This paper presents a methodology for identifying the kinetic parameters of a biological system and their relationships with the concentration variations of the species by means of in silico experiments. A nonlinear goal programming technique is employed to identify the kinetic parameters that best satisfy the biological hypothesis of the system behaviour. The simulations are performed on a stochastic simulator for the Calculus of Wrapped Compartments. The extraction of parameters with optimization techniques is usually applied to systems modeled by means of differential equations. Its application in a stochastic framework is rather new. The methodology may open a new path for the investigation of a broader class of biochemical systems (including those that cannot be easily modeled by differential equations) when in vitro experimental measurements are unavailable. The methodology is applied to model the nutrient exchanges in arbuscular mycorrhiza, the most wide-spread plant/fungus symbiosis focusing in particular to a newly discovered ammonium transporter: LjAMT2;2. This case study of ammonia and phosphate plant uptake from the fungus has been dissected in known and hypothetical mechanisms. The results of the analysis provide setting of recent experimental results of carrier LjAMT2;2 and support new insights into biological hypotheses to be put in place.

Parameter Identification and Assessment of Nutrient Transporters in AM Symbiosis through Stochastic Simulations

SCIACCA, EVA;SPINELLA, SALVATORE;CALCAGNO, CRISTINA;DAMIANI, Ferruccio;COPPO, Mario
2013-01-01

Abstract

This paper presents a methodology for identifying the kinetic parameters of a biological system and their relationships with the concentration variations of the species by means of in silico experiments. A nonlinear goal programming technique is employed to identify the kinetic parameters that best satisfy the biological hypothesis of the system behaviour. The simulations are performed on a stochastic simulator for the Calculus of Wrapped Compartments. The extraction of parameters with optimization techniques is usually applied to systems modeled by means of differential equations. Its application in a stochastic framework is rather new. The methodology may open a new path for the investigation of a broader class of biochemical systems (including those that cannot be easily modeled by differential equations) when in vitro experimental measurements are unavailable. The methodology is applied to model the nutrient exchanges in arbuscular mycorrhiza, the most wide-spread plant/fungus symbiosis focusing in particular to a newly discovered ammonium transporter: LjAMT2;2. This case study of ammonia and phosphate plant uptake from the fungus has been dissected in known and hypothetical mechanisms. The results of the analysis provide setting of recent experimental results of carrier LjAMT2;2 and support new insights into biological hypotheses to be put in place.
2013
Third International Workshop on Interactions Between Computer Science and Biology (CS2Bio'12)
Stockholm, Sweden
June 16, 2012
293
83
96
http://www.sciencedirect.com/science/article/pii/S1571066113000224
Systems Biology; Formal Calculi; CWC; Mycorrhizal Symbiosis; Optimization; Parameter Identification
Eva Sciacca;Salvatore Spinella;Cristina Calcagno;Ferruccio Damiani;Mario Coppo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/139517
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