Spatially resolved transcriptomics for evaluation of intracranial vessels in a rabbit model: Proof of concept.

Abstract

Better understanding of vessel biology and vascular pathophysiology is needed to improve understanding of cerebrovascular disorders. Tissue from diseased vessels can offer the best data. Rabbit models can be effective for studying intracranial vessels, filling gaps resulting from difficulties acquiring human tissue. Spatially-resolved transcriptomics (SRT) in particular hold promise for studying such models as they build on RNA sequencing methods, augmenting such data with histopathology. Rabbit brains with intact arteries were flash frozen, cryosectioned, and stained with H&E to confirm adequate inclusion of intracranial vessels before proceeding with tissue optimization and gene expression analysis using the Visium SRT platform. SRT results were analyzed with k-means clustering analysis, and differential gene expression was examined, comparing arteries to veins. Cryosections were successfully mounted on Visium proprietary slides. Quality control thresholds were met. Optimum permeabilization was determined to be 24 min for the tissue optimization step. In analysis of SRT data, k-means clustering distinguished vascular tissue from parenchyma. When comparing gene expression traits, the most differentially expressed genes were those found in smooth muscle cells. These genes were more commonly expressed in arteries compared to veins. Intracranial vessels from model rabbits can be processed and analyzed with the Visium SRT platform. Face validity is found in the ability of SRT data to distinguish vessels from parenchymal tissue and differential expression analysis accurately distinguishing arteries from veins. SRT should be considered for future animal model investigations into cerebrovascular diseases.