A mathematical model of non-photochemical quenching to study short-term light memory in plants.

Abstract

Plants are permanently exposed to rapidly changing environments, therefore it is evident that they had to evolve mechanisms enabling them to dynamically adapt to such fluctuations. Here we study how plants can be trained to enhance their photoprotection and elaborate on the concept of the short-term illumination memory in Arabidopsis thaliana. By monitoring fluorescence emission dynamics we systematically observe the extent of non-photochemical quenching (NPQ) after previous light exposure to recognise and quantify the memory effect. We propose a simplified mathematical model of photosynthesis that includes the key components required for NPQ activation, which allows us to quantify the contribution to photoprotection by those components. Due to its reduced complexity, our model can be easily applied to study similar behavioural changes in other species, which we demonstrate by adapting it to the shadow-tolerant plant Epipremnum aureum. Our results indicate that a basic mechanism of short-term light memory is preserved. The slow component, accumulation of zeaxanthin, accounts for the amount of memory remaining after relaxation in darkness, while the fast one, antenna protonation, increases quenching efficiency. With our combined theoretical and experimental approach we provide a unifying framework describing common principles of key photoprotective mechanisms across species in general, mathematical terms.

Plant phenotyping relevance

NPQ蛍光動態を用いた植物の光防御状態の定量と、他種にも適用可能な数学モデルの開発が研究の中心であり、単なる生物学的 routine 測定ではない。

Code and data availability

The authors explicitly provide open-source code (the npqmodel repository) that reproduces all figures in the paper, including the simulations of the PAM fluorescence measurements. No separate public phenotype dataset deposit is stated (data extraction is referenced only vaguely as 'the database').