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Edited by: Sonia Osorio, Málaga University, Spain

Reviewed by: Alexander R. van der Krol, Wageningen University, Netherlands; Kansuporn Sriyudthsak, RIKEN Center for Sustainable Resource Science, Japan

*Correspondence: Thomas Nägele, Department Ecogenomics and Systems Biology, University of Vienna, Althanstr. 14, 1090 Vienna, Austria e-mail:

This article was submitted to Plant Systems Biology, a section of the journal Frontiers in Plant Science.

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During the last decade genome sequencing has experienced a rapid technological development resulting in numerous sequencing projects and applications in life science. In plant molecular biology, the availability of sequence data on whole genomes has enabled the reconstruction of metabolic networks. Enzymatic reactions are predicted by the sequence information. Pathways arise due to the participation of chemical compounds as substrates and products in these reactions. Although several of these comprehensive networks have been reconstructed for the genetic model plant

The rapidly increasing knowledge about whole plant genome sequences represents a corner stone in the understanding of plant metabolism. Next-generation sequencing (NGS) technologies have been developed allowing for the fast and cheap production of huge sets of genome data sequences (Metzker,

Here, we present a workflow aiming at the development of such a platform. Based on a recently published metabolic network reconstruction accounting for subcellular organization of leaf metabolism in

The model adaptation was performed starting with the original metabolic reconstruction model for (juvenile) leaf metabolism, which was derived by Mintz-Oron and co-workers (Mintz-Oron et al., _{2}. In the following step, all intermediates in the reduced model were (re)connected manually according to the reactions described in the original reconstruction model and no further reactions were added. Hence, the reduced model describes a subset of the metabolic connections in the original model with a lower degree of detail. A step of this reduction procedure is exemplarily shown in Figure

A metabolic interaction matrix was derived from the reduced model describing all metabolic interactions in the model. Hence, the metabolic interaction matrix represents a simplified version of the stoichiometric matrix of the original metabolic reconstruction model. This metabolic interaction matrix was applied for inverse calculation of the Jacobian matrix of the metabolic model. The calculation procedure was based on an algorithm, which is implemented in the metabolomics toolbox COVAIN (Sun and Weckwerth, _{a} and J_{b}, which describe two different metabolic states, were calculated 10^{5} times each. Medians of calculated Jacobians were normalized to the square of the interquartile distance in order to increase the median-to-noise ratio of the inverse calculations (Eq. 1). To compare two different metabolic states, we determined the absolute values of the differential Jacobian, dJ_{ij, abs}, defining the relative change of the two normalized Jacobians J_{a,norm} and J_{b,norm} which are associated with different treatments or genotypes:

The reduction process of the metabolic reconstruction network of leaf metabolism (Mintz-Oron et al., _{2}. These intermediates are experimentally accessible by, for example, GC-MS analysis of starch hydrolysate, photometric assays (starch) and infrared gas analysis (CO_{2}) as previously described (Wienkoop et al.,

While the metabolic network reconstruction of subcellular leaf metabolism resulted in a stoichiometric matrix derived from genome sequence information (Mintz-Oron et al.,

To test the applicability of the reduced model structure to analyse subcellular metabolic interaction, we used the underlying metabolic interaction matrix for inverse calculation of Jacobian matrices to a recently published data set on subcellular carbohydrate compartmentation (Nägele and Heyer,

The development of genome-scale metabolic network models has become a central approach to approximate the topology of metabolic networks

Our reduced metabolic model of subcellular primary leaf metabolism in _{ij}_{ij}

Previous studies have shown that NAF coupled to high-throughput analysis enables the comprehensive characterization of a metabolic homeostasis (Klie et al.,

Thomas Nägele performed model programming, calculation, modeling and wrote the manuscript. Wolfram Weckwerth wrote the manuscript. Thomas Nägele and Wolfram Weckwerth performed the design of the study.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

We would like to thank the members of the Department Ecogenomics and Systems Biology at the University of Vienna for critical and helpful discussions. We thank the EU-Marie-Curie ITN MERIT (GA 2010-264474) for financial support of Thomas Nägele. Finally, we would like to thank the reviewers for their comments and suggestions to improve the manuscript.

The Supplementary Material for this article can be found online at: