Fast mass spectrometry search and clustering of untargeted metabolomics data

Fast mass spectrometry search and clustering of untargeted metabolomics data

Kale, N. S. et al. MetaboLights: an analog-access database repository for metabolomics data. Curr. Protoc. Bioinformatics53, 14–13 (2016).

Article 

Google Scholar 

Sud, M. et al. Metabolomics Workbench: an international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Res.44, D463–D470 (2016).

Article 
CAS 
PubMed 

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 

Wang, M. et al. Mass spectrometry searches using MASST. Nat. Biotechnol.38, 23–26 (2020).

Article 
PubMed 
PubMed Central 

Google Scholar 

Courraud, J., Ernst, M., Svane Laursen, S., Hougaard, D. M. & Cohen, A. S. Studying autism using untargeted metabolomics in newborn screening samples. J. Mol. Neurosci.71, 1378–1393 (2021).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Ernst, M. et al. Gestational age-dependent development of the neonatal metabolome. Pediatr. Res.89, 1396–1404 (2021).

Article 
CAS 
PubMed 

Google Scholar 

Frank, A. M. et al. Clustering millions of tandem mass spectra. J. Proteome Res.7, 113–122 (2008).

Article 
CAS 
PubMed 

Google Scholar 

Jarmusch, A. K. et al. ReDU: a framework to find and reanalyze public mass spectrometry data. Nat. Methods17, 901–904 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Quinn, R. A. et al. Global chemical effects of the microbiome include new bile-acid conjugations. Nature579, 123–129 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Petras, D. et al. Non-targeted metabolomics enables the prioritization and tracking of anthropogenic pollutants in coastal seawater. Chemosphere271 (2020).

Kuo, T.-H., Yang, C.-T., Chang, H.-Y., Hsueh, Y.-P. & Hsu, C.-C. Nematode-trapping fungi produce diverse metabolites during predator–prey interaction. Metabolites10, 117 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Depke, T., Thöming, J. G., Kordes, A., Häussler, S. & Brönstrup, M. Untargeted LC-MS metabolomics differentiates between virulent and avirulent clinical strains of Pseudomonas aeruginosa. Biomolecules10, 1041 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Eberhard, F. E., Klimpel, S., Guarneri, A. A. & Tobias, N. J. Metabolites as predictive biomarkers for Trypanosoma cruzi exposure in triatomine bugs. Comput. Struct. Biotechnol. J.19, 3051–3057 (2021).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Lybbert, A. C., Williams, J. L., Raghuvanshi, R., Jones, A. D. & Quinn, R. A. Mining public mass spectrometry data to characterize the diversity and ubiquity of P. aeruginosa specialized metabolites. Metabolites10, 445 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Mohimani, H. et al. Dereplication of peptidic natural products through database search of mass spectra. Nat. Chem. Biol.13, 30–37 (2017).

Article 
CAS 
PubMed 

Google Scholar 

Frank, A. M. et al. Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra. Nat. Methods8, 587–591 (2011).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Bandeira, N., Tsur, D., Frank, A. & Pevzner, P. A. Protein identification by spectral networks analysis. Proc. Natl Acad. Sci. USA104, 6140–6145 (2007).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Ramos, A. E. F., Evanno, L., Poupon, E., Champy, P. & Beniddir, M. A. Natural products targeting strategies involving molecular networking: different manners, one goal. Nat. Prod. Rep.36, 960–980 (2019).

Article 

Google Scholar 

Kalinski, J.-C. J. et al. Molecular networking reveals two distinct chemotypes in pyrroloiminoquinone-producing Tsitsikamma favus sponges. Marine Drugs17, 60 (2019).

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 

Trautman, E. P., Healy, A. R., Shine, E. E., Herzon, S. B. & Crawford, J. M. Domain-targeted metabolomics delineates the heterocycle assembly steps of colibactin biosynthesis. J. Am. Chem. Soc.139, 4195–4201 (2017).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Vizcaino, M. I., Engel, P., Trautman, E. & Crawford, J. M. Comparative metabolomics and structural characterizations illuminate colibactin pathway-dependent small molecules. J. Am. Chem. Soc.136, 9244–9247 (2014).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Nguyen, D. D. et al. Indexing the Pseudomonas specialized metabolome enabled the discovery of poaeamide B and the bananamides. Nat. Microbiol.2, 16197 (2016).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Woo, S., Kang, K. B., Kim, J. & Sung, S. H. Molecular networking reveals the chemical diversity of selaginellin derivatives, natural phosphodiesterase-4 inhibitors from Selaginella tamariscina. J. Nat. Prod.82, 1820–1830 (2019).

Article 
CAS 
PubMed 

Google Scholar 

Reginaldo, F. P. S. et al. Molecular networking discloses the chemical diversity of flavonoids and selaginellins in Selaginella convoluta. Planta Med.87, 113–123 (2021).

Article 
CAS 
PubMed 

Google Scholar 

Bittremieux, W. et al. Analog access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics. Preprint at bioRxiv https://doi.org/10.1101/2022.05.15.490691 (2022).

Schnell, N. et al. Prepeptide sequence of epidermin, a ribosomally synthesized antibiotic with four sulphide-rings. Nature333, 276–278 (1988).

Article 
CAS 
PubMed 

Google Scholar 

Mohr, K. I. et al. Pinensins: the first antifungal lantibiotics. Angew. Chem. Int. Ed.54, 11254–11258 (2015).

Article 
CAS 

Google Scholar 

Férir, G. et al. The lantibiotic peptide labyrinthopeptin A1 demonstrates broad anti-HIV and anti-HSV activity with potential for microbicidal applications. PLoS ONE8, e64010 (2013).

Article 
PubMed 
PubMed Central 

Google Scholar 

Iorio, M. et al. A glycosylated, labionin-containing lanthipeptide with marked antinociceptive activity. ACS Chem. Biol.9, 398–404 (2014).

Article 
CAS 
PubMed 

Google Scholar 

Arnison, P. G. et al. Ribosomally synthesized and post-translationally modified peptide natural products: overview and recommendations for a universal nomenclature. Nat. Prod. Rep.30, 108–160 (2013).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Frank, A. & Pevzner, P. PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal. Chem.77, 964–973 (2005).

Article 
CAS 
PubMed 

Google Scholar 

Walker, M. C. et al. Precursor peptide-targeted mining of more than one hundred thousand genomes expands the lanthipeptide natural product family. BMC Genomics21, 387 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Kodani, S., Lodato, M. A., Durrant, M. C., Picart, F. & Willey, J. M. SapT, a lanthionine-containing peptide involved in aerial hyphae formation in the streptomycetes. Mol. Microbiol.58, 1368–1380 (2005).

Article 
CAS 
PubMed 

Google Scholar 

Ueda, K. et al. AmfS, an extracellular peptidic morphogen in Streptomyces griseus. J. Bacteriol.184, 1488–1492 (2002).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

da Silva, R. R., Dorrestein, P. C. & Quinn, R. A. Illuminating the dark matter in metabolomics. Proc. Natl Acad. Sci. USA112, 12549–12550 (2015).

Article 
PubMed 
PubMed Central 

Google Scholar 

Aron, A. T. et al. Reproducible molecular networking of untargeted mass spectrometry data using GNPS. Nat. Protoc.15, 1954–1991 (2020).

Article 
CAS 
PubMed 

Google Scholar 

Nothias, L.-F. et al. Feature-based molecular networking in the GNPS analysis environment. Nat. Methods17, 905–908 (2020).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

van Der Hooft, J. J. et al. Linking genomics and metabolomics to chart specialized metabolic diversity. Chem. Soc. Rev.49, 3297–3314 (2020).

Article 
PubMed 

Google Scholar 

Yang, J. Y. et al. Molecular networking as a dereplication strategy. J. Nat. Prod.76, 1686–1699 (2013).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Watrous, J. et al. Mass spectral molecular networking of living microbial colonies. Proc. Natl Acad. Sci. USA109, E1743–E1752 (2012).

Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 

Ludwig, M., Fleischauer, M., Dührkop, K., Hoffmann, M. A. & Böcker, S. De novo molecular formula annotation and structure elucidation using SIRIUS 4. Methods Mol. Biol.2104, 185–207 (2020).

Dührkop, K. et al. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nat. Biotechnol39, 462–471 (2021).

Article 
PubMed 

Google Scholar 

Mohimani, H., Kim, S. and Pevzner, P. A. A new approach to evaluating statistical significance of spectral identifications. J. Proteome Res.12, 1560–1568 (2013).

>>> Read full article>>>
Copyright for syndicated content belongs to the linked Source : Nature.com – https://www.nature.com/articles/s41587-023-01985-4

Exit mobile version