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Automated work-flow for processing high-resolution direct infusion electrospray ionization mass spectral fingerprints

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Abstract

The use of mass spectrometry (MS) is pivotal in analyses of the metabolome and presents a major challenge for subsequent data processing. While the last few years have given new high performance instruments, there has not been a comparable development in data processing. In this paper we discuss an automated data processing pipeline to compare large numbers of fingerprint spectra from direct infusion experiments analyzed by high resolution MS. We describe some of the intriguing problems that have to be addressed, starting with the conversion and pre-processing of the raw data to the final data analysis. Illustrated on the direct infusion analysis (ESI-TOF-MS) of complex mixtures the method exploits the full quality of the high-resolution present in the mass spectra. Although the method is illustrated as a new library search method for high resolution MS, we demonstrate that the output of the preprocessing is applicable to cluster-, discriminant analysis, and related multivariate methods applied directly to mass spectra from direct infusion analysis of crude extracts. This is done to find the relationship between several terverticillate Penicillium species and identify the ions responsible for the segregation.

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Acknowledgments

The authors thank Professor Jens Christian Frisvad (BioCentrum-DTU) for identification of the species. Ellen Kirstine Lyhne and Hanne Jacobsen are greatly acknowledged for cutting the plugs, doing the extraction and analysis of the samples. The project was supported by the Danish Technical Research Council under the project “Programme for predictive biotechnology: Functional biodiversity in Penicillium and Aspergillus” (grant no. 9901295) and The Danish Research Council (grant no. 274–05-0606).

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Author notes

  1. Michael Adsetts Edberg Hansen

    Present address: Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA, 02139, USA

Authors and Affiliations

  1. Center for Microbial Biotechnology, Technical University of Denmark, BioCentrum–DTU, Søltofts Plads, building 221, DK-2800, Kgs. Lyngby, Denmark

    Michael Adsetts Edberg Hansen & Jørn Smedsgaard

Authors
  1. Michael Adsetts Edberg Hansen
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  2. Jørn Smedsgaard
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Corresponding author

Correspondence to Michael Adsetts Edberg Hansen.

Appendix

Appendix

Scripts

The software used for extracting data from the MassLynx data files, can be obtained together with a full documentation of the scripts doing the processing by contacting the corresponding author by email: meh@biocentrum.dtu.dk.

Adaptive binning

The adaptive binning algorithm used

  • Require: \({\varvec{\Phi} =\left\{{\varphi _p^{{\rm S}_k} }\right\}}\)

  •  for all k∈{ 1,...,K }and p∈{ 1,...,| S k | } do

  •   find the nearest cluster c to φ S p k

  •   if no cluster is found or distance \({d_{cp} \geq d_{max}}\) then

  •    create a new cluster with element p;

  •   else if \({d_{cp} \leq d_{min}}\) then

  •    add element p to cluster k

  •   end if

  •  end for

  •  for all cluster i do

  •   if cluster i has at least N m elements then

  •    update centroid c i of cluster i

  •    remove cluster i

  •   end if

  •  end for

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Hansen, M.A.E., Smedsgaard, J. Automated work-flow for processing high-resolution direct infusion electrospray ionization mass spectral fingerprints. Metabolomics 3, 41–54 (2007). https://doi.org/10.1007/s11306-006-0044-0

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