CelloS: A Multi-level Approach to Evolutionary Dynamics

We study the evolution of simple cells equipped with a genome, a rudimentary gene regulation network at transcription level and two classes of functional genes: motion effectors which allow the cell to move in response to nutrient gradients and nutrient importers required to actually feed from the environment. The model is inspired by the protist Naegleria gruberi which can switch between a feeding and dividing amoeboid state and a mobile flagellate state depending on environmental conditions. Simulation results demonstrate how selection in a variable environment affects the gene number and efficiency making the cells to rapidly switch from one expression regime to the other depending on the external conditions.

[1]  Paulien Hogeweg,et al.  Modelling Dictyostelium discoideum morphogenesis: The culmination , 2002, Bulletin of mathematical biology.

[2]  Wolfgang Banzhaf,et al.  Advances in Artificial Life , 2003, Lecture Notes in Computer Science.

[3]  Wolfgang Banzhaf On the Dynamics of an Artificial Regulatory Network , 2003, ECAL.

[4]  Christian M. Reidys,et al.  Evolutionary Dynamics and Optimization: Neutral Networks as Model-Landscapes for RNA Secondary-Structure Folding-Landscapes , 1995, ECAL.

[5]  Roeland M. H. Merks,et al.  A cell-centered approach to developmental biology , 2005 .

[6]  Janet Wiles,et al.  Structure and dynamics of a gene network model incorporating small RNAs , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[7]  H. Sauro,et al.  Preliminary Studies on the In Silico Evolution of Biochemical Networks , 2004, Chembiochem : a European journal of chemical biology.

[8]  Risto Miikkulainen,et al.  Efficient Reinforcement Learning Through Evolving Neural Network Topologies , 2002, GECCO.

[9]  W. F.,et al.  Shaping Space : the Possible and the Attainable in RNA Genotype – phenotype Mapping , 1997 .

[10]  Jacques Monod,et al.  On the Regulation of Gene Activity , 1961 .

[11]  W. Fontana Modelling 'evo-devo' with RNA. , 2002, BioEssays : news and reviews in molecular, cellular and developmental biology.

[12]  M. Huynen,et al.  Neutral evolution of mutational robustness. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[13]  M. Huynen,et al.  Smoothness within ruggedness: the role of neutrality in adaptation. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[14]  V. Hakim,et al.  Design of genetic networks with specified functions by evolution in silico. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[15]  P. Schuster,et al.  From sequences to shapes and back: a case study in RNA secondary structures , 1994, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[16]  C. Walsh,et al.  Cell differentiation and flagellar elongation in Naegleria gruberi. Dependence on transcription and translation , 1980, The Journal of cell biology.

[17]  Janet Wiles,et al.  Dynamics of gene expression in an artificial genome , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[18]  Ivo L. Hofacker,et al.  Vienna RNA secondary structure server , 2003, Nucleic Acids Res..

[19]  Peter Eggenberger-Hotz Evolving Morphologies of Simulated 3d Organisms Based on Differential Gene Expression , 2007 .

[20]  Peter F. Stadler,et al.  Fitness landscapes arising from the sequence-structure maps of biopolymers , 1999 .

[21]  Michael Famulok,et al.  All you wanted to know about SELEX , 2004, Molecular Biology Reports.

[22]  Marc Ebner,et al.  How neutral networks influence evolvability , 2001, Complex..

[23]  Peter F. Stadler,et al.  A Graph-Based Toy Model of Chemistry , 2003, J. Chem. Inf. Comput. Sci..