Development and application of imaging-based spatial multi-omics

Single-cell sequencing technology enables the acquisition of high-resolution gene expression data from a large number of cells within biological tissues, widely employed in biomedical research. However, this technique inherently lacks spatial information due to cell lysis during the sequencing process, resulting in the absence of cells' in situ spatial positions in the data. The spatial context of cells within their tissue microenvironment is of paramount importance for understanding their roles in physiological and pathological processes. As a result, spatial omics methods that can integrate spatial information are in urgent need in the biomedical field as a fundamental approach.

Drawing on the principles of single-molecule imaging, we have developed a series of original methods, including spatial transcriptomics, spatial proteomics, spatial transcriptome, and spatial multi-omics, and employ these advanced technologies to systematically investigate the spatial heterogeneity underlying processes such as neural network development, aging, and disease progression.