The evolution of the bacterial chemotaxis network

Advances in biomolecular technology allow us to sequence entire genomes, but how genes and molecular networks influence the emergence and evolution of phenotypic traits is still unclear. Different fields in biology and medicine are working hard to unravel the relationship between the genome and phenotypes. In this thesis, a new (mechanistic) approach combining systems biology and evolutionary biology is explored to tackle the genotype-phenotype problem. The chemotaxis network of Escherichia coli is used as a model system for its relatively simple network configuration associated with a complex trait such as chemotactic performance. A mathematical model was developed and in silico evolutionary experiments were performed with different environmental conditions. The results show that due to the complexity of the genomic architecture, most individual gene loci have an inconsistent relationship with fitness. In other words, direct relationships between genes and phenotypes are far more complex than just a linear correlation. The reconstruction of the fitness landscape shows that its structure is highly heterogeneous and there are cases in which mutations have unpredictable and inconsistent effects. Another result shows that contrary to static environments, fluctuating environments facilitate the exploration of the fitness landscape. The results in this thesis show the potential of the evolutionary-systems-biology approach, which could help to understand how complex diseases (e.g. cancer or diabetes) develop or how bacteria evolve to become drug resistant