Scaling and Integration of Kinetic Models of Photosynthesis: Towards Comprehensive E-Photosynthesis
Mathematical models are essential to understand dynamic behavior of complex biological systems. Photosynthesis as it occurs in a natural environment reflects not only the primary biophysical and biochemical reactions but also a network of regulatory interactions that act across timescales and spatial boundaries. Modeling such a tightly regulated biosystem is feasible when the model is reduced to describe only a rather particular experimental situation such as fluorescence response to a single turnover light flash or the dynamics around the steady-state of Calvin—Benson cycle. Then, the external egulatory interactions can be considered negligible or not changing so that the investigated dynamics can be predicted by modeling the system with only few key components that are relevant for the given time and complexity scale. Such an empiric dimensionality reduction has been successfully applied in photosynthesis research, leading to a mosaic of partial models that map along the Z-scheme of light reactions as well as covering parts of carbon metabolism. The validity ranges of the partial models are frequently not overlapping, leaving gaps in the photosynthesis modeling space. Filling the gaps and, even more important, modeling of regulatory interactions between modeled entities are hampered by incompatibility of the partial models that focus on different time scales or that are restricted to particular experimental situations. This led us to propose the Comprehensive Modeling Space, CMS where the partial photosynthesis models would be shared by means of the Systems Biology Mark-Up Language, SBML, which is the de-facto standard for the formal representation of biochemical models. The model validity is defined by a customized extension of the biology-wide standard of Minimum Information Requested in the Annotation of Biochemical Models, MIRIAM. The hierarchy and connectivity of the partial models within the Comprehensive Modeling Space is determined by rigorous dimensionality reduction techniques. Here, we exemplify the principles of the comprehensive modeling approach based on partial models of the Photosystem II.
KeywordsPartial Model Light Reaction System Biology Markup Language Biochemical Model Primary Charge Separation
Unable to display preview. Download preview PDF.
- Duysens LNM and Sweers HE (1963) Mechanism of the two photochemical reactions in algae as studied by means of fluorescence. In: Studies on Microalgae and Photosynthetic Bacteria, pp. 353–372. University of Tokyo Press, TokyoGoogle Scholar
- Hucka M, Finney A, Sauro H, Bolouri H, Doyle J, Kitano H, Arkin A, Bornstein B, Bray D, Cornish-Bowden A, Cuellar A, Dronov S, Gilles E, Ginkel M, Gor V, Goryanin I, Hedley W, Hodgman T, Hofmeyr J-H, Hunter P, Juty N, Kasberger J, Kremling A, Kummer U, Le Novére N, Loew L, Lucio D, Mendes P, Minch E, Mjolsness E, Nakayama Y, Nelson M, Nielsen P, Sakurada T, Schaff J, Shapiro B, Shimizu T, Spence H, Stelling J, Takahashi K, Tomita M, Wagner J and Wang J (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19: 524–531PubMedCrossRefGoogle Scholar
- Le Novère N, Finney A, Hucka M, Bhalla US, Campagne F, Collado-Vides J, Crampin EJ, Halstead M, Klipp E, Mendes P, Nielsen P, Sauro H, Shapiro B, Snoep JL, Spence HD, and Wanner BL (2005) Minimum information requested in the annotation of biochemical models (MIRIAM). Nature Biotech 23: 1509–1515CrossRefGoogle Scholar
- Maertens J, Donckels BMR, Lequeux G and Vanrolleghem PA (2005) Metabolic model reduction by metabolite pooling on the basis of dynamic phase planes and metabolite correlation analysis. In: Proceedings of the Conference on Modeling and Simulation in Biology, pp. 147–151. Linköping, SwedenGoogle Scholar
- Nedbal L, Březina V, Adamec F, Štys D, Oja V, Laisk A and Govindjee (2003) Negative feedback regulation is responsible for the non-linear modulation of photosynthetic activity in plants and cyanobacteria exposed to a dynamic light environment. Biochim Biophys Acta 1607: 5–17PubMedCrossRefGoogle Scholar
- Rugh WJ (1996) Linear System Theory. PrenticeHall, NJ, USAGoogle Scholar
- Skogestad S and Postlethwaite I (1996) Mutlivariable Feedback Control. Wiley, Hoboken, NJ, USAGoogle Scholar