IR-MALDESI质谱成像的紫甘蓝叶片z轴自动校正地形成像。

IF 3.8 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS
Quinn Mills, Sarah M Ashbacher, Alexandria L Sohn, David C Muddiman
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引用次数: 0

摘要

质谱(MS)是一种多功能的技术,用于阐明生物样品的化学成分。除了分析粗提取物,质谱还可以进一步应用于通过一种称为质谱成像(MSI)的技术对样品区域内的化合物进行空间解析。红外基质辅助激光解吸电离(IR-MALDESI)平台结合了基质辅助激光解吸电离(MALDI)和电喷雾电离(ESI)的元素,利用样品中的内源水作为基质,实现了哺乳动物组织的MSI。对于基于激光的技术,如IR-MALDESI,当样品表面在激光焦平面上下移动时,样品表面的地形变化会导致不一致的烧蚀。化学物种在植物中的定位揭示了代谢过程的关键信息,如Nemes和Vertes (Anal。chemistry . 79(21), 8098-8106, 2007)和Zou等人的生物合成途径(Trends in Plant Science, 2024),甚至可以为Sakurai (Breed Sci 72(1), 56-65, 2022)所讨论的作物选择性育种提供信息;然而,叶片地形提出了一个独特的挑战。静脉和毛状体等特征表现出独特的地形,但平坦化有分析物脱位和激活不需要的信号通路的风险,并且将代谢物转移到膜上进行间接分析可能导致脱位和限制代谢组学覆盖。为了克服这些挑战,我们采用了一种彩色共聚焦传感器探针(CA探针),对甘蓝叶的部分进行IR-MALDESI-MSI检测。CA探针测量样品所有点的高度,并从高度差产生自动z轴校正(AzC),以不断升高和降低阶段。这些阶段高度校正使样品表面在分析期间保持在激光的焦点上。该方法已应用于相对均匀的样品,但尚未表征具有相当地形的异质叶组织。本文比较了应用AzC和不应用AzC的MSI分析的数据质量,重点关注已知集中在羽衣甘蓝叶不同层中的分析物的定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topographic imaging with automatic z-axis correction of Brassica oleracea var. viridis leaves by IR-MALDESI mass spectrometry imaging.

Mass spectrometry (MS) is a versatile technique for elucidating the chemical composition of biological samples. Beyond analysis of crude extracts, MS can be further applied to spatially resolve compounds across the area of a sample with a technique called mass spectrometry imaging (MSI). The infrared matrix-assisted laser desorption ionization (IR-MALDESI) platform combines elements of matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) to enable MSI of mammalian tissue using endogenous water in the sample as a matrix. For laser-based techniques such as IR-MALDESI, changes in topography across the sample surface cause inconsistent ablation as the sample surface moves above and below the focal plane of the laser. The localization of chemical species in plants reveals crucial information about metabolic processes as reported by Nemes and Vertes (Anal. Chem. 79 (21), 8098-8106, 2007) and biosynthetic pathways by Zou et al. (Trends in Plant Science, 2024) and can even inform selective breeding of crops as discussed by Sakurai (Breed Sci 72 (1), 56-65, 2022); however, leaf topography raises a unique challenge. Features such as veins and trichomes exhibit unique topography, but flattening risks delocalization of analytes and activation of unwanted signaling pathways, and transferring metabolites to a membrane for indirect analysis may incur delocalization and limit metabolomic coverage. To overcome these challenges, a chromatic confocal sensor probe (CA probe) was incorporated for IR-MALDESI-MSI of sections of a collard (Brassica oleracea var. viridis) leaf. The CA probe measures the height at all points of the sample, and automatic z-axis corrections (AzC) are generated from height differences to continuously raise and lower the stage. These stage height corrections keep the sample surface in focus of the laser for the duration of analysis. This method has been applied to relatively homogenous samples, but has not yet been characterized on heterogeneous leaf tissue with considerable topography. Herein, data quality is compared between MSI analyses with and without AzC applied, focusing on the localization of analytes known to be concentrated in different layers of collard leaves.

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来源期刊
CiteScore
8.00
自引率
4.70%
发文量
638
审稿时长
2.1 months
期刊介绍: Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.
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