Mathematical Modeling of Acclimation Processes of the Photosynthetic Chain

Document Type : Research Article

Authors

• S Heidari ¹
• S. H Marashi ¹
• S Malekzadeh Shafaroudi ¹
• M Ghaderi Zafreyi ²

¹ Ferdowsi University of Mashhad

² Yasouj University

10.22067/gsc.v14i2.39666

Abstract

Introduction
Photosynthetic energy conversion efficiency is characteristic of a system which is determined by interactions between various components of the system. The complex process of photosynthesis has been studied as a whole system which enables in silico examination of a large number of candidate genes for genetic engineering for a higher photosynthetic energy conversion efficiency. One of the most important environmental factors which influence the photosynthesis efficiency is light regime which can cause producing ROS components. To acclimate to such fluctuations, plants have evolved adaptive mechanisms to minimize damage of the photosynthetic apparatus excess light. A fast compatibility response to high light stresses is non-photochemical quenching process (NPQ), dissipating excessive energy to heat. Light harvested state switches into a quenched state by a conformational change of light harvesting complex (LHCII) that regulated by xanthophylls and the PsbS protein within seconds. Low lumen pH activates xanthophyll synthesis via a xanthophyll cycle which consists of the de-epoxidation of violaxanthin to zeaxanthin by violaxanthin de-epoxidase in high light and inversely by zeaxanthin epoxidase in low light which occurs more slowly.
Materials and Methods
Thale cress (Arabidopsis thaliana) (Chlombia-0) were grown on soil at 25/22 °C day/night temperature, with a 16/8 h photoperiod, and 40-70% (depend of plant species) relative humidity. The light intensity was 150–200 µE m-2s-1 white light. Intensity of chlorophyll fluorescence was measured with PAM-2000 fluorometer (Heinz Walz, Germany) and the manufacturer’s software (PamWin v.2).
Results and Discussion
In the present study, a dynamic kinetics amplified mathematical model was developed based on differential equations in order to predict short-term changes in NPQ in the process of adaptation to different light conditions. We investigated the stationary and dynamic behavior of the model and systematically analyze the dependence of system key characteristic such as rate constant and pool size. For medium and high light intensity, experimental evidence has been predicted with high accuracy by simulation. In low light intensity (100μE m-2s-1) in a few seconds the light phase, a temporary increase in the rate of NPQ was observed after about 60 seconds it reaches to a steady state level. Model simulation of the induction of NPQ relaxation is more accurate than previous predictions, due to the introduction of more stringent quenching agents (xanthophylls cycle and also the light-harvesting complex protonations). The results showed that the pH drop in the transition from darkness to light and high light intensity increases. For low light intensity quenching process occurs with a more gentle slope to the prediction model based on previous experiments is more realistic. In low light conditions, the proton concentration can easily be balanced by ATP synthase activity. This leads to a reduction in current proton-proton feedback gathered during few seconds is balanced. Thus, at high light intensities ATP levels remained stable in the new model is more consistent with reality.
Conclusions
A simple mathematical model which has been developed in this paper provides a more detailed description of this process and be able to predict the various components and parameters associated with it. Comparison of simulation results with experimental data revealed that protonated light harvesting complex and Zeaxanthin simultaneously induce NPQ quenching processes. The results can be seen as theoretical basis for developing more accurate models to study molecular mechanisms of acclimation processes of the photosynthetic chain.

Keywords

• Modeling
• Non-photochemical Quenching
• Photosynthesis

20.1001.1.20081472.1395.14.2.10.9

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