title: Metabolic profiling of laser microdissected vascular bundles of Arabidopsis thaliana.
abstract: BACKGROUND
  Laser microdissection is a useful tool for collecting tissue-specific samples or even single cells from animal and plant tissue sections. This technique has been successfully employed to study cell type-specific expression at the RNA, and more recently also at the protein level. However, metabolites were not amenable to analysis after laser microdissection, due to the procedures routinely applied for sample preparation. Using standard tissue fixation and embedding protocols to prepare histological sections, metabolites are either efficiently extracted by dehydrating solvents, or washed out by embedding agents.
  
  
  RESULTS
  In this study, we used cryosectioning as an alternative method that preserves sufficient cellular structure while minimizing metabolite loss by excluding any solute exchange steps. Using this pre-treatment procedure, Arabidopsis thaliana stem sections were prepared for laser microdissection of vascular bundles. Collected samples were subsequently analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS) to obtain metabolite profiles. From 100 collected vascular bundles (approximately 5,000 cells), 68 metabolites could be identified. More than half of the identified metabolites could be shown to be enriched or depleted in vascular bundles as compared to the surrounding tissues.
  
  
  CONCLUSIONS
  This study uses the example of vascular bundles to demonstrate for the first time that it is possible to analyze a comprehensive set of metabolites from laser microdissected samples at a tissue-specific level, given that a suitable sample preparation procedure is used.
authors.affiliation: Max-Planck-Institute of Molecular Plant Physiology, Department Lothar Willmitzer, 14424 Potsdam, Germany. kehr@mpimp-golm.mpg.de
authors.forename: Martina
authors.initials: M
authors.lastname: Schad
authors.forename: Rajsree
authors.initials: R
authors.lastname: Mungur
authors.forename: Oliver
authors.initials: O
authors.lastname: Fiehn
authors.forename: Julia
authors.initials: J
authors.lastname: Kehr