Engineering an Ecosystem : Taking Cues from Nature’s Paradigm to Build Tissue in the Lab and the Body

This manuscript took a 'top down' approach to understanding survival of inhabitant cells in the ecosystem bone, working from higher to lower length and time scales through the hierarchical ecosystem of bone. Our working hypothesis is that nature “engineered” the skeleton using a 'bottom up' approach,where mechanical properties of cells emerge from their adaptation to their local me-chanical milieu. Cell aggregation and formation of higher order anisotropic struc- ture results in emergent architectures through cell differentiation and extracellular matrix secretion. These emergent properties, including mechanical properties and architecture, result in mechanical adaptation at length scales and longer time scales which are most relevant for the survival of the vertebrate organism [Knothe Tate and von Recum 2009]. We are currently using insights from this approach to har-ness nature’s regeneration potential and to engineer novel mechanoactive materials [Knothe Tate et al. 2007, Knothe Tate et al. 2009]. In addition to potential applications of these exciting insights, these studies may provide important clues to evolution and development of vertebrate animals. For instance, one might ask why mesenchymal stem cells condense at all? There is a putative advantage to self-assembly and cooperation, but this advantage is somewhat outweighed by the need for infrastructural complexity (e.g., circulatory systems comprised of specific differentiated cell types which in turn form conduits and pumps to overcome limitations of mass transport via diffusion, for example; dif-fusion is untenable for multicellular organisms larger than 250 microns in diameter. A better question might be: Why do cells build skeletal tissue? Once cooperatingcells in tissues begin to deplete local sources of food in their aquatic environment, those that have evolved a means to locomote likely have an evolutionary advantage. Once the environment becomes less aquarian and more terrestrial, self-assembled organisms with the ability to move on land might have conferred evolutionary ad-vantages as well. So did the cytoskeleton evolve several length scales, enabling the emergence of skeletal architecture for vertebrate animals? Did the evolutionary advantage of motility over noncompliant terrestrial substrates (walking on land) favor adaptations including emergence of intracellular architecture (changes in the cytoskeleton and upregulation of structural protein manufacture), inter-cellular con- densation, mineralization of tissues, and emergence of higher order architectures?How far does evolutionary Darwinism extend and how can we exploit this knowl- edge to engineer smart materials and architectures on Earth and new, exploratory environments?[Knothe Tate et al. 2008]. We are limited only by our ability to imagine. Ultimately, we aim to understand nature, mimic nature, guide nature and/or exploit nature’s engineering paradigms without engineer-ing ourselves out of existence.

In vitro and in vivo examination of the cell surface glycoprotein CDCP1

A number of reports have demonstrated the importance of the CUB domaincontaining protein 1 (CDCP1) in facilitating cancer progression in animal models and the potential of this protein as a prognostic marker in several malignancies. CDCP1 facilitates metastasis formation in animal models by negatively regulating anoikis, a type of apoptosis triggered by the loss of attachment signalling from cell-cell contacts or cell-extra cellular matrix (ECM) contacts. Due to the important role CDCP1 plays in cancer progression in model systems, it is considered a potential drug target to prevent the metastatic spread of cancers. CDCP1 is a highly glycosylated 836 amino acid cell surface protein. It has structural features potentially facilitating protein-protein interactions including 14 N-glycosylation sites, three CUB-like domains, 20 cysteine residues likely to be involved in disulfide bond formation and five intracellular tyrosine residues. CDCP1 interacts with a variety of proteins including Src family kinases (SFKs) and protein kinase C ä (PKCä). Efforts to understand the mechanisms regulating these interactions have largely focussed on three CDCP1 tyrosine residues Y734, Y743 and Y762. CDCP1-Y734 is the site where SFKs phosphorylate and bind to CDCP1 and mediate subsequent phosphorylation of CDCP1-Y743 and -Y762 which leads to binding of PKCä at CDCP1-Y762. The resulting trimeric protein complex of SFK•CDCP1•PKCä has been proposed to mediate an anti-apoptotic cell phenotype in vitro, and to promote metastasis in vivo. The effect of mutation of the three tyrosines on interactions of CDCP1 with SFKs and PKCä and the consequences on cell phenotype in vitro and in vivo have not been examined. CDCP1 has a predicted molecular weight of ~90 kDa but is usually detected as a protein which migrates at ~135 kDa by Western blot analysis due to its high degree of glycosylation. A low molecular weight form of CDCP1 (LMWCDCP1) of ~70 kDa has been found in a variety of cancer cell lines. The mechanisms leading to the generation of LMW-CDCP1 in vivo are not well understood but an involvement of proteases in this process has been proposed. Serine proteases including plasmin and trypsin are able to proteolytically process CDCP1. In addition, the recombinant protease domain of the serine protease matriptase is also able to cleave the recombinant extracellular portion of CDCP1. Whether matriptase is able to proteolytically process CDCP1 on the cell surface has not been examined. Importantly, proteolytic processing of CDCP1 by trypsin leads to phosphorylation of its cell surface-retained portion which suggests that this event leads to initiation of an intracellular signalling cascade. This project aimed to further examine the biology of CDCP1 with a main of focus on exploring the roles played by CDCP1 tyrosine residues. To achieve this HeLa cells stably expressing CDCP1 or the CDCP1 tyrosine mutants Y734F, Y743F and Y762F were generated. These cell lines were used to examine: • The roles of the tyrosine residues Y734, Y743 and Y762 in mediating interactions of CDCP1 with binding proteins and to examine the effect of the stable expression on HeLa cell morphology. • The ability of the serine protease matriptase to proteolytically process cell surface CDCP1 and to examine the consequences of this event on HeLa cell phenotype and cell signalling in vitro. • The importance of these residues in processes associated with cancer progression in vitro including adhesion, proliferation and migration. • The role of these residues on metastatic phenotype in vivo and the ability of a function-blocking anti-CDCP1 antibody to inhibit metastasis in the chicken embryo chorioallantoic membrane (CAM) assay. Interestingly, biochemical experiments carried out in this study revealed that mutation of certain CDCP1 tyrosine residues impacts on interactions of this protein with binding proteins. For example, binding of SFKs as well as PKCä to CDCP1 was markedly decreased in HeLa-CDCP1-Y734F cells, and binding of PKCä was also reduced in HeLa-CDCP1-Y762F cells. In contrast, HeLa-CDCP1-Y743F cells did not display altered interactions with CDCP1 binding proteins. Importantly, observed differences in interactions of CDCP1 with binding partners impacted on basal phosphorylation of CDCP1. It was found that HeLa-CDCP1, HeLa-CDCP1-Y743F and -Y762F displayed strong basal levels of CDCP1 phosphorylation. In contrast, HeLa-CDCP1-Y734F cells did not display CDCP1 phosphorylation but exhibited constitutive phosphorylation of focal adhesion kinase (FAK) at tyrosine 861. Significantly, subsequent investigations to examine this observation suggested that CDCP1-Y734 and FAK-Y861 are competitive substrates for SFK-mediated phosphorylation. It appeared that SFK-mediated phosphorylation of CDCP1- Y734 and FAK-Y861 is an equilibrium which shifts depending on the level of CDCP1 expression in HeLa cells. This suggests that the level of CDCP1 expression may act as a regulatory mechanism allowing cells to switch from a FAK-Y861 mediated pathway to a CDCP1-Y734 mediated pathway. This is the first time that a link between SFKs, CDCP1 and FAK has been demonstrated. One of the most interesting observations from this work was that CDCP1 altered HeLa cell morphology causing an elongated and fibroblastic-like appearance. Importantly, this morphological change depended on CDCP1- Y734. In addition, it was observed that this change in cell morphology was accompanied by increased phosphorylation of SFK-Y416. This suggests that interactions of SFKs with CDCP1-Y734 increases SFK activity since SFKY416 is critical in regulating kinase activity of these proteins. The essential role of SFKs in mediating CDCP1-induced HeLa cell morphological changes was demonstrated using the SFK-selective inhibitor SU6656. This inhibitor caused reversion of HeLa-CDCP1 cell morphology to an epithelial appearance characteristic of HeLa-vector cells. Significantly, in vitro studies revealed that certain CDCP1-mediated cell phenotypes are mediated by cellular pathways dependent on CDCP1 tyrosine residues whereas others are independent of these sites. For example, CDCP1 expression caused a marked increase in HeLa cell motility that was independent of CDCP1 tyrosine residues. In contrast, CDCP1- induced decrease in HeLa cell proliferation was most prominent in HeLa- CDCP1-Y762F cells, potentially indicating a role for this site in regulating proliferation in HeLa cells. Another cellular event which was identified to require phosphorylation of a particular CDCP1 tyrosine residue is adhesion to fibronectin. It was observed that the CDCP1-mediated strong decrease in adhesion to fibronectin is mostly restored in HeLa-CDCP1-Y743F cells. This suggests a possible role for CDCP1-Y743 in causing a CDCP1-mediated decrease in adhesion. Data from in vivo experiments indicated that HeLa-CDCP1-Y734F cells are more metastic than HeLa-CDCP1 cells in vivo. This indicates that interaction of CDCP1 with SFKs and PKCä may not be required for CDCP1-mediated metastasis formation of HeLa cells in vivo. The metastatic phenotype of these cells may be caused by signalling involving FAK since HeLa-CDCP1- Y734F cells are the only CDCP1 expressing cells displaying constitutive phosphorylation of FAK-Y861. HeLa-CDCP1-Y762F cells displayed a very low metastatic ability which suggests that this CDCP1 tyrosine residue is important in mediating a pro-metastatic phenotype in HeLa cells. More detailed exploration of cellular events occurring downstream of CDCP1-Y734 and -Y762 may provide important insights into the mechanisms altering the metastatic ability of CDCP1 expressing HeLa cells. Complementing the in vivo studies, anti-CDCP1 antibodies were employed to assess whether these antibodies are able to inhibit metastasis of CDCP1 and CDCP1 tyrosine mutants expressing HeLa cells. It was found that HeLa- CDCP1-Y734F cells were the only cell line which was markedly reduced in the ability to metastasise. In contrast, the ability of HeLa-CDCP1, HeLa- CDCP1-Y743F and -Y762F cells to metastasise in vivo was not inhibited. These data suggest a possible role of interactions of CDCP1 with SFKs, occurring at CDCP1-Y734, in preventing an anti-metastatic effect of anti- CDCP1 antibodies in vivo. The proposal that SFKs may play a role in regulating anti-metastatic effects of anti-CDCP1 antibodies was supported by another experiment where differences between HeLa-CDCP1 cells and CDCP1 expressing HeLa cells (HeLa-CDCP1-S) from collaborators at the Scripps Research Institute were examined. It was found that HeLa-CDCP1-S cells express different SFKs than CDCP1 expressing HeLa cells generated for this study. This is important since HeLa-CDCP1-S cells can be inhibited in their metastatic ability using anti-CDCP1 antibodies in vivo. Importantly, these data suggest that further examinations of the roles of SFKs in facilitating anti-metastatic effects of anti-CDCP1 antibodies may give insights into how CDCP1 can be blocked to prevent metastasis in vivo. This project also explored the ability of the serine protease matriptase to proteolytically process cell surface localised CDCP1 because it is unknown whether matriptase can cleave cell surface CDCP1 as it has been reported for other proteases such as trypsin and plasmin. Furthermore, the consequences of matriptase-mediated proteolysis on cell phenotype in vitro and cell signalling were examined since recent reports suggested that proteolysis of CDCP1 leads to its phosphorylation and may initiate cell signalling and consequently alter cell phenotype. It was found that matriptase is able to proteolytically process cell surface CDCP1 at low nanomolar concentrations which suggests that cleavage of CDCP1 by matriptase may facilitate the generation of LWM-CDCP1 in vivo. To examine whether matriptase-mediated proteolysis induced cell signalling anti-phospho Erk 1/2 Western blot analysis was performed as this pathway has previously been examined to study signalling in response to proteolytic processing of cell surface proteins. It was found that matriptase-mediated proteolysis in CDCP1 expressing HeLa cells initiated intracellular signalling via Erk 1/2. Interestingly, this increase in phosphorylation of Erk 1/2 was also observed in HeLa-vector cells. This suggested that initiation of cell signalling via Erk 1/2 phosphorylation as a result of matriptase-mediated proteolysis occurs by pathways independent of CDCP1. Subsequent investigations measuring the flux of free calcium ions and by using a protease-activated receptor 2 (PAR2) agonist peptide confirmed this hypothesis. These data suggested that matriptase-mediated proteolysis results in cell signalling via a pathway induced by the activation of PAR2 rather than by CDCP1. This indicates that induction of cell signalling in HeLa cells as a consequence of matriptase-mediated proteolysis occurs via signalling pathways which do not involve phosphorylation of Erk 1/2. Consequently, it appears that future attempts should focus on the examination of cellular pathways other than Erk 1/2 to elucidate cell signalling initiated by matriptase-mediated proteolytic processing of CDCP1. The data presented in this thesis has explored in vitro and in vivo aspects of the biology of CDCP1. The observations summarised above will permit the design of future studies to more precisely determine the role of CDCP1 and its binding partners in processes relevant to cancer progression. This may contribute to further defining CDCP1 as a target for cancer treatment.

Ureaplasma parvum and ureaplasma urealyticum detected in semen after washing prior to assisted reproductive technology procedures

Objective: This study investigated: (i) the prevalence of ureaplasmas in semen and washed semen and (ii) the effect of ureaplasmas on semen andrology parameters. Design: Prospective study. Setting: IVF unit -private hospital, Brisbane, Australia. Patient(s): Three hundred and forty three men participating in an assisted reproductive technology (ART) treatment cycle. Intervention(s): Semen and washed semen tested by culture, PCR assays and indirect immunofluorescent antibody assays. Statistical differences were determined by a t-test, Wilcoxon or Pearson’s Chi- square test where appropriate. Main Outcome Measure(s): The prevalence of ureaplasmas in semen and washed semen and the effect of these microorganisms on semen andrology parameters. Result(s): Ureaplasmas were detected in 73/343 (22%) semen samples and 29/343 (8.5%) washed semen samples. Ureaplasmas adherent to the surface of spermatozoa were demonstrated by indirect immunofluorescent antibody testing. U. parvum serovar 6 (36.6%) and U. urealyticum (30%) were the most prevalent isolates in washed semen. A comparison of the semen andrology parameters of washed semen ureaplasma positive and negative groups demonstrated a lower proportion of non-motile sperm in the washed semen ureaplasma positive group. Conclusion(s): Ureaplasmas are not always removed from semen by a standard ART washing procedure and can remain adherent to the surface of spermatozoa.

Corrected mean-field models for spatially-dependent advection-diffusion-reaction phenomena

In the exclusion-process literature, mean-field models are often derived by assuming that the occupancy status of lattice sites is independent. Although this assumption is questionable, it is the foundation of many mean-field models. In this work we develop methods to relax the independence assumption for a range of discrete exclusion process-based mechanisms motivated by applications from cell biology. Previous investigations that focussed on relaxing the independence assumption have been limited to studying initially-uniform populations and ignored any spatial variations. By ignoring spatial variations these previous studies were greatly simplified due to translational invariance of the lattice. These previous corrected mean-field models could not be applied to many important problems in cell biology such as invasion waves of cells that are characterised by moving fronts. Here we propose generalised methods that relax the independence assumption for spatially inhomogeneous problems, leading to corrected mean-field descriptions of a range of exclusion process-based models that incorporate (i) unbiased motility, (ii) biased motility, and (iii) unbiased motility with agent birth and death processes. The corrected mean-field models derived here are applicable to spatially variable processes including invasion wave type problems. We show that there can be large deviations between simulation data and traditional mean-field models based on invoking the independence assumption. Furthermore, we show that the corrected mean-field models give an improved match to the simulation data in all cases considered.

A mathematical model of chlamydial infection incorporating movement of chlamydial particles

We present a spatiotemporal mathematical model of chlamydial infection, host immune response and spatial movement of infectious particles. The re- sulting partial differential equations model both the dynamics of the infection and changes in infection profile observed spatially along the length of the host genital tract. This model advances previous chlamydia modelling by incorporating spatial change, which we also demonstrate to be essential when the timescale for movement of infectious particles is equal to, or shorter than, the developmental cycle timescale. Numerical solutions and model analysis are carried out, and we present a hypothesis regarding the potential for treatment and prevention of infection by increasing chlamydial particle motility.

Ghrelin and cancer

Ghrelin is a peptide hormone that was originally isolated from the stomach as the endogenous ligand for the growth hormone secretagogue receptor (GHSR). Ghrelin has many functions, including the regulation of appetite and gut motility, growth hormone release from the anterior pituitary and roles in the cardiovascular and immune systems. Ghrelin and its receptor are expressed in a number of cancers and cancer cell lines and may play a role in processes associated with cancer progression, including cell proliferation, apoptosis, and cell invasion and migration.

Models of collective cell motion for cell populations with different aspect ratio : diffusion, proliferation and travelling waves

Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealizations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data for with varying cell shape.

The Ghrelin axis : does it have an appetite for cancer progression?

Ghrelin, the endogenous ligand for the GH secretagogue receptor (GHSR), is a peptide hormone with diverse physiological roles. Ghrelin regulates GH release, appetite and feeding, gut motility, and energy balance and also has roles in the cardiovascular, immune, and reproductive systems. Ghrelin and the GHSR are expressed in a wide range of normal and tumor tissues, and a fluorescein-labeled, truncated form of ghrelin is showing promise as a biomarker for prostate cancer. Plasma ghrelin levels are generally inversely related to body mass index and are unlikely to be useful as a biomarker for cancer, but may be useful as a marker for cancer cachexia. Some single nucleotide polymorphisms in the ghrelin and GHSR genes have shown associations with cancer risk; however, larger studies are required. Ghrelin regulates processes associated with cancer, including cell proliferation, apoptosis, cell migration, cell invasion, inflammation, and angiogenesis; however, the role of ghrelin in cancer is currently unclear. Ghrelin has predominantly antiinflammatory effects and may play a role in protecting against cancer-related inflammation. Ghrelin and its analogs show promise as treatments for cancer-related cachexia. Further studies using in vivo models are required to determine whether ghrelin has a role in cancer progression.

Irritable bowel syndrome : the role of gut neuroendocrine peptides

Irritable bowel syndrome (IBS) is a common chronic disorder with a prevalence ranging from 5 to 10 % of the world's population. This condition is characterised by abdominal discomfort or pain, altered bowel habits, and often bloating and abdominal distension. IBS reduces quality of life in the same degree of impairment as major chronic diseases such as congestive heart failure and diabetes and the economic burden on the health care system and society is high. Abnormalities have been reported in the neuroendocrine peptides/amines of the stomach, small- and large intestine in patients with IBS. These abnormalities would cause disturbances in digestion, gastrointestinal motility and visceral hypersensitivity, which have been reported in patients with IBS. These abnormalities seem to contribute to the symptom development and appear to play a central role in the pathogenesis of IBS. Neuroendocrine peptides/amines are potential tools in the treatment and diagnosis of IBS. In particular, the cell density of duodenal chromogranin A expressing cells appears to be a good histopathological marker for the diagnosis of IBS with high sensitivity and specificity.

Travelling waves for a velocity–jump model of cell migration and proliferation

Cell invasion, characterised by moving fronts of cells, is an essential aspect of development, repair and disease. Typically, mathematical models of cell invasion are based on the Fisher–Kolmogorov equation. These traditional parabolic models can not be used to represent experimental measurements of individual cell velocities within the invading population since they imply that information propagates with infinite speed. To overcome this limitation we study combined cell motility and proliferation based on a velocity–jump process where information propagates with finite speed. The model treats the total population of cells as two interacting subpopulations: a subpopulation of left–moving cells, $L(x,t)$, and a subpopulation of right–moving cells, $R(x,t)$. This leads to a system of hyperbolic partial differential equations that includes a turning rate, $\Lambda \ge 0$, describing the rate at which individuals in the population change direction of movement. We present exact travelling wave solutions of the system of partial differential equations for the special case where $\Lambda = 0$ and in the limit that $\Lambda \to \infty$. For intermediate turning rates, $0 < \Lambda < \infty$, we analyse the travelling waves using the phase plane and we demonstrate a transition from smooth monotone travelling waves to smooth nonmonotone travelling waves as $\Lambda$ decreases through a critical value $\Lambda_{crit}$. We conclude by providing a qualitative comparison between the travelling wave solutions of our model and experimental observations of cell invasion. This comparison indicates that the small $\Lambda$ limit produces results that are consistent with experimental observations.

Sensitivity of edge detection methods for quantifying cell migration assays

Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

Cell migration and proliferation on homogeneous and non-homogeneous domains : modelling on the scale of individuals and populations

Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

Lattice-free models of cell invasion : discrete simulations and travelling waves

Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.