{"title":"Unraveling the molecular dynamics of wound healing: integrating spatially resolved lipidomics and temporally resolved proteomics.","authors":"Hongxia Bai, Alejandra Suarez Arnedo, Yining Liu, Tatiana Segura, David Muddiman","doi":"10.1007/s00216-025-05865-5","DOIUrl":null,"url":null,"abstract":"<p><p>Understanding the spatial-temporal molecular dynamics of wound healing is crucial for devising effective treatments. Three-dimensional mass spectrometry imaging (3D MSI) enables the comprehensive visualization of molecular distribution throughout skin layers, offering valuable insights into the wound healing process. However, traditional 3D MSI often faces challenges in maintaining data integrity and accurate image registration in the third dimension. To address this, we employed infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), a hybrid ambient ionization technique capable of sequential imaging through consecutive ablation events for precise 3D image reconstruction. Herein, 3D IR-MALDESI MSI was used to compare the lipidome of fresh-frozen wound samples at three stages of wound healing (inflammation, proliferation, and remodeling) with the healthy skin of SKH- 1 mice. Supplementing this data with a refined LC-MS-based proteomics protocol on selected wound biopsies, our integrated approach deepens our understanding of the molecular intricacies inherent in tissue regeneration.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"3299-3314"},"PeriodicalIF":3.8000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and Bioanalytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s00216-025-05865-5","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the spatial-temporal molecular dynamics of wound healing is crucial for devising effective treatments. Three-dimensional mass spectrometry imaging (3D MSI) enables the comprehensive visualization of molecular distribution throughout skin layers, offering valuable insights into the wound healing process. However, traditional 3D MSI often faces challenges in maintaining data integrity and accurate image registration in the third dimension. To address this, we employed infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI), a hybrid ambient ionization technique capable of sequential imaging through consecutive ablation events for precise 3D image reconstruction. Herein, 3D IR-MALDESI MSI was used to compare the lipidome of fresh-frozen wound samples at three stages of wound healing (inflammation, proliferation, and remodeling) with the healthy skin of SKH- 1 mice. Supplementing this data with a refined LC-MS-based proteomics protocol on selected wound biopsies, our integrated approach deepens our understanding of the molecular intricacies inherent in tissue regeneration.
期刊介绍:
Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.