From Cellular Components to Living Cells (and Back): Evolution of Function in Biological Networks
Year: 2011
Type: dissertation
Abstract: Network models pervade modern biology. From ecosystems down to molecular interactions in cells, they provide abstraction and explanation for biological processes. Thus, the relation between structure and function of networks is central to any comprehensive attempt for a theoretical understanding of life. Just as any living system, biological networks are shaped by evolutionary processes. In reverse, artificial evolution can be employed to reconstruct networks and to study their evolution. To this end, I have implemented an evolutionary algorithm specifically designed for the evolution of network models. With the developed evolutionary framework, a study of the evolution of information-processing networks was performed. It is shown that selection favours an organisational structure that is related to function, such that computations can be visualised as transitions between organisations. Furthermore, mathematical modelling is applied to extract reaction-kinetic constants from fluorescence microscopy data, and the model is presented and discussed in detail. Using this approach, a detailed quantitative model of exchange dynamics at PML nuclear bodies (NBs) is created, showing that PML NB components exhibit highly individual exchange kinetics. The FRAP data for PML NBs is additionally used as a test-case for automatic model inference using evolutionary methods, and a set of necessary and sufficient criteria for a good model fit is revealed. In the last part of this thesis, a stochastic \nanalysis of the genetic regulatory system of DEF-like and GLO-like class B floral homeotic genes provides an explanation for their intricate regulatory wiring. The different potential regulatory architectures are investigated using Monte Carlo simulation, a simplified master-equation model, and fixedpoint analysis. It is shown that a positive autoregulatory loop via obligate heterodimerisation of transcription factor proteins reduces noise in cell-fate organ identity decisions.
Author: Lenser, Thorsten
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W246784873