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Quality control for plant metabolomics: reporting MSI‐compliant studies
Author(s) -
Fiehn Oliver,
Wohlgemuth Gert,
Scholz Martin,
Kind Tobias,
Lee Do Yup,
Lu Yun,
Moon Stephanie,
Nikolau Basil
Publication year - 2008
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/j.1365-313x.2007.03387.x
Subject(s) - metabolomics , metadata , computer science , ecotype , identification (biology) , computational biology , data quality , data mining , bioinformatics , biology , engineering , genetics , world wide web , metric (unit) , operations management , botany
Summary 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.