Plants synthesize a vast array of natural products that serve crucial functions in protection against pests, as attractants for pollinators, as structural components and as signalling molecules. Such natural products offer a great potential for the development of new phyto-pharmaceuticals, biomaterials, and to enhance crop properties. But a fundamental pre-requisite for such biotechnological developments is a thorough understanding of the underlying biosynthetic pathways. Recent genome sequencing projects have revealed the existence of large gene families likely to encode the enzymes forming these pathways. The largest among them is the super-family of cytochrome P450 (CYP450) monooxygenases.
The size of this family reflects the complexity of plant secondary metabolism, and demonstrates that most of it is still unexplored. CYP450s often constitute rate-limiting steps and points-of-no-return in metabolic networks. They are thus under tight developmental control, and frequently respond transcriptionally to environmental cues. Here we propose a new integrative approach for the functional characterization of the orphan CYP450s in Arabidopsis. It combines bioinformatics with reverse genetics, metabolic profiling and reverse biochemistry. Based on large-scale expression data, co-expression analysis with known and putative metabolic genes will be exploited to place CYP450s onto existing metabolic pathways, and to identify novel metabolic networks.
Based on these results, selected CYP450 genes will be characterized u sing reverse genetics (over-expressers, knock out mutants) combined with targeted metabolic profiling. Employing an available collection of recombinant enzymes, biochemical functions will be identified, either directly or by using medium throughput enzymatic screening methods. We thereby hope to promote the field of natural product biosynthesis, and to develop a widely applicable strategy for characterizing large gene families and secondary pathways in plants.
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