Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications.
Key defatting tissue pretreatment protocol for enhanced MALDI MS Imaging of peptide biomarkers visualization in the castor beans and their attribution applications.
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DOI：
10.3389/fpls.2022.1083901
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发表时间：
2022
影响因子：
5.6
通讯作者：
中科院分区：
文献类型：
--
作者：
蓖麻毒素中毒或暴恐事件已经威胁到公共安全和社会安全。潜在的资源或材料包括豆类、粗提取产品、粗毒素和纯化蓖麻毒素。因此，追踪蓖麻子的起源对于法医和反恐调查至关重要。基质辅助激光解吸电离质谱成像（MALDI-MSI）作为一种新型的无标记、快速、高通量的成像技术，在植物研究中逐渐受到重视。然而，植物组织的样品制备方法仍然面临着严峻的挑战，特别是对于一些富含脂质，富含水或脆弱的组织。适当的组织清洗程序将是关键，但迄今为止所知甚少。对于含有大量脂质的蓖麻子，这些脂质在处理时是脆弱的，我们开发了一种全面的组织预处理方案。详细讨论了八种旨在去除脂质的洗涤程序。然后，我们构建了一个强大的MALDI-MSI方法，以提高蓖麻籽中RCBs的检测灵敏度。选择改良的六步洗涤程序作为关于肽的MSI可视化的最关键参数。该方法进一步应用于可视化和定量防御肽，蓖麻生物标志物（RCB）蓖麻子组织切片从9个不同的地理来源，来自中国，巴基斯坦和埃塞俄比亚。包括深度学习网络在内的多元统计模型揭示了有关国籍和海拔高度的有价值的分类线索。
Castor bean or ricin-induced intoxication or terror events have threatened public security and social safety. Potential resources or materials include beans, raw extraction products, crude toxins, and purified ricin. The traceability of the origins of castor beans is thus essential for forensic and anti-terror investigations. As a new imaging technique with label-free, rapid, and high throughput features, matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) has been gradually stressed in plant research. However, sample preparation approaches for plant tissues still face severe challenges, especially for some lipid-rich, water-rich, or fragile tissues. Proper tissue washing procedures would be pivotal, but little information is known until now. For castor beans containing plenty of lipids that were fragile when handled, we developed a comprehensive tissue pretreatment protocol. Eight washing procedures aimed at removing lipids were discussed in detail. We then constructed a robust MALDI-MSI method to enhance the detection sensitivity of RCBs in castor beans. A modified six-step washing procedure was chosen as the most critical parameter regarding the MSI visualization of peptides. The method was further applied to visualize and quantify the defense peptides, Ricinus communis biomarkers (RCBs) in castor bean tissue sections from nine different geographic sources from China, Pakistan, and Ethiopia. Multivariate statistical models, including deep learning network, revealed a valuable classification clue concerning nationality and altitude.
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DOI：
10.3760/cma.j.issn.0529-5807.2019.03.017
发表时间：
2019-03-08
期刊：
Zhonghua bing li xue za zhi = Chinese journal of pathology
影响因子：
--
作者：
Ding, W;Zhou, L X;Zhang, S
通讯作者：
Zhang, S
影响因子：
3.6
作者：
Pigott, Eloise J.;Roberts, Warren;Bourne, David J.
通讯作者：
Bourne, David J.
影响因子：
6.1
作者：
Fredriksson, Sten-Ake;Wunschel, David S.;Astot, Crister
通讯作者：
Astot, Crister
影响因子：
3.6
作者：
Sturtevant, Drew;Romsdahl, Trevor B.;Chapman, Kent D.
通讯作者：
Chapman, Kent D.
影响因子：
5.8
作者：
Behrmann, Jens;Etmann, Christian;Maass, Peter
通讯作者：
Maass, Peter