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MRC Precision Medicine DTP: Connecting Molecular Profiles to Phenotype: A Proteomic Resource for Assigning Cell Cycle and Senescent States

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  • Full or part time
    Dr T Ly
    Dr Arne Lindqvist
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Background

A hallmark of cancer is aberrant cell cycle control leading to pathological cell proliferation. Cell cycle progression is controlled by key kinases, such as cyclin-dependent kinases (CDKs) and polo-like kinases (PLKs). Polo-like kinase 1 (PLK1) activity rises during G2 after the completion of DNA replication (S-phase) and has been shown to control mitotic entry and the spindle assembly checkpoint. Cell cycle-promoting kinases are often targeted in clinical therapies to treat cancer by blocking proliferation of cancer cells. Indeed, PLK1 is frequently upregulated in tumours and PLK1 inhibitor therapy is under continued investigation in clinical trials.

Emerging data from mass spectrometry-based proteomics1 and timelapse microscopy2 suggest the ‘classic’ cell cycle interphase stages of the cell cycle (G1, S, G2) can be further divided by molecular differences into subphases that have divergent cellular phenotypes in response to stress. For example, early versus late G2 cells differ in how they respond to exogenous stresses, such as DNA damage-induced senescence3. The broader aim of the PhD project is to explore cell cycle transitions during G2 and to identify proteins and signaling events that underpin the divergent cell fate trajectories in an unbiased manner using mass spectrometry-based proteomics and phosphoproteomics. In addition to the unbiased, ‘hypothesis-generating’ screens, the PhD project will also take a focused approach to identify and characterise PLK1 substrates and to understand their function during the G2-M transition. The project will also explore whether meta analysis with clinical proteomic datasets (e.g. TCGA, Cancer Moonshot Project) allows inference of cellular phenotype, such as senescence, cell cycle stage and kinase activation (e.g. PLK1), from clinical data.

Aims

1. A proteomic characterization of early versus late G2 cells

Early and late G2 cells will be separated using intracellular immunostaining of appropriate markers (such as Cyclin B1 and phospho-PLK1 substrates) followed by Fluorescence Activated Cell Sorting (FACS). Cells will then be processed for mass spectrometry-based quantitative analysis of the proteome and phosphoproteome using tandem mass tag (TMT) quantitation and the current generation Orbitrap mass spectrometry technology (Orbitrap Fusion Lumos).

2. Large-scale identification of Polo-like kinase 1 (Plk1) G2-phase substrates

Kinetic in vitro assays will be performed using recombinant Plk1 and ATM. Kinase assays will be performed in G2-phase arrested cells. Substrate phosphorylation dynamics will be measured by mass spectrometry-based phosphoproteomics using the workflow described in Aim 1. The resulting data will be used to define Plk1- and ATM- substrate relationships.

3. Mechanisms underlying DNA-damage induced senescence in G2

Time-lapse imaging and quantitative microscopy will be performed to study how DNA-damage induced senescence is forced at different stages within G2 phase. In particular, Plk1 and ATM activity will be followed in single live cells by FRET-based probes. After fixation, the cells will be stained for immunofluorescence, with a particular focus on proteins and phosphorylations identified in aim 1 and 2. The functional relevance of kinase activities will be tested by addition of selective inhibitors and the use of knock-out cell lines.

Training outcomes

The student will be trained in ‘wet lab’ biochemistry and cell biology techniques, including immunocytochemistry, flow cytometry, immunoblotting, and cell culture. The student will learn how to perform mass spectrometry-based proteomics and phosphoproteomics, how to analyse the resulting datasets, and how to correlate these data with publicly available clinical datasets containing patient outcomes. Bioinformatic data analysis will be performed with the assistance and training of the core bioinformatics facility at the Wellcome Centre for Cell Biology. Molecular profiles will be compared with phenotypic data from timelapse and immunofluorescence microscopy. The combined expertise at Edinburgh University and Karolinska Institutet provide for excellent training in these areas.

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: 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 should contact the primary supervisor prior to making your application. Additional information on the application process if available from the link above.

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

Funding Notes

Start: September 2019

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 qualifications, in an appropriate science/technology area.

Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £14,777 (RCUK rate 2018/19) for UK and EU nationals that meet all required eligibility criteria.


Full eligibility details are available: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/

Enquiries regarding programme: [Email Address Removed]

References

1. Scialddone et al. Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods 2015, 85, 54-61.
2. Ly et al. Proteomic analysis of cell cycle progression in asynchronous cultures, including mitotic subphases, using PRIMMUS. eLife 2017, 6, e27574.
3. Akopyan et al. Assessing kinetics from fixed cells reveals activation of the mitotic entry network at the S/G2 transition. Mol. Cell. 2014, 53, 843-853.
4. Jaiswal et al. ATM/Wip1 activities at chromatin control Plk1 re-activation to determine G2 checkpoint duration. EMBO J. 2017, 36, 2161-2176.

Related Subjects

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