Real-time visualisation of thyroid hormone signalling

About the Project

This project will develop the first genetically-encoded biosensor for real-time monitoring of thyroid hormone (TH) signalling. Using protein engineering, molecular biology and live-cell imaging, it will characterise sensor performance and validate function in cells. The tool will reveal dynamic TH regulation, advance understanding of endocrine physiology, and support therapeutic discovery in metabolic and developmental disorders.

Background. Thyroid hormones (THs) are essential regulators of metabolism, growth and development. They influence processes ranging from energy balance and body temperature, to cardiovascular function and brain maturation. Proper TH signalling is critical for health, and dysregulation can lead to a wide range of disorders (e.g. hypothyroidism, hyperthyroidism) with cardiovascular complications. Despite their importance, our understanding of TH dynamics in living tissues remains limited. Current clinical and research methods primarily rely on blood assays or invasive tissue sampling, which provide only static measurements and cannot capture rapid, tissue-specific changes in hormone signalling. As a result, critical aspects of how THs regulate cellular function in real time, and how dysregulation contributes to disease, remain poorly understood. Developing new tools to monitor TH activity dynamically and non-invasively could transform our understanding of endocrine physiology, reveal novel disease mechanisms, and guide more precise therapeutic interventions.

Aims and objectives. This project aims to develop a genetically-encoded biosensor capable of reporting TH activity with high spatiotemporal resolution. The sensor will allow live monitoring of TH dynamics in cells and, potentially, in tissues, providing a transformative tool to study hormone regulation under physiological and pathological conditions.The specific objectives are:

1. Design and engineering of a TH biosensor.
2. In vitro characterisation of sensor sensitivity, specificity, and dynamic range.
3. Functional validation in cellular models.

By combining protein engineering, molecular biology, and live-cell imaging, this project will generate a versatile tool for real-time study of TH signalling, providing insights into hormone regulation that could inform future therapeutic strategies.

Research plan. This interdisciplinary project will investigate thyroid hormone signalling dynamics and their role in health and disease.

• Biosensor design and optimisation: The biosensor will be engineered by fusing the thyroid hormone receptor ligand-binding domain to a fluorescent reporter with optimal sensitivity and dynamic range.
• In vitro characterisation: Recombinant biosensor proteins will be expressed and purified for biochemical assays. Sensitivity, ligand specificity, and response kinetics will be quantified in controlled in vitro systems.
• Live-cell functional assays: Biosensor constructs will be expressed in cultured mammalian cells. Confocal imaging will be used to monitor TH-induced dynamics in real time.

Outcomes. This project will create the first genetically encoded biosensor for dynamic, live-cell monitoring of thyroid hormone (TH) signalling. It will provide spatiotemporal insights inaccessible with current assays, enabling mechanistic studies at cellular and subcellular levels and supporting drug screening. The biosensor will also pave the way for in vivo studies, advancing research in metabolism, development, and targeted therapies.

Student training and development. The successful candidate will receive comprehensive training in:

• Molecular cloning and protein engineering: design, optimization, and in vitro characterisation of genetically-encoded biosensors.
• Fluorescence-based imaging techniques: confocal microscopy and quantitative imaging approaches to evaluate biosensor performance, localisation and kinetics in cells.
• Cell biology and live-cell assays: monitoring real-time signalling dynamics in mammalian systems, linking molecular function to cellular outcomes.
• Data analysis and scientific communication: interpretation of complex datasets, preparation of manuscripts and conference presentations.