Cross-Disciplinary Fellowships (XDF)

Notable outcomes & achievements

Publications, awards and other achievements.

XDF Programme Fellow published papers in physics and biomedicine journals

Zebrafish MITF-low melanoma models of human MITF-low melanoma (MITF is a transcription factor essential for melanocyte development and survival). While the bulk of the tumour is dependent on MITF activity, MITF-independent cells pre-exist and arise de novo in residual disease.
Zebrafish MITF-low melanoma models of human MITF-low melanoma (MITF is a transcription factor essential for melanocyte development and survival). While the bulk of the tumour is dependent on MITF activity, MITF-independent cells pre-exist and arise de novo in residual disease.

One of the main objectives of the XDF Programme is to train the fellows in biomedical sciences while at the same time helping them to nourish knowledge and skills they had already gained from their previously studied disciplines. This is hoped to be achieved through carefully designed collaborations and joint projects with people from informatics, physics and similar fields of research. In Summer/Autumn 2019, one of the XDF Programme Fellows, Dr Ava Khamseh, published two very interesting papers in high impact journals from different disciplines – physics and cancer research. She achieved it by working with two separate teams on very different topics using both numerical and biomedical methodologies - suggesting perhaps, that the XDF Programme approach to cross-disciplinarity might be working well.

The first study, titled “Machine learning determination of dynamical parameters: The Ising model” and published in the journal “Physical Review B”, was performed in collaboration with investigators from Higgs Centre for Theoretical Physics at the University of Edinburgh, Alan Turing Institute in London and Ascent Robotics in Tokyo. The study uses machine learning (training of a set of restricted Boltzmann machines on one- and two- dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations) to develop new approaches for data distribution analysis. It forms the foundation for further investigations of interactions between variables in biological systems. Notably Ava has been designated one of the corresponding authors for this work.

The second study, titled “Zebrafish MITF-low melanoma subtype models reveal transcriptional subclusters and MITF-independent residual disease” and published in the journal “Cancer Research”, identified novel cell states in melanoma progression and residual disease. Melanoma is the deadliest type of skin cancer with almost 16,000 new cases every year in the UK and the study used state-of-the-art high-resolution imaging combined with single cell gene expression analysis to understand these new cell states for the first time in a complex living system. The study, led by Dr Elizabeth Patton from IGMM, involved research institutions from Australia, Belgium, Iceland, USA and UK (including IGMM’s MRC Human Genetics Unit and CRUK Edinburgh Centre).

Related Links

Super-resolved image of SAF-A protein in cell nucleus (Credit: Dr Mattia Marenda).
Super-resolved image of SAF-A protein in cell nucleus (Credit: Dr Mattia Marenda).

First successful research grant application with an XDF Programme Fellow as the Lead Applicant

Ability to secure research funding represents one of the essential skills for successful scientists in today’s highly competitive research environment and the XDF Programme places strong emphasis on providing its Fellows with education and training opportunities in this area with the overarching aim of facilitating their transition to independence.

Summer 2019 was notable in this respect as it marked the first successful outcome of a grant application led by an XDF Programme Fellow - Dr Mattia Marenda. In May 2019 – less than a year from the beginning of the XDF Programme - Mattia and his colleagues from IGMM (Prof Nick Gilbert, Dr Dimitrios Papadopoulos), the University of Edinburgh’s School of Physics and Astronomy (Dr Davide Michieletto) and the Department of Physics of the Strathclyde University (Dr Sebastian van de Linde) submitted an application titled “Investigating the Bio-Physical Properties of SAF-A Assembly via Live-Cell Super-Resolution Microscopy, Machine Learning and Molecular Dynamics Simulations” for consideration by the SULSA Technology Seed Funding scheme. The application had been deemed highly innovative and funds were awarded to enable its implementation.

Understanding the three-dimensional organisation of the genome in eukaryotic cells represents one of the greatest challenges in Life Sciences and the cross-disciplinary team assembled will use a broad spectrum cutting-edge technologies to characterise and understand the biophysical principles with which SAF-A, a protein with structural and functional roles in chromatin organisation, organises the genome.

Related Links

Melissa Model Overview
Melissa Model Overview

First research publication attributed to the XDF Programme

The 21st of March 2019 was a notable date for the Programme as it marked the first scientific-research journal publication that acknowledges the XDF Programme support. In a study titled “Melissa: Bayesian clustering and imputation of single-cell methylomes” published in the journal “Genome Biology”, Dr Chantriolnt-Andreas Kapourani (one of the Fellows recruited in 2018) and Prof Guido Sanguinetti describe a new computational method - Methylation Inference for Single Cell Analysis (Melissa) – to aid single cell DNA methylation studies in biomedicine.

DNA methylation is a process by which methyl groups are added to the DNA molecule. It belongs to so called epigenetic modifications – modifications that do not involve changes to the underlying DNA sequence. Methylation can change the activity of a DNA segment. In mammals DNA methylation is essential for normal development and is associated with a number of key processes including genomic imprinting, X-chromosome inactivation, repression of transposable elements, aging, and carcinogenesis. Yet its role in gene regulation and the molecular mechanisms underpinning its association with diseases are still imperfectly understood. DNA methylation measurements at single-cell level are rapidly becoming a major tool to understand epigenetic gene regulation in individual cells, however all available technologies are plagued by intrinsically low coverage in terms of numbers of assayed methylated DNA stretches (so called CpGs). The authors propose Melissa as a way of addressing low coverage issue by sharing information between CpGs with local smoothing and between cells with Bayesian clustering prior. This methodology should have significant impact on future methylation studies.    

Related Links

Article in “Genome Biology”: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1665-8

General information about DNA methylation: https://en.wikipedia.org/wiki/DNA_methylation

“Training multi-discipline scientists can fight disease” – article in “The Scotsman” by Professor Chris Ponting

On the 27th of August 2018, just after a successful completion of the first ever XDF Programme Induction Week (20-24 August 2018), “The Scotsman” newspaper published an article by the XDF Programme lead Prof. Chris Ponting. The article entitled “Training multi-discipline scientists can fight disease” explains to a lay audience reasons behind training new generation of data-savvy multi-disciplinary scientists. It was intended to inform general public about the Medical Research Council – University of Edinburgh Cross-Disciplinary Post-Doctoral Fellowships and trigger some reflection on the challenges facing contemporary biomedical sciences.       

Link to the article: https://www.pressreader.com/uk/the-scotsman/20180827/281930248842677