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Growth and maintenance processes requiring carbon must be maintained despite daily fluctuations in light and dark conditions. Buffering against daily fluctuations in the carbon supply is achieved through a diel turnover of starch. Starch accumulates in the day and decreases in the night with almost linearly. Moreover, starch accumulates rapidly and decreases slowly as night-period decreases, which allows plants to maintain the same amount of starch at the end of the night regardless of photoperiod. Recent studies reported the importance of feedbacks between circadian clocks and carbon metabolism for optimal growth. However how plants adjust starch metabolism in response to changing photoperiod remains elusive. To investigate the mechanism of flexible coordination of starch metabolism, we modeled the interplay of carbon metabolism and circadian clocks. We first showed that the linearity of starch metabolism is an emergent property of sucrose homeostasis. We next demonstrated that hyperbolic function of starch degradation rate that has a peak at dawn is necessary for sucrose homeostasis. We then showed that a phase response curve to sucrose signals that realizes sucrose homeostasis is the same as the one determined by the experiment, which shows phase advance in the morning and delay in the night. We finally showed that the phase response to sucrose signals leads to appropriate adjustment of starch accumulation and degradation rates. These results indicate that the responsiveness of plant circadian clocks to sucrose signals has the adaptive significance for optimal growth under diel and seasonal fluctuations in environments. [mehr]

There is a growing demand for the effective metabolic and genetic manipulation of plants to benefit human society in many ways. The layers of complex interacting biological networks affecting plant growth makes this a difficult task, and several genome-scale metabolic reconstructions have been published as a means to enable researchers to explore these networks in silico. However the construction of these networks rely heavily on the evidence available for the biochemistry, gene-reaction associations, and compartmentalization. Furthermore propagating these networks for any species other than the model plant Arabidopsis thaliana in turn rely heavily on the phylogeny of plant protein families. I present the PlantSEED project where we set a gold standard for the curation of enzymes involved in plant primary metabolism, including isofunctional paralogs, from which we generate a draft top-down model of Arabidopsis thaliana and, via conservative use of EnsemblCompara families, 9 other species. I will also discuss the use of additional evidence to build a larger, compartmentalized model of Maize, and the use of transcript profiles to build. The data, along with additional functionality for metabolic flux analysis, is available in both the DOE Systems Biology Knowledgebase and our PlantSEED web portal. Finally I will describe our future plans for the expansion of PlantSEED. [mehr]