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Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger

BACKGROUND: In this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysi...

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Autores principales: Omony, Jimmy, de Graaff, Leo H, van Straten, Gerrit, van Boxtel, Anton J B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3121114/
https://www.ncbi.nlm.nih.gov/pubmed/21689473
http://dx.doi.org/10.1186/1752-0509-5-S1-S14
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author Omony, Jimmy
de Graaff, Leo H
van Straten, Gerrit
van Boxtel, Anton J B
author_facet Omony, Jimmy
de Graaff, Leo H
van Straten, Gerrit
van Boxtel, Anton J B
author_sort Omony, Jimmy
collection PubMed
description BACKGROUND: In this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysis is performed. The activating, repressive feedback, and the combined effect of the two feedbacks on the network behavior are analyzed. RESULTS: Simulation and systems analysis showed significant influence of activating and repressing feedback on metabolite expression profiles. The dynamics of the D-xylose input function has an important effect on the profiles of the individual metabolite concentrations. Variation of the time delay in the feedback loop has no significant effect on the pattern of the response. The stability and existence of oscillatory behavior depends on which proteins are involved in the feedback loop. CONCLUSIONS: The dynamics in the regulation properties of the network are dictated mainly by the transcription and translation degradation rate parameters, and by the D-xylose consumption profile. This holds true with and without feedback in the network. Feedback was found to significantly influence the expression dynamics of genes and proteins. Feedback increases the metabolite abundance, changes the steady state values, alters the time trajectories and affects the response oscillatory behavior and stability conditions. The modeling approach provides insight into network behavioral dynamics particularly for small-sized networks. The analysis of the network dynamics has provided useful information for experimental design for future in vitro experimental work.
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spelling pubmed-31211142011-06-23 Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger Omony, Jimmy de Graaff, Leo H van Straten, Gerrit van Boxtel, Anton J B BMC Syst Biol Report BACKGROUND: In this paper the dynamics of the transcription-translation system for XlnR regulon in Aspergillus niger is modeled. The model is based on Hill regulation functions and uses ordinary differential equations. The network response to a trigger of D-xylose is considered and stability analysis is performed. The activating, repressive feedback, and the combined effect of the two feedbacks on the network behavior are analyzed. RESULTS: Simulation and systems analysis showed significant influence of activating and repressing feedback on metabolite expression profiles. The dynamics of the D-xylose input function has an important effect on the profiles of the individual metabolite concentrations. Variation of the time delay in the feedback loop has no significant effect on the pattern of the response. The stability and existence of oscillatory behavior depends on which proteins are involved in the feedback loop. CONCLUSIONS: The dynamics in the regulation properties of the network are dictated mainly by the transcription and translation degradation rate parameters, and by the D-xylose consumption profile. This holds true with and without feedback in the network. Feedback was found to significantly influence the expression dynamics of genes and proteins. Feedback increases the metabolite abundance, changes the steady state values, alters the time trajectories and affects the response oscillatory behavior and stability conditions. The modeling approach provides insight into network behavioral dynamics particularly for small-sized networks. The analysis of the network dynamics has provided useful information for experimental design for future in vitro experimental work. BioMed Central 2011-06-20 /pmc/articles/PMC3121114/ /pubmed/21689473 http://dx.doi.org/10.1186/1752-0509-5-S1-S14 Text en Copyright ©2011 Omony et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Report
Omony, Jimmy
de Graaff, Leo H
van Straten, Gerrit
van Boxtel, Anton J B
Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title_full Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title_fullStr Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title_full_unstemmed Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title_short Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger
title_sort modeling and analysis of the dynamic behavior of the xlnr regulon in aspergillus niger
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3121114/
https://www.ncbi.nlm.nih.gov/pubmed/21689473
http://dx.doi.org/10.1186/1752-0509-5-S1-S14
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