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Metabolomics

, Volume 9, Supplement 1, pp 84–91 | Cite as

Nearline acquisition and processing of liquid chromatography-tandem mass spectrometry data

  • Steffen Neumann
  • Andrea Thum
  • Christoph Böttcher
Original Article

Abstract

Liquid chromatography–mass spectrometry (LC–MS) is a commonly used analytical platform for non-targeted metabolite profiling experiments. Although data acquisition, processing and statistical analyses are almost routine in such experiments, further annotation and subsequent identification of chemical compounds are not. For identification, tandem mass spectra provide valuable information towards the structure of chemical compounds. These are typically acquired online, in data-dependent mode, or offline, using handcrafted acquisition methods and manually extracted from raw data. Here, we present several methods to fast-track and improve both the acquisition and processing of LC–MS/MS data. Our nearly online (nearline) data-dependent tandem MS strategy creates a minimal set of LC–MS/MS acquisition methods for relevant features revealed by a preceding non-targeted profiling experiment. Using different filtering criteria, such as intensity or ion type, the acquisition of irrelevant spectra is minimized. Afterwards, LC–MS/MS raw data are processed with feature detection and grouping algorithms. The extracted tandem mass spectra can be used for both library search and de-novo identification methods. The algorithms are implemented in the R package MetShot and support the export to Bruker, Agilent or Waters QTOF instruments and the vendor-independent TraML standard. We evaluate the performance of our workflow on a Bruker micrOTOF-Q by comparison of automatically acquired and extracted tandem mass spectra obtained from a mixture of natural product standards against manually extracted reference spectra. Using Arabidopsis thaliana wild-type and biosynthetic gene knockout plants, we characterize the metabolic products of a biosynthetic pathway and demonstrate the integration of our approach into a typical non-targeted metabolite profiling workflow.

Keywords

Metabolomics Tandem mass spectrometry Data-dependent acquisition Feature detection Feature grouping Collision-induced dissociation 

Notes

Acknowledgements

Ralf Tautenhahn (The Scripps Research Institute, La Jolla, CA) tested the nearline data-dependent tandem MS approach and contributed the export for the Agilent QTOF instruments.

Supplementary material

11306_2012_401_MOESM1_ESM.pdf (395 kb)
PDF (395 KB)
11306_2012_401_MOESM2_ESM.xls (42 kb)
XLS (42 KB)
11306_2012_401_MOESM3_ESM.xls (32 kb)
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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Steffen Neumann
    • 1
  • Andrea Thum
    • 2
  • Christoph Böttcher
    • 1
  1. 1.Department of Stress and Developmental BiologyLeibniz Institute of Plant BiochemistryHalleGermany
  2. 2.Institute of Computer ScienceMartin-Luther-Universität Halle-Wittenberg06099 HalleGermany

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