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RepoRT: a comprehensive repository for small molecule retention times

Nature Methods volume 21, pages 153–155 (2024)Cite this article

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Liquid chromatography (LC) is frequently used to separate metabolites and other small molecules. Retention time is the time required for a particular molecule to pass through the LC column. Prediction of retention times is one of the most investigated problems in the field of quantitative structure–property relationships1. However, transferable predictions are intrinsically complicated because retention times depend on both compound structure and the chromatographic system used. Despite four decades of development1,2 and literally hundreds of published machine learning models, prediction of small molecule retention time is still far from everyday use. The resulting models are restricted to the chosen specific chromatographic conditions, but also by the molecules used in training and evaluation. Consequently, few computational methods use retention time for compound annotation, with at best moderate improvements in annotation power3,4.

We present RepoRT (https://github.com/michaelwitting/RepoRT), a data repository for storing and retrieving retention time data as well as rich metadata on chromatographic conditions. RepoRT currently contains 373 datasets, 8,809 unique compounds, and 88,325 retention time entries measured on 49 different chromatographic columns using varying eluents, flow rates, and temperatures (Supplementary Note 1, Supplementary Fig. 1). Here, 295 datasets were measured on reversed-phase columns and 71 datasets on hydrophilic interaction chromatography (HILIC) columns. Column models that are regularly used in metabolomics5 are also well covered in RepoRT. The recorded metadata include chromatographic columns, the composition of eluents and gradients, and temperatures. Automated workflows allow processing and standardization of input data. Notably, several datasets were imported from PredRet6. To ensure the longevity of RepoRT, we use GitHub for data storage (Supplementary Table 1). Version control allows data to be updated and corrected, and changes are tracked throughout this process.

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Fig. 1: RepoRT, a repository for small molecule retention times.

Data availability

Data are freely available from the dedicated GitHub repository (https://github.com/michaelwitting/RepoRT). Source data are provided with this paper.

Code availability

All code is freely available from the dedicated GitHub repository (https://github.com/michaelwitting/RepoRT).

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Acknowledgements

F.K., M.A.H., and S.B. are supported by Deutsche Forschungsgemeinschaft (BO 1910/23). F.K. and S.B. are supported by the Ministry for Economics, Sciences and Digital Society of Thuringia (Framework ProDigital, DigLeben-5575/10-9). E.-M.H. and M.W. are supported by Deutsche Forschungsgemeinschaft (MW 4382/10-1). We thank everybody who publicly shared their retention time data. We thank J. Büscher for providing and uploading unpublished data. We express particular thanks to J. Stanstrup, who allowed us to integrate data from PredRet into RepoRT.

Author information

Author notes

  1. Martin A. Hoffmann

    Present address: Bright Giant GmbH, Jena, Germany

  2. These authors contributed equally: Fleming Kretschmer, Eva-Maria Harrieder.

Authors and Affiliations

  1. Chair for Bioinformatics, Institute for Computer Science, Friedrich Schiller University Jena, Jena, Germany

    Fleming Kretschmer, Martin A. Hoffmann & Sebastian Böcker

  2. Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg, Germany

    Eva-Maria Harrieder & Michael Witting

  3. Metabolomics and Proteomics Core, Helmholtz Zentrum München, Neuherberg, Germany

    Michael Witting

  4. Chair of Analytical Food Chemistry, TU München, Freising, Germany

    Michael Witting

Authors
  1. Fleming Kretschmer
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  2. Eva-Maria Harrieder
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  3. Martin A. Hoffmann
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  4. Sebastian Böcker
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  5. Michael Witting
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Contributions

S.B. and M.W. designed the research. F.K., M.A.H., and M.W. implemented the repository. E.-M.H. manually curated datasets. F.K. and S.B. developed methods for automated error detection. E.-M.H. measured the systematically varying chromatographic parameters of the datasets. F.K. and M.A.H. implemented methods. E.-M.H. and M.W. performed a statistical analysis of the repository content. F.K., E.-M.H., S.B., and M.W. wrote the manuscript.

Corresponding authors

Correspondence to Sebastian Böcker or Michael Witting.

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Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Methods thanks Joshua Rabinowitz and Juho Rousu for their contribution to the peer review of this work.

Supplementary information

Supplementary Information

Supplementary Notes 1–7, Supplementary Figs. 1–6, and Supplementary Tables 1, 4, 6 and 7

Reporting Summary

Supplementary Table 2

Tanaka parameters

Supplementary Table 3

Hydrophobic subtraction model parameters

Supplementary Table 5

Standard column names used in RepoRT

Source data

Source Data Fig. 1

Raw data for panels a,b,c,d,f

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Kretschmer, F., Harrieder, EM., Hoffmann, M.A. et al. RepoRT: a comprehensive repository for small molecule retention times. Nat Methods 21, 153–155 (2024). https://doi.org/10.1038/s41592-023-02143-z

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