Publicação
Development of microbial community simulation methods to characterize and analyze the effects of metal concentrations on pathogen silencing/promotion
| Resumo: | Genome-scale metabolic modeling has become a widespread methodology for analyzing microbial metabolism. The mathematical modeling of these networks has proven itself as an indispensable tool for understand ing microbes by predicting their behavior and systematically allowing the testing of different hypotheses. On microbial communities, it further allows the prediction of interactions at the level of metabolites and metabolic reactions, therefore providing valuable insights on the inner working of the vast networks they constitute. Current extensions of this methodology have considered the addition of enzymatic data to single models in order to further constraint reaction fluxes and produce far more accurate results. The goal of the research presented in this dissertation is to combine different methodologies currently in existence in order to create a methodology that allows the effective and accurate simulation of the behaviour of gut microbial species inside a communal space. These simulations will ultimately aim to predict growth under low levels of transition metals in situations that resemble those of infection, where the host limits the availability of iron and other elements essential to all life forms in order to fight pathogenesis. Through the combination of the enhancement of models with enzymatic data with the creation of compartmentalized models under different simulation methods, the devised work aimed to extend both existent methodologies and produce results that were improved throughout the entirety of the work by basing and aiming to replicate provided results obtained from in vitro conditions. The obtained results reveal not only that the enhancement of models with enzyme constraints provide community stability but also the extension of the capabilities of community simulation methods previously established. The results of this work constitute a novel approach to the simulation of gut microbial communities that revealed the impact the enhancement process has on both the way models behave in singular settings and also in providing community stability. Moreover, the devised approach and subsequent results provide the oportunity of extension and improvement with ever more data in the application to similar or other study cases. |
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| Autores principais: | Castro, Alexandre Areias |
| Assunto: | Gut microbial communities Metabolism Community modeling Genome-scale metabolic models Transition metals Comunidades microbianas intestinais Metabolismo Modelação de comunidades Modelos metabólicos em escala genómica Metais de transição |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Genome-scale metabolic modeling has become a widespread methodology for analyzing microbial metabolism. The mathematical modeling of these networks has proven itself as an indispensable tool for understand ing microbes by predicting their behavior and systematically allowing the testing of different hypotheses. On microbial communities, it further allows the prediction of interactions at the level of metabolites and metabolic reactions, therefore providing valuable insights on the inner working of the vast networks they constitute. Current extensions of this methodology have considered the addition of enzymatic data to single models in order to further constraint reaction fluxes and produce far more accurate results. The goal of the research presented in this dissertation is to combine different methodologies currently in existence in order to create a methodology that allows the effective and accurate simulation of the behaviour of gut microbial species inside a communal space. These simulations will ultimately aim to predict growth under low levels of transition metals in situations that resemble those of infection, where the host limits the availability of iron and other elements essential to all life forms in order to fight pathogenesis. Through the combination of the enhancement of models with enzymatic data with the creation of compartmentalized models under different simulation methods, the devised work aimed to extend both existent methodologies and produce results that were improved throughout the entirety of the work by basing and aiming to replicate provided results obtained from in vitro conditions. The obtained results reveal not only that the enhancement of models with enzyme constraints provide community stability but also the extension of the capabilities of community simulation methods previously established. The results of this work constitute a novel approach to the simulation of gut microbial communities that revealed the impact the enhancement process has on both the way models behave in singular settings and also in providing community stability. Moreover, the devised approach and subsequent results provide the oportunity of extension and improvement with ever more data in the application to similar or other study cases. |
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