Metabolic network modeling - Toward an in-silico plant.
Michael Vacher PhD Student
One of the main challenges in Systems Biology is to reveal the extensive biochemical description of organisms. Understanding the interplay between the abundance of molecular entities within cells would help researchers to gain better insight into the macromolecular machinery responsible driving all cellular functions.
Plant biologists have generated a large amount of data over the years, significantly extending our knowledge of plant metabolism. One of our the goal is to take advantage of these resources in order to reverse-engineer plants at the molecular scale. To this end, we are developing computational models, focusing on Arabidopsis thaliana energy metabolism, that are capable of simulating the behaviour of living plant cells. These models are organized integrations of all our current knowledge of Arabidopsis and therefore, represent accurate descriptions of the molecular biology and metabolism of the plant species.
Applications of these computational models include the metabolic engineering of specific industrial strains, for improving plant performance, particularly in marginal environments and in response to climate change. They are also valuable tools guide experimentations by rapidly testing new hypothesis. Finally, metabolic network modeling provides a system perspective that will allow us to investigate fundamental biological questions and help researchers to gain a better understanding on how metabolism is orchestrated within cells, in order to achieve high-level cellular and physiological functions.
Simple Example: The Mitochondrion Metabolite Reaction Network
This interactive picture shows the basic reaction pathways (groups of reactions) for the Mitochodria of Arabidopsis thaliana. Click a pathway (blue circle) to expand into a full network of reactions. Watch how tangled it gets!