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<p>Recent developments in spatially resolved -omics have enabled the joint study of gene expression, metabolite levels and tissue morphology, offering greater insights into biological pathways. Integrating these modalities from matched tissue sections to probe spatially-coordinated processes, however, remains challenging. Here we introduce MAGPIE, a framework for co-registering spatially resolved transcriptomics, metabolomics, and tissue morphology from the same or consecutive sections. We show MAGPIE’s generalisability and scalability on spatial multi-omics data from multiple tissues, combining Visium with MALDI and DESI mass spectrometry imaging. MAGPIE was also applied to new multi-modal datasets generated with a specialised sampling strategy to characterise the metabolic and transcriptomic landscape in an in vivo model of drug-induced pulmonary fibrosis and to link small-molecule co-detection with endogenous lung responses. MAGPIE demonstrates the refined resolution and enhanced interpretability that spatial multi-modal analyses provide for studying tissue injury especially in pharmacological contexts, and delivers a modular, accessible workflow for data integration.</p>

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Spatially resolved integrative analysis of transcriptomic and metabolomic changes in tissue injury studies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月7日

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  • Eleanor C. Williams,
  • Lovisa Franzén,
  • Martina Olsson Lindvall,
  • Gregory Hamm,
  • Steven Oag,
  • Muntasir Mamun Majumder,
  • James Denholm,
  • Azam Hamidinekoo,
  • Javier Escudero Morlanes,
  • Marco Vicari,
  • Joakim Lundeberg,
  • Laura Setyo,
  • Trevor M. Godfrey,
  • Livia S. Eberlin,
  • Aleksandr Zakirov,
  • Jorrit J. Hornberg,
  • Marianna Stamou,
  • Patrik L. Ståhl,
  • Anna Ollerstam,
  • Jennifer Y. Tan,
  • Irina Mohorianu

摘要

Recent developments in spatially resolved -omics have enabled the joint study of gene expression, metabolite levels and tissue morphology, offering greater insights into biological pathways. Integrating these modalities from matched tissue sections to probe spatially-coordinated processes, however, remains challenging. Here we introduce MAGPIE, a framework for co-registering spatially resolved transcriptomics, metabolomics, and tissue morphology from the same or consecutive sections. We show MAGPIE’s generalisability and scalability on spatial multi-omics data from multiple tissues, combining Visium with MALDI and DESI mass spectrometry imaging. MAGPIE was also applied to new multi-modal datasets generated with a specialised sampling strategy to characterise the metabolic and transcriptomic landscape in an in vivo model of drug-induced pulmonary fibrosis and to link small-molecule co-detection with endogenous lung responses. MAGPIE demonstrates the refined resolution and enhanced interpretability that spatial multi-modal analyses provide for studying tissue injury especially in pharmacological contexts, and delivers a modular, accessible workflow for data integration.