Genome Mining To Identify New Plant Triterpenoids

Abstract

Arabidopsis thaliana is a well-established model organism for plant genetics, and its recently sequenced genome reveals a wealth of enzymes similar to known examples that biosynthesize secondary metabolites. We describe experiments that exploit this genomic information to identify novel terpenoids. A predicted open reading frame with high similarity to known oxidosqualene cyclases was shown to convert 3(S)-oxidosqualene to the previously unknown triterpene alcohol (3S,13S,14R)-malabarica-8,17,21-trien-3-ol, which we named thalianol. Genome mining offers a systematic approach to exhaustively characterize the biosynthetic potential of an organism, and is considerably more sensitive than classical approaches. Because even rare transcripts can be heterologously expressed at high levels, genome mining coupled to heterologous expression may be more sensitive than classical extraction approaches for isolating and characterizing trace metabolites.