Effects of varying nitrogen sources on amino acid synthesis costs in Arabidopsis thaliana under different light and carbon-source conditions.

Plants as sessile organisms cannot escape their environment and have to adapt to any changes in the availability of sunlight and nutrients. The quantification of synthesis costs of metabolites, in terms of consumed energy, is a prerequisite to understand trade-offs arising from energetic limitations...

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Bibliographic Details
Main Authors: Anne Arnold, Max Sajitz-Hermstein, Zoran Nikoloski
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4338252?pdf=render
Description
Summary:Plants as sessile organisms cannot escape their environment and have to adapt to any changes in the availability of sunlight and nutrients. The quantification of synthesis costs of metabolites, in terms of consumed energy, is a prerequisite to understand trade-offs arising from energetic limitations. Here, we examine the energy consumption of amino acid synthesis in Arabidopsis thaliana. To quantify these costs in terms of the energy equivalent ATP, we introduce an improved cost measure based on flux balance analysis and apply it to three state-of-the-art metabolic reconstructions to ensure robust results. We present the first systematic in silico analysis of the effect of nitrogen supply (nitrate/ammonium) on individual amino acid synthesis costs as well as of the effect of photoautotrophic and heterotrophic growth conditions, integrating day/night-specific regulation. Our results identify nitrogen supply as a key determinant of amino acid costs, in agreement with experimental evidence. In addition, the association of the determined costs with experimentally observed growth patterns suggests that metabolite synthesis costs are involved in shaping regulation of plant growth. Finally, we find that simultaneous uptake of both nitrogen sources can lead to efficient utilization of energy source, which may be the result of evolutionary optimization.
ISSN:1932-6203