Vailati-Riboni, M., Palombo, V. & Loor, J. J. What are omics sciences? in Periparturient Diseases of Dairy Cows (ed. Ametaj, B.) Ch. 1 (Springer, 2017); https://doi.org/10.1007/978-3-319-43033-1_1.

Patti, G. J., Yanes, O. & Siuzdak, G. Metabolomics: the apogee of the omics trilogy. Nat. Rev. Mol. Cell Biol. 13, 263–269 (2012).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dayalan, S., Xia, J., Spicer, R. A., Salek, R. & Roessner, U. Metabolome analysis. in Encyclopedia of Bioinformatics and Computational Biology (eds. Ranganathan, S., Gribskov, M., Nakai, K. & Schönbach, C.) 396–409 (Academic Press, 2019); https://doi.org/10.1016/B978-0-12-809633-8.20251-3.

Tolstikov, V., Moser, A. J., Sarangarajan, R., Narain, N. R. & Kiebish, M. A. Current status of metabolomic biomarker discovery: impact of study design and demographic characteristics. Metabolites 10, 224 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

de Jonge, N. F. et al. Good practices and recommendations for using and benchmarking computational metabolomics metabolite annotation tools. Metabolomics 18, 103 (2022).

Article  PubMed  PubMed Central  Google Scholar 

Nothias, L.-F. et al. Feature-based molecular networking in the GNPS analysis environment. Nat. Methods 17, 905–908 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 34, 828–837 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ottosson, F. et al. Effects of long-term storage on the biobanked neonatal dried blood spot metabolome. J. Am. Soc. Mass Spectrom. 34, 685–694 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dantas Machado, A. C. et al. Portosystemic shunt placement reveals blood signatures for the development of hepatic encephalopathy through mass spectrometry. Nat. Commun. 14, 5303 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xie, H.-F. et al. Feature-based molecular networking analysis of the metabolites produced by in vitro solid-state fermentation reveals pathways for the bioconversion of epigallocatechin gallate. J. Agric. Food Chem. 68, 7995–8007 (2020).

Article  CAS  PubMed  Google Scholar 

Berlanga-Clavero, M. V. et al. Bacillus subtilis biofilm matrix components target seed oil bodies to promote growth and anti-fungal resistance in melon. Nat. Microbiol. 7, 1001–1015 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Raheem, D. J., Tawfike, A. F., Abdelmohsen, U. R., Edrada-Ebel, R. & Fitzsimmons-Thoss, V. Application of metabolomics and molecular networking in investigating the chemical profile and antitrypanosomal activity of British bluebells (Hyacinthoides non-scripta). Sci. Rep. 9, 2547 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Pendergraft, M. A. et al. Bacterial and chemical evidence of coastal water pollution from the Tijuana River in sea spray aerosol. Environ. Sci. Technol. 57, 4071–4081 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Petras, D. et al. Non-targeted tandem mass spectrometry enables the visualization of organic matter chemotype shifts in coastal seawater. Chemosphere 271, 129450 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stincone, P. et al. Evaluation of data-dependent MS/MS acquisition parameters for non-targeted metabolomics and molecular networking of environmental samples: focus on the Q exactive platform. Anal. Chem. 95, 12673–12682 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wegley Kelly, L. et al. Distinguishing the molecular diversity, nutrient content, and energetic potential of exometabolomes produced by macroalgae and reef-building corals. Proc. Natl Acad. Sci. Usa. 119, e2110283119 (2022).

Article  PubMed  PubMed Central  Google Scholar 

Mannochio-Russo, H. et al. Microbiomes and metabolomes of dominant coral reef primary producers illustrate a potential role for immunolipids in marine symbioses. Commun. Biol. 6, 896 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Shaffer, J. P. et al. Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity. Nat. Microbiol. 7, 2128–2150 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Molina-Santiago, C. et al. Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence. Cell Rep. 36, 109449 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Reher, R. et al. Native metabolomics identifies the rivulariapeptolide family of protease inhibitors. Nat. Commun. 13, 4619 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Aron, A. T. et al. Native mass spectrometry-based metabolomics identifies metal-binding compounds. Nat. Chem. 14, 100–109 (2022).

Article  CAS  PubMed  Google Scholar 

Behnsen, J. et al. Siderophore-mediated zinc acquisition enhances enterobacterial colonization of the inflamed gut. Nat. Commun. 12, 7016 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pang, Z. et al. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 49, W388–W396 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pang, Z. et al. Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nat. Protoc. 17, 1735–1761 (2022).

Article  CAS  PubMed  Google Scholar 

Cajka, T. & Fiehn, O. Toward merging untargeted and targeted methods in mass spectrometry-based metabolomics and lipidomics. Anal. Chem. 88, 524–545 (2016).

Article  CAS  PubMed  Google Scholar 

Alder, L., Greulich, K., Kempe, G. & Vieth, B. Residue analysis of 500 high priority pesticides: better by GC–MS or LC–MS/MS? Mass Spectrom. Rev. 25, 838–865 (2006).

Article  CAS  PubMed  Google Scholar 

Díaz-Cruz, M. S., López de Alda, M. J., López, R. & Barceló, D. Determination of estrogens and progestogens by mass spectrometric techniques (GC/MS, LC/MS and LC/MS/MS). J. Mass Spectrom. 38, 917–923 (2003).

Article  PubMed  Google Scholar 

Michely, J. A., Helfer, A. G., Brandt, S. D., Meyer, M. R. & Maurer, H. H. Metabolism of the new psychoactive substances N,N-diallyltryptamine (DALT) and 5-methoxy-DALT and their detectability in urine by GC–MS, LC–MSn, and LC–HR–MS–MS. Anal. Bioanal. Chem. 407, 7831–7842 (2015).

Article  CAS  PubMed  Google Scholar 

Di Masi, S. et al. HPLC–MS/MS method applied to an untargeted metabolomics approach for the diagnosis of “olive quick decline syndrome”. Anal. Bioanal. Chem. 414, 465–473 (2022).

Article  PubMed  Google Scholar 

Reveglia, P. et al. Untargeted and targeted LC–MS/MS based metabolomics study on in vitro culture of phaeoacremonium species. J. Fungi 8, 55 (2022).

Article  CAS  Google Scholar 

Baig, F., Pechlaner, R. & Mayr, M. Caveats of untargeted metabolomics for biomarker discovery∗. J. Am. Coll. Cardiol. 68