Unified Mouse and Human Kidney Single-Cell Expression Atlas Reveal Commonalities and Differences in Disease States. Unified Mouse and Human Kidney Single-Cell Expression Atlas Reveal Commonalities and Differences in Disease States

Mouse models have been widely used to understand kidney disease pathomechanisms and play an important role in drug discovery. However, these models have not been systematically analyzed and compared. We analyzed single-cell RNA sequencing data (36 samples) and bulk gene expression data (42 samples) from 18 commonly used mouse kidney disease models. We compared single-nucleus RNA sequencing data from a mouse diabetic kidney disease model with data from patients with diabetic kidney disease and healthy controls. We generated a uniformly processed mouse single-cell atlas containing information for nearly 300,000 cells, identifying all major kidney cell types and states. Our analysis revealed that changes in fractions of cell types are major drivers of differences in bulk gene expression. Although gene expression changes at the single-cell level were mostly model-specific, different disease models showed similar changes when compared at a pathway level. Tensor decomposition analysis highlighted the important changes in proximal tubule cells in disease states. Specifically, we identified important alterations in expression of metabolic and inflammation-associated pathways. The mouse diabetic kidney disease model and patients with diabetic kidney disease shared only a small number of conserved cell type-specific differentially expressed genes, but we observed pathway-level activation patterns conserved between mouse and human diabetic kidney disease samples. This study provides a comprehensive mouse kidney single-cell atlas and defines gene expression commonalities and differences in disease states in mice. The results highlight the key role of cell heterogeneity in driving changes in bulk gene expression and the limited overlap of single-cell gene expression changes between animal models and patients, but they also reveal consistent pathway-level changes. Overall design: n=6 mouse kidney scRNA-seq samples: n=2 control, n=1 transgenic overexpression of Notch1, n=2 transgenic overexpression of PGC1a, n=1 Esrra KO

小鼠模型已被广泛用于阐明肾脏疾病的发病机制研究，并在药物研发中发挥关键作用。然而，此类模型尚未得到系统性分析与比对。本研究针对18种常用小鼠肾脏疾病模型的单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）数据（36个样本）及批量基因表达（bulk gene expression）数据（42个样本）开展分析。我们将小鼠糖尿病肾病模型的单细胞核RNA测序数据，与糖尿病肾病患者及健康对照的测序数据进行了比对。本研究构建了经过统一标准化处理的小鼠单细胞转录组图谱，涵盖近30万个细胞的信息，成功鉴定出肾脏所有主要细胞类型与细胞状态。分析结果显示，细胞类型占比的变化是导致批量基因表达差异的核心驱动因素。尽管单细胞水平的基因表达变化大多具有模型特异性，但不同疾病模型在通路层面展现出高度相似的变化模式。张量分解分析揭示了疾病状态下近端肾小管细胞的关键变化，具体而言，我们鉴定出代谢通路与炎症相关通路的表达发生了显著改变。小鼠糖尿病肾病模型与糖尿病肾病患者仅共享少量保守的细胞类型特异性差异表达基因，但我们观察到小鼠与人类糖尿病肾病样本在通路层面的激活模式具有保守性。本研究提供了一套全面的小鼠肾脏单细胞转录组图谱，并明确了小鼠疾病状态下基因表达的共性与差异。研究结果强调了细胞异质性在驱动批量基因表达变化中的关键作用，同时也揭示了动物模型与患者间单细胞基因表达变化的重叠度有限，且展现出通路层面的保守变化。总体实验设计：共计6个小鼠肾脏单细胞RNA测序样本，其中2个为对照样本、1个为Notch1转基因过表达样本、2个为PGC1α转基因过表达样本、1个为Esrra基因敲除样本。