Keywords: Metabolomics, Automation, Solid Phase Extraction, LC-QTOF
In metabolomics studies, large sample sets have to be analyzed to allow statistical differentiation of sample types. Obviously, repeatability of the whole analytical workfl ow, including sample preparation, sample introduction, separation and detection, is hereby of the utmost importance. In this respect, automation of the sample preparation is very useful in order to reduce the analytical variability.
In a series of articles, we describe the use of the Gerstel MPS WorkStation for automated sample preparation applied to metabolomics studies. In a first part, an automated ultrasonic assisted extraction and fi ltration method was discussed. In this second part, an automated fractionation of lipid classes using solid phase extraction (SPE) is presented. The SPE fractions are concentrated using an mVAP evaporation station and re-dissolved in small amounts of solvent, followed by LC-QTOF analysis.
Keywords: GC/MS,Standard Operating Procedure, SOP, Abiotic Stress, Wounding, BinBase, SetupX
The Metabolomics Standards Initiative (MSI) has recently released documents describing minimum parameters for reporting metabolomics experiments, in order to validate metabolomic studies and to facilitate data exchange. The reporting parameters encompassed by MSI include the biological study design, sample preparation, data acquisition, data processing, data analysis and interpretation relative to the biological hypotheses being evaluated. Herein we exemplify how such metadata can be reported by using a small case study – the metabolite profiling by GC-TOF mass spectrometry of Arabidopsis thaliana leaves from a knockout allele of the gene At1g08510 in the Wassilewskija ecotype. Pitfalls in quality control are highlighted that can invalidate results even if MSI reporting standards are fulfilled, including reliable compound identification and integration of unknown metabolites. Standardized data processing methods are proposed for consistent data storage and dissemination via databases.
From - The Plant Journal (2008) 53, 691-704
Oliver Fiehn1,* , Gert Wohlgemuth1 , Martin Scholz1 , Tobias Kind1 , Do Yup Lee1 , Yun Lu1 , Stephanie Moon2 and Basil Nikolau2
1Davis Genome Center, University of California, Davis, CA 95616, USA, and
2Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA
Keywords: Metabolomics, Automation, Ultrasonic Assisted Liquid Extraction, LC-MS
In metabolomics studies, large sample sets have to be analyzed to allow statistical differentiation of sample types. Obviously, repeatability of the whole analytical workfl ow, including sample preparation, sample introduction, separation and detection, is extremely important in order to achieve such a differentiation. Automating the sample preparation workflow is a very useful first step towards reducing analytical variability.
In a series of articles, we will describe the use of the GERSTEL MPS WorkStation for automated sample preparation applied to metabolomics studies. In this fi rst part, we highlight an automated sample preparation method, which was developed for the extraction of glycosides from plant material using the GERSTEL MPS Dual Head WorkStation. Ultrasonic assisted solvent extraction was performed on the plant material, and the extract was prepared for subsequent LC-MS analysis by two fully automated consecutive fi ltration steps, combining a fi rst fi ltration on a 17 μm stainless steel screen fi lter placed in the sample vial and an additional fi ltration step using a 0.45 μm syringe filter. The obtained extracts were analyzed by LC-MS with excellent reproducibility.