This project focuses on two different areas in computational or systems biology, namely:
i) The dynamics and mechanisms of cardiac arrhythmias
ii) The dynamics of evolutionary processes
The dynamics and mechanisms of cardiac arrhythmias
Our aim is to elucidate mechanisms behind cardiac arrhythmias which may contribute to improving medical prevention and intervention techniques. Contraction of cardiac myocytes is initiated by an electrical excitation signal. Under normal conditions, this signal is emitted by the sinus node and spreads as a regular wavefront across the atria and then the ventricles, leading to coordinated contraction. Arrhythmias, pathological disturbances in the normal rhythm of contraction of the heart, are caused by disturbances in the generation and / or propagation of this excitation wave. They may either seriously reduce pumping capacity of the heart, or lead to complete failure to circulate blood and hence be lethal within minutes.
As arrhythmias are mostly caused by abnormalities in excitation, we focus and modeling normal and abnormal electrophysiology of cardiac cells, tissue and the whole heart, ignoring the cardiac contraction process. To increase the clinical applicability of our research we use detailed quantitative models of human cardiac cells and tissue.
Our research will focus on the role of two factors, which over recent years have received considerable attention for their potential role in arrhythmogenesis. The first is intracellular calcium dynamics and the second is fibrosis (connective tissue formation). Intracellular calcium dynamics links electrical excitation and mechanical contraction and is a highly complex and non-linear process. Under disease conditions aberrant calcium dynamics may lead to alternans instability of the action potential and spontaneous electrical activity, which both are highly arrhythmogenic. Fibrosis refers to the deposition of larger than normal amounts of fibrotic tissue, containing both fibroblast cells and extracellular matrix proteins. This occurs in normal hearts during the process of ageing, but also occurs in response to infarcts or chronic heart disease. The occurrence of fibrosis and arrhythmias is strongly correlated, but arrhythmia mechanisms are poorly understood. An intruiging possibility is that arrhythmia mechanisms under high calcium concentrations and high levels of fibrosis may be fundamentally different.
The dynamics of evolutionary processes
The goal of the evolutionary dynamics projects is to study questions from two main areas of evolutionary biology, speciation and development. For speciation the question is how a single biological species may give rise to multiple species, given that sexual reproduction (by exchanging genetic material) tends to dampen arising differences. For development the question is how a single fertilized egg cell gives rise to a multicellular body consisting of a large range of specialised cell types at specialised locations, despite that all these cells contain the same set of DNA instructions. Furthermore, the question is how this developmental algorithm evolved through evolution to give rise to the complexity and diversity of current day life forms.
Classically, highly simplified evolutionary models have been used. In these models, the properties of an organism depended solely on the type of genes it contains. As a consequence these models employ a one-to-one genotype-phenotype map: there is only one way in which the DNA can code for particular properties of an organism. This severely restricts the potential routes for evolution. However, nowadays it is well known that organism's properties are determined by which genes are expressed when and where; that this spatiotemporal dynamics of gene expression depends on where on the genome genes are located and how they are regulated; and that the mapping from genotype to phenotype is many-to-one: there are various ways for how DNA can code for the properties of an organism. Such a mapping may dramatically increase the flexibility of the evolutionary process and hence the "solutions" obtainable by evolution.
We will use stochastic agent based models to simulate evolving populations. We model agents as containing a genome, a gene regulatory network and a phenotype. Genome organization (how genes and gene regulatory regions are organized on the DNA) evolves through mutation and selection. The genome organization determines the gene regulatory network architecture (which genes influence which other genes to be on or off) which, through the resulting spatiotemporal gene expression pattern, subsequently determines the phenotype of the organism. This naturally leads to a realistic many-to-one genotype-phenotype map. We will study how these more realistic models can help shed light on long standing evolutionary questions. Because of the size and complexity of these models, part of the effort will be on efficient numerical techniques, algorithms and parallellization.
