Modeling the flux of metabolites in the juvenile hormone biosynthesis pathway using generalized additive models and ordinary differential equations
Juvenile hormone (JH) regulates development and reproductive maturation in insects. Thecorpora allata (CA) from female adult mosquitoes synthesize fluctuating levels of JH, whichhave been linked to the ovarian development and are influenced by nutritional signals. Therate of JH biosynthesis is contr...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/78966 |
| Acceso en línea: | http://hdl.handle.net/11336/78966 |
| Access Level: | acceso abierto |
| Palabra clave: | JUVENILE HORMONE SYNTHESIS MODELING BIOSYNTHESIS AEDES AEGYPTI MEVALONIC ACID PATHWAY https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
| Sumario: | Juvenile hormone (JH) regulates development and reproductive maturation in insects. Thecorpora allata (CA) from female adult mosquitoes synthesize fluctuating levels of JH, whichhave been linked to the ovarian development and are influenced by nutritional signals. Therate of JH biosynthesis is controlled by the rate of flux of isoprenoids in the pathway, whichis the outcome of a complex interplay of changes in precursor pools and enzyme levels. Acomprehensive study of the changes in enzymatic activities and precursor pool sizes havebeen previously reported for the mosquito Aedes aegypti JH biosynthesis pathway. In thepresent studies, we used two different quantitative approaches to describe and predict howchanges in the individual metabolic reactions in the pathway affect JH synthesis. First, weconstructed generalized additive models (GAMs) that described the association betweenchanges in specific metabolite concentrations with changes in enzymatic activities and sub-strate concentrations. Changes in substrate concentrations explained 50% or more of themodel deviances in 7 of the 13 metabolic steps analyzed. Addition of information on enzy-matic activities almost always improved the fitness of GAMs built solely based on substrateconcentrations. GAMs were validated using experimental data that were not included whenthe model was built. In addition, a system of ordinary differential equations (ODE) wasdeveloped to describe the instantaneous changes in metabolites as a function of the levelsof enzymatic catalytic activities. The results demonstrated the ability of the models to predictchanges in the flux of metabolites in the JH pathway, and can be used in the future to designand validate experimental manipulations of JH synthesis. |
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