Analytical Chemistry · 2010 · 208 citations · 26 references
Life SciencesBiochemistryMass Spectrometric AnalysisMetabolismMetabolomicsMass Spectrometry-based MetabolomicsMetabolite IdentificationMetabolite ProfilingMetabolite QuantificationTargeted MetabolomicsUntargeted MetabolomicsChromatography-based MetabolomicsMass Spectrometry-based Metabolite ProfilingMetabolite Separation TechniquesQuantitative Metabolite ProfilingQuantitative MetabolomicsTargeted Metabolite ProfilingTargeted Metabolomics AnalysisUntargeted Metabolomics Analysis
Target-based metabolomics, focused on a subset of metabolites representative of key pathways, is a valuable tool for assessing metabolic changes resulting from genetic mutation, altered gene expression, and protein dysfunction in a given disease state or as a consequence of an environmental perturbation, such as a pharmaceutical. However, simultaneously analyzing hundreds of endogenous metabolites presents a challenge because of their diverse chemical structures and properties. In this study, we report a high-throughput, sensitive, and reproducible method for target-based metabolomics studies. It combines different separation conditions, optimal ionization polarities, and the most sensitive triple-quadrupole MS-based data acquisition mode (MRM). In 10 min, 205 endogenous metabolites, divided into three subgroups (amino acids, sugar and nucleic acids, and organic acids), are sequentially analyzed on a LC/MS/MRM system. Low picogram sensitivity is achieved for more than half of the metabolites. A 3-4 order of linearity and assay coefficient of variation less than 15% are observed for approximately 80% of the metabolites. In summary, we have established a multiplex LC/MS/MRM method for quantitatively profiling hundreds of known metabolites from complex biological samples. The methodology is generally applicable and easily expandable to include more endogenous or drug metabolites.
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Metabolomics – the link between genotypes and phenotypes
Oliver Fiehn · Plant Molecular Biology · 2002 · 3.4K citations
Metabolite profiling for plant functional genomics
Oliver Fiehn, Joachim Kopka, Peter Dörmann et al. · Nature Biotechnology · 2000 · 2.1K citations