Slow growth rate triggered transition to a pseudohyphal lifestyle of the protein production host Pichia pastoris

Specific growth rate is an important process control parameter for industrial protein production. In the widely used yeast protein production host Pichia pastoris, growth rate is known to significantly impact protein expression and secretion [1]. In that regard, glucose-limited chemostat cultivations carried out over a wide range of specific growth rates have revealed that slow growth rates can trigger a pseudohyphal phenotype in P. pastoris [2]. Such phenotypes are undesirable during large-scale protein production processes since they can lead to foam production. In Saccharomyces cerevisiae pseudohyphal growth is controlled by FLO11, a member of the FLO gene family, which is a group of genes encoding cell surface proteins responsible for conferring a diverse array of adhesion-related phenotypes and reported to be controlled by epigenetic mechanisms. P. pastoris also carries a number of FLO genes but their functions and regulatory patterns are yet unknown. Thus, we set out to investigate this gene family to shed some light on how pseudohyphal growth and other adhesion phenotypes are triggered and regulated in P. pastoris. Please click Additional Files below to see the full abstract

Systems-level organization of yeast methylotrophic lifestyle

BACKGROUND: Some yeasts have evolved a methylotrophic lifestyle enabling them to utilize the single carbon compound methanol as a carbon and energy source. Among them, Pichia pastoris (syn. Komagataella sp.) is frequently used for the production of heterologous proteins and also serves as a model organism for organelle research. Our current knowledge of methylotrophic lifestyle mainly derives from sophisticated biochemical studies which identified many key methanol utilization enzymes such as alcohol oxidase and dihydroxyacetone synthase and their localization to the peroxisomes. C1 assimilation is supposed to involve the pentose phosphate pathway, but details of these reactions are not known to date. RESULTS: In this work we analyzed the regulation patterns of 5,354 genes, 575 proteins, 141 metabolites, and fluxes through 39 reactions of P. pastoris comparing growth on glucose and on a methanol/glycerol mixed medium, respectively. Contrary to previous assumptions, we found that the entire methanol assimilation pathway is localized to peroxisomes rather than employing part of the cytosolic pentose phosphate pathway for xylulose-5-phosphate regeneration. For this purpose, P. pastoris (and presumably also other methylotrophic yeasts) have evolved a duplicated methanol inducible enzyme set targeted to peroxisomes. This compartmentalized cyclic C1 assimilation process termed xylose-monophosphate cycle resembles the principle of the Calvin cycle and uses sedoheptulose-1,7-bisphosphate as intermediate. The strong induction of alcohol oxidase, dihydroxyacetone synthase, formaldehyde and formate dehydrogenase, and catalase leads to high demand of their cofactors riboflavin, thiamine, nicotinamide, and heme, respectively, which is reflected in strong up-regulation of the respective synthesis pathways on methanol. Methanol-grown cells have a higher protein but lower free amino acid content, which can be attributed to the high drain towards methanol metabolic enzymes and their cofactors. In context with up-regulation of many amino acid biosynthesis genes or proteins, this visualizes an increased flux towards amino acid and protein synthesis which is reflected also in increased levels of transcripts and/or proteins related to ribosome biogenesis and translation. CONCLUSIONS: Taken together, our work illustrates how concerted interpretation of multiple levels of systems biology data can contribute to elucidation of yet unknown cellular pathways and revolutionize our understanding of cellular biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12915-015-0186-5) contains supplementary material, which is available to authorized users

Additional file 3: of Systems-level organization of yeast methylotrophic lifestyle

Enrichment of the peroxisomal marker protein Pex3p in the peroxisomal fraction. (PDF 271 kb

Additional file 4: of Systems-level organization of yeast methylotrophic lifestyle

Proteomic identification and quantification of methanol metabolic enzymes and control proteins in peroxisomal fractions and homogenates of P. pastoris cells grown on methanol. Containing the following three sheets: Protein hits: contains all identified proteins that met the threshold in at least one sample, with their respective MASCOT scores, number of peptides, and percent sequence coverage. Peptide hits: list of all identified peptides, their MASCOT scores, mass and charge values, and intensities. Peptides used for quant + areas: lists all peptides of the proteins in Table 3 that were used for quantification, and their respective peak areas in the different samples. (XLSX 879 kb

Additional file 1: of Systems-level organization of yeast methylotrophic lifestyle

Transcriptomic, proteomic, and metabolomic regulation of P. pastoris during methylotrophic growth. Containing the following eight sheets: Summary Omics Data: number of significantly regulated genes, proteins or metabolites (e.g. “up” refers to up-regulation in methanol/glycerol compared to glucose). Transcriptomics and proteomics: Average fold changes and P values of transcriptomics and proteomics comparing P. pastoris cultivated with methanol/glycerol or glucose as carbon source in chemostat. Average values derive from three biological replicates per condition. Metabolomics: Average fold changes and P values of metabolomics measurements comparing P. pastoris cultivated with methanol/glycerol or glucose as carbon source in chemostat cultivations. Average values derive from three biological replicates per condition. Co-regulation (related to Fig. 1 in the text): Regulation of the 575 gene-protein pairs with transcriptomics and proteomics data available and assignment to regulatory groups. Central carbon metabolism (related to Fig. 4 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 4. Amino acid metabolism (related to Fig. 6 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 6. Vitamin biosynthesis (related to Fig. 7 in the text): Average fold changes and P values of transcriptomics, proteomics, and metabolomics measurement depicted in Fig. 7. Peroxisomal gene regulation: Average fold changes and P values of transcriptomics and proteomics for all mentioned peroxisomal genes. Average values derive from three biological replicates per condition. (XLSX 2348 kb