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Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Published on: December 16, 2022

Spatially resolved metabolomics: From metabolite mapping to function visualising.

Xinyue Min^1,2,3, Yiran Zhao^2,3, Meng Yu^2,3

¹School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, China.

Clinical and Translational Medicine

|October 26, 2024

Summary

Mass spectrometry imaging (MSI) spatial metabolomics preserves tissue context, improving disease analysis and biomarker discovery. Advances in MSI technology and AI integration accelerate drug development and precision medicine applications.

Keywords:

clinical translation drug discovery mass spectrometry imaging spatially resolved metabolomics tumour metabolism

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Last Updated: Jun 9, 2025

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

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Published on: December 16, 2022

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

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A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

Area of Science:

Biomedical Imaging
Analytical Chemistry
Metabolomics

Background:

Traditional metabolomics loses spatial context in heterogeneous tissues.
Mass spectrometry imaging (MSI) offers spatially resolved metabolomics.
MSI converts metabolite data into visual images for enhanced analysis.

Purpose of the Study:

Review key advancements in MSI-driven spatially resolved metabolomics.
Highlight innovations in instrumentation, preprocessing, and visualization.
Discuss applications in translational medicine and drug development.

Main Methods:

Review of recent innovations in MSI instrumentation and preprocessing.
Analysis of progress in functional visualization techniques for metabolite identification.
Exploration of AI integration for enhanced data analysis.

Main Results:

MSI preserves metabolite spatial information, crucial for disease etiology and biomarker discovery.
Improved MSI sensitivity and accuracy expand bioanalytical applications.
Enhanced visualization techniques refine metabolite identification and spatial distribution analysis.

Conclusions:

MSI-driven spatial metabolomics provides critical insights into complex biological systems.
Technological advancements are enhancing the precision and scope of MSI applications.
The integration of MSI with AI holds significant promise for precision medicine and drug development.