Wang Zixuan, Yang Ran, Zhang Yaxin, Hui Xiangyi, Yan Liuyan, Zhang Ruiping, Li Xin, Abliz Zeper
State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Center for Imaging and Systems Biology, Minzu University of China, Beijing, China.
Front Chem. 2021 Dec 21;9:807868. doi: 10.3389/fchem.2021.807868. eCollection 2021.
Mass spectrometry imaging (MSI) serves as an emerging tool for spatial profiling of metabolic dysfunction in ischemic tissue. Prior to MSI data analysis, commonly used staining methods, e.g., triphenyltetrazole chloride (TTC) staining, need to be implemented on the adjacent tissue for delineating lesion area and evaluating infarction, resulting in extra consumption of the tissue sample as well as morphological mismatch. Here, we propose an ratiometric MSI method for simultaneous demarcation of lesion border and spatial annotation of metabolic and enzymatic signatures in ischemic tissue on identical tissue sections. In this method, the ion abundance ratio of a reactant pair in the TCA cycle, e.g., fumarate to malate, is extracted pixel-by-pixel from an ambient MSI dataset of ischemic tissue and used as a surrogate indicator for metabolic activity of mitochondria to delineate lesion area as if the tissue has been chemically stained. This method is shown to be precise and robust in identifying lesions in brain tissues and tissue samples from different ischemic models including heart, liver, and kidney. Furthermore, the proposed method allows screening and predicting metabolic and enzymatic alterations which are related to mitochondrial dysfunction. Being capable of concurrent lesion identification, metabolomics analysis, and screening of enzymatic alterations, the ratiometric MSI method bears great potential to explore ischemic damages at both metabolic and enzymatic levels in biological research.
质谱成像(MSI)是一种新兴工具,用于对缺血组织中的代谢功能障碍进行空间分析。在进行MSI数据分析之前,通常需要在相邻组织上采用常用的染色方法,如氯化三苯基四氮唑(TTC)染色,以划定病变区域并评估梗死情况,这会导致组织样本的额外消耗以及形态学上的不匹配。在此,我们提出一种比率型MSI方法,用于在同一组织切片上同时划定缺血组织中病变边界以及对代谢和酶特征进行空间标注。在该方法中,从缺血组织的环境MSI数据集中逐像素提取三羧酸循环中反应物对的离子丰度比,例如富马酸与苹果酸的离子丰度比,并将其用作线粒体代谢活性的替代指标,从而划定病变区域,就好像组织已进行化学染色一样。结果表明,该方法在识别来自不同缺血模型(包括心脏、肝脏和肾脏)的脑组织和组织样本中的病变时精确且稳健。此外,所提出的方法能够筛选和预测与线粒体功能障碍相关的代谢和酶改变。比率型MSI方法能够同时进行病变识别、代谢组学分析以及酶改变的筛选,在生物学研究中具有在代谢和酶水平上探索缺血损伤的巨大潜力。