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Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen

Metabolomics volume 14, Article number: 48 (2018) Cite this article

Abstract

Introduction

Van Krevelen (VK) diagrams provide a promising but uncommon solution to a number of challenges associated with the visualization of metabolomics data. VK diagrams are created by plotting H:C ratios against O:C ratios of the compounds in a chemical mixture.

Objectives

The aim of this manuscript is to present an open-source software tool and reference map that we have developed to make VK diagrams for visualization of metabolomics data.

Methods

Software was created with a prompt-driven command line user interface and was written using Python 2.7. We empirically derived an accompanying map by plotting where compounds from seven biomolecule types fall within the VK plot space.

Results

We’ve created an easy to use, open source software tool named OpenVanKrevelen for making a range of VK diagrams that is available on GitHub: https://github.com/HegemanLab/VanKrevelenLocal. The empirical mapping approach has produced several improvements from previously published maps.

Conclusions

OpenVanKrevelen provides the metabolomics community with access to a new tool for visualization of complex metabolomics datasets.

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Fig. 1
Fig. 2

Abbreviations

HRMS:

High-resolution mass spectrometry

VK:

Van Krevelen

H:

Hydrogen

O:

Oxygen

N:

Nitrogen

LC-MS:

Liquid-chromatography mass-spectrometry

Q-TOF:

Quadrupole time-of-flight mass spectrometer

References

  • Arita, M., & Suwa, K. (2017). Flavonoid database. Database. Arita Laboratory, National Institute of Genetics. Retrieved November 6, 2015 from http://metabolomics.jp/wiki/Index:FL#Index_by_Formula.

  • Bald, T., Barth, J., Niehues, A., Specht, M., Hippler, M., & Fufezan, C. (2012). pymzML—Python module for high throughput bioinformatics on mass spectrometry data. Bioinformatics, 1;28(7), 1052–1053.

    CAS  Article  PubMed  Google Scholar 

  • Chambers, M. C., MacLean, B., & Mallick, P. A. (2012). Cross-platform toolkit for mass spectrometry and proteomics. Nature Biotechnology, 30, 918–920.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Deutsch, E. W. (2010). Mass spectrometer output file format mzML. Methods Molecular Biology, 604, 319–331.

    CAS  Article  Google Scholar 

  • Doerfler, H., Sun, X., Wang, L., Engelmeier, D., Lyon, D., & Weckwerth, W. (2014). mzGroupAnalyzer-predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. PLoS ONE, 9, e96188.

    Article  PubMed  PubMed Central  Google Scholar 

  • Guy, J. J., Llonch, J., Reed, M. M., & Timmer, J. J. W. (2009). heatmap.py: Create heatmaps in python. Resource document. Retrieved February 16, 2017 from http://jjguy.com/heatmap/.

  • Hegeman, A. D., Schulte, C. F., Cui, Q., Lewis, I. A., Huttlin, E. L., Eghbalnia, H., Harms, A. C., Ulrich, E. L., Markley, J. L., & Sussman, M. R. (2007). Stable isotope assisted assignment of elemental compositions for metabolomics. Analytical Chemistry, 79, 6912–6921.

    CAS  Article  PubMed  Google Scholar 

  • Holman, J. D., Tabb, D. L., & Mallick, P. (2014). Employing ProteoWizard to convert raw mass spectrometry data. Current Protocols in Bioinformatics, 9, 13–24.

    Google Scholar 

  • Kew, W., Blackburn, J. W. T., Clarke, D. J., & Uhrín, D. (2017). Interactive van Krevelen diagrams—advanced visualisation of mass spectrometry data of complex mixtures. Rapid Communications in Mass Spectrometry, 31, 658–662.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Kim, S., Kramer, R. W., & Hatcher, P. G. (2003). Graphical method for analysis of ultrahigh-resolution broadband mass spectra of natural organic matter, the Van Krevelen diagram. Analytical Chemistry, 75(20), 5336–5344.

    CAS  Article  PubMed  Google Scholar 

  • König, W. A., Joulain, D., Grasse, R. S. A., & Hochmuth, D. H. (2012). Terpenoids Library. Database. University of Hamburg, Germany and Hochmuth Scientific Consulting. Retrieved November 8, 2015 from http://massfinder.com/wiki/Terpenoids_Library.

  • Lütteke, T. (2016). MonosaccharideDB. Database. EUROCarbDB. Retrieved November 15, 2015 from http://www.monosaccharidedb.org/browse_monosaccharides.action.

  • Mann, B. F., Chen, H., Herndon, E. M., Chu, R. K., Tolic, N., Portier, E. F., et al. (2015). Indexing permafrost soil organic matter degradation using high-resolution mass spectrometry. PLoS ONE, 10, e0130557

    Article  PubMed  PubMed Central  Google Scholar 

  • Mazzer, P. A. (2017). MatLab scripts for FTICR-MS data analysis. Resource document. Old Dominion University. Retrieved January 26, 2017 from http://ww2.odu.edu/~pmazzer/fticrml.shtml.?.

  • Ohta, D., Kanaya, S., & Suzuki, H. (2010). Application of Fourier-transform ion cyclotron resonance mass spectrometry to metabolic profiling and metabolite identification. Current Opinion in Biotechnology, 21, 35–44.

    CAS  Article  PubMed  Google Scholar 

  • Sud, M., Fahy, E., Cotter, D., Brown, A., Dennis, E. A., Glass, C. K., Merrill, A. H., Jr, et al. (2017). Flavonoid Database. Database. LIPID MAPS Consortium. Retrieved November 7, 2015 from http://www.lipidmaps.org/data/structure/.

  • Ulrich, E. L., Akutsu, H., Doreleijers, J. F., Harano, Y., Ioannidis, Y. E., Lin, J., et al. (2008). BioMagResBank. Nucleic Acids Research, 36, D402−D408.

    Google Scholar 

  • Van Krevelen, D. W. (1950). Graphical-statistical method for the study of structure and reaction processes of coal. Fuel, 24, 269–284.

    Google Scholar 

  • Vogel, C. (2008). Resource document. Retrieved February 16, 2017 from https://code.google.com/p/massspec-toolbox/source/browse/#svn/trunk/mzxml.

  • Wu, Z., Rodgers, R. P., & Marshall, A. G. (2004). Two- and three-dimensional van Krevelen Diagrams: A graphical analysis complementary to the Kendrick mass plot for sorting elemental compositions of complex organic mixtures based on ultrahigh-resolution broadband Fourier Transform ion cyclotron resonance mass measurements. Analytical Chemistry, 76, 2511–2516.

    CAS  Article  PubMed  Google Scholar 

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Acknowledgements

The authors thank Dana M. Freund, Kate A. Sammons, Katrina Freund Saxhaug, Nadia R. Handler and Jayanti Suresh for helpful feedback and/or advice on ease of use. We also thank Geoffrey A. Dubrow for providing test data, and the Biological Magnetic Resonance Bank for providing the database and useful feedback. We are grateful for funding provided by the National Science Foundation Plant Genome Research Program Grants IOS-0923960 and IOS-1238812 and National Science Foundation grant DBI-1458524. We thank the Minnesota Agriculture Experiment Station and the University of Minnesota, College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota–Twin Cites for support.

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Affiliations

  1. Microbial and Plant Genomics Institute and the Departments of Horticultural Science and Plant and Microbial Biology, University of Minnesota, Twin Cities, 1970 Folwell Avenue, St. Paul, MN, USA

    Stephen A. Brockman, Eric V. Roden & Adrian D. Hegeman

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  1. Stephen A. Brockman
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  2. Eric V. Roden
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  3. Adrian D. Hegeman
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Corresponding author

Correspondence to Adrian D. Hegeman.

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The authors declare that they have no conflict of interest.

Ethical approval

No human participants or animals were involved in this study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

11306_2018_1343_MOESM1_ESM.pdf

Supplementary material 1. Online Resource 1 A van Krevelen heat map visualization of the same high-resolution liquid-chromatography mass-spectrometry data used in Fig. 2. The heatmap only displays the areas of highest feature density and does not convey the same depth of information as a van Krevelen scatter plot. However sometimes a simpler plot is desirable and for this and other reasons van Krevelen heatmaps are still quite useful. In this case the heatmap accurately portrays flavonoid compounds as the most abundant metabolites in the sample. This function of EasyVanKrevelen allows users to create reference maps of their own, for classes of compounds we did not include in the provided map or other applications. The data used were collected using a 25 min reversed phase gradient and a Q Exactive high resolution mass spectrometer (Thermo-Fisher Scientific, Germany) (PDF 347 KB)

11306_2018_1343_MOESM2_ESM.csv

Supplementary material 2. Online Resource 2 Because a suitable database could not be found the nucleic acids section of the empirical map was plotted using a manually compiled lists of compounds. This list has been provided as a .CSV file. The .CSV file contains a manually curated list of nucleic acids and derivatives known to be important in many major biological processes (CSV 0 KB)

11306_2018_1343_MOESM3_ESM.csv

Supplementary material 3. Online Resource 3 Because a suitable database could not be found the amino acids and peptides section of the empirical map was plotted using a manually compiled lists of compounds. This list has been provided as a .CSV file. The .CSV file contains a list of proteinogenic, non-proteinogenic amino acids, and their derivatives (CSV 2 KB)

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Brockman, S.A., Roden, E.V. & Hegeman, A.D. Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen. Metabolomics 14, 48 (2018). https://doi.org/10.1007/s11306-018-1343-y

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Keywords

  • Metabolomics
  • Mass-spectrometry
  • Van Krevelen