Case study: Nicola Trendel

Case study: Nicola Trendel

When choosing her first degree Nicola was undecided about which subject to focus on, although she was particularly interested in the interface between the natural sciences. Her interdisciplinary degree in Liberal Arts and Sciences degree at the Amsterdam University College enabled her to focus on Sciences while also taking courses in Social Sciences and Humanities. She majored in physics, but was also able to take biology modules such as molecular cell biology and computational biophysics (for example, using maths to explore information processing within the cell).

During her final undergraduate year Nicola was introduced to ‘systems biology’, searched online for more information and discovered the course at the Systems Biology CDT, which instantly appealed to her, as it tied together all her main interests.

Nicola found that the first year at the CDT provided a very smooth transition from her undergraduate degree and gave her excellent support. She really valued the ability to try out supervisors as well as projects. Both her first year rotations had experimental and mathematical modelling aspects. The first, at the Dunn School of Pathology, involved stimulating T-cells with antigens and measuring a downstream output, and then using mathematical modelling to describe the relationship. The second project, through the Wellcome Trust Centre for Human Genetics, examined insulin-producing beta cells and looked at modelling autocrine signalling that might play an important role in the development of type 2 diabetes.

Although both projects were equally interesting, Nicola chose the T-cell project as the subject of her DPhil. Her research focusses on taking multiple readouts from a T-cell stimulated with an antigen and investigating how to capture all the outputs in one model.

When a T-cell is stimulated it triggers a vast signalling cascade that involves large numbers of different proteins. The complexity of the response has the potential to make mathematical models extremely complex, which in turn can make it difficult for those models to predict or describe what is happening. Instead of trying to model everything in the cascade, Nicola is working on models that describe the overall features of the cell signalling pathways (a phenotypic approach). By using a coarse-grained approach rather than one that includes every minute detail, Nicola aims to identify the minimum network architecture that is necessary to explain the data.

The overall goal of the group is to provide a better model of T-cell activation that makes it possible to predict T-cell responses to different types of antigens or concentrations of antigens. A better understanding of how T-cell signalling works could lead to better treatments and therapies in future.

Nicola hopes to be able to take advantage of an internship through the CDT. She is very enthusiastic about public engagement and science communication. The CDT offers many opportunities for DPhil students to explain their research to other students with very different backgrounds, and also offers training in how to do this – something that Nicola values and intends to make use of in the future.