Spatially resolved metabolomics: From metabolite mapping to function visualising

IF 7.9 1区医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL

Clinical and Translational Medicine Pub Date : 2024-10-25 DOI:10.1002/ctm2.70031

Xinyue Min, Yiran Zhao, Meng Yu, Wenchao Zhang, Xinyi Jiang, Kaijing Guo, Xiangyi Wang, Jianpeng Huang, Tong Li, Lixin Sun, Jiuming He

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Abstract

Mass spectrometry imaging (MSI)-based spatially resolved metabolomics addresses the limitations inherent in traditional liquid chromatography-tandem mass spectrometry (LC–MS)-based metabolomics, particularly the loss of spatial context within heterogeneous tissues. MSI not only enhances our understanding of disease aetiology but also aids in the identification of biomarkers and the assessment of drug toxicity and therapeutic efficacy by converting invisible metabolites and biological networks into visually rendered image data. In this comprehensive review, we illuminate the key advancements in MSI-driven spatially resolved metabolomics over the past few years. We first outline recent innovations in preprocessing methodologies and MSI instrumentation that improve the sensitivity and comprehensiveness of metabolite detection. We then delve into the progress made in functional visualization techniques, which enhance the precision of metabolite identification and annotation. Ultimately, we discuss the significant potential applications of spatially resolved metabolomics technology in translational medicine and drug development, offering new perspectives for future research and clinical translation.

Highlights

MSI-driven spatial metabolomics preserves metabolite spatial information, enhancing disease analysis and biomarker discovery.
Advances in MSI technology improve detection sensitivity and accuracy, expanding bioanalytical applications.
Enhanced visualization techniques refine metabolite identification and spatial distribution analysis.
Integration of MSI with AI promises to advance precision medicine and accelerate drug development.

Abstract Image

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空间解析代谢组学：从代谢物图谱到功能可视化。

基于质谱成像（MSI）的空间分辨代谢组学解决了传统液相色谱-串联质谱法（LC-MS）代谢组学固有的局限性，特别是异质组织内空间背景的缺失。MSI 通过将不可见的代谢物和生物网络转化为可视化的图像数据，不仅增强了我们对疾病病因的了解，还有助于生物标记物的鉴定以及药物毒性和疗效的评估。在这篇综述中，我们阐述了过去几年 MSI 驱动的空间解析代谢组学的主要进展。我们首先概述了预处理方法和 MSI 仪器方面的最新创新，这些创新提高了代谢物检测的灵敏度和全面性。然后，我们深入探讨了功能可视化技术的进展，这些技术提高了代谢物鉴定和注释的精确度。最后，我们讨论了空间解析代谢组学技术在转化医学和药物开发中的重要潜在应用，为未来的研究和临床转化提供了新的视角。亮点MSI 驱动的空间代谢组学保留了代谢物的空间信息，加强了疾病分析和生物标记物的发现。MSI 技术的进步提高了检测灵敏度和准确性，扩大了生物分析的应用范围。增强的可视化技术完善了代谢物鉴定和空间分布分析。MSI 与人工智能的结合有望推动精准医学的发展并加速药物开发。

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

Clinical and Translational Medicine Multiple-

CiteScore

15.90

自引率

1.90%

发文量

450

审稿时长

4 weeks

期刊介绍： Clinical and Translational Medicine (CTM) is an international, peer-reviewed, open-access journal dedicated to accelerating the translation of preclinical research into clinical applications and fostering communication between basic and clinical scientists. It highlights the clinical potential and application of various fields including biotechnologies, biomaterials, bioengineering, biomarkers, molecular medicine, omics science, bioinformatics, immunology, molecular imaging, drug discovery, regulation, and health policy. With a focus on the bench-to-bedside approach, CTM prioritizes studies and clinical observations that generate hypotheses relevant to patients and diseases, guiding investigations in cellular and molecular medicine. The journal encourages submissions from clinicians, researchers, policymakers, and industry professionals.