Coupling proteomics and metabolomics for the unsupervised identification of 
protein–metabolite interactions in Chaetomium thermophilum

Li, Yuanyue; Kuhn, Michael; Zukowska-Kasprzyk, Joanna; Hennrich, Marco L.; Kastritis, Panagiotis L.; O’Reilly, Francis J.; Phapale, Prasad; Beck, Martin; Gavin, Anne-Claude; Bork, Peer

doi:10.1371/journal.pone.0254429

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Coupling proteomics and metabolomics for the unsupervised identification of protein–metabolite interactions in Chaetomium thermophilum

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Zitation

Li, Y., Kuhn, M., Zukowska-Kasprzyk, J., Hennrich, M. L., Kastritis, P. L., O’Reilly, F. J., et al. (2021). Coupling proteomics and metabolomics for the unsupervised identification of protein–metabolite interactions in Chaetomium thermophilum. PLoS One, 16(7): e0254429. doi:10.1371/journal.pone.0254429.

Zitierlink: https://hdl.handle.net/21.11116/0000-0008-FECC-5

Zusammenfassung

Protein–metabolite interactions play an important role in the cell’s metabolism and many methods have been developed to screen them in vitro. However, few methods can be applied at a large scale and not alter biological state. Here we describe a proteometabolomic approach, using chromatography to generate cell fractions which are then analyzed with mass spectrometry for both protein and metabolite identification. Integrating the proteomic and metabolomic analyses makes it possible to identify protein-bound metabolites. Applying the concept to the thermophilic fungus Chaetomium thermophilum, we predict 461 likely protein-metabolite interactions, most of them novel. As a proof of principle, we experimentally validate a predicted interaction between the ribosome and isopentenyl adenine.