BMC Bioinformatics (Jun 2019)

A mass and charge balanced metabolic model of Setaria viridis revealed mechanisms of proton balancing in C4 plants

  • Rahul Shaw,
  • C. Y. Maurice Cheung

DOI
https://doi.org/10.1186/s12859-019-2941-z
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 11

Abstract

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Abstract Background C4 photosynthesis is a key domain of plant research with outcomes ranging from crop quality improvement, biofuel production and efficient use of water and nutrients. A metabolic network model of C4 “lab organism” Setaria viridis with extensive gene-reaction associations can accelerate target identification for desired metabolic manipulations and thereafter in vivo validation. Moreover, metabolic reconstructions have also been shown to be a significant tool to investigate fundamental metabolic traits. Results A mass and charge balance genome-scale metabolic model of Setaria viridis was constructed, which was tested to be able to produce all major biomass components in phototrophic and heterotrophic conditions. Our model predicted an important role of the utilization of NH 4+ $_{4}^{+}$ and NO 3− $_{3}^{-}$ ratio in balancing charges in plants. A multi-tissue extension of the model representing C4 photosynthesis was able to utilize NADP-ME subtype of C4 carbon fixation for the production of lignocellulosic biomass in stem, providing a tool for identifying gene associations for cellulose, hemi-cellulose and lignin biosynthesis that could be potential target for improved lignocellulosic biomass production. Besides metabolic engineering, our modeling results uncovered a previously unrecognized role of the 3-PGA/triosephosphate shuttle in proton balancing. Conclusions A mass and charge balance model of Setaria viridis, a model C4 plant, provides the possibility of system-level investigation to identify metabolic characteristics based on stoichiometric constraints. This study demonstrated the use of metabolic modeling in identifying genes associated with the synthesis of particular biomass components, and elucidating new role of previously known metabolic processes.

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