High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry

Abstract

Flow injection electrospray–mass spectrometry (FIE–MS) is finding utility as a first-pass metabolite fingerprinting tool in many research fields. We provide a protocol that has proved reliable in large-scale research projects involving diverse sample matrices originating from plants, microbes and mammalian biofluids. Using Brachypodium leaf material as an example matrix all steps are summarized from sample extraction to data quality assessment. Alternative procedures for dealing with other common matrices such as bloods and urine are included. With little sample pretreatment, no chromatography and instrument cycle times of <5 min it is feasible to analyze >1,000 samples per week. Analysis of a typical batch of 240 samples (including first-pass data analysis) can be accomplished within 48 h.

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Figure 1: Ideal flow-infusion chromatogram of Brachypodium-infected leaf extract acquired on the LTQ mass spectrometer.
Figure 2: Applying background subtraction for signal processing.
Figure 3: Averaged mass spectra of a typical infusion peak.
Figure 4: Example plot of a nominal-mass raw-intensity matrix after signal processing.
Figure 5
Figure 6: Work flow in flow injection electrospray–mass spectrometry (FIE–MS) high-throughput analysis.
Figure 7: Use of principal components analysis (PCA) and principal component linear discriminant analysis (PC-LDA) for initial investigation of data quality.
Figure 8: Reanalysis of data after removal of sample outliers.
Figure 9: Score plots obtained after instrument troubleshooting and sample reanalysis.
Figure 10: PC2 loading plot revealing a mass binning error.
Figure 11: Final score plots obtained after repeating data signal processing using adjusted binning limit.

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Acknowledgements

We thank all collaborators who provided valuable samples to develop this protocol and, in particular, Rob Darby for overarching support with laboratory infrastructure, equipment and materials. Metabolite analysis and statistical work (M.B. and D.E.) was partly funded by the Food Standards Agency (London) as part of its G02006 and G03012 projects and biological materials used in example data were generated as part of the UK Biotechnology and Biological Sciences Research council grant BBD0069531 (D.P. and E.D.).

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Correspondence to Manfred Beckmann.

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Beckmann, M., Parker, D., Enot, D. et al. High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry. Nat Protoc 3, 486–504 (2008). https://doi.org/10.1038/nprot.2007.500

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