title: Can phylogeny predict chemical diversity and potential medicinal activity of plants? A case study of Amaryllidaceae.
abstract: BACKGROUND
  During evolution, plants and other organisms have developed a diversity of chemical defences, leading to the evolution of various groups of specialized metabolites selected for their endogenous biological function. A correlation between phylogeny and biosynthetic pathways could offer a predictive approach enabling more efficient selection of plants for the development of traditional medicine and lead discovery. However, this relationship has rarely been rigorously tested and the potential predictive power is consequently unknown.
  
  
  RESULTS
  We produced a phylogenetic hypothesis for the medicinally important plant subfamily Amaryllidoideae (Amaryllidaceae) based on parsimony and Bayesian analysis of nuclear, plastid, and mitochondrial DNA sequences of over 100 species. We tested if alkaloid diversity and activity in bioassays related to the central nervous system are significantly correlated with phylogeny and found evidence for a significant phylogenetic signal in these traits, although the effect is not strong.
  
  
  CONCLUSIONS
  Several genera are non-monophyletic emphasizing the importance of using phylogeny for interpretation of character distribution. Alkaloid diversity and in vitro inhibition of acetylcholinesterase (AChE) and binding to the serotonin reuptake transporter (SERT) are significantly correlated with phylogeny. This has implications for the use of phylogenies to interpret chemical evolution and biosynthetic pathways, to select candidate taxa for lead discovery, and to make recommendations for policies regarding traditional use and conservation priorities.
authors.affiliation: Botanic Garden, Natural History Museum of Denmark, Sølvgade 83, Opg. S, Copenhagen DK-1307, Denmark. nronsted@snm.ku.dk
authors.forename: Nina
authors.initials: N
authors.lastname: Rønsted
authors.forename: Matthew R E
authors.initials: MR
authors.lastname: Symonds
authors.forename: Trine
authors.initials: T
authors.lastname: Birkholm
authors.forename: Søren Brøgger
authors.initials: SB
authors.lastname: Christensen
authors.forename: Alan W
authors.initials: AW
authors.lastname: Meerow
authors.forename: Marianne
authors.initials: M
authors.lastname: Molander
authors.forename: Per
authors.initials: P
authors.lastname: Mølgaard
authors.forename: Gitte
authors.initials: G
authors.lastname: Petersen
authors.forename: Nina
authors.initials: N
authors.lastname: Rasmussen
authors.forename: Johannes
authors.initials: J
authors.lastname: van Staden
authors.forename: Gary I
authors.initials: GI
authors.lastname: Stafford
authors.forename: Anna K
authors.initials: AK
authors.lastname: Jäger
mesh_terms: D000470:Alkaloids / Q000737:chemistry / Q000235:genetics / Q000494:pharmacology; D000818:Animals; D001499:Bayes Theorem; D002467:Cell Nucleus / Q000235:genetics; D002800:Cholinesterase Inhibitors / Q000737:chemistry / Q000494:pharmacology; D004272:DNA, Mitochondrial / Q000235:genetics; D018744:DNA, Plant / Q000235:genetics; D021903:DNA, Ribosomal Spacer / Q000235:genetics; D004593:Electrophorus; D019668:Liliaceae / Q000737:chemistry* / Q000235:genetics*; D010802:Phylogeny; D010946:Plants, Medicinal / Q000737:chemistry* / Q000235:genetics*; D051381:Rats; D017422:Sequence Analysis, DNA; D017367:Selective Serotonin Reuptake Inhibitors / Q000737:chemistry / Q000494:pharmacology
chemical_list: D000470:Alkaloids; D002800:Cholinesterase Inhibitors; D004272:DNA, Mitochondrial; D018744:DNA, Plant; D021903:DNA, Ribosomal Spacer; D017367:Selective Serotonin Reuptake Inhibitors