Development of an Enzymatic Organic Electrochemical Transistor for Studying Cerebral Cholesterol Metabolism in Alzheimer's Pathology

Lead Research Organisation: University of Cambridge
Department Name: Chemical Engineering and Biotechnology


Alzheimer's disease (AD) affects more than 50 million people worldwide and is expected to affect three times more people by 2050. AD is the most common form of dementia and causes progressive decline of neurons in the brain, which leads to memory impairment, decline in language and problem-solving skills. Recent studies show that dysfunction in cerebral cholesterol metabolism is directly linked to AD pathogenesis. Moreover, there is a significant change in cholesterol metabolism in the cerebral spinal fluid (CSF) of AD's patients. However, the current laboratory methods used for analysis of CSF cholesterol impose limitations to experiments because they are complex, expensive, and time-consuming. Therefore, in this PhD project, a novel method for measuring cerebral cholesterol from CSF is proposed. Organic polymer electrochemical transistors (OECTs) will be used as point-of-care (POC) biosensors, which can outperform current clinical detection methods. This will offer a fast, easily accessible, and reliable in-vitro method to study whether cholesterol in CSF can act as an early biomarker of AD.

The first aim of the project is to design and fabricate an in-vitro biosensor to investigate the role of cholesterol's metabolism in the spread of AD in the brain. This will be achieved through treating cell cultures and samples with different cerebral cholesterol concentrations and using high resolution imaging to investigate the effect of cholesterol metabolism on AD's biomarkers. The second aim of the project is to develop the OECT biosensor into a point-of-care device, which can perform reliable monitoring of the cerebral cholesterol's concentration from CSF sample at the time of the medical consultation to help patients recognise the risk of developing AD at the early stages. For this purpose, the fabricated organic electrochemical transistors will be biofunctionalised with redox enzymes that are specific for cerebral cholesterol and are safe and reliable for long-term use.

In this project, OECTs with a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) channel will be fabricated by processes such as layer deposition, lithography, etching, and spin-coating. PEDOT:PSS is one of the most promising bioelectronics materials due to its combined ionic and electronic charge, leading to huge signal amplification, outperforming most transistors. Moreover, it is very stable in aqueous media, which makes it very suitable for detection of cholesterol in CSF. Techniques for biofunctionalising the gate with different cholesterol oxidases including nanoparticles and artificial mediators will be investigated for achieving optimum response time and high selectivity. Then the accuracy of the OECTs will be tested by using CSF samples. Finally, they will be applied in real-time experiments to investigate the correlation between AD's pathology and cerebral cholesterol. Thus, OECTs hold a great potential for POC, which can address the challenges imposed by the current complex and time-consuming clinical methods for quantifying CSF cholesterol.

Thus, at the end of this project, a novel biosensor for measuring CSF cholesterol will be produced, aligning with the strategies of sensors and instrumentation to incorporate a new advanced device to provide a future with better healthcare and diagnosis. The implementation of the project will be based on knowledge and ideas from microelectronic device technology in healthcare since it incorporates a low-power design of the OECTs microelectronic devices by novel technologies and materials such as the PEDOT:PSS organic polymer and nanoparticles. The vision of this project aligns fully with the ideas from clinical technologies research area since it focuses on developing a novel POC device for diagnosis and monitoring of AD and thus improves health and care by proposing a novel, reliable and fast sensing technology.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023046/1 30/09/2019 30/03/2028
2408391 Studentship EP/S023046/1 30/09/2020 29/09/2024 Stefany Jivkova Kissovsky