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Brown, Sarah (2023) An in vitro and in silico study of altered airway smooth muscle structure and function in a remodelled asthmatic airway. PhD thesis, University of Nottingham.

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Abstract

Inflammatory processes in the airway lead to altered extracellular matrix (ECM) and increased airway smooth muscle (ASM), which is responsible for the rapid contraction of asthmatic airways during exacerbations. Increased ASM contributes substantially to the thickening of airways (airway remodelling), and a higher likelihood of experiencing potentially fatal attacks. In culture, ASM cells exhibit changes in shape and contractile ability between a spindle-shaped contractile phenotype and a more rounded proliferative phenotype with synthetic properties capable of depositing ECM. The link between phenotype switching and corresponding changes in structure, function and relative bio-mechanical abilities in vivo is unclear, but key in understanding remodelling. The aim of this project is to combine in silico and in vitro techniques in order to develop models that contribute to the identification of key mechanisms involved in airway remodelling and provide a framework for predicting dynamic mechanical changes in airway tissue.

We first summarise and extend our previously developed ODE model accounting for ASM phenotype and ECM changes triggered by environmental stimuli, based on a newly discovered pathway of remodelling (Chapter 2). Bifurcation analysis of this model identifies a mechanism by which irreversible increases in ECM and ASM mass could occur, given a particular parameter range. We therefore develop two novel experimental serum deprivation protocols using cultured human ASM and microscopy to more accurately quantify the cell phenotype switching rates, as these are the parameters to which the model is most sensitive (Chapter 3). Our experimental results suggest that ASM contractility is increased and that there are structural changes in ASM cells upon switching to a contractile phenotype. Using this temporal data, we demonstrate the use of a Bayesian inference approach to estimate model parameters and inform future experimental design (Chapter 4).

We then extend this work through the development of a new bio-mechanical vertex-based cell model represented by a network of damped springs and contractile elements, in combination with spatial traction force microscopy data, to investigate changes in mechanical properties of the altered tissue (Chapter 5). We incorporate a physical and functional change in contractile cells and find that the model replicates the elongation, stress and strain properties that we would expect of this cell phenotype. In order to replicate the ASM phenotype switching that we initiate experimentally through serum deprivation, we then further develop this model by adding the random switching of cell phenotypes over the simulation period. This allows us to explore the hypothesis that the mechanical environment of ASM cells and their neighbours drives changes in the structure and function of the tissue, and hence is key in the phenotype switching process (Chapter 6).

The vertex-based bio-mechanical model is also used to test the impact of simulating an asthmatic exacerbation and, much like with the ODE model, results show a mechanism by which long-term changes to ASM cells could occur (Chapter 7). Having tested the impact of a single exacerbation event in isolation, we then mimic the full traction force microscopy experimental protocol using this model and appropriate cell numbers. We find that the model qualitatively agrees well with the dynamics displayed in the experimental results. This computational framework could be exploited to investigate whether cell signalling changes the alignment of internal contractile machinery (increases cell elongation) first, which then drives phenotype change, or vice versa. Understanding more about these processes and their impact on asthma development is key for the ultimate aim of finding new therapeutic targets. This and other scope for future work is discussed in Chapter 8.

Item Type:	Thesis (University of Nottingham only) (PhD)
Supervisors:	Brook, Bindi O'Dea, Reuben Johnson, Simon
Keywords:	biomathematics, asthma, airway muscles, extracellular matrix, Bayesian statistics
Subjects:	Q Science > QA Mathematics > QA276 Mathematical statistics Q Science > QH Natural history. Biology > QH301 Biology (General)
Faculties/Schools:	UK Campuses > Faculty of Science > School of Mathematical Sciences
Item ID:	76637
Depositing User:	Brown, Sarah
Date Deposited:	21 Dec 2023 11:47
Last Modified:	21 Dec 2023 11:47
URI:	https://eprints.nottingham.ac.uk/id/eprint/76637

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