Single-cell spatial transcriptomics and proteomics of APOE Christchurch in 5xFAD and PS19 mice

This collection of datasets comprises results from four single-cell spatial experiments conducted on mouse brains: two spatial transcriptomics experiments and two spatial proteomics experiments. These experiments were performed using the Bruker Nanostring CosMx technology on 10µm coronal brain sections from the following mouse models: (1) 14-month-old male 5xFAD;ApoeCh mice and genotype controls, and (2) 9-month-old PS19;ApoeCh mice and genotype controls. Each dataset is provided as an RDS file which includes raw and corrected counts for the RNA data and mean fluorescent intensity for the protein data, along with comprehensive metadata. Metadata includes mouse genotype, sample ID, cell type annotations, sex (for PS19;ApoeCh dataset), and X-Y coordinates of each cell. Results from differential gene expression analysis for each cell type between genotypes using MAST are also included as .csv files.

Methods
Sample preparation: Isopentane fresh-frozen brain hemispheres were embedded in optimal cutting temperature (OCT) compound (Tissue-Tek, Sakura Fintek, Torrance, CA), and 10µm thick coronal sections were prepared using a cryostat (CM1950, LeicaBiosystems, Deer Park, IL). Six hemibrains were mounted onto each VWR Superfrost Plus microscope slide (Avantor, 48311-703) and kept at -80°C until fixation. For both 5xFAD (14 months old, males) and PS19 (9 months old, females and 1 male ApoeCh) models, n=3 mice per genotype except for n=2 for PS19;ApoeCh (wild-type, ApoeCh HO, 5xFAD HEMI or PS19 HEMI, and 5xFAD HEMI; ApoeCh HO or PS19 HEMI;ApoeCh HO) were used for transcriptomics and proteomics. The same mice were used for both transcriptomics and proteomics. Tissues were processed according to the Nanostring CosMx fresh-frozen slide preparation manual for RNA and protein assays (NanoString University).

Data processing: Spatial transcriptomics datasets were filtered using the AtoMx RNA Quality Control module to flag outlier negative probes (control probes targeting non-existent sequences to quantify non-specific hybridization), lowly-expressing cells, FOVs, and target genes. Datasets were then normalized and scaled using Seurat 5.0.1 SCTransform to account for differences in library size across cell types [31]. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were performed to reduce dimensionality and visualize clusters in space. Unsupervised clustering at 1.0 resolution yielded 33 clusters for the 5xFAD dataset and 40 clusters for the PS19 dataset. Clusters were manually annotated based on gene expression and spatial location.

Spatial proteomics data were filtered using the AtoMx Protein Quality Control module to flag unreliable cells based on segmented cell area, negative probe expression, and overly high/low protein expression. Mean fluorescence intensity data were hyperbolic arcsine transformed with the AtoMx Protein Normalization module. Cell types were automatically annotated based on marker gene expression using the CELESTA algorithm.

本数据集集合包含四项针对小鼠大脑的单细胞空间实验结果，其中两项为空间转录组学（spatial transcriptomics）实验，两项为空间蛋白质组学（spatial proteomics）实验。这些实验均采用布鲁克（Bruker）Nanostring CosMx技术完成，实验样本来自以下两种小鼠模型的10μm厚冠状脑切片：(1) 14月龄雄性5xFAD;ApoeCh小鼠及其基因型对照小鼠，(2) 9月龄PS19;ApoeCh小鼠及其基因型对照小鼠。

每个数据集均以RDS文件格式提供，其中包含RNA数据的原始计数与校正后计数、蛋白质数据的平均荧光强度，以及完整元数据（metadata）。元数据涵盖小鼠基因型、样本ID、细胞类型注释、（PS19;ApoeCh数据集的）性别信息，以及每个细胞的X-Y坐标。此外，还提供了使用MAST工具针对不同基因型间各细胞类型开展差异基因表达分析（differential gene expression analysis）所得结果的.csv格式文件。

方法
样本制备：将经异戊烷新鲜冰冻的大脑半球包埋于最优切割温度（optimal cutting temperature，OCT）胶（Tissue-Tek，Sakura Fintek，美国加利福尼亚州托伦斯市），使用冷冻切片机（CM1950，LeicaBiosystems，美国伊利诺伊州迪尔帕克市）制备厚度为10μm的冠状切片。将6个半脑样本固定于每张VWR Superfrost Plus显微镜载玻片（Avantor，48311-703）上，并置于-80℃保存直至固定步骤。针对5xFAD模型（14月龄，雄性）与PS19模型（9月龄，雌性及1只雄性ApoeCh小鼠），除PS19;ApoeCh组（野生型、ApoeCh纯合子、5xFAD半合子或PS19半合子，以及5xFAD半合子;ApoeCh纯合子或PS19半合子;ApoeCh纯合子）每组n=2外，其余基因型组小鼠样本量均为n=3。转录组学与蛋白质组学实验使用同一批小鼠。组织处理流程严格遵循Nanostring CosMx新鲜冰冻切片RNA与蛋白质检测制备手册（NanoString University）。

数据处理：空间转录组学数据集通过AtoMx RNA质量控制模块进行过滤，以标记异常阴性探针（靶向非存在序列的对照探针，用于量化非特异性杂交信号）、低表达细胞、视野（Field of View，FOV）及靶基因。随后采用Seurat 5.0.1的SCTransform方法对数据进行归一化与缩放，以校正不同细胞类型间的文库大小差异[31]。通过主成分分析（Principal Component Analysis，PCA）与均匀流形近似与投影（Uniform Manifold Approximation and Projection，UMAP）分析实现降维，并可视化空间聚类。以1.0的分辨率开展无监督聚类，5xFAD数据集共得到33个聚类，PS19数据集共得到40个聚类。聚类结果基于基因表达模式与空间位置进行人工注释。

空间蛋白质组学数据通过AtoMx蛋白质质量控制模块进行过滤，基于分割后的细胞面积、阴性探针表达量以及过高/过低的蛋白质表达量标记不可靠细胞。采用AtoMx蛋白质归一化模块对平均荧光强度数据进行双曲反正弦变换。基于标记基因表达量，采用CELESTA算法自动完成细胞类型注释。