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Integrative analysis of multimodal mass spectrometry data in MZmine 3

Nature Biotechnology volume 41, pages 447–449 (2023)Cite this article

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Innovation in mass spectrometry (MS) and the rapidly increasing throughput and sensitivity of MS instrumentation require adaptations and innovations in data processing tools. Here, we introduce MZmine 3, a scalable MS data analysis platform that supports hybrid datasets from various instrumental setups, including liquid and gas chromatography (LC and GC)–MS, ion mobility spectrometry (IMS)–MS and MS imaging. In particular, the integration of IMS–MS imaging and LC–IMS–MS datasets provides opportunities for spatial metabolomics analyses with increased annotation confidence.

Recent advances in MS instrumentation push sensitivity, resolving power and data acquisition speed, resulting in increased data volume and complexity. Notably, IMS gains traction in the field by including an additional separation dimension to LC–MS or imaging-based techniques like matrix-assisted laser desorption/ionization (MALDI)–MS. These advances introduce new acquisition modes (for example, parallel accumulation–serial fragmentation (PASEF))11 or enable combination of IMS and imaging, which was shown to improve annotation quality in MS imaging12. Furthermore, the number of large-scale cohort and multifactorial studies in clinical, environmental and other fields is growing, as registered in the three main metabolomics data repositories: MassIVE/GNPS8, MetaboLights and Metabolomics Workbench13. The need for scalable, reproducible and flexible data analysis workflows that can combine MS data from various sources remains unaddressed by existing tools. For example, to combine LC–(IMS–)MS and MS imaging results from the same sample, users are forced to master multiple software tools12 that divide the workflow and are specialized for either chromatography–MS (for example, MS-DIAL, XCMS, OpenMS)14,15,16 or MS imaging (for example, METASPACE, rMSI, Cardinal MSI, SpectralAnalysis)17.

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Fig. 1: MZmine, an open-source community project for integrative LC–IMS–MS and IMS–MS data processing.

Data availability

Datasets are available on MassIVE8 with the following accession IDs: MSV000088054, human cohort study, LC–MS, neg; MSV000087728, diverse plant extracts, LC–MS2, top-3 DDA, pos; MSV000090079, dissolved organic matter, LC–MS2, top-5 DDA, pos; MSV000090328, sheep brain, LC–TIMS-MS, PASEF, pos; MSV000090327, piper plant extracts, LC–TIMS-MS, PASEF, pos. IMS resolved ion identity molecular networking results are available through GNPS: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=7a06fa3dfadd4158bcb4ee300b574747

Code availability

The latest release of MZmine can be downloaded from https://www.mzmine.org. The complete source code is available at https://github.com/mzmine/mzmine3/ under the MIT license. The MZmine documentation is hosted on GitHub and available at https://www.mzmine.org/documentation.

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Acknowledgements

We thank Christopher Jensen and Gauthier Boaglio for their contributions to the MZmine codebase. We thank Jianbo Zhang and Zachary Russ for their donations to MZmine development. The MZmine 3 logo was designed by the Bioinformatics & Research Computing group at the Whitehead Institute for Biomedical Research. T.P. is supported by Czech Science Foundation (GA CR) grant 21-11563M and by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement 891397. Support for P.C.D. was from US NIH U19 AG063744, P50HD106463, 1U24DK133658 and BBSRC-NSF award 2152526. T.S. acknowledges funding by Deutsche Forschungsgemeinschaft (441958208). M. Wang acknowledges the US Department of Energy Joint Genome Institute (https://ror.org/04xm1d337, a DOE Office of Science User Facility) and is supported by the Office of Science of the US Department of Energy operated under subcontract No. 7601660. E.R. and H.H. thank Wen Jiang (HILICON AB) for providing the iHILIC Fusion(+) column for HILIC measurements. M.F., K.D. and S.B. are supported by Deutsche Forschungsgemeinschaft (BO 1910/20). L.-F.N. is supported by the Swiss National Science Foundation (project 189921). D.P. was supported through the Deutsche Forschungsgemeinschaft (German Research Foundation) through the CMFI Cluster of Excellence (EXC-2124 — 390838134 project-ID 1-03.006_0) and the Collaborative Research Center CellMap (TRR 261 - 398967434). J.-K.W. acknowledges the US National Science Foundation (MCB-1818132), the US Department of Agriculture, and the Chan Zuckerberg Initiative. MZmine developers have received support from the European COST Action CA19105 — Pan-European Network in Lipidomics and EpiLipidomics (EpiLipidNET). We acknowledge the support of the Google Summer of Code (GSoC) program, which has funded the development of several MZmine modules through student projects. We thank Adam Tenderholt for introducing MZmine to the GSoC program.

Author information

Author notes

  1. These authors contributed equally: Robin Schmid, Steffen Heuckeroth, Ansgar Korf.

Authors and Affiliations

  1. Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA

    Robin Schmid, Zheng Zhang & Pieter C. Dorrestein

  2. Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany

    Robin Schmid, Steffen Heuckeroth, Ansgar Korf, Mark Wesner, Edward Rudt, Patrick O. Helmer, Heiko Hayen & Uwe Karst

  3. Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic

    Robin Schmid, Roman Bushuiev, Olena Mokshyna, Corinna Brungs, Kirill Ponomarov, Lana Mutabdžija, Tito Damiani & Tomáš Pluskal

  4. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, USA

    Aleksandr Smirnov, Owen Myers & Xiuxia Du

  5. Steno Diabetes Center Copenhagen, Gentofte, Denmark

    Thomas S. Dyrlund

  6. Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota - Twin Cities, Minneapolis, MN, USA

    Kevin J. Murray

  7. Institute for Bio- and Geosciences (IBG-5), Forschungszentrum Jülich GmbH, Jülich, Germany

    Nils Hoffmann

  8. School of Engineering, Westlake University, Hangzhou, China

    Miaoshan Lu

  9. BlockLab, Center for Large Datasystems Research, San Diego Supercomputer Center, La Jolla, CA, USA

    Abinesh Sarvepalli

  10. Chair for Bioinformatics, Friedrich Schiller University Jena, Jena, Germany

    Markus Fleischauer, Kai Dührkop & Sebastian Böcker

  11. Agriculture and Agri-Food Canada, London Research and Development Centre, London, Ontario, Canada

    Shawn J. Hoogstra

  12. Datacraft Technologies, Mosman Park, Washington, Western Australia, Australia

    Chris J. Pudney

  13. Analytical Solutions Group, Product Technology and Engineering, Jealott’s Hill International Research Centre, Bracknell, UK

    Mark Earll

  14. Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA

    Timothy R. Fallon

  15. Department of Effect-Directed Analysis, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany

    Tobias Schulze

  16. Ecology and Forest Genetics, Institute of Forest Sciences (ICIFOR-INIA-CSIC), Madrid, Spain

    Albert Rivas-Ubach

  17. Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA

    Aivett Bilbao

  18. Clinic for Diagnostic Imaging, Diagnostic Imaging Research Unit (DIRU), University of Zurich, Zürich, Switzerland

    Henning Richter

  19. School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland

    Louis-Félix Nothias

  20. Department of Computer Science, University of California Riverside, Riverside, CA, USA

    Mingxun Wang

  21. School of Medical Sciences, Örebro University, Örebro, Sweden

    Matej Orešič

  22. Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland

    Matej Orešič

  23. Whitehead Institute for Biomedical Research, Cambridge, MA, USA

    Jing-Ke Weng

  24. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA

    Jing-Ke Weng

  25. Institute of Neuropathology, University Hospital Münster, Münster, Germany

    Astrid Jeibmann

  26. CMFI Cluster of Excellence, University of Tuebingen, Tuebingen, Germany

    Daniel Petras

Authors
  1. Robin Schmid
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  2. Steffen Heuckeroth
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  41. Xiuxia Du
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  42. Tomáš Pluskal
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Contributions

R.S., S.H., T.P. are coordinating the MZmine open source project. S.H., R.S., P.C.D., T.P., A.K. wrote and edited the initial manuscript. S.H., R.S., A.K., T.P. conceived the combined workflow for MALDI–IMS–MS imaging and LC–IMS–MS, developed the code and tested the workflow. R.S., S.H., A.K., T.P. A. Smirnov, O. Myers, T.S.D., R.B., K.J.M., N.H., M.L., A. Sarvepalli, Z.Z., M.F., K.D., M. Wesner., M. Wang, S.J.H., O. Mokshyna, K.P., C.J.P., T.R.F., T.S. and more have contributed open source code to MZmine. C.B., T.D., S.H., L.M., O. Mokshyna, R.S., M.E. wrote the documentation for MZmine. L.-F.-N., A.R.-U., A.B., R.S., S.H., A.K., M.O., P.C.D., D.P., U.K., J.-K.W., H.H., X.D., S.B. initiated and/or supervised projects related to MZmine development. T.S., A.K., S.H., R.S., T.P., A.R.-U., A.B., N.H., D.P. were involved in the supervision of students for the Google Summer of Code program. R.S., L.-F.N., D.P., A. Sarvepalli, Z.Z., M. Wang, P.C.D. contributed to the linking with GNPS to facilitate molecular networking in MZmine. R.S., D.P., L.-F.N., M. Wang conceived and developed the FBMN and IIMN workflows in MZmine. S.H., R.S., A.K. implemented imzML support and developed imaging feature detection. S.H. developed the ion mobility data support, native .tdf support, ion mobility gap filling; added ion mobility visualization modules; recreated project load/save. A.K. provided TDF-SDK for native .tdf import and supervised S.H. for its implementation. S.H., A.K. developed ion mobility feature detection. A.K., H.H. developed lipid annotation modules and workflows and made it IMS aware. R.S., M. Wang developed parallel gap-filling. S.H., R.S. developed parallel sample alignment. T.S.D. implemented mzTab, MGF and MSP support and various peak information (FWHM, tailing factor, asymmetry factor, RT start and RT end). R.S., C.B., A.K. worked on the mass spectral library creation and matching workflows. K.D., M.F., R.S., S.H., S.B. assisted with the integration of SIRIUS and data exchange. A.R.-U., T.P. conceived the exact mass calibration module. M.L. developed support for the open data format ‘Aird’. S.J.H. developed diagnostic fragmentation filtering. M. Wesner developed the mass-voltammogram module. R.S., S.H. profiled and optimized MZmine’s memory consumption and processing throughput. S.H. prepared sheep brain lipid extracts, prepared MALDI samples, acquired imaging data, analyzed imaging and chromatographic data. H.R. and A.J. planned and carried out animal study ZH235/17. A.J. prepared thin sections and histologic tissue staining of the sheep brain dataset and supplied the tissue samples for extraction. P.O.H., C.B. provided testing data and feedback for LC–MS and IMS–MS imaging workflows. E.R. acquired LC–IMS–MS2 lipid data. R.S., S.H., D.P. conducted the performance tests. All authors edited and approved the final manuscript.

Corresponding author

Correspondence to Tomáš Pluskal.

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Competing interests

A.K. is employed at Bruker Daltonics GmbH & Co. KG. S.B., K.D. and M.F. are co-founders of Bright Giant. P.C.D. is a scientific advisor for Cybele and is a scientific advisor and a co-founder of Enveda, Arome and Ometa with prior approval by the University of California San Diego. M. Wang is a co-founder of Ometa Labs LLC. J.-K.W. is a member of the Scientific Advisory Board and a shareholder of DoubleRainbow Biosciences, Galixir and Inari Agriculture, which develop biotechnologies related to natural products, drug discovery and agriculture.

Peer review

Peer review information

Nature Biotechnology thanks Xiaotao Shen and Zheng-Jiang Zhu for their contribution to the peer review of this work.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6, Supplementary Notes 1–3, Supplementary References

Supplementary Code

A ZIP archive with batch files for data processing using MZmine 3 and MZmine 2

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Schmid, R., Heuckeroth, S., Korf, A. et al. Integrative analysis of multimodal mass spectrometry data in MZmine 3. Nat Biotechnol 41, 447–449 (2023). https://doi.org/10.1038/s41587-023-01690-2

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