Comprehensive temporal protein dynamics during the diauxic shift in saccharomyces cerevisiae

Yeast (Saccharomyces cerevisiae) has served as a key model system in biology and as a benchmark for "omics" technology. Although near-complete proteomes of log phase yeast have been measured, protein abundance in yeast is dynamic, particularly during the transition from log to stationary phase. Defining the dynamics of proteomic changes during this transition, termed the diauxic shift, is important to understand the basic biology of proliferative versus quiescent cells. Here, we perform temporal quantitative proteomics to fully capture protein induction and repression during the diauxic shift. Accurate and sensitive quantitation at a high temporal resolution and depth of proteome coverage was achieved using TMT10 reagents and LC-MS3 analysis on an Orbitrap Fusion tribrid mass spectrometer deploying synchronous precursor selection. Triplicate experiments were analyzed using the time-course R package and a simple template matching strategy was used to reveal groups of proteins with similar temporal patterns of protein induction and repression. Within these groups are functionally distinct types of proteins such as those of glyoxylate metabolism and many proteins of unknown function not previously associated with the diauxic shift (e.g. YNR034W-A and FMP16). We also perform a dual time-course experiment to determine Hap2-dependent proteins during the diauxic shift. These data serve as an important basic model for fermentative versus respiratory growth of yeast and other eukaryotes and are a benchmark for temporal quantitative proteomics. The yeast proteome serves as a valuable model in systems biology (1) and as such has been used to gauge technological milestones in proteomics. In recent years, the depth of protein identification in logarithmically-growing yeast has expanded to near-comprehensiveness (>4000 identified proteins) (2–3). However, the yeast proteome is dynamic, and understanding regulatory networks requires a comprehensive grasp of the timing of induction or repression of specific sets of proteins. Proteome dynamics in yeast depend largely on substrate availability, the major of which is glucose. The diauxic shift, the transition from log phase growth on glucose to stationary phase upon glucose exhaustion, involves temporal coordination of protein regulation that is still not completely understood. Because log phase yeast resemble fermentative cancer cells, the diauxic shift is also considered important basic model for understanding the requirements of proliferative cell growth. As such, a landmark gene expression study of the diauxic shift at the transcript level (4) has served as an important resource in biology (5). However, despite recent progress, the dynamic nature of the diauxic shift at the proteome level has not been adequately explored. Doing so requires the ability to perform comprehensive quantitative proteomic analysis with a sufficient number of time-points to resolve the timing of protein induction or repression. Although temporal proteomic data changes have recently been reported within both log and stationary phase (6) using six-plex quantitative proteomics with TMT, and during the transition between log and stationary phase using a four-plex Neucode strategy, highly resolved proteomic data able to fully capture protein dynamics between the two states are lacking. Several recent advances in mass spectrometry and multiplexed quantitative proteomics potentiate accurate measurements of highly resolved time courses at a comprehensive depth of proteome coverage. First, tandem mass tag technology (TMT)1 has been expanded to compare up to 10 samples simultaneously (TMT10) using isotopologue-containing reporter ions distinguishable by high-resolution mass spectrometry (7). TMT reagents work on the principle of isobaric tagging whereby their addition to a peptide maintains a nominal mass, but cleavable reporter ions are used to compare peptide abundance between samples (8). Second, although isobaric reporter ion tagging strategies have been plagued by interference from co-isolated peptides, using MS3 scans for reporter ion quantitation has been shown to ensure quantitative accuracy (9). Third, the MS3 approach has recently been enhanced by techniques to isolate multiple MS2 precursors (SPS) for greater MS3 scan sensitivity (10). These advancements, deployed on the Orbitrap Fusion tribrid mass spectrometer allow high temporal resolution (10 time points), proteomic depth (>4500 proteins), and quantitative accuracy (11). We here aimed to fully capture the intricate temporal proteome dynamics over the full diauxic shift at a comprehensive level using 10-plex TMT and LC-MS3. The data we present here extend current understanding of protein dynamics during diauxic shift in yeast by virtue of the high temporal resolution and comprehensive depth achieved. Data were collected in triplicate allowing us to assess temporal significance, following which we applied a simple template-profile matching strategy to map the timing of induction or repression of proteins of specific functions in relation to glucose exhaustion. The data set also resolves the timing of the induction of many proteins of unknown function (e.g. FMP16, YNR034W-A, and TMA17) as well those not previously associated with the transition to stationary phase (e.g. YKL065W-A and PAI3). In an additional, dual time-course experiment, we show both high reproducibility between analyses of different strains and provide a putative list of proteins dependent on the respiratory growth-related transcription factor, Hap2. These include many known Hap2-dependent proteins such as those of glyoxylate metabolism and oxidative phosphorylation as well as several novel Hap2-dependent proteins supporting carnitine metabolism (e.g. AGP2). These data serve as a benchmark in temporal quantitative proteomics and are a valuable resource for the biological community in understanding fermentative versus respiratory metabolism in eukaryotic cells.