Spatially resolved transcriptomics in the APPSWE [Tg2576] mouse model of Alzheimer’s disease

Abstract

AbstractBackgroundAlzheimer's and other neurodegenerative diseases remain pervasive, impacting patients and their families as the disease progresses. Despite the continual expansion of our understanding of these conditions, the detailed molecular mechanisms and progression of pathology throughout the brain remain elusive and complex. Using genomic and RNA‐seq approaches, identification of individual cells and their genetic makeup provide an added perspective on their roles in how the central nervous system (CNS) function in both healthy and diseased states. Here we demonstrate the characterization of spatial transcriptomic patterns in the APPSWE [Tg2576] mouse model of familial Alzheimer’s Disease using the Visium Spatial Gene Expression Solution.MethodSerial sections of fresh‐frozen transgenic APPSWE [Tg2576] and littermate control mouse brains were placed onto Visium Spatial Gene Expression slides. The slides consist of ∼5,000 spot arrays with uniquely barcoded probes allowing for the capture of native mRNA. The samples were H&E or immunostained and then permeabilized, allowing for the capture of transcripts and library generation. The resulting libraries were then sequenced on an Illumina NovaSeq. Then, using the 10x Genomics Space Ranger analysis pipeline and the Loupe Browser desktop software, the RNA‐seq data were merged with stained tissue images to align reads, perform clustering, and gene expression analysis.ResultWith the generated data, we demonstrated an improved version of the spotted oligo array technology that increases tissue coverage and spatial resolution with reduced spot size, and increased spot number and packing density. We captured spatial patterns of gene expression and mapped the information back to H&E and immunostained images with regional annotations. Performing differential analysis on the resulting spatial gene expression data, we observed elevated expression of the Pmch (pro‐melanin concentrating hormone) gene within the hypothalamic region of APPSWE [Tg2576] transgenic mice compared to the littermate controls. By immunofluorescence staining, we confirmed the gene expression patterns and utilized this approach to identify the cells and refine the gene expression characterization.ConclusionTogether, this confluence of imaging and sequencing is a valuable tool for understanding the relationships between CNS cell types in healthy and diseased samples with an unbiased anatomical and gene expression‐driven method.