Loughborough University
Laurissa_Joy_Havins_thesis_final_2022.pdf (14.21 MB)

Bioengineering dual gradient platforms for the control of cell behaviour and differentiation

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posted on 2022-07-05, 15:58 authored by Laurissa Havins

There is a large unmet clinical need for effective treatments for neurodegenerative diseases, and in an ageing population where these diseases are becoming more prevalent, the urgent need for therapies targeting the disease becomes a growing problem. Cellular therapies focusing on the differentiation of stem cell sources for the efficient and reproducible generation of mature neuronal cell types is one potential avenue. Traditional cell culture protocols have been able to demonstrate direction differentiation into a variety of neuronal cell types, but these techniques are often costly. Protein and morphogen gradients in vivo are important for the spatio-temporal patterning and guidance of cell differentiation and tissue organisation, and recapitulating aspects of these gradients is an area of great interest. Further, cell interactions and behaviour on traditional culture plastic does not effectively represent their behaviour in vivo, thus there is a need for biomimetic environments to provide better cell support and interactions. The biomaterial research field has aimed to combat this by combining the useful techniques and protocols developed in traditional culture with the ability to enhance the cell environments, through ECM mimic and protein surface interactions. Directing differentiation using biomaterial surfaces has enabled an improvement in cellular control and differentiation efficiency. Polymer brush technology, combined with the ability to bind protein, has established a field of research developing protein bound surfaces and gradients to control cell attachment and behaviour. However, generating surfaces controlling both a protein gradient and environmental support has not yet been done.

This thesis focuses on the development of a protein-bound dual gradient polymer brush surface for the control of cell behaviour and differentiation. The aim is to generate a biomimetic surface capable of high-throughput cellular control, to further understanding of protein gradients, and cellular differentiation in an efficient and lower cost manner. Polymer brush technology was used to develop surfaces presenting a continuous change in polymer density and polymer chain length to provide an orthogonal gradient surface. Covalent binding of proteins and growth factors of interest to the polymer provided the presentation of a continuous protein concentration gradient to interact with cells. This process was optimised and analysed to confirm the presence of the dual gradient and the successful fabrication of protein-bound surfaces. The SH-SY5Y cell line was used to optimise the surfaces for cellular control. NGF and BDNF bound dual gradient surfaces were developed, and SHSY5Y behaviour was determined through the use of cell count and neurite length analysis, followed by analysis of TrkB expression and concentration through PCR and ELISA. This work was then followed by the use of embryonic stem cell and neural progenitor cells on specialised protein gradient surfaces, to begin to investigate the use of these dual gradient surfaces for stem cell differentiation and control.


EPSRC and MRC Centre for Doctoral Training in Regenerative Medicine

Engineering and Physical Sciences Research Council

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  • Science


  • Chemistry


Loughborough University

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© Laurissa Havins

Publisher statement

This thesis is published under a CC BY-NC-ND 4.0 licence which covers the entirety of the thesis. Exception is the article Gradient biomimetic platforms for neurogenesis studies, attached in the appendices to which a CC BY 4.0 licence applies. For more information on licensing see https://creativecommons.org/licenses/

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A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy of Loughborough University.


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Paul Roach ; Mark Lewis ; Steve Christie

Qualification name

  • PhD

Qualification level

  • Doctoral

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