Details
Over the past 60 years, we have discovered many of the rules which determine how our genetic makeup affects our health, from Rosalind Franklin’s pioneering discovery of the helical structure of DNA, through to the human genome project. However, we still do not have the tools to measure DNA’s secondary, mechanical code, which affects nearly all interactions and therefore our wellbeing at a cellular level. This is due in part to the complexity of cellular DNA, caused by its innate flexibility, compaction in the nucleus, and manipulation by DNA-processing enzymes. These processes cause DNA to adopt a vast range of intricate structures, conformations and topologies which are hard to quantify as they occur at the nanometre length scale.
Furthermore, many essential therapies, such as anti-cancer drugs, are affected by the underlying mechanical and structural properties of DNA within the cells that they are targeting. Though the past 15 years have seen the development of precision medicines to target cancer (e.g. PARP inhibitors), therapies that damage DNA indiscriminately remain the cornerstone of cancer therapy, (e.g. radiation or cisplatin treatments). To develop new, better targeted therapies, we must understand the role of DNA’s mechanical code in healthy and damaged DNA.
We have developed Atomic Force Microscopy (AFM) methods which enable us to routinely visualise single DNA molecules with sub-molecular resolution. This allows us to measure the twist, writhe, and topology of individual DNA molecules and quantify their mechanical and conformational structure. This project combines cell biology, high-resolution atomic force microscopy (AFM) imaging, and quantitative image analysis methodologies to understand how the hidden mechanical code of DNA changes following DNA damage. This will enable us to understand and identify novel opportunities for therapeutic intervention.
Objectives:
1. Generate healthy, and damaged DNA substrates, and determine their mechanical “fingerprints” using AFM imaging and quantitative image analysis and machine learning methods.
2. Determine how changes in their mechanical “fingerprints” affect the interactions of DNA with key drug targets (e.g. PARP).
3. Differentiate the effect of radiotherapy / chemotherapeutic agents on the mechanical structure of DNA and correlate this with cellular survival, DNA repair kinetics and the DNA damage response.
Novelty/Timeliness:
This multidisciplinary project applies our cutting-edge AFM techniques, capable of visualising the double helix of individual DNA molecules, to quantify the mechanical signatures associated with DNA in various healthy or damaged states. Given the growing awareness of the role of mechanobiology in cell survival and therapies, this project is perfectly positioned to provide new information which can guide the development of new precision cancer medicines.
Experimental Approach:
The project will combine cellular biology, single molecule imaging and quantitative image analysis to quantify the mechanical structure of healthy and damaged DNA structures at the resolution of the DNA double helix. The project will include training in high-resolution AFM which will enable you to visualise different telomeric DNA structures down to the resolution of the double-helix. The project will use and develop our Python pipeline TopoStats, integrating machine learning approaches to quantitatively determine the mechanical state of individual DNA molecules. The project will benchmark this tool against the gold standard techniques in this field e.g. cellular DNA damage response assays.
You will be supervised by Dr Alice Pyne, Dr Helen Bryant, & Dr Matt Newton. All supervisors are committed to embedding positive and inclusive research cultures in their groups. The supervisors will work together to ensure expectations on students and of supervisors are clearly defined and communicated. We welcome applicants from a diverse range of backgrounds across the physical and biological sciences and engineering.
Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application. Please refer to the EPSRC DTP webpage for detailed information about the EPSRC DTP and you can apply using this form. Please ensure you include the reference for this project MAT-01-Pyne
Funding Notes
The award will fund the full (UK or Overseas) tuition fee and UKRI stipend (currently £18,622 per annum) for 3.5 years, as well as a research grant to support costs associated with the project.