Imaging Mass Spectrometry of Biological Tissues

生物组织的成像质谱分析

• 批准号: RGPIN-2017-05584
• 负责人: Yeung, Ken
• 金额: $ 2.04万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711476
• 关键词: Imaging; Mass; Spectrometry; Biological; Tissues

Imaging Mass Spectrometry of Biological Tissues Mass spectrometry is a powerful analytical tool for the identification and quantification of chemical molecules from a sample. It operates by separating and measuring the molecular masses of these chemicals. To perform matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of biological tissues, the sampling of chemicals is focused to a very small area of a tissue section (< 0.1 mm) using a laser beam. In a spot-by-spot (or pixel-by-pixel) fashion, the abundances and masses of the chemicals on the tissue are recorded. The data set is then displayed as heat maps to reveal the 2-dimensional distribution of any detected molecules. When combined with strategically designed sample treatment, researchers are able to correlate the changes in molecular distribution to biological functions. Ideally, statistical software should be able to identify changes in a non-targeted and unbiased manner. In practice, the presence of chemical noise, signals that do not directly originate from the analytes, can drown out small changes in analyte signals, making them undetectable by statistical tools. This is particularly problematic for the IMS of low molecular weight (MW) compounds, because the chemical matrix required to promote the laser ionization of analytes can generate a substantial level of background noise in the low-MW region. This region consists of many important metabolites and signaling molecules, such as biogenic amines and neurotransmitters. Hence, further research is needed to improve IMS for the non-targeted profiling of these small analytes. This research grant will support the exploration of three approaches to improve the quality of tissue IMS in the low-MW region. Firstly, novel materials are proposed as the laser absorbing matrices which will reduce chemical noise. Studies will focus on the use of metal oxide nanoparticles, and their uniform application on the tissue surfaces, to facilitate the analysis of low-MW metabolites and neurotransmitters in rat brain tissue. The second approach is to derivatize the analytes with on-tissue chemical reactions, to enhance the ionization efficiency, and to label them for differentiation from background. Finally, post-analysis data processing will remove the matrix-related background noise. Identification of background noise signals will be assisted with the use of matrix compounds labeled with special isotopes. Together, the three proposed approaches will significantly improve the quality of IMS in the non-targeted profiling low-MW chemicals in tissue.

生物组织的成像质谱 质谱法是用于从样品中鉴定和定量化学分子的强大分析工具。 它通过分离和测量这些化学物质的分子量来工作。 为了进行生物组织的基质辅助激光解吸/电离成像质谱（MALDI IMS），使用激光束将化学品的采样聚焦到组织切片的非常小的区域（< 0.1 mm）。以逐点（或逐像素）的方式，记录组织上化学物质的丰度和质量。然后将数据集显示为热图，以揭示任何检测到的分子的二维分布。当与策略性设计的样品处理相结合时，研究人员能够将分子分布的变化与生物功能相关联。理想情况下，统计软件应该能够以非目标和无偏见的方式识别变化。在实践中，化学噪声的存在，不直接源自分析物的信号，可以淹没分析物信号中的微小变化，使其无法通过统计工具检测到。这对于低分子量（MW）化合物的IMS尤其成问题，因为促进分析物的激光电离所需的化学基质可在低MW区域中产生显著水平的背景噪声。该区域由许多重要的代谢物和信号分子组成，如生物胺和神经递质。因此，需要进一步的研究来改进IMS用于这些小分析物的非靶向分析。 该研究基金将支持三种方法的探索，以提高低分子量地区组织IMS的质量。首先，提出了新型材料作为激光吸收基质，这将降低化学噪声。研究将集中在金属氧化物纳米粒子的使用，以及它们在组织表面的均匀应用，以促进大鼠脑组织中低分子量代谢物和神经递质的分析。第二种方法是用组织上的化学反应衍生分析物，以提高电离效率，并标记它们以与背景区分。最后，分析后的数据处理将去除与基质相关的背景噪声。背景噪声信号的识别将通过使用特殊同位素标记的基质化合物来辅助。总之，这三种方法将显著提高IMS在组织中非靶向分析低分子量化学品方面的质量。