Publication: Reconstrucción y análisis de modelos metabólicos a escala genómica. Aplicación al estudio de bacterias endosimbiontes
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2018-08-23
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Peretó Magraner, Juli
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Universidad Complutense de Madrid
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Abstract
La reconstrucción metabólica es el proceso computacional que tiene como objetivo elucidar la red metabólica de un organismo a partir de su genoma anotado y otras fuentes de información. El objetivo final de una reconstrucción es desarrollar un modelo metabólico a escala genómica (GEMM), i.e. una representación in-silico de la red metabólica. Un GEMM se puede utilizar para generar simular el funcionamiento del sistema a través del marco teórico denominado modelado basado en restricciones (CBM). En este contexto, el objetivo principal de esta Tesis es abordar los problemas metodológicos de la reconstrucción y refinado de GEMM, con énfasis en su aplicación al estudio de bacterias endosimbiontes. En trabajo se pretenden desarrollar nuevas aproximaciones para detectar y resolver inconsistencias estructurales, empleando como casos de estudio metabolismos de bacterias endosimbiontes. Estos aproximaciones también serán empleadas para analizar la consistencia de bases de datos metabólicas. Finalmente, se abordará el problema de la complementación metabólica en bacterias endosimbiontes...
Metabolic reconstruction is the computational process that aims to elucidate the metabolic network of a given organism from its annotated genome and other sources of information. This integrative process implies the addition of a new level to the genomic annotation. In this process, various enzymatic activities encoded in a genome are put in the context of functional modules, i.e. the metabolic pathways. The final goal of a metabolic reconstruction is to develop a genome-scale metabolic model (GEMM), that is to say, an in-silico representation of the metabolic network. A GEMM can be used to generate hypotheses about the metabolic capabilities of a network (which can be experimentally tested) through the theoretical framework known as constraint-based modeling (CBM). In this context, the main purpose of this Thesis is to address the methodological problems of reconstruction and refinement of GEMMs, with emphasis on their application to the study of bacterial endosymbionts. On one hand this work attempts to develop new approaches to detect and resolve structural inconsistencies using endosymbiotic bacteria as the case of study. These approaches will be also used to analyze the consistency of metabolic databases. Finally, the problem of the metabolic complementation exhibited by endosymbiotic bacteria, will also be addressed...
Metabolic reconstruction is the computational process that aims to elucidate the metabolic network of a given organism from its annotated genome and other sources of information. This integrative process implies the addition of a new level to the genomic annotation. In this process, various enzymatic activities encoded in a genome are put in the context of functional modules, i.e. the metabolic pathways. The final goal of a metabolic reconstruction is to develop a genome-scale metabolic model (GEMM), that is to say, an in-silico representation of the metabolic network. A GEMM can be used to generate hypotheses about the metabolic capabilities of a network (which can be experimentally tested) through the theoretical framework known as constraint-based modeling (CBM). In this context, the main purpose of this Thesis is to address the methodological problems of reconstruction and refinement of GEMMs, with emphasis on their application to the study of bacterial endosymbionts. On one hand this work attempts to develop new approaches to detect and resolve structural inconsistencies using endosymbiotic bacteria as the case of study. These approaches will be also used to analyze the consistency of metabolic databases. Finally, the problem of the metabolic complementation exhibited by endosymbiotic bacteria, will also be addressed...
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Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Químicas, Departamento de Bioquímica y Biología Molecular I, leída el 26-01-2007