Plant Physiology Preview
Published on August 24, 2007; 10.1104/pp.107.103713
OPEN ACCESS ARTICLE
Received June 11, 2007
Accepted July 22, 2007
Optimizing the Distribution of Resources between Enzymes of Carbon Metabolism can Dramatically Increase Photosynthetic Rate. A Numerical Simulation using an Evolutionary Algorithm
Xin-Guang Zhu , Eric deSturler , and Stephen P. Long *
Department of Plant Biology and Crop Sciences, University of Illinois at Urbana Champaign, 379 Madigan Laboratory, 1201 W. Gregory Drive, Urbana, IL, 61801, USA; Department of Mathematics, 544 McBryde Hall, Virginia Tech, Blacksburg, VA 24601-0123; National Center for Supercomputing Applications, 1319 Beckman Institute, 405 N. Mathews, Urbana 61801; Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1207 West Gregory Drive, Urbana, IL 61801
* Corresponding author; email: stevel{at}life.uiuc.edu.
The distribution of resources between enzymes of photosynthetic carbon metabolism might be assumed to have been optimized by natural selection. However, natural selection for survival and fecundity does not necessarily select for maximal photosynthetic productivity. Further atmospheric CO2 concentration, the key substrate, has changed more over the past 100 years than the past 25M years with the likelihood that natural selection has had inadequate time to re-optimize resource partitioning for this change. Could photosynthetic rate be increased by altered partitioning of resource among the enzymes of carbon metabolism? This question is addressed by using an "evolutionary" algorithm to progressively search for multiple alterations in partitioning that increase photosynthetic rate. To do this, we extended existing metabolic models of C3 photosynthesis by including the photorespiratory pathway (PCOP) and metabolism to starch and sucrose to develop a complete dynamic model of photosynthetic carbon metabolism. The model consists of linked differential equations, each representing the changes of concentration of one metabolite. Initial concentrations of metabolites and maximal activities of enzymes were extracted from the literature. The dynamics of CO2 fixation and metabolite concentrations were realistically simulated by numerical integration, such that the model could mimic well established physiological phenomena. For example, a realistic steady-state rate of CO2 uptake was attained and then re-attained after perturbing O2 concentration. Using an evolutionary algorithm, partitioning of a fixed total amount of protein-nitrogen between enzymes was allowed to vary. The individual with the higher light saturated photosynthetic rate was selected and used to seed the next generation. After 1500 generations, photosynthesis was increased substantially. This suggests that the "typical" partitioning in C3 leaves might be suboptimal for maximizing the light-saturated rate of photosynthesis. An over-investment in PCOP enzymes and under-investment in Rubisco, SBPase (sedoheptulose-1:7-bisphosphatase) and FBP aldolase were indicated. Increase in sink capacity such as increase in ADP glucose pyrophosphorylase was also indicated to lead to increased CO2 uptake rate. These results suggest that manipulation of partitioning could greatly increase carbon gain without any increase in the total protein-nitrogen investment in the apparatus for photosynthetic carbon metabolism.
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