使用顶空固相微萃取与气相色谱-质谱联用分析黑醋栗果实中的挥发性化合物
Summary
这里描述了一个顶空固相微萃取气相色谱平台，用于在成熟的黑醋栗果实中快速、可靠和半自动地进行挥发性鉴定和定量。该技术可用于增加有关水果香气的知识，并选择具有增强风味的品种以进行育种。
Abstract
人们越来越有兴趣测量成熟水果排放的挥发性有机化合物（VOCs），以培育具有增强感官特性的品种或品种，从而提高消费者的接受度。最近开发了高通量代谢组学平台，用于量化不同植物组织中的各种代谢物，包括负责水果味道和香气质量的关键化合物（挥发性组学）。这里描述了一种使用顶空固相微萃取（HS-SPME）与气相色谱-质谱（GC-MS）结合使用的方法，用于鉴定和定量成熟黑醋栗果实排放的VOCs，这种浆果因其风味和健康益处而受到高度赞赏。
收获黑醋栗植物（Ribes nigrum）的成熟果实并直接在液氮中冷冻。组织均质后产生细粉，解冻样品并立即与氯化钠溶液混合。离心后，将上清液转移到含有氯化钠的顶空玻璃小瓶中。然后使用固相微萃取（SPME）纤维和与离子阱质谱仪耦合的气相色谱仪提取VOC。通过积分峰面积，对所得离子色谱图进行挥发性定量，对每个VOC使用特定的 m / z 离子。通过比较在与样品相同条件下运行的纯商业标准的保留时间和质谱，确认了正确的VOC注释。在不同欧洲地区种植的成熟黑醋栗果实中鉴定出60多种VOC。在已确定的VOC中，关键的芳香化合物，如萜类化合物和C6挥发物，可用作黑醋栗果实质量的生物标志物。此外，还讨论了该方法的优缺点，包括预期的改进。此外，还强调了使用控制装置进行批量校正和最小化漂移强度。
Introduction
风味是任何水果的基本质量特征，会影响消费者的接受度，从而显着影响适销性。风味感知涉及味道和嗅觉系统的组合，并且在化学上取决于成熟水果排放的各种化合物的存在和浓度，这些化合物积聚在可食用植物部分，或者在VOC的情况下，由成熟的水果排放1，2。虽然传统育种一直专注于产量和抗虫性等农艺性状，但由于遗传复杂性和难以正确表型这些特征，水果品质性状（包括风味）的改善长期以来一直被忽视，导致消费者不满3，4。代谢组学平台的最新进展已成功鉴定和量化负责水果味道和香气的关键化合物5，6，7，8。此外，代谢物分析与基因组或转录组学工具的结合可以阐明水果风味背后的遗传学，这反过来将有助于育种计划开发具有增强感官特征的新品种2，4，9，10，11，12，13，14。
黑醋栗（Ribes nigrum）浆果因其风味和营养特性而受到高度赞赏，在欧洲，亚洲和新西兰的温带地区广泛种植15。大部分生产是加工食品和饮料，这在北欧国家非常受欢迎，主要是由于浆果的感官特性。水果的强烈颜色和风味是成熟水果中存在的花青素，糖，酸和VOC的组合的结果16，17，18。对黑醋栗挥发物的分析可以追溯到20世纪60年代19，20，21。最近，一些研究集中在黑醋栗VOCs上，确定了水果香气感知的重要化合物，并评估了基因型，环境或储存和加工条件对VOC含量的影响5，17，18，22，23。
由于其众多优点，高通量易失性分析的首选技术是HS-SPME/GC-MS24，25。涂有聚合物相的二氧化硅纤维安装在注射器装置上，允许吸附纤维中的挥发物，直到达到平衡相。顶空萃取可保护纤维免受基质中存在的非挥发性化合物的影响24。SPME可以成功地分离出大量高度可变浓度（十亿分之一到百万分之一）的挥发性有机化合物25。此外，它是一种无溶剂技术，需要有限的样品处理。HS-SPME的其他优点是易于自动化和相对较低的成本。
然而，其成功可能有限，具体取决于VOC的化学性质，提取方案（包括时间，温度和盐浓度），样品稳定性以及足够的果实组织的可用性26，27。本文提出了一种通过HS-SPME分离黑加仑VOCs的方案，并通过气相色谱结合离子阱质谱仪进行分析。在植物材料的数量，样品稳定性以及提取和色谱的持续时间之间实现了平衡，以便能够处理大量的黑醋栗样品，其中一些在本研究中提出。特别是，五个品种（”Andega”，”Ben Tron”，”Ben Gairn”，”Ben Tirran”和”Tihope”）的VOC图谱和/或色谱图将作为示例数据进行介绍和讨论。此外，在其他水果浆果物种（如草莓（Fragaria x ananassa），覆盆子（Rubusidaeus）和蓝莓（Vaccinium spp.）中，相同的方案已成功用于VOC测量。
Protocol
1. 水果收获 每个基因型和/或处理种植4至6株植物，以确保足够的果实材料和变异性。 如果可能的话，在同一天收获样品;如果没有足够的水果材料，将不同日期收获的样品汇集在一起。注意：建议收获时间（上午，中午，下午）保持大致相同，因为VOC曲线受白天/昼夜节律的影响28，29，30，<sup class="xre…
Representative Results
在不同条件或地点生长或属于不同基因型的大量水果作物中进行高通量VOC分析对于准确的香气表型是必要的。本文介绍了一个快速、半自动化的HS-SPME/GC-MS平台，用于黑加仑品种的VOC相对定量。VOC检测和鉴定基于为分析浆果果实种类而开发的文库（表1）。在上述条件下，HS-SPME/GC-MS获得的典型成熟黑醋栗果实挥发性剖面图（总离子色谱图）如图 1A所示。总共确定?…
Discussion
长期以来，由于挥发性化合物合成背后的复杂遗传学和生物化学以及缺乏适当表型的技术，水果香气的滋生一直受到阻碍。然而，代谢组学平台的最新进展，结合基因组工具，最终允许鉴定负责消费者偏好的代谢物，并培育出风味更好的作物3。虽然在模型水果番茄9，10方面取得了大部分进展，但在其他经济相关的作物物种（如草莓，?…
Disclosures
The authors have nothing to disclose.
Acknowledgements
作者感谢马拉加大学的 Servicios Centrales de Apoyo a la Investigación 对HS-SPME /GC-MS的测量。我们感谢萨拉·费尔南德斯-帕拉西奥斯·坎波斯在波动性定量方面提供的帮助。我们也感谢GoodBerry的财团成员提供水果材料。
Materials
| 10 mL screw top headspace vials | Thermo Scientific | 10-HSV | |
| 18 mm screw cap Silicone/PTFE | Thermo Scientific | 18-MSC | |
| 5 mL Tube with HDPE screw cap | VWR | 216-0153 | |
| Centrifuge | Thermo Scientific | 75002415 | |
| Methanol for HPLC | Merck | 34860-1L-R | |
| N-pentadecane (D32, 98%) | Cambridge Isotope Laboratories | DLM-1283-1 | |
| Sodium chloride | Merck | S9888 | |
| SPME fiber PDMS/DVB | Merck | 57345-U | |
| Stainless grinding jars for TissueLyser | Qiagen | 69985 | |
| TissueLyser II | Qiagen | 85300 | Can be subsituted by mortar and pestle or cryogenic mill |
| Trace GC gas chromatograph-ITQ900 ion trap mass spectrometer | Thermo Scientific | ||
| Triplus RSH autosampler with automated SPME device | Thermo Scientific | 1R77010-0450 | |
| Water for HPLC | Merck | 270733-1L | |
| Xcalibur 4.2 SP1 | Thermo Scientific | software |
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Tags
Volatile CompoundsBlackcurrant FruitHeadspace Solid-phase MicroextractionGas Chromatography-mass SpectrometryFruit AromaBreeding ProgramsSemi-automated TechniqueBerry CropsSodium Chloride SolutionCentrifugationInternal StandardGC-MS Auto SamplerHeadspace VialSPME DeviceVolatile DesorptionGC-MS AnalysisRetention TimeMass SpectraKovats Linear Retention IndexPeak AreaInternal StandardBatch Effect Correction
Cite This Article
Pott, D. M., Vallarino, J. G., Osorio, S. Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry. J. Vis. Exp. (172), e62421, doi:10.3791/62421 (2021).