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用于空间分辨多组学分子图谱的质谱成像

Mass spectrometry imaging for spatially resolved multi-omics molecular mapping.

作者信息

Zhang Hua, Lu Kelly H, Ebbini Malik, Huang Penghsuan, Lu Haiyan, Li Lingjun

机构信息

School of Pharmacy, University of Wisconsin-Madison, Madison, WI 53705 USA.

Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706 USA.

出版信息

Npj Imaging. 2024;2(1):20. doi: 10.1038/s44303-024-00025-3. Epub 2024 Jul 17.

Abstract

The recent upswing in the integration of spatial multi-omics for conducting multidimensional information measurements is opening a new chapter in biological research. Mapping the landscape of various biomolecules including metabolites, proteins, nucleic acids, etc., and even deciphering their functional interactions and pathways is believed to provide a more holistic and nuanced exploration of the molecular intricacies within living systems. Mass spectrometry imaging (MSI) stands as a forefront technique for spatially mapping the metabolome, lipidome, and proteome within diverse tissue and cell samples. In this review, we offer a systematic survey delineating different MSI techniques for spatially resolved multi-omics analysis, elucidating their principles, capabilities, and limitations. Particularly, we focus on the advancements in methodologies aimed at augmenting the molecular sensitivity and specificity of MSI; and depict the burgeoning integration of MSI-based spatial metabolomics, lipidomics, and proteomics, encompassing the synergy with other imaging modalities. Furthermore, we offer speculative insights into the potential trajectory of MSI technology in the future.

摘要

近期,空间多组学整合用于进行多维信息测量的趋势不断上升,这正在开启生物学研究的新篇章。绘制包括代谢物、蛋白质、核酸等在内的各种生物分子图谱,甚至破译它们的功能相互作用和途径,有望为生命系统内分子复杂性提供更全面、细致入微的探索。质谱成像(MSI)是在不同组织和细胞样本中对代谢组、脂质组和蛋白质组进行空间映射的前沿技术。在本综述中,我们对用于空间分辨多组学分析的不同MSI技术进行了系统概述,阐明了它们的原理、能力和局限性。特别地,我们关注旨在提高MSI分子灵敏度和特异性的方法学进展;描绘基于MSI的空间代谢组学、脂质组学和蛋白质组学的蓬勃整合,包括与其他成像方式的协同作用。此外,我们对MSI技术未来的潜在发展轨迹提出了推测性见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/016e/12118663/aa2db365ead9/44303_2024_25_Fig1_HTML.jpg

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