Defining the role of Death Associated Protein Kinase 1 in cell fate using genomic and proteomic analysis

Lead Research Organisation: University of Reading
Department Name: Pharmacy

Abstract

Project Overview: Death associated protein kinase 1 (DAPK1) is key regulator of cell fate in human cells, acting as a control point for autophagic cell death, and has been implicated in cancer and neurodegneration. Despite two decades of research, the molecular pathways coordinated by DAPK1 remain poorly defined.

The aim of this project is to use new advances in genomic and proteomic technology, coupled with novel insights into the enzymatic function of DAPK1, to dissect the pathways downstream of this protein. This will, in turn, help define the cellular role of this important protein and aid in the development of new drugs to modulate DAPK1.

This four year studentship, funded by an Industrial CASE award from the BBSRC, will be based partly at the University of Reading School of Pharmacy and partly at BC platforms, a leader in the field of bioinformatics. The student will use cellular and biochemical methods to characterise DAPK1, leading on to genomic and proteomic analysis of the cellular impact of modulating the enzymes activity. Bioinformatic investigation of the latter will be carried out with BC platforms, providing industry experience. During the course of the PhD, the student will have the opportunity to register for a Certificate in Business Administration at Henley Business School, part of the University of Reading.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M017222/1 30/09/2015 29/09/2019
1644051 Studentship BB/M017222/1 30/09/2015 29/09/2019 James Tomkins
 
Description This studentship has included the further development of a bioinformatic pipeline to query and process protein-protein interaction data, this pipeline is available in the public domain for constructing protein interaction networks (PINOT - protein interaction network online tool). This approach was applied to several projects, and in relation to this studentship, to complement novel protein microarray data centred on the ROCO proteins to prioritise interactors for further validation. We have identified numerous common and distinct protein interactors of the human ROCO proteins and provided functional associations. Further work was focussed on establishing mutant DAPK-1 models in C. elegans and assessing the interactome of DAPK-1 in this species using both prediction and novel data generation.
Exploitation Route The pipeline developed is now freely available for the research community to use. The results we have presented in our recent publications will provide the foundation for other researchers interested in the ROCO protein interaction network, also more broadly, researchers interested in data integration approaches for explore protein interaction landscapes. The novel C elegans models established will form the foundation for future research into DAPK-1.
Sectors Pharmaceuticals and Medical Biotechnology

URL http://onlinelibrary.wiley.com/doi/10.1002/pmic.201700444/abstract
 
Description BAND consortium
Amount £77,983 (GBP)
Organisation Alzheimer's Research UK 
Sector Charity/Non Profit
Country United Kingdom
Start 12/2019 
End 05/2021
 
Title PINOT - Protein Interaction Network Online Tool 
Description PINOT collates and processes protein interaction data from numerous repositories to enable protein interaction network analysis. This tool is freely available for the research community to use. 
Type Of Material Improvements to research infrastructure 
Year Produced 2020 
Provided To Others? Yes  
Impact This pipeline has been used in multiple projects and around 10 publications to date, to obtain understanding into the protein interactome of proteins of interest and in particular proteins with direct disease associations. 
URL https://biosignaling.biomedcentral.com/articles/10.1186/s12964-020-00554-5
 
Title PINOT 
Description PINOT (Protein Interaction Network Online Tool) is an open access we resource for querying protein interaction data curated into molecular interaction repositories. The pipeline processes data and provides confidence scoring for each protein protein interaction. 
Type Of Material Data analysis technique 
Year Produced 2019 
Provided To Others? Yes  
Impact Ongoing analysis for several projects 
URL https://doi.org/10.1101/788000
 
Description Eva Kevei 
Organisation University of Reading
Department School of Biological Sciences Reading
Country United Kingdom 
Sector Academic/University 
PI Contribution Developing C. elegans models for investigating DAPK-1
Collaborator Contribution Provided lab environment and expertise for C. elegans research
Impact Thesis chapter
Start Year 2018