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

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

doi:10.1371/journal.pone.0254429

Abstract

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.

Highlights

Interactions between proteins and endogenous metabolites are a hallmark of all cellular processes, from metabolism to signaling
We applied the concept to Chaetomium thermophilum, a thermophilic fungus and model organism for structural biology [14] as its protein complexes are stable and is an ideal model organism for studying multimolecular interactions [15]
As metabolites usually have a molecular weight below 1.5 kDa [16], those fractions can only contain metabolites which were bound to proteins or protein complexes

Summary

Introduction

Interactions between proteins and endogenous metabolites are a hallmark of all cellular processes, from metabolism to signaling. In the former, enzymes interact with metabolites to catalyze chemical reactions, and in the latter, chemical compounds serve as co-factors for proteins to mediate protein function [1]. Protein–metabolite interactions have been historically discovered mostly individually, but more recently by a variety of in vitro screening approaches. Proteometabolomics for unsupervised identification of protein–metabolite interactions

Methods

Results

Conclusion