This is a PhD project. The successful applicant will be top up scholarship. This study will lead to publish high quality of papers and apply a new NHMRC project grant.
We have identified a 13 gene set that predicts renal transplant fibrosis and graft loss in patients. Interestingly some of these genes are donor as well as recipient related. In this project we aim to investigate these gene pathways in cell lines and animal models to better understand how the cause of renal fibrosis after transplantation.
The aim of this project is to identify gene pathways that are responsible for progressive fibrosis following renal transplantation. We have identified a predictive gene set in renal transplant patients that is capable of classifying renal allografts at risk for progressive injury due to fibrosis and the development of fibrosis at 1 year. The high predictive capacity of the gene set (AUC=0·967) was superior to clinical indicators. The 13-genes also accurately predicted early allograft loss (AUC-0·842 and 0·844 at 2- and 3-yrs respectively). Investigation of the genes indicate that collectively they represent both donor and recipient biological pathways. Donor pathways of potential importance include the Notch/Wnt and HIF pathways. These 13 genes will be selectively and independently deleted using CRISPR/Cas9 in cell lines of proximal tubular cell, endothelial cell and mesangial cell lines to determine if the produce a proinflammatory phenotype. From this assay genes of interest will be screened in Zebra fish wilh a readout for renal impairment and in conditional knock-out mice where available. The role of HIF-1a pathway and its impact on the 13 gene set will be evaluated in with conditional HIF-1a KO targeted at the proximal tubular cell. Recipient gene pathways including the TNF pathway will be evaluated by similar screening methods. Mouse models used to evaluate fibrosis include well established models of renal ischemia reperfusion injury, ureteric obstruction and mouse allogeneic and syngeneic transplantation.
The opportunity ID for this research opportunity is 2260