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Integrative spatial metallomics: a tutorial review of multimodal elemental imaging workflows, challenges and opportunities.

Created on 04 Nov 2026

Authors

Naina Kumar, Nishita Paruchuri, Tracy Punshon, Brian Jackson, Kevin Cornell, Elijah Stommel, Hrishikesh Deosthali, Vismay Ravikumar, Engie Mostafa, Scott Palisoul, Louis Vaickus, Sunita Ho, Joshua Levy

Published in

Analytical methods : advancing methods and applications. Nov 04, 2026. Epub Nov 04, 2026.

Abstract

Spatially resolved molecular assays are increasingly used to study human health and disease, revealing complex tissue organization beyond what is accessible through bulk analyses. While spatial transcriptomic, metabolomic, and proteomic approaches have rapidly matured, quantitative mapping of metals and trace elements in biological tissues and biominerals through elemental imaging remains comparatively nascent. Elemental distributions alone often provide limited biological interpretation without contextualization within the tissue microenvironment. Here, we summarize themes and computational strategies for integrating spatial elemental data with histopathology and complementary spatial molecular assays. We highlight multimodal approaches for tissue alignment, pixel-wise clustering, and correlative analysis, illustrated through limited use cases involving amyotrophic lateral sclerosis (ALS) and kidney stone formation. In the ALS cohort, pixel-level elemental profiles were clustered and compared with annotated tissue structures. In the kidney stone cohort, spatial gradients and correlations in elemental and biomolecular features from the renal papilla through the medulla to cortex were examined. Finally, we discuss key challenges for cross-sample, cohort-level analyses, including differences in spatial resolution, normalization, tissue architecture, and mechanistic inference. Addressing these challenges will require interdisciplinary collaboration, enhanced biobanking practices, and development of computational and statistical frameworks.

PMID:
42980369
Bibliographic data and abstract were imported from PubMed on 04 Nov 2026.

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