Natural variation of temperature acclimation of Arabidopsis thaliana.

Acclimation is a multigenic trait by which plants adjust photosynthesis and metabolism to cope with a changing environment. Here, natural variations of photosynthetic efficiency and acclimation of the central carbohydrate metabolism were analyzed in response to low and elevated temperatures. For this, 18 natural accessions of Arabidopsis thaliana, originating from Cape Verde Islands and Europe, were grown at 22°C before being exposed to 4°C and 34°C for cold and heat acclimation, respectively. Absolute amounts of carbohydrates were quantified together with their subcellular distribution across plastids, cytosol and vacuole. Linear electron transport rates (ETRs) were determined together with the maximum quantum efficiency of photosystem II (Fv/Fm) for all growth conditions and under temperature fluctuation. Under elevated temperature, ETR residuals under increasing photosynthetic photon flux densities significantly correlated with the degree of temperature fluctuation at the original habitat of accessions, indicating a geographical east/west gradient of photosynthetic acclimation capacities. Plastidial sucrose concentrations positively correlated with maximal ETRs under fluctuating temperature, indicating a stabilizing role within the chloroplast. Our findings revealed specific subcellular carbohydrate distributions that contribute differentially to the photosynthetic efficiency of natural Arabidopsis thaliana accessions across a longitudinal gradient. This sheds light on the relevance of subcellular metabolic regulation for photosynthetic performance in a fluctuating environment and supports the physiological interpretation of naturally occurring genetic variation of temperature tolerance and acclimation.

Quantifying the impact of dynamic plant-environment interactions on metabolic regulation.

A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana, has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation.

Predicting plant growth response under fluctuating temperature by carbon balance modelling.

Quantification of system dynamics is a central aim of mathematical modelling in biology. Defining experimentally supported functional relationships between molecular entities by mathematical terms enables the application of computational routines to simulate and analyse the underlying molecular system. In many fields of natural sciences and engineering, trigonometric functions are applied to describe oscillatory processes. As biochemical oscillations occur in many aspects of biochemistry and biophysics, Fourier analysis of metabolic functions promises to quantify, describe and analyse metabolism and its reaction towards environmental fluctuations. Here, Fourier polynomials were developed from experimental time-series data and combined with block diagram simulation of plant metabolism to study heat shock response of photosynthetic CO2 assimilation and carbohydrate metabolism in Arabidopsis thaliana. Simulations predicted a stabilising effect of reduced sucrose biosynthesis capacity and increased capacity of starch biosynthesis on carbon assimilation under transient heat stress. Model predictions were experimentally validated by quantifying plant growth under such stress conditions. In conclusion, this suggests that Fourier polynomials represent a predictive mathematical approach to study dynamic plant-environment interactions.