Dr Tom Webb

Supervisor Details

Contact Details

Department of Cardiovascular Sciences, University of Leicester

Scientific Background

Research Interests

My research group investigates how genetic variants, genes and molecular pathways control the health of blood vessels and how their disruption leads to heart attacks and other cardiovascular diseases. We use a combination of discovery genetics, computational genomics and laboratory experiments to uncover the mechanisms linking genetic variation to cell behaviour, health and disease risk.

Current projects focus on how endothelial and smooth muscle cells, the key building blocks of blood vessels, respond to inflammation, stress, and blood flow, and why these responses differ between individuals. We integrate data from human cohorts and omic to identify causal genes and pathways. Experimental work uses unique primary vascular cell banks, iPSC-derived vascular models and gene editing to test how specific variants alter vascular function. By linking human genetics to cell biology, our aim is to understand vascular health and identify more precise prevention and treatments of cardiovascular disease.

Supervision Style

In three words or phrases: Laid-back, understanding, collaborative.

Provision of Training

Your training will be supervised predominantly by my experienced post docs/PhD students.

Progression Monitoring and Management

I will set out my expectations of your progression on a weekly/monthly basis. If these progression criteria are not met we will always discuss a plan of action together.

Communication

I am happy to discuss any issues that are impacting your ability to fulfil your potential or my/our expectations.

Meetings

PhD Students can expect scheduled meetings with me at least once per week. These meetings will be a mixture of face-to-face and via video chat or telephone. I am usually contactable for an instant response on every working day.

Work Patterns

The timing of work in my lab is completely flexible, and (other than attending pre-arranged meetings) I expect students to manage their own time.

Notice Period for Feedback

I need at least 2 weeks' notice to provide feedback on written work of up to 5,000 words.

MIBTP Project Details

Primary supervisor for:

Systems genetics of gene regulation and cell behaviour

See the PhD Opportunities section to see if this project is currently open for applications via MIBTP.

Please Note: The main page lists projects via BBSRC Research Theme(s) quoted and then relevant Topic(s).

Systems genetics of gene regulation and cell behaviour

Secondary Supervisor(s): Dr David McVey, Dr Charles Solomon

University of Registration: University of Leicester

BBSRC Research Themes:

Understanding the Rules of Life (Systems Biology)

Project Outline

This project uses systems genetics to link natural DNA variation, epigenetic data, gene expression, molecular pathways and measurable cell behaviours that are fundamental to human health. Current interests include senescence, inflammatory signalling, mechanotransduction and post-transcriptional RNA regulation. Our primary resource is the Leicester vascular cell bank comprising thousands of genotyped smooth muscle cell and endothelial cell lines from the same donors. We already hold high-content measurements of proliferation, migration and apoptosis, and bulk RNA sequencing on ~1,500 smooth muscle lines. This scale allows us to map variant-to-gene effects and connect them to cell phenotypes.

Objectives

1. Map genetic variants to molecular traits (expression/epigenetic/phenotypic QTLs) under basal conditions and after defined stimuli.

2. Identify genetic variants and genes which predict molecular/cell behaviours.

3. Test causality with RNAi, CRISPR.

4. Integrate results into network models and phenotype prediction.

Panels of primary vascular cells will be exposed to a relevant treatment (inflammatory cytokines, shear stress etc). We will generate multi-omics data (RNA-seq, DNA methylation, chromatin modifications and proteomics) and high-content phenotype readouts. Statistical genetics and machine learning will be used to discover variant-to-gene and gene-to-process/phenotype links. RNAi/CRISPR perturbation will validate key findings.

Projects will deliver causal maps that explain how genetic variation shapes core cellular functions and are suitable for both wet and dry lab students. Students will gain broad skills in cell biology, functional genomics and/or data science.

Co-supervisor on a project: Dr Jenny Shepherd