The yeast Saccharomyces cerevisiae is a widely-used eukaryotic model organism and a promising cell factory for industry. However, despite decades of research, the regulation of its metabolism is not yet fully understood, and its complexity represents a major challenge for engineering and optimizing biosynthetic routes. Recent studies have demonstrated the potential of resource and proteomic allocation data in enhancing models for metabolic processes. However, comprehensive and accurate proteome dynamics data that can be used for such approaches are still very limited. Therefore, we performed a quantitative proteome dynamics study to comprehensively cover the transition from exponential to stationary phase for both aerobically and anaerobically grown yeast cells. The combination of highly controlled reactor experiments, biological replicates, and standardized sample preparation procedures ensured reproducibility and accuracy. In addition, we selected the CEN.PK lineage for our experiments because of its relevance for both fundamental and applied research. Together with the prototrophic standard haploid strain CEN.PK113-7D, we also investigated an engineered strain with genetic minimization of the glycolytic pathway, resulting in the quantitative assessment of 54 proteomes. The anaerobic cultures showed remarkably less proteome-level changes compared with the aerobic cultures, during transition from the exponential to the stationary phase as a consequence of the lack of the diauxic shift in the absence of oxygen. These results support the notion that anaerobically growing cells lack resources to adequately adapt to starvation. This proteome dynamics study constitutes an important step toward better understanding of the impact of glucose exhaustion and oxygen on the complex proteome allocation process in yeast. Finally, the established proteome dynamics data provide a valuable resource for the development of resource allocation models as well as for metabolic engineering efforts.

The importance of obtaining comprehensive and accurate information from cellular proteomics experiments asks for a systematic investigation of sample preparation protocols. In particular when working with unicellular organisms with strong cell walls, such as found in the model organism and cell factory Saccharomyces cerevisiae. Here, we performed a systematic comparison of sample preparation protocols using a matrix of different conditions commonly applied in whole cell lysate, bottom-up proteomics experiments. The different protocols were evaluated for their overall fraction of identified spectra, proteome and amino acid sequence coverage, GO-term distribution and number of peptide modifications, by employing a combination of database and unrestricted modification search approaches. Ultimately, the best protocols enabled the identification of approximately 65–70% of all acquired fragmentation spectra, where additional de novo sequencing suggests that unidentified spectra were largely of too low spectral quality to provide confident spectrum matches. Generally, a range of peptide modifications could be linked to solvents, additives as well as filter materials. Most importantly, the use of moderate incubation temperatures and times circumvented excessive formation of modification artefacts. The collected protocols and large sets of mass spectrometric raw data provide a resource to evaluate and design new protocols and guide the analysis of (native) peptide modifications. Significance: The single-celled eukaryote yeast is a widely used model organism for higher eukaryotes in which, for example, the regulation of glycolysis is studied in the context of health and disease. Moreover, yeast is a widely employed cell factory because it is one of the few eukaryotic organisms that can efficiently grow under both aerobic and anaerobic conditions. Large-scale proteomics studies have become increasingly important for single-celled model organisms, such as yeast, in order to provide fundamental understanding of their metabolic processes and proteome dynamics under changing environmental conditions. However, comprehensive and accurate cellular proteomics experiments require optimised sample preparation procedures, in particular when working with unicellular organisms with rigid cell walls, such as found in yeast. Protocols may substantially bias towards specific protein fractions, modify native protein modifications or introduce artificial modifications. That lowers the overall number of spectral identifications and challenges the study of native protein modifications. Therefore, we performed a systematic study of a large array of protocols on yeast grown under highly controlled conditions. The obtained outcomes, the collected protocols and the mass spectrometric raw data enable the selection of suitable sample preparation elements and furthermore support the evaluation of (native) peptide modifications in yeast, and beyond.