Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration.

IF 3.4 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Proteomics Pub Date : 2025-05-12 DOI:10.1002/pmic.202400378
Jessica K Lukowski, Byoung-Kyu Cho, Antonia Zamacona Calderon, Borna Dianati, Katherine Stumpo, Savannah Snyder, Young Ah Goo
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引用次数: 0

Abstract

Mass spectrometry has long been utilized to characterize a variety of biomolecules such as proteins, metabolites, and lipids. Most MS-based omics studies rely on bulk analysis; however, bulk approaches often overlook low-abundance molecules that may exert critical biological effects. Recently, multi-omics analyses have been driving an explosion of knowledge about how biomolecules interact within biological systems. In particular, spatial multi-omics has emerged as a groundbreaking approach for implementing multi-omic and multi-modal analyses. Broadly defined, spatial omics has the ability to analyze biomolecules within their native spatial contexts, offering transformative insights. This review focuses on mass spectrometry-based spatial omics, specifically matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We will explore how MALDI-MSI, in combination with laser capture microdissection (LCM) and traditional liquid chromatography-mass spectrometry (LC-MS) workflow, is advancing spatially resolved multi-omics research.

空间多组学研究进展:多模态质谱成像和激光捕获显微解剖- lcms集成综述。
质谱法长期以来被用于表征各种生物分子,如蛋白质、代谢物和脂质。大多数基于ms的组学研究依赖于批量分析;然而,散装方法往往忽略了可能发挥关键生物效应的低丰度分子。最近,多组学分析已经推动了关于生物分子如何在生物系统中相互作用的知识的爆炸。特别是,空间多组学已经成为实施多组学和多模态分析的开创性方法。广义上讲,空间组学具有在其原生空间环境中分析生物分子的能力,提供变革性的见解。本文综述了基于质谱的空间组学,特别是基质辅助激光解吸/电离质谱成像(MALDI-MSI)。我们将探讨MALDI-MSI如何结合激光捕获显微解剖(LCM)和传统的液相色谱-质谱(LC-MS)工作流程,推进空间分辨多组学研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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