Phytochromes control metabolic flux, and their action at the seedling stage determines adult plant biomass

Phytochrome (phy) photoreceptors are known to regulate plastic growth responses to vegetation shade. However, recent reports also suggest an important role for phys in carbon resource management, metabolism, and growth. Here, we use 13CO2 labelling patterns in multi-allele phy mutants to investigate the role of phy in the control of metabolic fluxes. We also combine quantitative data of 13C incorporation into protein and cell wall polymers, gas exchange measurements and system modelling to investigate why biomass is decreased in adult multi-allele phy mutants. Phy influences the synthesis of stress metabolites like raffinose and proline, and the accumulation of sugars, possibly through regulating vacuolar sugar transport. Remarkably, despite their modified metabolism and vastly altered architecture, growth rates in adult phy mutants resemble those of wild-type plants. Our results point to delayed seedling growth and smaller cotyledon size as the cause of the adult-stage phy mutant biomass defect. Our data signify a role for phy in metabolic stress physiology, carbon partitioning and illustrate that phy action at the seedling stage sets the trajectory for adult biomass production

The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation

Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. The three candidate mechanisms tested did not explain this organic acid accumulation. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth

Understanding how dynamic molecular networks affect wholeorganism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field. (Résumé d'auteur

Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure

Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell−1) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell−1) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible

Data, Code and Models for Flis et al. RS Open Biology 2015

Provides URLs to the Data, Code and Models for Flis et al. RS Open Biology 2015 article entitled, "Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure".Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak ~50 copies/cell) compared with other clock genes, and three-fold higher levels of LHY RNA (>1500 copies/cell) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focussed timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly-available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly-interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible.Citations are detailed for each URL listed below

Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit.

Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits

Leaf starch turnover occurs in long days and in falling light at the end of the day

We investigated whether starch degradation occurs at the same time as starch synthesis in Arabidopsis (Arabidopsis thaliana) leaves in the light. Starch accumulated in a linear fashion for about 12 h after dawn, then accumulation slowed and content plateaued. Following decreases in light intensity, the rate of accumulation of starch declined in proportion to the decline in photosynthesis if the decrease occurred 14 h after dawn and in response to decreases in light intensity that occurred >10 h after dawn. Starch measurements in circadian clock mutants suggested that the clock influences the timing of onset of degradation. We conclude that the propensity for leaf starch to be degraded increases with time after dawn. The importance of this phenomenon for efficient use of carbon for growth in long days and for prevention of starvation during twilight is discussed.This work was supported by the European Commission FP7 Collaborative Project TiMet (contract 245143 to O.F., V.M., and A.F.), by BBSRC Institute Strategic Programme Grant BB/J004561/1 to the John Innes Centre (O.F., A.M.S.), by the Max-Planck Society, Germany (H.I., D.S., S.A., R.F., J.E.L., M.S.), by ETH (Zurich), and by SystemsX (Switzerland) grant “Plant Growth in a Changing Environment” (G.M.G., S.C.Z.)

Leaf starch turnover occurs in long days and in falling light at the end of the day

International audienceWe investigated whether starch degradation occurs at the same time as starch synthesis in Arabidopsis (Arabidopsis thaliana) leaves in the light. Starch accumulated in a linear fashion for about 12 h after dawn, then accumulation slowed and content plateaued. Following decreases in light intensity, the rate of accumulation of starch declined in proportion to the decline in photosynthesis if the decrease occurred, 10 h after dawn, but accumulation ceased or loss of starch occurred if the same decrease in light intensity was imposed more than 10 h after dawn. These changes in starch accumulation patterns after prolonged periods in the light occurred at both high and low starch contents and were not related to time-dependent changes in either the rate of photosynthesis or the partitioning of assimilate between starch and Suc, as assessed from metabolite measurements and (CO2)-C-14 pulse experiments. Instead, measurements of incorporation of C-13 from (CO2)-C-13 into starch and of levels of the starch degradation product maltose showed that substantial starch degradation occurred simultaneously with synthesis at time points > 14 h after dawn and in response to decreases in light intensity that occurred > 10 h after dawn. Starch measurements in circadian clock mutants suggested that the clock influences the timing of onset of degradation. We conclude that the propensity for leaf starch to be degraded increases with time after dawn. The importance of this phenomenon for efficient use of carbon for growth in long days and for prevention of starvation during twilight is discussed