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

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.

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Publication Details

Journal
Nature Communications
Published
2026-01-07
DOI
https://doi.org/10.1038/s41467-025-68003-w
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
22.24
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article

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

Azam Hamidinekoo, Irina Mohorianu, Grégory Hamm, Steven Oag et al.
1 citations
Nature Communications
Single-cell and spatial transcriptomics
22.24
article

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

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

Abstract

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.

Nature CommunicationsVol. 17(1)
AstraZeneca (United Kingdom) (GB), Baylor College of Medicine (US), Wellcome/MRC Cambridge Stem Cell Institute (GB), University of Cambridge (GB), Science for Life Laboratory (SE), Karolinska Institutet (SE), AstraZeneca (Australia) (AU), AstraZeneca (Finland) (FI), AstraZeneca (Sweden) (SE), KTH Royal Institute of Technology (SE)
Good health and well-being
Openalex Percentile: Top 3%
Single-cell and spatial transcriptomics
22.24
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