Back

Spatiotemporal transcriptomic analysis during cold ischemic injury to the murine kidney reveals compartment-specific changes

Singh, S.; Patel, S. K.; Matsuura, R.; Velazquez, D.; Sun, Z.; Noel, S.; Rabb, H.; Fan, J.

2026-04-18 bioinformatics
10.1101/2025.05.25.654911 bioRxiv
Show abstract

Background: Kidney transplantation is the preferred treatment strategy for end-stage kidney disease. Deceased donor kidneys usually undergo cold storage until kidney transplantation, leading to cold ischemia injury that may contribute to poor graft outcomes. However, the molecular characterization of potential mechanisms of cold ischemia injury remains incomplete. Results: To bridge this knowledge gap, we leveraged the 10x Visium spatial transcriptomic technology to perform full transcriptome profiling of murine kidneys subject to varying durations of cold ischemia typical in a deceased donor kidney transplant setting. We developed a computational workflow to identify and compare spatiotemporal transcriptomic changes that accompany the injury pathophysiology in a tissue compartment-specific manner. We identified proportional enrichment of oxidative phosphorylation (OXPHOS) genes with increasing duration of cold ischemia injury within the oxygen-lean inner medulla region, suggestive of atypical metabolic presentation. This was distinct in cold ischemia injury tissue compared to warm ischemia-reperfusion kidney injury tissue. Spatiotemporal trends were validated by qPCR and immunofluorescence in a larger cohort of mice. We provide an interactive online browser at https://jef.works/CellCarto-ColdIschemia/ to facilitate exploration of our results by the broader scientific and clinical community. Conclusions: Altogether, our spatiotemporal transcriptomic analysis identified coordinated molecular changes within metabolic pathways such as OXPHOS deep within the cold ischemic kidney, highlighting the need for increased attention to the inner medulla and potential opportunities for new insights beyond those available from superficial biopsy-focused tissue examinations.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
Scientific Reports
3102 papers in training set
Top 7%
9.5%
2
JCI Insight
241 papers in training set
Top 0.4%
7.1%
3
Journal of Translational Medicine
46 papers in training set
Top 0.1%
5.0%
4
Transplantation
13 papers in training set
Top 0.1%
5.0%
5
PLOS ONE
4510 papers in training set
Top 33%
4.5%
6
American Journal of Transplantation
15 papers in training set
Top 0.1%
3.8%
7
BMC Nephrology
13 papers in training set
Top 0.1%
3.7%
8
Journal of the American Society of Nephrology
52 papers in training set
Top 0.3%
3.4%
9
International Journal of Molecular Sciences
453 papers in training set
Top 3%
3.4%
10
Kidney360
22 papers in training set
Top 0.3%
2.8%
11
Frontiers in Physiology
93 papers in training set
Top 2%
2.2%
50% of probability mass above
12
Nature Communications
4913 papers in training set
Top 48%
2.0%
13
Communications Biology
886 papers in training set
Top 7%
1.8%
14
Genome Medicine
154 papers in training set
Top 4%
1.8%
15
Computational and Structural Biotechnology Journal
216 papers in training set
Top 4%
1.8%
16
Clinical and Translational Science
21 papers in training set
Top 0.5%
1.5%
17
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 2%
1.4%
18
Frontiers in Veterinary Science
30 papers in training set
Top 0.5%
1.3%
19
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 6%
1.3%
20
Frontiers in Genetics
197 papers in training set
Top 7%
1.2%
21
Kidney International
25 papers in training set
Top 0.3%
1.2%
22
The Journal of Infectious Diseases
182 papers in training set
Top 4%
1.2%
23
Frontiers in Immunology
586 papers in training set
Top 6%
1.0%
24
Advanced Science
249 papers in training set
Top 15%
1.0%
25
Cell Reports Medicine
140 papers in training set
Top 6%
1.0%
26
Frontiers in Pharmacology
100 papers in training set
Top 4%
0.9%
27
iScience
1063 papers in training set
Top 25%
0.9%
28
eBioMedicine
130 papers in training set
Top 3%
0.8%
29
Disease Models & Mechanisms
119 papers in training set
Top 2%
0.8%
30
Journal of Extracellular Vesicles
50 papers in training set
Top 0.3%
0.8%