Smart Spatial Omics (S2-Omics) Optimizes Region of Interest Selection To Capture Molecular Heterogeneity in Diverse Tissues

Authors

Musu Yuan
Kaitian Jin
Hanying Yan
Amelia Schroeder
Chunyu Luo
Sicong Yao
Bernhard Dumoulin
Jonathan Levinsohn
Tianhao Luo
Jean R Clemenceau
Inyeop Jang
Minji Kim
Yunhe Liu
Minghua Deng
Emma E Furth
Parker Wilson
Anupma Nayak
Idania Lubo
Luisa Maren Solis Soto
Linghua Wang
Jeong Hwan Park
Katalin Susztak
Tae Hyun Hwang
Mingyao Li

Language

English

Publication Date

12-1-2025

Journal

Nature Cell Biology

DOI

10.1038/s41556-025-01811-w

PMID

41298871

PMCID

PMC12662399

PubMedCentral® Posted Date

11-26-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Spatial omics technologies have transformed biomedical research by enabling high-resolution molecular profiling while preserving the native tissue architecture. These advances provide unprecedented insights into tissue structure and function. However, the high cost and time-intensive nature of spatial omics experiments necessitate careful experimental design, particularly in selecting regions of interest (ROIs) from large tissue sections. Currently, ROI selection is performed manually, which introduces subjectivity, inconsistency and a lack of reproducibility. Previous studies have shown strong correlations between spatial molecular patterns and histological features, suggesting that readily available and cost-effective histology images can be leveraged to guide spatial omics experiments. Here we present Smart Spatial omics (S2-omics), an end-to-end workflow that automatically selects ROIs from histology images with the goal of maximizing molecular information content in the ROIs. Through comprehensive evaluations across multiple spatial omics platforms and tissue types, we demonstrate that S2-omics enables systematic and reproducible ROI selection and enhances the robustness and impact of downstream biological discovery.

Keywords

Animals, Humans, Reproducibility of Results, Mice, Genomics, Proteomics, Workflow, Transcriptomics, Computational biology and bioinformatics, Biotechnology

Published Open-Access

yes

Recommended Citation

Yuan, Musu; Jin, Kaitian; Yan, Hanying; et al., "Smart Spatial Omics (S2-Omics) Optimizes Region of Interest Selection To Capture Molecular Heterogeneity in Diverse Tissues" (2025). Faculty, Staff and Student Publications. 6767.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6767