Global mapping of protein–metabolite interactions in Saccharomyces cerevisiae reveals that Ser-Leu dipeptide regulates phosphoglycerate kinase activity

Abstract

Protein–metabolite interactions are of crucial importance for all cellular processes but remain understudied. Here, we applied a biochemical approach named PROMIS, to address the complexity of the protein–small molecule interactome in the model yeast Saccharomyces cerevisiae. By doing so, we provide a unique dataset, which can be queried for interactions between 74 small molecules and 3982 proteins using a user-friendly interface available at https://promis.mpimp-golm.mpg.de/yeastpmi/. By interpolating PROMIS with the list of predicted protein–metabolite interactions, we provided experimental validation for 225 binding events. Remarkably, of the 74 small molecules co-eluting with proteins, 36 were proteogenic dipeptides. Targeted analysis of a representative dipeptide, Ser-Leu, revealed numerous protein interactors comprising chaperones, proteasomal subunits, and metabolic enzymes. We could further demonstrate that Ser-Leu binding increases activity of a glycolytic enzyme phosphoglycerate kinase (Pgk1). Consistent with the binding analysis, Ser-Leu supplementation leads to the acute metabolic changes and delays timing of a diauxic shift. Supported by the dipeptide accumulation analysis our work attests to the role of Ser-Leu as a metabolic regulator at the interface of protein degradation and central metabolism.

2’,3’-cAMP treatment mimics stress molecular response inArabidopsis thaliana

“…At the 30 min time point, the 2′,3′-cAMP-induced genes were involved in many biological processes, with the highest fold enrichment for genes responding to biotic and abiotic stress, such as heat shock factors, transcription factors, and response to JA. This parallels the metabolomics data, where the accumulation of mainly RNA-degradation products and dipeptides (29) (Figure 1C) are signatures for stress response (Doppler et al, 2019; Thirumalaikumar et al, 2020; Camilo Moreno et al, 2021) not only in plants (Luzarowski et al, 2021).…”

PROMISed: A novel web-based tool to facilitate analysis and visualization of the molecular interaction networks from co-fractionation mass spectrometry (CF-MS) experiments

“…In addition, for datasets comprising two replicates, a single profile is treated as reproducible when the other replicate comprises an empty profile. Two of our previous studies exploiting PROMIS for system-wide detection of protein–metabolite complexes in Arabidopsis thaliana and Saccharomyces cerevisiae showed high reproducibility of fractionation (PCC > 0.9) between biological replicates [17] , [23] .…”

“…Profile deconvolution aims at splitting a complex fractionation profile into several profiles containing one peak each, corresponding to independent homomeric or heteromeric states of a protein or a protein partner of a metabolite. Profile deconvolution based on identifying local maxima was first used in studies aiming to identify protein–protein complexes using CN-PAGE [11] and later adapted for identification of protein–metabolite complexes using PROMIS [17] . In a nutshell, deconvolution is achieved by first identifying local maxima and subsequently finding the shape of the underlying fractionation peak ( Fig.…”

“…PROMIS builds upon the observation that metabolites remain in protein complexes during mild cell lysis and biochemical fractionation. Analogously to PPIs [13] , [24] , PMIs are delineated by correlating the fractionation profiles of a protein–metabolite pair [17] , [21] , [22] , [23] . Table 1 list examples of CF-MS studies.…”

“…PCC 6803 2062 proteins, 291 multiprotein complexes Yes Global landscape of native protein complexes in Synechocystis sp . Pcc 6803 [25] SEC S. cerevisiae (log-phase) 3982 proteins, 74 metabolites Yes Global mapping of protein–metabolite interactions in Saccharomyces cerevisiae reveals that Ser-Leu dipeptide regulates phosphoglycerate kinase activity [17] SEC Chaetomium thermophilum 3286 proteins, 257 metabolites No Coupling proteomics and metabolomics for the unsupervised identification of protein-metabolite interactions in Chaetomium thermophilum [15] …”