The confident high-throughput identification of small molecules is one of the most challenging tasks in mass spectrometry-based metabolomics. Annotating the molecular formula of a compound is the first step towards its structural elucidation. Yet even the annotation of molecular formulas remains highly challenging. This is particularly so for large compounds above 500 daltons, and for de novo annotations, for which we consider all chemically feasible formulas. Here we present ZODIAC, a network-based algorithm for the de novo annotation of molecular formulas. Uniquely, it enables fully automated and swift processing of complete experimental runs, providing high-quality, high-confidence molecular formula annotations. This allows us to annotate novel molecular formulas that are absent from even the largest public structure databases. Our method re-ranks molecular formula candidates by considering joint fragments and losses between fragmentation trees. We employ Bayesian statistics and Gibbs sampling. Thorough algorithm engineering ensures fast processing in practice. We evaluate ZODIAC on five datasets, producing results substantially (up to 16.5-fold) better than for several other methods, including SIRIUS, which is the state-of-the-art algorithm for molecular formula annotation at present. Finally, we report and verify several novel molecular formulas annotated by ZODIAC.
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Input mzML/mzXML files for the five datasets are available at MassIVE (https://massive.ucsd.edu/), with the following accession numbers for dendroides (MSV000080502), for NIST1950 (MSV000081364), for tomato (MSV000081463), for diatoms (MSV000081731) and for the mice stool (MSV000079949) datasets. SIRIUS and ZODIAC results and a virtual machine on which to reproduce the data are available from https://bio.informatik.uni-jena.de/data/ and https://doi.org/10.6084/m9.figshare.12911171. Source data are provided with this paper.
ZODIAC has been integrated into the SIRIUS software and is written in Java. It is open source under the GNU General Public License (version 3), and works on Windows, macOS X and Linux. A command-line version allows batch processing and results can be visualized in a graphical user interface. We provide executable binaries, example files and additional information on the ZODIAC website (https://bio.informatik.uni-jena.de/software/zodiac/). A source copy is hosted on GitHub (https://github.com/boecker-lab/sirius-libs60); the branch ‘zodiac_in_sirius_4_release’ contains the SIRIUS and ZODIAC code used for evaluation in this paper.
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We thank M. Witting for discussions and F. Kretschmer for the fragmentation tree visualization. We acknowledge financial support by the Deutsche Forschungsgemeinschaft to S.B., K.D., M.F., M.A.H. and M.L. (grant BO 1910/20) and D.P. (grant PE 2600/1). I.K. acknowledges funding from the Blasker Environmental Grant, San Diego Foundation. F.V. was funded by the Department of Navy, Office of Naval Research Multidisciplinary University Research Initiative (MURI) Award (award number N00014-15-1-2809). L.-F.N. was supported by European Union’s Horizon 2020 grants (MSCA-GF, 704786). M.M. acknowledges funding from the National Science Foundation (award number 1354050). We acknowledge financial support by the US National Institutes of Health to P.C.D. for the Center for Computational Mass Spectrometry (grant P41 GM103484), the re-use of metabolomics data (grant R03 CA211211) and the tools for rapid and accurate structure elucidation of natural products (grant R01 GM107550). P.C.D. also acknowledges support from the Sloan Foundation and from the Gordon and Betty Moore Foundation.
S.B, K.D., M.F., M.A.H. and M.L. are founders of Bright Giant GmbH. P.C.D. is the scientific advisor for Sirenas LLC.
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Given is the number of total compounds, the number of compounds with a ground truth molecular formula and the number which are in the top 50 of SIRIUS-ranked candidates. The median m/z and 25 and 75 percentile considers only candidates in the top 50. We report the maximum absolute value of all relative mass errors in a dataset. Finally, sample standard deviations (STD) of relative mass errors are computed assuming a mean mass error of zero.
Distribution of precursor ion m/z of the compounds used as ground truth for the evaluation of the molecular formula annotation on the five datasets. Bins of width 100 are centred at 100, 200, …, 800 m/z.
(1) Each LC-MS/MS run is processed individually; input mzML/mzXML files are processed using OpenMS, performing feature and adduct detection and producing files in SIRIUS input format. Resulting features combine MS1, MS/MS and adduct information. (2), (3) Filtering is performed on feature, MS/MS and peak level. (4) Similar features are merged between different runs using hierarchical clustering; MS/MS are combined and a best isotope pattern is selected per feature. (5) Missing isotope peaks are searched in MS1 spectra to extend isotope patterns. (6) A final feature filtering step is performed; the remaining features are considered as compounds. (7) SIRIUS is executed. (8) Compounds with few explained peaks are discarded, since a badly explained MS/MS spectrum indicates low quality. (9) ZODIAC is run on the remaining compounds. (10) SIRIUS and ZODIAC are evaluated on the same set of compounds.
Error rates on five datasets. Methods are SIRIUS; ZODIAC (without anchors); exact mass over elements carbon, hydrogen, nitrogen and oxygen (‘exact mass (CHNO)’); exact mass over CHNO plus phosphorus and sulfur (‘exact mass (CHNOPS)’); Seven Golden Rules with elements CHNOPS (‘7GR (CHNOPS)’); Seven Golden Rules with elements CHNOPS plus bromine and chlorine (‘7GR (CHNOPSBrCl)’); and GenForm. Between 44 an 271 compounds were processed per dataset, see Extended Data Fig. 1 for details. GenForm is the only publicly available tool for molecular formula inference besides SIRIUS, and considers both the isotope pattern and the fragmentation spectrum. GenForm was restricted to elements CHNOPS, and 7GR (CHNOPSBrCl) cannot annotate iodine-containing compounds; to this end, only SIRIUS and ZODIAC are in theory capable of annotating the two novel molecular formulas C24H47BrNO8P and C15H30ClIO5 reported here. Error rates are based on all compounds with established ground truth, resulting in slightly higher error rates for SIRIUS and ZODIAC on dendroides, tomato and mice stool compared to Fig. 1. Error rates on the five datasets agree well with the mass of compounds in the respective dataset, see Extended Data Fig. 1: larger compounds result in substantially more candidates to be considered, in particular for a larger set of elements, and result in worse annotation rates. For evaluation details see the Methods section.
For each ZODIAC molecular formula annotation, we test whether it meets the molecular formula subset of the Seven Golden Rules (7GR). Each dot represents one annotated compound; molecular formulas are sorted by ZODIAC score.
All molecular formulas are absent from the largest molecular structure databases PubChem and ChemSpider. Only molecular formula annotations with a minimum ZODIAC score of 0.98 are reported such that at least 95% of the MS/MS spectrum intensity is being explained by the SIRIUS fragmentation tree, and at least one molecular formula of the compound is connected to 5 or more compounds. There may be more than one hypothetical compound in an LC-MS run being annotated with one molecular formula, potentially corresponding to different isomers. For such cases, ‘#comp.’ is the number of hypothetical compounds being annotated with the given molecular formula, and ‘max score’ is the maximum ZODIAC score among these annotations. The corresponding compounds are given in Supplementary Table 5. For 90.00% of the compounds, SIRIUS top-ranks the same molecular formula.
Supplementary Figs. 1–7, Supplementary Table 4, Supplementary Note 1.
Manually annotated molecular formulas for compounds in the dendroides dataset. These molecular formulas serve as ground truth for evaluation of SIRIUS and ZODIAC.
Spectral library hits for datasets NIST1950, tomato, diatoms and mice stool. The molecular formulas of these library hits serve as ground truth for evaluation of SIRIUS and ZODIAC.
List of input files used for evaluation of five datasets. The included files in mzML/mzXML format correspond to LC-MS/MS runs which were used for evaluation. These runs are subsets of the data provided at MassIVE repository.
Compounds with a novel molecular formula. Provided are the detailed information for compounds corresponding to the novel molecular formulas in Extended Data Fig. 6. All molecular formulas are absent from the largest molecular structure databases PubChem and ChemSpider.
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Ludwig, M., Nothias, LF., Dührkop, K. et al. Database-independent molecular formula annotation using Gibbs sampling through ZODIAC. Nat Mach Intell 2, 629–641 (2020). https://doi.org/10.1038/s42256-020-00234-6
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