Application of Single-cell and Spatial Omics Technologies in Ischemic Stroke Research
10.13865/j.cnki.cjbmb.2025.10.1273
- VernacularTitle:单细胞与空间组学技术在缺血性脑卒中研究中的应用
- Author:
Xiao-Xi ZHU
1
;
Cheng WANG
1
;
Li-Mei YU
1
Author Information
1. 遵义医科大学附属医院贵州省生物制造实验室,贵州遵义 563000;遵义医科大学教育部组织损伤修复与再生医学协同创新中心,贵州遵义 563000
- Publication Type:Journal Article
- Keywords:
ischemic stroke(IS);
single-cell omics;
spatial omics;
biomarkers;
precision therapy
- From:
Chinese Journal of Biochemistry and Molecular Biology
2025;41(11):1600-1609
- CountryChina
- Language:Chinese
-
Abstract:
Ischemic stroke(IS)research has faced bottlenecks due to the limitations of conventional technologies in resolving cellular heterogeneity and spatiotemporal dynamics.The development of single-cell and spatial omics technologies provides revolutionary tools to break through these constraints.Single-cell omics technologies,by performing high-throughput sequencing on thousands of cells,reveal the high heterogeneity and dynamic state transitions of neurons,glial cells,immune cells,and others post-IS.For instance,microglia contain pro-inflammatory and anti-inflammatory functional subsets,while astrocytes exhibit distinct activation state spectra.Pseudotime analysis further reconstructs the fate trajectories of cells during the damage and repair processes.Spatial omics technologies,conversely,reconstruct spatial maps of gene expression through in situ capture,elucidating molecular gradients between the ischemic core,penumbra,and healthy brain regions,and enabling the analysis of critical cell-cell interaction net-works.Integrating the deep phenotyping capability of single-cell sequencing with the in situ localization information from spatial omics constitutes the current core strategy.This multimodal analysis allows for precise anchoring of cell subtypes to their spatial microenvironments,revealing their distribution patterns and functions,and constructing a more accurate atlas of cell-cell communication.This significantly ad-vances the refined dissection of IS mechanisms.This strategy has already accelerated the discovery of po-tential biomarkers and spatiotemporally specific therapeutic targets.Although challenges remain in sample preparation,data integration,and technical noise,future interdisciplinary collaboration,multi-omics in-tegration,and in-depth mining with artificial intelligence promise to comprehensively transform our under-standing of IS.Ultimately,it holds the potential to promote advances in its early diagnosis,precise sub-typing,and the development of individualized treatment strategies.
