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Spatial multiomics in biomedical research: advances beyond transcriptomics
Xinchen Mao, Zhuo Chen, Emily J. Hwang, Jun Liu, Junrou Huang, Haikuo Li
Xinchen Mao, Zhuo Chen, Emily J. Hwang, Jun Liu, Junrou Huang, Haikuo Li
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Review

Spatial multiomics in biomedical research: advances beyond transcriptomics

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Abstract

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Authors

Xinchen Mao, Zhuo Chen, Emily J. Hwang, Jun Liu, Junrou Huang, Haikuo Li

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Figure 4

Overview of spatial metabolomics methods.

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Overview of spatial metabolomics methods.
On the left, MS imaging (MSI) ...
On the left, MS imaging (MSI) approaches, including matrix-assisted laser desorption/ionization MSI (MALDI-MSI) and desorption electrospray ionization MSI (DESI-MSI), acquire pixel-resolved mass spectra to generate spatially resolved metabolite ion maps. In the middle, label-free optical metabolomics, such as Raman and stimulated Raman scattering (SRS), second harmonic generation (SHG) microscopy, and two-photon fluorescence (TPEF), captures lipid and redox signatures, ECM architecture, and autofluorescence-based metabolic features. On the right, computational pipelines integrate preprocessed intensity matrices with manifold-based spatial embedding and multivariate modeling to derive spatially resolved maps of metabolic reprogramming, ischemic niches, drug distribution, and cell-state organization.

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ISSN 2379-3708

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