The well-documented ability to degrade lignin and a variety of complex chemicals showed by the white-rot fungus Phanerochaete chrysosporium has made it the subject of many studies in areas of environmental concern, including pulp bioleaching and bioremediation technologies. However, until now, most of the work in this field has been focused on the ligninolytic sub-system but, due to the great complexity of the involved processes, less progress has been made in understanding the biochemical regulatory structure that could explain growth dynamics, the substrate utilization and the ligninolytic system production itself. In this work we want to tackle this problem from the perspectives and approaches of systems biology, which have been shown to be effective in the case of complex systems. We will use a top-down approach to the construction of this model aiming to identify the cellular sub-systems that play a major role in the whole process. We have investigated growth dynamics, substrate consumption and lignin peroxidase production of the P. chrysosporium wild type under a set of definite culture conditions. Based on data gathered from different authors and in our own experimental determinations, we built a model using a GMA power-law representation, which was used as platform to make predictive simulations. Thereby, we could assess the consistency of some current assumptions about the regulatory structure of the overall process. The model parameters were estimated from a time series experimental measurements by means of an algorithm previously adapted and optimized for power-law models. The model was subsequently checked for quality by comparing its predictions with the experimental behavior observed in new, different experimental settings and through perturbation analysis aimed to test the robustness of the model. Hence, the model showed to be able to predict the dynamics of two critical variables such as biomass and lignin peroxidase activity when in conditions of nutrient deprivation and after pulses of veratryl alcohol. Moreover, it successfully predicts the evolution of the variables during both, the active growth phase and after the deprivation shock. The close agreement between the predicted and observed behavior and the advanced understanding of its kinetic structure and regulatory features provides the necessary background for the design of a biotechnological set-up designed for the continuous production of the ligninolityc system and its optimization.

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   |area=    PhanerochaeteV1
   |flux=    Main
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   |type=    RBID
   |clé=     pubmed:18694789
   |texte=   Growth and ligninolytic system production dynamics of the Phanerochaete chrysosporium fungus A modelling and optimization approach.
}}

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