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Precision Medicine DTP – Integration of single-cell RNA sequencing data from human and murine kidney disease to identify novel therapeutic targets


Project Description

Background

Chronic kidney disease (CKD) is a major risk factor for cardiovascular disease and for end-stage kidney disease (ESRD), at which point patients require dialysis or transplantation. CKD affects 7% of the UK population and therefore constitutes a major public health problem. Despite the best current management, a minority of patients with CKD progress to ESRD, hence novel therapies are required to prevent progression of CKD or promote regeneration of the injured kidney.

To identify novel therapeutic targets, we are conducting studies to identify molecular pathways that are differentially activated in the kidney in patients with CKD compared with healthy controls. We are also employing a number of animal models of kidney disease including diabetic nephropathy, unilateral ureteric obstruction (UUO), ischaemia-reperfusion injury (IRI) and subtotal nephrectomy. Importantly, we have adapted the diabetic nephropathy, UUO and IRI models to investigate mechanisms of renal repair after injury(1); this cannot be easily monitored in human disease as kidney biopsies are rarely performed in patients who are improving clinically. Our research focuses on understanding which pathways are activated in our animal models during injury and repair as this may highlight novel therapeutic targets to inhibit progression of disease or promote kidney repair.

The kidney is a particularly complex organ with multiple specialist cell types. To understand how each of these cell types behave during injury and repair, the Conway, Chandra and Ferenbach groups have collaborated to employ single-cell RNA sequencing (scRNAseq), which can determine the gene expression in tens of thousands of individual cells simultaneously (manuscript in preparation for Nat Comms). This generates very large and complex datasets and requires the collaboration between expert bioinformaticians and biologists to formulate hypotheses, interrogate the data and test the outcomes in biological experiments.

While multiple studies have used bulk transcriptomics to identify differentially expressed genes in human kidney disease (www.nephroseq.org), human scRNAseq data available to date is largely derived from the normal kidney(2, 3), with few studies on patients with kidney disease(4). We have access to >200 kidney biopsies from patients with CKD and we are funded to perform single nuclear RNAseq (snRNAseq) on banked frozen blocks from a focused subset of these patients and from controls (the normal kidney portion of tumour nephrectomy specimens). This will enable us to identify the renal cellular heterogeneity in human CKD, the pathways differentially expressed in these cells and to determine which pathways are associated with rapid disease progression.

Aims

The focus of the current proposal is on integrating and interrogating the scRNAseq datasets from the various murine datasets to highlight novel therapeutic targets to inhibit progression of CKD or promote renal repair, and on integrating the murine datasets with those from patients with CKD to ensure relevance to human disease.

Specific aims include:

To integrate the datasets from our murine models in order to identify common and disease-specific pathways of renal injury and repair
To perform a detailed analysis of the murine datasets to further understand the biology, in particular assessing the cell-to-cell signaling pathways that promote inflammation, fibrosis, senescence and regeneration
To integrate the snRNAseq data from patients with CKD with the murine datasets to determine which murine model most closely reflects the pathogenesis of specific kidney diseases and hence may be most suitable to employ in future mechanistic/drug development studies

This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.

All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.

http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919

Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.

For more information about Precision Medicine visit:
http://www.ed.ac.uk/usher/precision-medicine

Funding Notes

Start: September 2020

Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area.
Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,009 (RCUK rate 2019/20) for UK and EU nationals that meet all required eligibility criteria.

Full eligibility details are available: View Website

Enquiries regarding programme:

References

1. Conway BR, Rennie J, Bailey MA, Dunbar DR, Manning JR, Bellamy CO, et al. Hyperglycemia and renin-dependent hypertension synergize to model diabetic nephropathy. J Am Soc Nephrol. 2012;23(3):405-11.

2. Lake BB, Chen S, Hoshi M, Plongthongkum N, Salamon D, Knoten A, et al. A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys. Nat Comm. 2019;10(1):2832.

3. Young MD, Mitchell TJ, Vieira Braga FA, Tran MGB, Stewart BJ, Ferdinand JR, et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 2018;361:594-9.

4. Wilson PC, Wu H, Kirita Y, Uchimura K, Ledru N, Rennke HG, et al. The single-cell transcriptomic landscape of early human diabetic nephropathy. Proc Natl Acad Sci. 2019. ePub

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