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.
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.
People |
ORCID iD |
Patrick Lewis (Primary Supervisor) | |
James Tomkins (Student) |
Publications
Cogo S
(2022)
The Roc domain of LRRK2 as a hub for protein-protein interactions: a focus on PAK6 and its impact on RAB phosphorylation.
in Brain research
Ferrari R
(2018)
Stratification of candidate genes for Parkinson's disease using weighted protein-protein interaction network analysis.
in BMC genomics
Leksmono CS
(2018)
Measuring Lactase Enzymatic Activity in the Teaching Lab.
in Journal of visualized experiments : JoVE
Lubbe S
(2016)
Additional rare variant analysis in Parkinson's disease cases with and without known pathogenic mutations: evidence for oligogenic inheritance
in Human Molecular Genetics
Mitchell R
(2019)
Secretome of adipose-derived mesenchymal stem cells promotes skeletal muscle regeneration through synergistic action of extracellular vesicle cargo and soluble proteins.
in Stem cell research & therapy
Tomkins JE
(2018)
Comparative Protein Interaction Network Analysis Identifies Shared and Distinct Functions for the Human ROCO Proteins.
in Proteomics
Tomkins JE
(2020)
PINOT: an intuitive resource for integrating protein-protein interactions.
in Cell communication and signaling : CCS
Vavouraki N
(2021)
Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias.
in iScience
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 |