Mathematical modeling of diurnal patterns of carbon allocation to shoot and root in Arabidopsis thaliana

Lisa Küstner,Arnd G Heyer,Thomas Nägele

doi:10.1038/s41540-018-0080-1

Abstract

We developed a mathematical model to simulate dynamics of central carbon metabolism over complete diurnal cycles for leaves of Arabidopsis thaliana exposed to either normal (120 µmol m−2 s−1) or high light intensities (1200 µmol m−2 s−1). The main objective was to obtain a high-resolution time series for metabolite dynamics as well as for shoot structural carbon formation (compounds with long residence time) and assimilate export of aerial organs to the sink tissue. Model development comprised a stepwise increment of complexity to finally approach the in vivo situation. The correct allocation of assimilates to either sink export or shoot structural carbon formation was a central goal of model development. Diurnal gain of structural carbon was calculated based on the daily increment in total photosynthetic carbon fixation, and this was the only parameter for structural carbon formation implemented in the model. Simulations of the dynamics of central metabolite pools revealed that shoot structural carbon formation occurred solely during the light phase but not during the night. The model allowed simulation of shoot structural carbon formation as a function of central leaf carbon metabolism under different environmental conditions without structural modifications. Model simulations were performed for the accession Landsberg erecta (Ler) and its hexokinase null-mutant gin2-1. This mutant displays a slow growth phenotype especially at increasing light intensities. Comparison of simulations revealed that the retarded shoot growth in the mutant resulted from an increased assimilate transport to sink organs. Due to its central function in sucrose cycling and sugar signaling, our findings suggest an important role of hexokinase-1 for carbon allocation to either shoot growth or assimilate export.

Highlights

With rising interest in plant biomass for nutritional, pharmaceutical, and energetic use, understanding of parameters that determine growth will become more and more important
To link metabolic regulation in central primary metabolism of Arabidopsis with growth processes, we developed a dynamic mathematical model to simulate structural carbon allocation to shoot tissue under varying environmental conditions
Extending previous work, the main goal of the present study was to develop a kinetic model allowing to simulate the interaction of central leaf carbon metabolism and structural carbon formation during a full diurnal cycle in order to yield a mechanistic understanding of how carbon allocation is affected by metabolic regulation

Summary

Introduction

With rising interest in plant biomass for nutritional, pharmaceutical, and energetic use, understanding of parameters that determine growth will become more and more important. In the CAM intermediate Clusia minor, leaf growth peaked in the night when in C3 mode of photosynthesis, while it was higher during the day in CAM mode.[9] In field grown wheat, growth was larger during the day,[10] while for maize grown in climate chambers the pattern was less clear.[11] In soybean and tobacco, leaf growth appeared to prevail in the dark period,[12,13] while it was stronger during daytime in Arabidopsis.[14] Mielewczik et al.[15] found that leaf growth tightly correlated with air humidity, while it did not correlate with temperature This reflects an important aspect of the imaging experiments: they document leaf expansion rather than structural carbon gain, and are strongly depending on the leaf water status. The resulting dynamic model of the central metabolism of A. thaliana leaves can simulate shoot structural carbon formation at high resolution in time This was achieved by allocating carbon, gained through photosynthesis, to either metabolic pools, root supply, or leaf structural carbon. The latter pool contains all carbon allocated to Received: 31 January 2018 Accepted: 7 December 2018

Objectives

Methods

Results

Conclusion