Mass spectrometry-based cellular proteomics has taken a prominent role in many fields of research, including life sciences, biotechnology and microbial ecology. Still, advanced mass spectrometry-based proteomics methods are not routinely applied to microbes. The cell factory and model organism Saccharomyces cerevisiae, for example, is very well characterized, however, many research questions surrounding proteome dynamics under different growth conditions, and the regulation of its complex metabolic network via post-translational modifications, remain to be answered. Therefore, the aim of this thesis was to establish and apply optimized protocols to enable the large-scale quantitative analysis of yeast proteome dynamics under highly controlled conditions. In addition, a novel mass spectrometric approach was established to quantify the degree of modification of metabolic enzymes, that allows for a better understanding of their role in metabolic regulation. @en

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.

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Both the identity and the amount of a carbon source present in laboratory or industrial cultivation media have major impacts on the growth and physiology of a microbial species. In the case of the yeast Saccharomyces cerevisiae, sucrose is arguably the most important sugar used in industrial biotechnology, whereas glucose is the most common carbon and energy source used in research, with many well-known and described regulatory effects, e.g. glucose repression. Here we compared the label-free proteomes of exponentially growing S. cerevisiae cells in a defined medium containing either sucrose or glucose as the sole carbon source. For this purpose, bioreactor cultivations were employed, and three different strains were investigated, namely: CEN.PK113-7D (a common laboratory strain), UFMG-CM-Y259 (a wild isolate), and JP1 (an industrial bioethanol strain). These strains present different physiologies during growth on sucrose; some of them reach higher specific growth rates on this carbon source, when compared to growth on glucose, whereas others display the opposite behavior. It was not possible to identify proteins that commonly presented either higher or lower levels during growth on sucrose, when compared to growth on glucose, considering the three strains investigated here, except for one protein, named Mnp1—a mitochondrial ribosomal protein of the large subunit, which had higher levels on sucrose than on glucose, for all three strains. Interestingly, following a Gene Ontology overrepresentation and KEGG pathway enrichment analyses, an inverse pattern of enriched biological functions and pathways was observed for the strains CEN.PK113-7D and UFMG-CM-Y259, which is in line with the fact that whereas the CEN.PK113-7D strain grows faster on glucose than on sucrose, the opposite is observed for the UFMG-CM-Y259 strain.

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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.

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Although transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light context-dependent responses. Human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, whereas hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire essential pathway paves the way for establishment of species-, tissue-, and disease-specific metazoan models.

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The construction of powerful cell factories requires intensive and extensive remodelling of microbial genomes. Considering the rapidly increasing number of these synthetic biology endeavors, there is an increasing need for DNA watermarking strategies that enable the discrimination between synthetic and native gene copies. While it is well documented that codon usage can affect translation, and most likely mRNA stability in eukaryotes, remarkably few quantitative studies explore the impact of watermarking on transcription, protein expression, and physiology in the popular model and industrial yeast Saccharomyces cerevisiae. The present study, using S. cerevisiae as eukaryotic paradigm, designed, implemented, and experimentally validated a systematic strategy to watermark DNA with minimal alteration of yeast physiology. The 13 genes encoding proteins involved in the major pathway for sugar utilization (i.e., glycolysis and alcoholic fermentation) were simultaneously watermarked in a yeast strain using the previously published pathway swapping strategy. Carefully swapping codons of these naturally codon optimized, highly expressed genes, did not affect yeast physiology and did not alter transcript abundance, protein abundance, and protein activity besides a mild effect on Gpm1. The markerQuant bioinformatics method could reliably discriminate native from watermarked genes and transcripts. Furthermore, presence of watermarks enabled selective CRISPR/Cas genome editing, specifically targeting the native gene copy while leaving the synthetic, watermarked variant intact. This study offers a validated strategy to simply watermark genes in S. cerevisiae.

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