Systems analysis of signalling cascades in cell migration
Lead Research Organisation:
University of Manchester
Department Name: School of Biological Sciences
Abstract
Receptor tyrosine kinases (RTKs) enable cells to respond to the extracellular environment and to decide whether to grow, differentiate or die. Growth factors binding to and activating RTKs control differentiation, proliferation and migration by initiating intracellular signalling cascades. However, how different ligands binding to the same receptor orchestrate the activation of specific signalling pathways and specific outputs (i.e. proliferation vs migration) is not understood.
Mass Spectrometry (MS)-based quantitative phosphoproteomics is a powerful technology to monitor changes in the activation of signalling pathways by measuring phosphorylated peptides. Focusing on the family of Fibroblast Growth Factor Receptors (FGFRs), which plays major roles during embryonic development and breast cancer, we have demonstrated that signals controlling cell proliferation and cell migration are encoded by the ligands binding to FGFRs. By combining quantitative phosphoproteomics with state-of-the-art systems biology analysis, mathematical modelling and cellular assays, this project will test whether molecular determinants of cell proliferation and migration can be predicted in silico. Specifically, we will:
1. Build a mathematical model from existing phosphoproteomics data collected in human epithelial cells upon stimulation with several FGFR ligands. We will use dynamic correlation analysis in order to reconstruct a network of functional interactions between proteins, and a range of network analysis methods to identify groups of functionally related proteins. We will also develop new methods to visualise networks of phosphorylated proteins.
2. Investigate the validity of the mathematical model by generating new quantitative phosphoproteomics datasets in cells stimulated with other ligand/receptor pairs and in breast cancer cells. We will search for common signalling modules predictive of cellular outcomes (proliferation and migration).
3. Verify the predictive potential of the mathematical model by testing the role of the molecular players identified above in cell proliferation and cell migration assays. We will use two and three dimension epithelial cell cultures.
This highly multidisciplinary project integrates cutting-edge mass spectrometry (MS)-based phosphoproteomics with mathematical modelling and cellular assays, addressing BBSRC remits for 'systems approaches to the biosciences'. Omics investigation of proteins involved in determining cellular responses (Dr. Francavilla) generate complex datasets to be analysed with system biology approaches (Dr. Schwartz) followed by validation in a variety of cell-based assays (Dr. Caswell). Through this 'new way of working' this project will exploit how a system-biology approach enables advancements in scientific discoveries when integrated with defined biological endpoints. Furthermore, training will be provided in quantitative proteomics, bioinformatics, mathematical modelling and core research disciplines (molecular and cell biology), thus forming the next generation of protein scientists.
Mass Spectrometry (MS)-based quantitative phosphoproteomics is a powerful technology to monitor changes in the activation of signalling pathways by measuring phosphorylated peptides. Focusing on the family of Fibroblast Growth Factor Receptors (FGFRs), which plays major roles during embryonic development and breast cancer, we have demonstrated that signals controlling cell proliferation and cell migration are encoded by the ligands binding to FGFRs. By combining quantitative phosphoproteomics with state-of-the-art systems biology analysis, mathematical modelling and cellular assays, this project will test whether molecular determinants of cell proliferation and migration can be predicted in silico. Specifically, we will:
1. Build a mathematical model from existing phosphoproteomics data collected in human epithelial cells upon stimulation with several FGFR ligands. We will use dynamic correlation analysis in order to reconstruct a network of functional interactions between proteins, and a range of network analysis methods to identify groups of functionally related proteins. We will also develop new methods to visualise networks of phosphorylated proteins.
2. Investigate the validity of the mathematical model by generating new quantitative phosphoproteomics datasets in cells stimulated with other ligand/receptor pairs and in breast cancer cells. We will search for common signalling modules predictive of cellular outcomes (proliferation and migration).
3. Verify the predictive potential of the mathematical model by testing the role of the molecular players identified above in cell proliferation and cell migration assays. We will use two and three dimension epithelial cell cultures.
This highly multidisciplinary project integrates cutting-edge mass spectrometry (MS)-based phosphoproteomics with mathematical modelling and cellular assays, addressing BBSRC remits for 'systems approaches to the biosciences'. Omics investigation of proteins involved in determining cellular responses (Dr. Francavilla) generate complex datasets to be analysed with system biology approaches (Dr. Schwartz) followed by validation in a variety of cell-based assays (Dr. Caswell). Through this 'new way of working' this project will exploit how a system-biology approach enables advancements in scientific discoveries when integrated with defined biological endpoints. Furthermore, training will be provided in quantitative proteomics, bioinformatics, mathematical modelling and core research disciplines (molecular and cell biology), thus forming the next generation of protein scientists.
Organisations
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/M011208/1 | 01/10/2015 | 31/03/2024 | |||
| 1917302 | Studentship | BB/M011208/1 | 01/10/2017 | 30/09/2021 |