Pichia pastoris is the most frequently used yeast system for heterologous protein production today. The last few years have seen several products based on this platform reach approval as biopharmaceutical drugs. Successful glycoengineering to humanize N-glycans is further fuelling this development. However, detailed understanding of the yeast's physiology, genetics and regulation has only developed rapidly in the last few years since published genome sequences have become available. An expanding toolbox of genetic elements and strains for the improvement of protein production is being generated, including promoters, gene copy-number enhancement, gene knockout and high-throughput methods. Protein folding and secretion have been identified as significant bottlenecks in yeast expression systems, pinpointing a major target for strain optimization. At the same time, it has become obvious that P. pastoris, as an evolutionarily more 'ancient' yeast, may in some cases be a better model for human cell biology and disease than Saccharomyces cerevisiae.

The production of recombinant proteins is frequently enhanced at the levels of transcription, codon usage, protein folding and secretion. Overproduction of heterologous proteins, however, also directly affects the primary metabolism of the producing cells. By incorporation of the production of a heterologous protein into a genome scale metabolic model of the yeast Pichia pastoris, the effects of overproduction were simulated and gene targets for deletion or overexpression for enhanced productivity were predicted. Overexpression targets were localized in the pentose phosphate pathway and the TCA cycle, while knockout targets were found in several branch points of glycolysis. Five out of 9 tested targets led to an enhanced production of cytosolic human superoxide dismutase (hSOD). Expression of bacterial β-glucuronidase could be enhanced as well by most of the same genetic modifications. Beneficial mutations were mainly related to reduction of the NADP/H pool and the deletion of fermentative pathways. Overexpression of the hSOD gene itself had a strong impact on intracellular fluxes, most of which changed in the same direction as predicted by the model. In vivo fluxes changed in the same direction as predicted to improve hSOD production. Genome scale metabolic modeling is shown to predict overexpression and deletion mutants which enhance recombinant protein production with high accuracy.

Production of heterologous proteins in Pichia pastoris (syn. Komagataella sp.) has been shown to exert a metabolic burden on the host metabolism. This burden is associated with metabolite drain, which redirects nucleotides and amino acids from primary metabolism. On the other hand, recombinant protein production affects energy and redox homeostasis of the host cell. In a previous study, we have demonstrated that overexpression of single genes of the oxidative pentose phosphate pathway (PPP) had a positive influence on recombinant production of cytosolic human superoxide dismutase (hSOD). In this study, different combinations of these genes belonging to the oxidative PPP were generated and analyzed. Thereby, a 3.8-fold increase of hSOD production was detected when glucose-6-phosphate dehydrogenase (ZWF1) and 6-gluconolactonase (SOL3) were simultaneously overexpressed, while the combinations of other genes from PPP had no positive effect on protein production. By measuring isotopologue patterns of 13C-labelled metabolites, we could detect an upshift in the flux ratio of PPP to glycolysis upon ZWF1 and SOL3 co-overexpression, as well as increased levels of 6-phosphogluconate. The substantial improvement of hSOD production by ZWF1 and SOL3 co-overexpression appeared to be connected to an increase in PPP flux. In conclusion, we show that overexpression of SOL3 together with ZWF1 enhanced both the PPP flux ratio and hSOD accumulation, providing evidence that in P. pastoris Sol3 limits the flux through PPP and recombinant protein production.Electronic supplementary materialThe online version of this article (doi:10.1007/s00253-016-7363-5) contains supplementary material, which is available to authorized users.

For the first time an analytical work flow based on accurate mass gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOFMS) with chemical ionization for analysis providing a comprehensive picture of (13)C distribution along the primary metabolism is elaborated. The method provides a powerful new toolbox for (13)C-based metabolic flux analysis, which is an emerging strategy in metabolic engineering. In this field, stable isotope tracer experiments based on, for example, (13)C are central for providing characteristic patterns of labeled metabolites, which in turn give insights into the regulation of metabolic pathway kinetics. The new method enables the analysis of isotopologue fractions of 42 free intracellular metabolites within biotechnological samples, while tandem mass isotopomer information is also accessible for a large number of analytes. Hence, the method outperforms previous approaches in terms of metabolite coverage, while also providing rich isotopomer information for a significant number of key metabolites. Moreover, the established work flow includes novel evaluation routines correcting for isotope interference of naturally distributed elements, which is crucial following derivatization of metabolites. Method validation in terms of trueness, precision, and limits of detection was performed, showing excellent analytical figures of merit with an overall maximum bias of 5.8%, very high precision for isotopologue and tandem mass isotopomer fractions representing >10% of total abundance, and absolute limits of detection in the femtomole range. The suitability of the developed method is demonstrated on a flux experiment of Pichia pastoris employing two different tracers, i.e., 1,6(13)C2-glucose and uniformly labeled (13)C-glucose.

The accurate quantification of the highly unstable intracellular cofactor nicotinamide adenine dinucleotide phosphate in its oxidized and reduced forms demands a thorough evaluation of the analytical workflow and dedicated methods reflecting their solution chemistry as well as the biological importance of their ratio. In this work, we present a workflow for the analysis of intracellular levels of oxidized and reduced nicotinamide adenine dinucleotide phosphate in the yeast Pichia pastoris, including hot aqueous extraction, chromatographic separation in reversed-phase conditions employing a 100% wettable stationary phase, and subsequent tandem mass spectrometric analysis. A thorough evaluation and optimization of the sample preparation procedure resulted in excellent biological repeatabilities (on average <10%, N = 3) without employing an internal standardization approach. As a consequence, the methodology proved to be appropriate for the relative assessment of intracellular levels of oxidized and reduced nicotinamide adenine dinucleotide phosphate in different P. pastoris strains. The ratio of reduced versus oxidized nicotinamide adenine dinucleotide phosphate was significantly higher in an engineered strain overexpressing glucose-6-phosphate dehydrogenase than in the corresponding wildtype strain. Interestingly, a difference was also observed in the nicotinamide adenine dinucleotide phosphate pool size, which was significantly higher in the wildtype than in the modified strain.

First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories.

No abstract