Gloaguen Pauline, Bournais Sylvain, Alban Claude, Ravanel Stéphane, Seigneurin-Berny Daphné, Matringe Michel, Tardif Marianne, Kuntz Marcel, Ferro Myriam, Bruley Christophe, Rolland Norbert, Vandenbrouck Yves, Curien Gilles
Laboratoire de Biologie à Grande Echelle (BGE), CEA, INSERM, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (P.G., S.B., M.T., M.F., C.B, Y.V.); Laboratoire de Physiologie Cellulaire et Végétale (LPCV), CNRS, CEA, INRA, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (C.A., S.R., D.S.-B., M.M., M.K., N.R., G.C.).
Laboratoire de Biologie à Grande Echelle (BGE), CEA, INSERM, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (P.G., S.B., M.T., M.F., C.B, Y.V.); Laboratoire de Physiologie Cellulaire et Végétale (LPCV), CNRS, CEA, INRA, BIG, Université Grenoble-Alpes, 38000, Grenoble, France (C.A., S.R., D.S.-B., M.M., M.K., N.R., G.C.)
Plant Physiol. 2017 Jun;174(2):922-934. doi: 10.1104/pp.17.00242. Epub 2017 Apr 25.
Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis () metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers.
高等植物作为自养生物，是分子的有效来源。它们在代谢工程方面具有巨大潜力，但植物代谢在网络层面的行为仍未得到完整描述。尽管结构模型（化学计量矩阵）和途径数据库非常有用，但它们无法描述代谢背景的复杂性，因此需要新的工具来直观呈现整合的生物编目知识，以供人类和计算机使用。在此，我们描述了ChloroKB，这是一个用于可视化探索和分析拟南芥叶绿体代谢网络及相关细胞途径的网络应用程序（http://chlorokb.fr/）。该网络通过广泛的生物编目进行人工重建，以提供实验数据的透明可追溯性。使用CellDesigner软件将蛋白质和代谢物置于其生物学背景中（细胞内的空间分布、网络中的连接性、参与超分子复合物以及调节相互作用）。该网络包含1147个经过审查的蛋白质（559个仅定位于质体，68个至少定位于一个其他区室，520个位于质体之外）、122个等待进行生化/遗传表征的蛋白质以及228个尚未鉴定出基因的蛋白质。其可视化展示直观，浏览流畅，可即时访问整合过程的图形表示以及大量精细的定性和定量数据。ChloroKB将为结构和定量动力学建模、生物学推理（在将新数据与现有知识进行比较时）、计算机分析以及教育目的提供重要支持。随着植物研究人员的贡献不断更新，ChloroKB将得到进一步完善。
