BackgroundLittle is known about the roles of myeloid cell subsets in kidney injury and in the limited ability of the organ to repair itself. Characterizing these cells based only on surface markers using flow cytometry might not provide a full phenotypic picture. Defining these cells at the single-cell, transcriptomic level could reveal myeloid heterogeneity in the progression and regression of kidney disease.MethodsIntegrated droplet– and plate-based single-cell RNA sequencing were used in the murine, reversible, unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single-cell level during renal injury and the resolution of fibrosis. Paired blood exchange tracked the fate of monocytes recruited to the injured kidney.ResultsA single-cell atlas of the kidney generated using transcriptomics revealed marked changes in the proportion and gene expression of renal cell types during injury and repair. Conventional flow cytometry markers would not have identified the 12 myeloid cell subsets. Monocytes recruited to the kidney early after injury rapidly adopt a proinflammatory, profibrotic phenotype that expresses Arg1, before transitioning to become Ccr2+ macrophages that accumulate in late injury. Conversely, a novel Mmp12+ macrophage subset acts during repair.ConclusionsComplementary technologies identified novel myeloid subtypes, based on transcriptomics in single cells, that represent therapeutic targets to inhibit progression or promote regression of kidney disease.
Short running title: Myeloid cell heterogeneity in kidney injury and repair Corresponding authors: Bryan Conway (Bryan.Conway@ed.ac.uk), Eoin O'Sullivan (Eoin.osullivan@ed.ac.uk), Tamir Chandra (Tamir.Chandra@ed.ac.uk) Laura Denby (Laura.Denby@ed.ac.uk) Word Count = 4810 Number of figures = 8 2 AbstractThe kidney has a limited capacity to repair following injury, however, the endogenous reparative pathways are not well understood. Here we employ integrated droplet-and platebased scRNA-seq in the murine reversible unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single cell level during renal injury and resolution of fibrosis.We generate a comprehensive catalogue of the changes induced during injury and repair, revealing significant myeloid cell heterogeneity, which would not have been identifiable by conventional flow cytometry. We identify new markers for the myeloid populations within the kidney as well as identification of novel subsets including an Arg1 + monocyte population specific to early injury and a Mmp12 + macrophage subset exclusive to repair. Finally, using paired blood exchange to track circulating immune cells, we confirm that monocytes are recruited to the kidney early after injury and are the source of Ccr2 + macrophages that accumulate in late injury. Our data demonstrate the utility of complementary technologies to identify novel myeloid subtypes that may represent therapeutic targets to inhibit progression or promote regression of kidney disease. Methods Animal modelsAll protocols and surgical procedures were approved by the Animal Ethics Committee, University of Edinburgh. Animal experiments were conducted in accordance with the Animals Scientific Procedures Act UK 1986, under Home Office project licenses 70/8093 and 70/8867. Reversible unilateral ureteric obstruction model (R-UUO)The R-UUO model was performed as previously described (33). Briefly, 8 week old male C57BL/6JOlaHsd mice (Enviago) underwent laparotomy and the left ureter was isolated and the distal portion was ligated twice with 6/O black braided silk suture close to the bladder. In
Chronic kidney disease (CKD) is prevalent worldwide and is associated with significant co-morbidities including cardiovascular disease (CVD). Traditionally, the subtotal nephrectomy (remnant kidney) experimental model has been performed in rats to model progressive renal disease. The model experimentally mimics CKD by reducing nephron number, resulting in renal insufficiency. Presently, there is a lack of translation of pre-clinical findings into successful clinical results. The pre-clinical nephrology field would benefit from reproducible progressive renal disease models in mice in order to avail of more widely available transgenics and experimental tools to dissect mechanisms of disease. Here we evaluate if a simplified single step subtotal nephrectomy (STNx) model performed in the 129S2/SV mouse can recapitulate the renal and cardiac changes observed in patients with CKD in a reproducible and robust way. The single step STNx surgery was well-tolerated and resulted in clinically relevant outcomes including hypertension, increased urinary albumin:creatinine ratio, and significantly increased serum creatinine, phosphate and urea. STNx mice developed significant left ventricular hypertrophy without reduced ejection fraction or cardiac fibrosis. Analysis of intra-renal inflammation revealed persistent recruitment of Ly6Chi monocytes transitioning to pro-fibrotic inflammatory macrophages in STNx kidneys. Unlike 129S2/SV mice, C57BL/6 mice exhibited renal fibrosis without proteinuria, renal dysfunction, or cardiac pathology. Therefore, the 129S2/SV genetic background is susceptible to induction of progressive proteinuric renal disease and cardiac hypertrophy using our refined, single-step flank STNx method. This reproducible model could be used to study the systemic pathophysiological changes induced by CKD in the kidney and the heart, intra-renal inflammation and for testing new therapies for CKD.
Introduction MicroRNAs are promising biomarkers of renal disease, however the cellular origin of their expression is usually unclear limiting their interpretation when measured in renal biopsies and urine. We hypothesised that by first defining renal cell-enriched microRNAs, we could select biomarkers based on the expected histopathological profile. Method Small RNA-sequencing of cortical, proximal tubular (LTL), macrophage (F480), endothelial (CD31) and fibroblast (PDGFRb) populations from the reversible unilateral ureteric obstruction (rUUO) murine model was performed. Hierarchical clustering was used to identify clusters. Findings were translated into an ischaemia reperfusion injury (IRI) model and then into urine samples from renal transplant recipients (n=16) with delayed graft function (DGF) vs. those with primary function. Result Kidney injury resulted in significant macrophage infiltration and tubular injury which improved upon reversal. We characterised novel microRNA clusters enriched for each cell type. With injury there was a significant increase in macrophage (p<0.0001), fibroblast (p<0.01) and decrease in proximal tubule (p<0.0001) enriched microRNAs vs. non-enriched microRNAs. We validated macrophage enriched miR-18a, miR-16 and tubular enriched miR-194 in the IRI model, demonstrating that microRNA expression reflected the histological profile. In humans, urinary miR-16 (FC 16.9; p<0.05) and miR-18a (FC 10: p=0.06) were upregulated at day 2 in patients with DGF; outperforming the traditional injury marker KIM1. Conclusion This is the first study to characterise cell-enriched microRNAs during renal injury and repair. By defining the source of microRNA expression we were able to rationally select miR-16 and miR-18a as promising urinary biomarkers of renal injury. Take-home message We have found that microRNAs have differences in expression between cell types and renal injury states which is important when considering microRNA expression in samples composed of varying cellular composition. By defining the cellular origins of microRNA expression we were able to rationally select microRNA biomarkers of human renal injury.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.