Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

The hidden impact of in-source fragmentation in metabolic and chemical mass spectrometry data interpretation

Nature Metabolism volume 6, pages 1647–1648 (2024)Cite this article

Subjects

Access through your institution
Buy or subscribe

Mass spectrometry, specifically liquid chromatography–tandem mass spectrometry (LC–MS/MS), stands at the forefront of metabolomic, pharmaceutical and clinical analyses, offering high sensitivity and specificity in detecting metabolites and other small molecules within biological samples. Yet, this powerful technique has unveiled a puzzling abundance of unidentified spectral features, coined the ‘dark metabolome’1,2, which starkly contrasts with the known metabolic diversity. While humans are known to host approximately 20,000 protein encoding genes3,4, with only a subset of these expressing enzymes, the presumed chemical diversity indicated by LC–MS/MS suggests hundreds of thousands to millions of metabolites remain to be characterized2,5. This discrepancy raises a crucial point: might there be a technological explanation inflating the perceived complexity instead of a biological one?

The central dogma of biology describes the relation and information flow between the different omic layers from genome to transcriptome to proteome to metabolome, with the genome being the master code imprinted in any living system at its conception6. The code linking the first three layers is rather straightforward, with three nucleotides encoding one amino acid. However, such an encryption with the metabolome is yet to be revealed. This fact, combined with vast arrays of unannotated LC–MS/MS data, are two of the main reasons that the metabolome (being the entirety of small molecules within a biological system) cannot yet be defined. Current estimates suggest that less than 2% of observed LC–MS/MS spectra can be annotated, pointing to a potentially broad spectrum of unknown compounds2.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: ESI ISF and its broad impact on mass spectrometry data analysis.

Code availability

The python code to analyse the METLIN library is available at https://metlin.scripps.edu/.

References

  1. Peisl, B. Y. L., Schymanski, E. L. & Wilmes, P. Anal. Chim. Acta 1037, 13–27 (2018).

    Article  CAS  PubMed  Google Scholar 

  2. da Silva, R. R., Dorrestein, P. C. & Quinn, R. A. Proc. Natl Acad. Sci. USA 112, 12549–12550 (2015).

    Article  PubMed Central  PubMed  Google Scholar 

  3. Amaral, P. et al. Nature 622, 41–47 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Varabyou, A. et al. Genome Biol. 24, 249 (2023).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Crow, J. M. Nature 599, S14–S15 (2021).

    Article  Google Scholar 

  6. Crick, F. Nature 227, 561–563 (1970).

    Article  CAS  PubMed  Google Scholar 

  7. Xu, Y. F., Lu, W. & Rabinowitz, J. D. Anal. Chem. 87, 2273–2281 (2015).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  8. Chen, L. et al. Rapid Commun. Mass Spectrom. 37, e9519 (2023).

    Article  CAS  PubMed  Google Scholar 

  9. Bernardo-Bermejo, S. et al. Nat. Protocols 18, 1296–1315 (2023).

    Article  CAS  PubMed  Google Scholar 

  10. Hoang, C. et al. Anal. Chem. 96, 5478–5488 (2024).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

This research was partially funded by the Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW) supported by Novo Nordisk Foundation grant (NNF21CC0073729) (M.G.) and by the National Institutes of Health R35 GM130385 (G.S.).

Author information

Authors and Affiliations

  1. Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands

    Martin Giera

  2. The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, Netherlands

    Martin Giera

  3. Scripps Center of Metabolomics and Mass Spectrometry, La Jolla, CA, USA

    Aries Aisporna, Winnie Uritboonthai & Gary Siuzdak

  4. Department of Chemistry, Molecular and Computational Biology Scripps Research Institute, La Jolla, CA, USA

    Gary Siuzdak

Authors
  1. Martin Giera
    View author publications

    Search author on:PubMed Google Scholar

  2. Aries Aisporna
    View author publications

    Search author on:PubMed Google Scholar

  3. Winnie Uritboonthai
    View author publications

    Search author on:PubMed Google Scholar

  4. Gary Siuzdak
    View author publications

    Search author on:PubMed Google Scholar

Corresponding authors

Correspondence to Martin Giera or Gary Siuzdak.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Metabolism thanks Caroline Bartman and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Giera, M., Aisporna, A., Uritboonthai, W. et al. The hidden impact of in-source fragmentation in metabolic and chemical mass spectrometry data interpretation. Nat Metab 6, 1647–1648 (2024). https://doi.org/10.1038/s42255-024-01076-x

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s42255-024-01076-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research