力。这种方法允许我们监测生物过程（ 例如酶促氧化，酒精发酵），筛选大样品组例如不同的来源，整个胚泡），并分析几种实验模式（ 例如 ，给定成分的不同浓度，特定技术参数的不同强度）在VOC含量方面。在这里，我们报告了实验方案，例示了我们的方法的不同可能的应用: 即酸奶发酵过程中释放的VOCs（在线生物过程监测），与不同苹果品种（大规模筛选）相关的VOC的监测， ，以及咖啡饮用期间维生素VOC释放的体内研究（鼻孔空间分析）。

<html>样品的挥发性曲线导致了每秒获得的所需质量范围的完整质谱。在图2中 ，给出了酸奶在线生物过程中获得的平均光谱的一个例子32 。在每个频谱中，可以识别在m / z范围内高达250 Th的300个质量峰。 <img alt="图2" src="/files/ftp_upload/54075/54075fig2.jpg" /> 图2: 酸奶制造过程中接?...

Watch this Scientific Journal Video about PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis at 

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 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 ...

ptr-tof-ms-coupled-with-an-automated-sampling-system-tailored-data

Universidad San Sebastian

Research

JoVE Journal

Chemistry

12.3K 次观看.  Fondazione Edmund Mach (FEM). 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).

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

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 ...

科研

环境科学

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.

利用目标筛选和非靶向筛选高分辨率质谱相结合的工作流程识别跨氟和多氟化学物种

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

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, which can take up significant person-hours of bench labor and present a source of batch-to-batch variability. Lab automation with pipetting robots can reduce manual work, maximize throughput, and increase research reproducibility. Still, the steep starting prices of standard automation stations make them unaffordable for many academic laboratories. This article describes a proteomics sample preparation workflow using an affordable, open-source automation system (The Opentrons OT-2), including instructions for setting up semi-automated protein reduction, alkylation, digestion, and clean-up steps; as well as accompanying open-source Python scripts to program the OT-2 system through its application programming interface.

Detailed protocol and three Python scripts are provided for operating an open-source robotic liquid handling system to perform semi-automated protein sample preparation for mass spectrometry experiments, covering detergent removal, protein digestion, and peptide desalting steps.

Shotgun 蛋白质组学 样品处理 由开源实验室机器人自动执行

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, ...

生物化学

<meta charset="utf8"></head><body>收集 LC 和 TIMS-TOF MS/MS 的正交性以筛选芬太尼类似物

Fentanyl Analog Screening using LC-TIMS-TOF MS/MS

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its analogs are the major contributors to fatal and nonfatal overdoses in the United States. Most recent cases of fentanyl-related overdose are linked to illicitly manufactured fentanyl and its associated extreme potency. In the present work, we describe a high-throughput analytical protocol for the screening of fentanyl analogs. The use of complementary liquid chromatography, trapped ion mobility spectrometry, and tandem mass spectrometry allow for the separation and assignment of hundreds of fentanyl analogs from a single sample in a single scan. The described approach takes advantage of the recent development of data-dependent acquisition and data-independent acquisition using parallel accumulation in the mobility trap followed by sequential fragmentation using collision-induced dissociation. The fentanyl analogs are confidently assigned based on their retention time, mobility, and MS fragmentation pattern.

<meta charset="utf8"></head><body>作者聚焦:一种自信地区分和表征芬太尼类似物的有效方法

A method for the screening of fentanyl analogs based on their retention time, mobility, and mass spectrometry fragmentation pattern.

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its ...

化学

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.

Here, we establish a mass spectrometry-based proteomic method using isolated regions of interest in formalin-fixed, paraffin-embedded tissue sections. This protocol is used to analyze proteome from specific tissue areas in archived formalin-fixed, paraffin-embedded tissue sections.

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and ...

Fruit Volatile Analysis Using an Electronic Nose

Numerous and diverse physiological changes occur during fruit ripening, including the development of a specific volatile blend that characterizes fruit aroma. Maturity at harvest is one of the key factors influencing the flavor quality of fruits and vegetables1. The validation of robust methods that rapidly assess fruit maturity and aroma quality would allow improved management of advanced breeding programs, production practices and postharvest handling. 
Over the last three decades, much research has been conducted to develop so-called electronic noses, which are devices able to rapidly detect odors and flavors2-4. Currently there are several commercially available electronic noses able to perform volatile analysis, based on different technologies. The electronic nose used in our work (zNose, EST, Newbury Park, CA, USA), consists of ultra-fast gas chromatography coupled with a surface acoustic wave sensor (UFGC-SAW). This technology has already been tested for its ability to monitor quality of various commodities, including detection of deterioration in apple5; ripeness and rot evaluation in mango6; aroma profiling of thymus species7; C6 volatile compounds in grape berries8; characterization of vegetable oil9 and detection of adulterants in virgin coconut oil10. 
This system can perform the three major steps of aroma analysis: headspace sampling, separation of volatile compounds, and detection. In about one minute, the output, a chromatogram, is produced and, after a purging cycle, the instrument is ready for further analysis. The results obtained with the zNose can be compared to those of other gas-chromatographic systems by calculation of Kovats Indices (KI). Once the instrument has been tuned with an alkane standard solution, the retention times are automatically converted into KIs. However, slight changes in temperature and flow rate are expected to occur over time, causing retention times to drift. Also, depending on the polarity of the column stationary phase, the reproducibility of KI calculations can vary by several index units11. A series of programs and graphical interfaces were therefore developed to compare calculated KIs among samples in a semi-automated fashion. These programs reduce the time required for chromatogram analysis of large data sets and minimize the potential for misinterpretation of the data when chromatograms are not perfectly aligned.
We present a method for rapid volatile compound analysis in fruit. Sample preparation, data acquisition and handling procedures are also discussed.

A rapid method for volatile compound analysis in fruit is described. The volatile compounds present in the headspace of a homogenate of the sample are rapidly separated and detected with ultra-fast gas chromatography (GC) coupled with a surface acoustic wave (SAW) sensor. A procedure for data handling and analysis is also discussed.

果实挥发分析，利用电子鼻

Numerous and diverse physiological changes occur during fruit ripening, including the development of a specific volatile blend that characterizes fruit ...

生物学

Protease- and Acid-catalyzed Labeling Workflows Employing 18O-enriched Water

Stable isotopes are essential tools in biological mass spectrometry. Historically, 18O-stable isotopes have been extensively used to study the catalytic mechanisms of proteolytic enzymes1-3. With the advent of mass spectrometry-based proteomics, the enzymatically-catalyzed incorporation of 18O-atoms from stable isotopically enriched water has become a popular method to quantitatively compare protein expression levels (reviewed by Fenselau and Yao4, Miyagi and Rao5 and Ye et al.6). 18O-labeling constitutes a simple and low-cost alternative to chemical (e.g. iTRAQ, ICAT) and metabolic (e.g. SILAC) labeling techniques7. Depending on the protease utilized, 18O-labeling can result in the incorporation of up to two 18O-atoms in the C-terminal carboxyl group of the cleavage product3. The labeling reaction can be subdivided into two independent processes, the peptide bond cleavage and the carboxyl oxygen exchange reaction8. In our PALeO (protease-assisted labeling employing 18O-enriched water) adaptation of enzymatic 18O-labeling, we utilized 50% 18O-enriched water to yield distinctive isotope signatures. In combination with high-resolution matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF/TOF MS/MS), the characteristic isotope envelopes can be used to identify cleavage products with a high level of specificity. We previously have used the PALeO-methodology to detect and characterize endogenous proteases9 and monitor proteolytic reactions10-11. Since PALeO encodes the very essence of the proteolytic cleavage reaction, the experimental setup is simple and biochemical enrichment steps of cleavage products can be circumvented. The PALeO-method can easily be extended to (i) time course experiments that monitor the dynamics of proteolytic cleavage reactions and (ii) the analysis of proteolysis in complex biological samples that represent physiological conditions. PALeO-TimeCourse experiments help identifying rate-limiting processing steps and reaction intermediates in complex proteolytic pathway reactions. Furthermore, the PALeO-reaction allows us to identify proteolytic enzymes such as the serine protease trypsin that is capable to rebind its cleavage products and catalyze the incorporation of a second 18O-atom. Such "double-labeling" enzymes can be used for postdigestion 18O-labeling, in which peptides are exclusively labeled by the carboxyl oxygen exchange reaction. Our third strategy extends labeling employing 18O-enriched water beyond enzymes and uses acidic pH conditions to introduce 18O-stable isotope signatures into peptides.

Protease- and Acid-catalyzed Labeling Workflows Employing 18O-enriched Water

Stable isotope labeling workflows employing 18O-enriched water (LeO-workflows) are versatile tools for quantitative and qualitative proteomics studies. In protease-assisted (PALeO) workflows, 18O-atoms are introduced by proteolytic cleavage and carboxyl oxygen exchange reactions mediated by proteases. In the acid-catalyzed (ALeO) workflow, 18O-atoms are introduced by carboxyl oxygen exchange at low pH.

蛋白酶和酸催化的贴标工作流程，用人<sup&gt; 18</sup&gt; O-富氧水

Stable isotopes are essential tools in biological mass spectrometry. Historically, 18O-stable isotopes have been extensively used to study the catalytic ...

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Single-molecule F&#246;rster resonance energy transfer (smFRET) is a versatile technique reporting on distances in the sub-nanometer to nanometer range. It has been used in a wide range of biophysical and molecular biological experiments, including the measurement of molecular forces, characterization of conformational dynamics of biomolecules, observation of intracellular colocalization of proteins, and determination of receptor-ligand interaction times. In a widefield microscopy configuration, experiments are typically performed using surface-immobilized probes. Here, a method combining single-molecule tracking with alternating excitation (ALEX) smFRET experiments is presented, permitting the acquisition of smFRET time traces of surface-bound, yet mobile probes in plasma membranes or glass-supported lipid bilayers. For the analysis of recorded data, an automated, open-source software collection was developed supporting (i) the localization of fluorescent signals, (ii) single-particle tracking, (iii) determination of FRET-related quantities including correction factors, (iv) stringent verification of smFRET traces, and (v) intuitive presentation of the results. The generated data can conveniently be used as input for further exploration via specialized software, e.g., for the assessment of the diffusional behavior of probes or the investigation of FRET transitions.

This article presents a method for spatiotemporal analysis of mobile, single-molecule F&#246;rster resonance energy transfer (smFRET)-based probes using widefield fluorescence microscopy. The newly developed software toolkit allows the determination of smFRET time traces of moving probes, including the correct FRET efficiency and the molecular positions, as functions of time.

移动式单分子FRET探头的自动化二维时空分析

Single-molecule F&#246;rster resonance energy transfer (smFRET) is a versatile technique reporting on distances in the sub-nanometer to nanometer range. ...

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

摘要

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此视频中的章节

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

利用目标筛选和非靶向筛选高分辨率质谱相结合的工作流程识别跨氟和多氟化学物种

Shotgun 蛋白质组学样品处理由开源实验室机器人自动执行

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

果实挥发分析，利用电子鼻

蛋白酶和酸催化的贴标工作流程，用人

移动式单分子FRET探头的自动化二维时空分析

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

摘要

探索更多视频

此视频中的章节

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

利用目标筛选和非靶向筛选高分辨率质谱相结合的工作流程识别跨氟和多氟化学物种

Shotgun 蛋白质组学 样品处理 由开源实验室机器人自动执行

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

使用 LC-TIMS-TOF MS/MS 进行芬太尼类似物筛选

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

果实挥发分析，利用电子鼻

蛋白酶和酸催化的贴标工作流程，用人

移动式单分子FRET探头的自动化二维时空分析

Shotgun 蛋白质组学样品处理由开源实验室机器人自动执行