Welcome to the Systems Biology Laboratory at the University of Melbourne, Australia.
At the Systems Biology Lab we develop biophysically-based mathematical models of biological processes, pathways and networks, and we apply these models to problems in medicine and biotechnology including heart disease, cancer, nanomedicine and synthetic biology.
We are based in the School of Mathematics and Statistics and in the Department of Biomedical Engineering at the University of Melbourne.
We are part of the ARC Centre of Excellence in Convergent Bio-Nano Science and Technology.
For more information contact Lab Director Professor Edmund Crampin
A new preprint from Stuart Johnston, with Mat Simpson (QUT), looks at a new approximation method for birth-death-movement random walks.
Normally, random walk models are approximated via an ODE (i.e. logistic growth), which predicts the population size quite well. However, because the ODE represents the number of agents as a continuum, the agent population will never actually go extinct.
Here instead we represent the random walk via an approximate state space (which includes the extinction state) and use a PDE (over time and state space) to describe how the population transitions through the state space.
This allows us to not only predict the population size accurately, but also determine the probability that the population has gone extinct by a certain time.
Read it here:
Predicting population extinction in lattice-based birth-death-movement models
S.T. Johnston, M.J. Simpson, E.J. Crampin
Our latest paper, which has just appeared online in the Journal of Theoretical Biology, considers how to build simplified, yet physically plausible mathematical models of complex biological systems. Our aim is to help speed up development of whole-cell models – i.e. virtual cell models which simulate all underlying biochemical processes occurring in a cell. To achieve this it is necessary to adopt a modular approach, in which different components are modelled individually and are subsequently assembled into a model of the whole system. For this to work these model components have to ‘play nicely’ with each other. One way to ensure that model components are compatible, and will plug together into a functioning composite model, is to require them to conform to basic physical conservation principles and thermodynamic consistency.
At the same time, however, to construct whole-cell models we also need simplified representations which capture essential biophysical features while avoiding unnecessarily complexity. In our new paper, using energy generation in the mitochondrial electron transport chain as an example, we demonstrate an approach to developing simplified but thermodynamically consistent models (which we call ‘physically-plausible’ models). We show that these physically-plausible models behave like the full system and can readily be incorporated into large scale biochemical simulations, without the requirement of full mechanistic simulation of the underlying biochemical processes. We think this is a significant step towards a modular and multi-scale framework for the development of genome-scale whole-cell models.
P.J. Gawthrop, P. Cudmore, E.J. Crampin
Physically-Plausible Modelling of Biomolecular Systems: A Simplified, Energy-Based Model of the Mitochondrial Electron Transport Chain
Journal of Theoretical Biology
Our congratulations to Michael Pan, who has been awarded his PhD at the Systems Biology Lab for his thesis entitled “A bond graph approach to integrative biophysical modelling”.
In his thesis, Michael used bond graph methodology to examine how energy is transferred between different biochemical and biophysical processes within cells. He developed new mathematical and computational methods for the analysis of energy flow within cellular biochemical networks and applied these methods to study heart cells. His work provides a foundation for the development of detailed modular, energy-based computational models to direct future advances in biotechnology.
Many congratulations Michael!
Many congratulations to Stuart Johnston who has been awarded a 2019 Victoria Fellowship!
Huge congratulations to Stuart, who has been awarded a DECRA fellowship from the ARC for his project entitled “From cells to whales: A mathematical framework to understand navigation”.
Experiments show that interactions between nanoparticles and cells are heterogeneous – there is a distribution of nanoparticle-cell uptake even when the nanoparticles being delivered are nominally identical. This is important because delivering the appropriate dose of a nanomedicine, in part, determines its efficacy.
Significantly, this heterogeneity changes over time following exposure of nanoparticles to cells. Our new paper uses a combination of modelling and experimental work to figure out why heterogeneity in nanoparticle-cell interactions appears to change over time, and to determine what are the potential sources of heterogeneity underlying this phenomenon.
Our study, led by Dr Stuart Johnston, shows that the key mechanisms driving early-time interactions and late-time interactions are different, and this transition between mechanisms makes it appear that heterogeneity changes over time. Read more about it here:
S.T. Johnston, M. Faria, E.J. Crampin
Isolating the sources of heterogeneity in nanoparticle-cell interactions
This work was in part funded by the Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology (CE140100036).
Our latest paper reports on computational modelling to simulate calcium release within realistic cardiomyocyte cell geometries to determine how cellular architecture can affect what you see under the microscope.
Read more in our paper:
D. Ladd, A. Tilunaite, H.L. Roderick, C. Soeller, E.J. Crampin, V. Rajagopal (2019)
Assessing cardiomyocyte excitation-contraction coupling site detection from live cell imaging using a structurally-realistic computational model of calcium release
Frontiers in Physiology 10:1263
For example, the image below indicates how the density of calcium release sites (ryanodine receptors, RyRs) within the cell will affect what you see in your confocal image.
Algorithms that detect “hot-spots” of calcium in these images as RyR sources will be affected by the density of RyRs that are present within the confocal plane, as well as ‘out of plane’ RyRs that are at a distance from the imaging plane.
This work was undertaken by David Ladd, and was lead by Vijay Rajagopal, and is the outcome of a great collaboration between Christian Soeller (@SoellerLab), Llew Roderick (@roderick_cardio) and the Crampin and Rajagopal (@cellsmb) groups.