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Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue
Published on: June 9, 2020
Single cell sequencing and spatial multiomics of diabetic kidney segmentation insights zonation-specific therapeutic
Shi Qiu1, Zhibo Wang1, Sifan Guo1
1International Advanced Functional Omics Platform, Scientific Experiment Center, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases, Hainan Medical University, Xueyuan Road 3, Haikou 571199, Hainan, China.
Abstract:
Diabetic nephropathy (DN) exhibits profound spatial metabolic heterogeneity across kidney regions, yet how compartmentalized pathways drive disease progression remains poorly defined. A deeper understanding of the organizational spatial environment and metabolic pathways of diabetic kidney damage will provide new insights to develop new therapies. By integrating high-resolution spatial multi-omics and single-cell transcriptomics, we mapped region-specific metabolic dysregulation in diabetic kidneys, identifying glutathione metabolism, pentose phosphate, and glycolytic pathways as zonally disrupted in cortical and medullary regions. Spatial metabolomics revealed distinct anatomical clustering of ten clinically associated metabolites, while spatial proteomic profiling uncovered sixty-four region-enriched proteins linked to these pathways. Specifically, depending on anatomic location, spatial protein signatures across multiple regions of diabetic mouse kidneys were enriched in each segmentation, respectively. Cross-species integration identified GPX3 as a fibroblast-enriched biomarker strongly correlated with kidney dysfunction and closely related to clinical indicators. Notably, astragaloside IV (ASIV) treatment reversed spatial metabolic perturbations in diabetic mice, restoring glutathione and glycolytic pathway activity in a compartment-specific manner. Single-cell analyses identified five cell types-endothelial cells, fibroblasts, epithelial cells, macrophages and neutrophils-and further revealed fibroblasts as key contributors to regulatory effects via GPX3 overexpression. Importantly, the higher expression of Gpx3 in fibroblasts compared to other cell types, Gpx3 (AUC = 0.995), was further validated, demonstrating the high sensitivity and specificity for DN patients. This multimodal atlas establishes the spatially resolved metabolic blueprint of DN, bridging molecular zoning with anatomical localization of renal tissue to unveil actionable therapeutic targets for metabolic disorders in kidney disease.
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