Resumen de Genomic patterns and phenotypic plasticity in prokaryotes analyzed within an ecological framework
Genomic diversity of microorganisms is the result of the combined effects of past evolutionary roads and ecological events. Thus, the specific genome structure in a bacterium is consequence of the selective pressure by the interactions between microorganisms and environment along evolution. Therefore, DNA is predicted to contain more structural information than would be expected from nucleotide bases composition alone. The general aim of this PhD thesis was to develop a theoretical framework based on genometric, statistic and mathematic modelling to study the relationship between genome structure, lifestyle and metabolism of prokaryotic microorganisms. To unveil the relationship between genome structure and lifestyle, a large set of genomes were analyzed by means of a statistical physics methodology which reduces the prokaryotic genomic complexity to a single parameter (the intrinsic long-range correlation that is related directly to the fractal structure of the DNA sequence) which can be further used for comparative genomics and ecological purposes. DNA walk and Detrended Fluctuation Analysis (DFA) were the methods used for the study of long-range correlations in genomes. DNA walking is a genometric method based on a derivative function of the sequential position for each nucleotide along a DNA sequence. The resulting walk is representative of the DNA landscape and enables the simultaneous comparison among different genomes. DFA method provides a single quantitative parameter (the scaling exponent ¿) to represent correlation properties of a sequence. The sequential approach DNA walk-DFA was combined with a functional approach (distribution of clusters of orthologous genes, COG) showing that both, correlations and COG distribution in genomes may be originated by similar factors such as expansions and contractions in the genomic repertoire or adaptation to extreme habitats. Relationships between lifestyle and metabolism were examined by means of a comprehensive comparative genomics study of two marine bacteria that exclusively use hydrocarbons as carbon and energy sources in different environmental scenarios, Alcanivorax borkumensis and Oleispira antarctica. The genomic bases of the unusual ecophysiological features of these microorganisms were studied to help for a better understanding of the influence of temperature on the oil-degrading based bacterial growth. Finally, a functional genomics approach using mathematical modelling for the whole metabolism network codified in the genome of Alcanivorax borkumensis was carried out in order to look into the relationship between genome composition and metabolic phenotype. The whole set of genes, proteins, reactions and metabolites that participated in the metabolic activity were identified, categorized and interconnected to form a network through in silico metabolic reconstruction. This metabolic network allowed, by means of constraint-based methods and Flux Balance Analysis (FBA), to characterize the peculiar ecophysiologic features of this microorganism and to predict mutant cellular phenotypes. The modelling of carbon versus nitrogen fluxes allowed the discovery of conditions in which the excess carbon available in hydrocarbons was not directly translated into bacterial biomass but carbon overflow was diverted to the production of bioplastics (polyhydroxyalkanoates). The predictions showed a potential in the use of the model as a high-throughput analysis in silico tool for detailed studies on the growth of A. borkumensis.
