Database intro

The kidneys play a critical role in maintaining homeostasis by filtering waste and excess fluids from the blood, regulating electrolyte balance, and controlling blood pressure. Each kidney is comprised of nephrons, which are the functional units responsible for these essential functions. Nephrons consist of several specialized structures that work together to filter blood, reabsorb vital substances, and excrete waste as urine.

The primary filtrating component of nephrons is the renal glomerulus (Glo), which is surrounded by the Bowman's capsule and located in the renal cortex. Following filtration, the processed fluid enters the secondary filtering stage, where reabsorption and further filtration occur. This stage includes various types of tubules:

  • The proximal tubule (PT_S1_S2 and PT_S3), predominantly located in the renal cortex.
  • The loop of Henle (TAL), extending into both the outer and inner regions of the renal medulla.
  • The distal tubule (DCT_CNT), primarily situated in the renal cortex.
  • The collecting duct (CD), present in both the renal cortex and medulla.

These specialized structures work harmoniously with the surrounding renal interstitium (Inter) and urothelium (Uro) to maintain proper kidney function.



Chronic Kidney Disease

Chronic Kidney Disease (CKD) is a progressive condition characterized by the gradual loss of kidney function over time. CKD affects about 10% of the population worldwide and is a significant public health concern due to its high prevalence and association with increased cardiovascular risk and mortality. One of the hallmark features of CKD is the development of renal fibrosis, a pathological process involving the excessive accumulation of extracellular matrix (ECM) proteins in the renal interstitium. Renal fibrosis disrupts the normal architecture of the kidney and impairs its function, ultimately leading to end-stage renal disease (ESRD).

Understanding kidney health and CKD relies on decoding the intricate landscape of cell types, their molecular profiles, and interactions within the tissue microenvironment. Here we present the generation of Spatial-Temporal transcriptOmic Profiling (STOP-CKD) in a mouse CKD model induced by unilateral ureteral obstruction (UUO).

The Visium Platform

The Visium platform by 10x Genomics is an advanced spatial transcriptomics technology that allows high-resolution mapping of gene expression within intact tissue sections. By combining spatial information with RNA sequencing, Visium enables researchers to visualize and quantify the spatial arrangement of distinct cell populations and their gene expression profiles within the tissue microenvironment. This powerful platform enhances our understanding of complex biological processes and disease mechanisms by providing spatial context to gene expression data.

STOP-CKD Database

STOP-CKD comprises comprehensive characterization of the spatial-temporal expression of 18,000 protein-coding genes and over 20,000 functional gene sets over one-week UUO progression. This resource database offers a high-resolution spatial-temporal cellular atlas that characterizes cellular states altered in kidney injury. It details adaptive or maladaptive repair processes, as well as transitioning and degenerative states affecting several nephron segments. These analyses further define biological pathways relevant to injury niches, including molecular signatures underlying the transition from reference to predicted maladaptive states, which are associated with declining kidney function during CKD.

The UUO Model

The Unilateral Ureteral Obstruction (UUO) model is a widely used experimental model for studying kidney disease, particularly renal fibrosis. In this model, one ureter is surgically obstructed, leading to progressive injury and fibrosis in the affected kidney. The UUO model mimics aspects of CKD and allows researchers to investigate the molecular and cellular mechanisms underlying kidney damage and repair. It is valuable for studying the pathophysiology of renal fibrosis and for testing potential therapeutic interventions aimed at preventing or reversing kidney damage.



Using the UUO model at 1 day, 3 days, and 7 days post-obstructive, the STOP-CKD database provides a time-course of kidney injury and fibrosis progression. Early inflammatory responses and tubular cell injury at 1d UUO are followed by progressive inflammation, tubular atrophy, and initial fibrotic changes at 3d UUO. By 7 days UUO, significant fibrosis, severe tubular damage, and functional impairment are evident.



Serial intravital 2-photon microscopy

2-photon microscopy of the kidney is a powerful method that uniquely allows simultaneous investigation of kidney structure and function in the living animal. To track dynamic structural and functional changes after UUO in vivo and over time, we applied serial 2-photon microscopy after implantation of an abdominal imaging window that enabled repeated imaging of the same kidney cells over time. This powerful approach documented tremendous tissue remodeling alongside functional impairment, luminating epithelial metabolic dysfunction, interstitial inflammation, blood flow alterations, and endothelial cell plasticity after UUO.

Left: Sham_D3_3D; Right: UUO_D3_3D


In summary, our STOP-CKD database, generated using the Visium platform from 10x Genomics, provides a valuable resource for understanding the spatial-temporal dynamics of gene expression during kidney injury and repair. This high-resolution atlas offers insights into cellular states and biological pathways involved in CKD, enhancing our ability to investigate potential therapeutic interventions and improve kidney health.







Please cite the STOP-CKD database as:

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Differential Expressed Genes in Selected Region


Type gene symbol for gene of interest for gene summary, statistics, spatial plot and dot plot


Gene Summary


            

Differential expressed genes in different time points compared to sham

* Wilcoxon Rank Sum test were used to identify differentially expressed genes between two groups of Spots
* pct: The percentage of Spots where the gene detected in the group
* avg_log2FC: log fold-chage of the average expression between the two groups.
* p_val_adj: Adjusted p-value, based on bonferroni correction using all genes in the dataset



Spatial gene expression: Spatial plot

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Regional gene expression: Dotplot

Spot information vs gene expression on reduced dimensions

in this section, users can visualise both Spot information and gene expression side-by-side on low-dimensional representions.


Dimension Reduction




Spot information

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Spot numbers / statistics

Gene expression

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Coexpression of two genes on reduced dimensions

in this section, users can visualise the coexpression of two genes on low-dimensional representions.

Dimension Reduction

Gene Expression

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Spot information / gene expression violin plot / box plot

in this section, users can visualise the gene expression or continuous Spot information (e.g. Number of UMIs / module score) across groups of Spots (e.g. libary / clusters).



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Gene expression bubbleplot / heatmap

in this section, users can visualise the gene expression patterns of multiple genes grouped by categorical Spot information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.




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In this section, users can visualise a total of 24604 GeneSet score from MsigDB across groups of Spots (e.g. libary / clusters)

Spatial geneset score: Spatial plot

insert key words for geneset of interest and then select from the pop up list

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GeneSet Score violin plot / box plot





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All rights reserved.

Corresponding authors:

Rikke Nørregaard: rn@clin.au.dk

Yonglun Luo: alun@biomed.au.dk

Lin Lin: lin.lin@biomed.au.dk

Copyright 2022 Steno Diabetes Center Aarhus (SDCA); Aarhus University



Created by DREAMlab, Department of Biomedicine, Aarhus University

Get in touch with us: lin.lin@biomed.au.dk

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