title: Medicinal plants: a public resource for metabolomics and hypothesis development.
abstract: Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq) for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range of antioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM) [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less studied species. The database is publicly available and can be used by researchers in medicine and plant biology.
authors: Department of Genetics, Cell and Developmental Biology, Iowa State University, Ames, IA 50011, USA. mash@iastate.edu.
authors: Eve Syrkin
authors: ES
authors: Wurtele
authors: Department of Cellular and Molecular Biochemistry, University of Kentucky, Lexington, KY, 40536, USA.
authors: Joe
authors: J
authors: Chappell
authors: Department of Biochemistry & Molecular Biology and Deptment of Chemistry, Michigan State University, East Lansing, MI 48824, USA.
authors: A Daniel
authors: AD
authors: Jones
authors: Department of Biochemistry & Molecular Biology and Deptment of Chemistry, Michigan State University, East Lansing, MI 48824, USA.
authors: Mary Dawn
authors: MD
authors: Celiz
authors: Department of Genetics, Cell and Developmental Biology, Iowa State University, Ames, IA 50011, USA.
authors: Nick
authors: N
authors: Ransom
authors: Department of Genetics, Cell and Developmental Biology, Iowa State University, Ames, IA 50011, USA.
authors: Manhoi
authors: M
authors: Hur
authors: Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA50011, USA.
authors: Ludmila
authors: L
authors: Rizshsky
authors: Department of Genetics, Cell and Developmental Biology, Iowa State University, Ames, IA 50011, USA.
authors: Matthew
authors: M
authors: Crispin
authors: Department of Statistics, Iowa State University, Ames, IA 50011, USA.
authors: Philip
authors: P
authors: Dixon
authors: Department of Statistics, Iowa State University, Ames, IA 50011, USA.
authors: Jia
authors: J
authors: Liu
authors: Department of Ecology, Evolution, and Organismal Biology and Department of Horticulture, Iowa State University, Ames, IA 50011, USA.
authors: Mark
authors: M
authors: P Widrlechner
authors: Center for Metabolic Biology, The Plant Science Institute, Iowa State University, Ames, IA 50011, USA.
authors: Basil J
authors: BJ
authors: Nikolau