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Decoding the Chloroplast

Researchers at CEA-BIG have developed a web application called ChloroKB, a software that will facilitate the quantitative and predictive modeling of plant metabolism.
Published on 20 December 2017

Cell metabolism is extremely complex, especially in plants, as they have a specific compartment called the chloroplast. An organelle in the cytoplasm of plant cells, the chloroplast conducts photosynthesis through chlorophyll, and performs many biosynthesis processes which make it essential to the functioning of plant cells.

Over the last 50 years, extensive research has led scientists to seek prediction of plant cell metabolism. Yet this task requires the pooling of knowledge, which is currently scattered between various specialized resources (databases, scientific literature, etc.). What's more, this knowledge must be represented in a form that is both human- and computer-readable for mathematical processing. Software ChloroKB, developed over five years by biologists and bioinformaticians from BIG, now makes this integrated data available to the scientific community.

ChloroKB focuses on plant Arabidopsis Thaliana—the reference organism in plant research. With ChloroKB, the scientists can navigate a network reconstructed manually that includes more than 1,100 proteins, 1,500 metabolites and 700 complexes located in 5 subcellular compartments. ChloroKB is a large database that provides expert-reviewed data on genes, and is also a software that provides relational data to visualize the links between metabolic pathways.

Visual analysis is at the core of the software in which biological processes are hierarchized, the different actors in the chloroplast and other cellular compartments sorted by shape and color, and the various transports of molecules connected by arrows on "Celldesigner", the software's modeling interface. The user can interactively explore the interrelationships in the metabolic network, locate the metabolites at the subcellular level and visualize transport and protein assemblies.

Finally, because of the contextual representation of the metabolic network of Arabidopsis, many elements that are usually absent from databases are represented, such as certain reactions that are still unclear to scientists, or missing steps within a network. ChloroKB leads to the formulation of new biological hypotheses. ­For example, data assembly reveals new elements such as the co-occurrence of synthesis and degradative processes unfolding in the same tissue—a co-occurrence that implies the existence of regulatory processes that have not yet been unraveled.

According to researcher Gilles Curien: "Without ChloroKB, accessing this amount of expert-reviewed data would require weeks of data acquisition." This web application "facilitates the acquisition of knowledge by neophytes and simplifies communication between experts in the field": ChloroKB thus comes as a very original analytical visual tool and an essential resource for the quantitative and predictive modeling of plant metabolism.

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