Metabolic flux profiling of Pichia pastoris grown on glycerol/methanol mixtures in chemostat cultures at low and high dilution rates

Comparative transcriptomic analysis-based identification of the regulation of foreign proteins with different stabilities expressed in Pichia pastoris

Introduction

The industrial yeast Pichia pastoris is widely used as a cell factory to produce proteins, chemicals and advanced biofuels. We have previously constructed P. pastoris strains that overexpress protein disulfide isomerase (PDI), which is a kind of molecular chaperone that can improve the expression of an exogenous protein when they are co-expressed. Chicken cystatin (cC) is a highly thermostable cysteine protease inhibitor and a homologous protein of human cystatin C (HCC). Wild-type cC and the two mutants, I66Q and ΔW (a truncated cC lacking the á-helix 2) represent proteins with different degrees of stability.

Methods

Wild-type cC, I66Q and ΔW were each overexpressed in P. pastoris without and with the coexpression of PDI and their extracellular levels were determined and compared. Transcriptomic profiling was performed to compare the changes in the main signaling pathways and cell components (other than endoplasmic reticulum quality control system represented by molecular chaperones) in P. pastoris in response to intracellular folding stress caused by the expression of exogenous proteins with different stabilities. Finally, hub genes hunting was also performed.

Results and discussion

The coexpression of PDI was able to increase the extracellular levels of both wild-type cC and the two mutants, indicating that overexpression of PDI could prevent the misfolding of unstable proteins or promote the degradation of the misfolded proteins to some extent. For P. pastoris cells that expressed the I66Q or ΔW mutant, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses of the common DEGs in these cells revealed a significant upregulation of the genes involved in protein processing, but a significant downregulation of the genes enriched in the Ribosome, TCA and Glycolysis/Gluconeogenesis pathways. Hub genes hunting indicated that the most downregulated ribosome protein, C4QXU7 in this case, might be an important target protein that could be manipulated to increase the expression of foreign proteins, especially proteins with a certain degree of instability.

Conclusion

These findings should shed new light on our understanding of the regulatory mechanism in yeast cells that responds to intracellular folding stress, providing valuable information for the development of a convenient platform that could improve the efficiency of heterologous protein expression in P. pastoris.

Role of Dissimilative Pathway of Komagataella phaffii (Pichia pastoris): Formaldehyde Toxicity and Energy Metabolism

Komagataella phaffii (aka Pichia pastoris) is a yeast able to grow in methanol as the sole carbon and energy source. This substrate is converted into formaldehyde, a toxic intermediary that can either be assimilated to biomass or dissimilated to CO₂ through the enzymes formaldehyde dehydrogenase (FLD) and formate dehydrogenase, also producing energy in the form of NADH. The dissimilative pathway has been described as an energy producing and a detoxifying route, but conclusive evidence has not been provided for this. In order to elucidate this theory, we generated mutants lacking the FLD activity (Δfld1) and used flux analysis to evaluate the metabolic impact of this disrupted pathway. Unexpectedly, we found that the specific growth rate of the Δfld1 strain was only slightly lower (92%) than the control. In contrast, the sensitivity to formaldehyde pulses (up to 8mM) was significantly higher in the Δfld1 mutant strain and was associated with a higher maintenance energy. In addition, the intracellular flux estimation revealed a high metabolic flexibility of K. phaffii in response to the disrupted pathway. Our results suggest that the role of the dissimilative pathway is mainly to protect the cells from the harmful effect of formaldehyde, as they were able to compensate for the energy provided from this pathway when disrupted.

Interferon-Based Biopharmaceuticals: Overview on the Production, Purification, and Formulation

The advent of biopharmaceuticals in modern medicine brought enormous benefits to the treatment of numerous human diseases and improved the well-being of many people worldwide. First introduced in the market in the early 1980s, the number of approved biopharmaceutical products has been steadily increasing, with therapeutic proteins, antibodies, and their derivatives accounting for most of the generated revenues. The success of pharmaceutical biotechnology is closely linked with remarkable developments in DNA recombinant technology, which has enabled the production of proteins with high specificity. Among promising biopharmaceuticals are interferons, first described by Isaacs and Lindenmann in 1957 and approved for clinical use in humans nearly thirty years later. Interferons are secreted autocrine and paracrine proteins, which by regulating several biochemical pathways have a spectrum of clinical effectiveness against viral infections, malignant diseases, and multiple sclerosis. Given their relevance and sustained market share, this review provides an overview on the evolution of interferon manufacture, comprising their production, purification, and formulation stages. Remarkable developments achieved in the last decades are herein discussed in three main sections: (i) an upstream stage, including genetically engineered genes, vectors, and hosts, and optimization of culture conditions (culture media, induction temperature, type and concentration of inducer, induction regimens, and scale); (ii) a downstream stage, focusing on single- and multiple-step chromatography, and emerging alternatives (e.g., aqueous two-phase systems); and (iii) formulation and delivery, providing an overview of improved bioactivities and extended half-lives and targeted delivery to the site of action. This review ends with an outlook and foreseeable prospects for underdeveloped aspects of biopharma research involving human interferons.

Recent advances in systems and synthetic biology approaches for developing novel cell-factories in non-conventional yeasts

Microbial bioproduction of chemicals, proteins, and primary metabolites from cheap carbon sources is currently an advancing area in industrial research. The model yeast, Saccharomyces cerevisiae, is a well-established biorefinery host that has been used extensively for commercial manufacturing of bioethanol from myriad carbon sources. However, its Crabtree-positive nature often limits the use of this organism for the biosynthesis of commercial molecules that do not belong in the fermentative pathway. To avoid extensive strain engineering of S. cerevisiae for the production of metabolites other than ethanol, non-conventional yeasts can be selected as hosts based on their natural capacity to produce desired commodity chemicals. Non-conventional yeasts like Kluyveromyces marxianus, K. lactis, Yarrowia lipolytica, Pichia pastoris, Scheffersomyces stipitis, Hansenula polymorpha, and Rhodotorula toruloides have been considered as potential industrial eukaryotic hosts owing to their desirable phenotypes such as thermotolerance, assimilation of a wide range of carbon sources, as well as ability to secrete high titers of protein and lipid. However, the advanced metabolic engineering efforts in these organisms are still lacking due to the limited availability of systems and synthetic biology methods like in silico models, well-characterised genetic parts, and optimized genome engineering tools. This review provides an insight into the recent advances and challenges of systems and synthetic biology as well as metabolic engineering endeavours towards the commercial usage of non-conventional yeasts. Particularly, the approaches in emerging non-conventional yeasts for the production of enzymes, therapeutic proteins, lipids, and metabolites for commercial applications are extensively discussed here. Various attempts to address current limitations in designing novel cell factories have been highlighted that include the advances in the fields of genome-scale metabolic model reconstruction, flux balance analysis, 'omics'-data integration into models, genome-editing toolkit development, and rewiring of cellular metabolisms for desired chemical production. Additionally, the understanding of metabolic networks using ¹³C-labelling experiments as well as the utilization of metabolomics in deciphering intracellular fluxes and reactions have also been discussed here. Application of cutting-edge nuclease-based genome editing platforms like CRISPR/Cas9, and its optimization towards efficient strain engineering in non-conventional yeasts have also been described. Additionally, the impact of the advances in promising non-conventional yeasts for efficient commercial molecule synthesis has been meticulously reviewed. In the future, a cohesive approach involving systems and synthetic biology will help in widening the horizon of the use of unexplored non-conventional yeast species towards industrial biotechnology.

Komagataella phaffii as Emerging Model Organism in Fundamental Research

Komagataella phaffii (Pichia pastoris) is one of the most extensively applied yeast species in pharmaceutical and biotechnological industries, and, therefore, also called the biotech yeast. However, thanks to more advanced strain engineering techniques, it recently started to gain attention as model organism in fundamental research. So far, the most studied model yeast is its distant cousin, Saccharomyces cerevisiae. While these data are of great importance, they limit our knowledge to one organism only. Since the divergence of the two species 250 million years ago, K. phaffii appears to have evolved less rapidly than S. cerevisiae, which is why it remains more characteristic of the common ancient yeast ancestors and shares more features with metazoan cells. This makes K. phaffii a valuable model organism for research on eukaryotic molecular cell biology, a potential we are only beginning to fully exploit. As methylotrophic yeast, K. phaffii has the intriguing property of being able to efficiently assimilate methanol as a sole source of carbon and energy. Therefore, major efforts have been made using K. phaffii as model organism to study methanol assimilation, peroxisome biogenesis and pexophagy. Other research topics covered in this review range from yeast genetics including mating and sporulation behavior to other cellular processes such as protein secretion, lipid biosynthesis and cell wall biogenesis. In this review article, we compare data obtained from K. phaffii with S. cerevisiae and other yeasts whenever relevant, elucidate major differences, and, most importantly, highlight the big potential of using K. phaffii in fundamental research.

Biocalorimetric monitoring of glycoengineered P. pastoris cultivation for the production of recombinant huIFNα2b: A quantitative study based on mixed feeding strategies

Real-time monitoring of glycoengineered Pichia pastoris by employing process analytical technology (PAT) tools is vital for gaining deeper insights into the therapeutic protein production process. The present study focuses on influence of mixed feed carbon substrates during the induction phases of glycoengineered P. pastoris cultivation, for recombinant human interferon α2b (huIFNα2b) production by employing calorimetric (biological heat rate, q _B ) and respirometric (oxygen uptake rate and carbon dioxide evolution rate) measurements. Mixed feed stream of carbon substrates (methanol + glycerol, methanol + sorbitol) at a predetermined "C-molar ratios" were added during the induction phases. Methanol- and sorbitol-based mixed feeding approach resulted in an improved huIFNα2b titer of 288 mg/L by channeling of methanol predominantly towards an optimal functioning of AOX expression system. A stand-off between biomass yield Y X S and biomass heat yield Y Q X coefficient, degree of reduction of methanol and its cosubstrate (glycerol and sorbitol) determines the fraction of carbon energy channeled toward biomass and protein production, under strict aerobic conditions. Calorespirometric monitoring and assessment of thermal yields enables a reliable prediction of process variables, leading to futuristic efficient PAT-based feed rate control.

Contextualized genome-scale model unveils high-order metabolic effects of the specific growth rate and oxygenation level in recombinant Pichia pastoris

Pichia pastoris is recognized as a biotechnological workhorse for recombinant protein expression. The metabolic performance of this microorganism depends on genetic makeup and culture conditions, amongst which the specific growth rate and oxygenation level are critical. Despite their importance, only their individual effects have been assessed so far, and thus their combined effects and metabolic consequences still remain to be elucidated. In this work, we present a comprehensive framework for revealing high-order (i.e., individual and combined) metabolic effects of the above parameters in glucose-limited continuous cultures of P. pastoris, using thaumatin production as a case study. Specifically, we employed a rational experimental design to calculate statistically significant metabolic effects from multiple chemostat data, which were later contextualized using a refined and highly predictive genome-scale metabolic model of this yeast under the simulated conditions. Our results revealed a negative effect of the oxygenation on the specific product formation rate (thaumatin), and a positive effect on the biomass yield. Notably, we identified a novel positive combined effect of both the specific growth rate and oxygenation level on the specific product formation rate. Finally, model predictions indicated an opposite relationship between the oxygenation level and the growth-associated maintenance energy (GAME) requirement, suggesting a linear GAME decrease of 0.56 mmol ATP/g_DCW per each 1% increase in oxygenation level, which translated into a 44% higher metabolic cost under low oxygenation compared to high oxygenation. Overall, this work provides a systematic framework for mapping high-order metabolic effects of different culture parameters on the performance of a microbial cell factory. Particularly in this case, it provided valuable insights about optimal operational conditions for protein production in P. pastoris.

High level extracellular production of recombinant human interferon alpha 2b in glycoengineered Pichia pastoris: culture medium optimization, high cell density cultivation and biological characterization

AIMS

The present study was aimed at design of experiments (DoE)- and artificial intelligence-based culture medium optimization for high level extracellular production of a novel recombinant human interferon alpha 2b (huIFNα2b) in glycoengineered Pichia pastoris and its characterization.

METHODS AND RESULTS

The artificial neural network-genetic algorithm model exhibited improved huIFNα2b production and better predictability compared to response surface methodology. The optimized medium exhibited a fivefold increase in huIFNα2b titre compared to the complex medium. A maximum titre of huIFNα2b (436 mg l^-1 ) was achieved using the optimized medium in the bioreactor. Real-time capacitance data from dielectric spectroscopy were utilized to model the growth kinetics with unstructured models. Biological characterization by antiproliferative assay proved that the purified recombinant huIFNα2b was biologically active, exhibiting growth inhibition on breast cancer cell line.

CONCLUSIONS

Culture medium optimization resulted in enhanced production of huIFNα2b in glycoengineered P. pastoris at both shake flask and bioreactor level. The purified huIFNα2b was found to be N-glycosylated and biologically active.

SIGNIFICANCE AND IMPACT OF THE STUDY

DoE-based medium optimization strategy significantly improved huIFNα2b production. The antiproliferative activity of huIFNα2b substantiates its potential scope for application in cancer therapy.

The growth of Pichia pastoris Mut+ on methanol-glycerol mixtures fits to interactive dual-limited kinetics: model development and application to optimised fed-batch operation for heterologous protein production

The methanol-glycerol co-feeding during the induction stage for heterologous protein production in Pichia pastoris has shown significant productive applications. Available model analysis applied to this dual-limited condition is scarce and normally does not consider the interaction effects between the substrates. In this work, a dual-limited growth model of P. pastoris considering an interactive kinetic effect was applied to an optimised fed-batch process production of heterologous Rhizopus oryzae lipase (ROL). In the proposed model, the growth kinetics on glycerol is fully expressed, whereas methanol kinetics is modulated by the co-metabolisation of glycerol, resulting in an enhancing effect of glycerol-specific growth rate. The modelling approach of fed-batch cultures also included the methanol volatilisation caused by the aeration that was found to be a not-negligible phenomenon. The model predicts the ability of P. pastoris to keep control of the methanol concentration in the broth during ROL-optimised production process in fed batch and fits satisfactorily the specific cell growth rate and ROL production. Implications of interaction effect are discussed applying the general procedure of modelling approach.

Methyl-selective isotope labeling using α-ketoisovalerate for the yeast Pichia pastoris recombinant protein expression system

Methyl-detected NMR spectroscopy is a useful tool for investigating the structures and interactions of large macromolecules such as membrane proteins. The procedures for preparation of methyl-specific isotopically-labeled proteins were established for the Escherichia coli (E. coli) expression system, but typically it is not feasible to express eukaryotic proteins using E. coli. The Pichia pastoris (P. pastoris) expression system is the most common yeast expression system, and is known to be superior to the E. coli system for the expression of mammalian proteins, including secretory and membrane proteins. However, this system has not yet been optimized for methyl-specific isotope labeling, especially for Val/Leu-methyl specific isotope incorporation. To overcome this difficulty, we explored various culture conditions for the yeast cells to efficiently uptake Val/Leu precursors. Among the searched conditions, we found that the cultivation pH has a critical effect on Val/Leu precursor uptake. At an acidic cultivation pH, the uptake of the Val/Leu precursor was increased, and methyl groups of Val and Leu in the synthesized recombinant protein yielded intense ¹H-¹³C correlation signals. Based on these results, we present optimized protocols for the Val/Leu-methyl-selective ¹³C incorporation by the P. pastoris expression system.

Metabolic engineering of Pichia pastoris

Besides its use for efficient production of recombinant proteins the methylotrophic yeast Pichia pastoris (syn. Komagataella spp.) has been increasingly employed as a platform to produce metabolites of varying origin. We summarize here the impressive methodological developments of the last years to model and analyze the metabolism of P. pastoris, and to engineer its genome and metabolic pathways. Efficient methods to insert, modify or delete genes via homologous recombination and CRISPR/Cas9, supported by modular cloning techniques, have been reported. An outstanding early example of metabolic engineering in P. pastoris was the humanization of protein glycosylation. More recently the cell metabolism was engineered also to enhance the productivity of heterologous proteins. The last few years have seen an increased number of metabolic pathway design and engineering in P. pastoris, mainly towards the production of complex (secondary) metabolites. In this review, we discuss the potential role of P. pastoris as a platform for metabolic engineering, its strengths, and major requirements for future developments of chassis strains based on synthetic biology principles.

Fine-tuning the P. pastoris iMT1026 genome-scale metabolic model for improved prediction of growth on methanol or glycerol as sole carbon sources

The methylotrophic yeast Pichia pastoris (Komagataella spp.) is widely used as cell factory for recombinant protein production. In the past recent years, important breakthroughs in the systems-level quantitative analysis of its physiology have been achieved. This wealth of information has allowed the development of genome-scale metabolic models, which make new approaches possible for host cell and bioprocess engineering. Nevertheless, the predictive accuracy of the previous consensus model required to be upgraded and validated with new experimental data sets for P. pastoris growing on glycerol or methanol as sole carbon sources, two of the most relevant substrates for this cell factory. In this study, we have characterized P. pastoris growing in chemostat cultures using glycerol or methanol as sole carbon sources over a wide range of growth rates, thereby providing physiological data on the effect of growth rate and culture conditions on biomass macromolecular and elemental composition. In addition, these data sets were used to improve the performance of the P. pastoris consensus genomic-scale metabolic model iMT1026. Thereupon, new experimentally determined bounds, including the representation of biomass composition for these growth conditions, have been incorporated. As a result, here, we present version 3 (v3.0) of the consensus P. pastoris genome-scale metabolic model as an update of the iMT1026 model. The v3.0 model was validated for growth on glycerol and methanol as sole carbon sources, demonstrating improved prediction capabilities over an extended substrate range including two biotechnologically relevant carbon sources.

13 C metabolic flux profiling of Pichia pastoris grown in aerobic batch cultures on glucose revealed high relative anabolic use of TCA cycle and limited incorporation of provided precursors of branched-chain amino acids

Carbon metabolism of Crabtree-negative yeast Pichia pastoris was profiled using ¹³ C nuclear magnetic resonance (NMR) to delineate regulation during exponential growth and to study the import of two precursors for branched-chain amino acid biosynthesis, α-ketoisovalerate and α-ketobutyrate. Cells were grown in aerobic batch cultures containing (a) only glucose, (b) glucose along with the precursors, or (c) glucose and Val. The study provided the following new insights. First, ¹³ C flux ratio analyses of central metabolism reveal an unexpectedly high anaplerotic supply of the tricarboxylic acid cycle for a Crabtree-negative yeast, and show that a substantial fraction of glucose catabolism proceeds through the pentose phosphate pathway. A comparison with previous flux ratio analyses for batch cultures of Crabtree-negative Pichia stipitis and Crabtree-positive Saccharomyces cerevisiae indicate that the overall regulation of central carbon metabolism in P. pastoris is intermediate in between P. stipitis and S. cerevisiae. Second, excess α-ketoisovalerate in the medium is not transported into the cytoplasm indicating that P. pastoris lacks a suitable transporter. In contrast, excess Val is efficiently taken up and largely fulfills demands for both Val and Leu for protein synthesis. Third, excess α-ketobutyrate is transported into the mitochondria for Ile biosynthesis. However, the import does not efficiently inhibit the synthesis of α-ketobutyrate from pyruvate indicating that P. pastoris has not been optimized evolutionarily to take full advantage of this carbon source. These findings have direct implications for preparing uniformly ² H,¹³ C,¹⁵ N-labeled proteins containing protonated Ile, Val, and Leu methyl groups in P. pastoris for NMR-based structural biology.

ENZYMES

Acetohydroxy acid isomeroreductase (EC 1.1.1.86), branched-chain amino acid aminotransferase (BCAT, EC 2.6.1.42), fumarase (EC 4.2.1.2), malic enzyme (EC 1.1.1.39/1.1.1.40), phosphoenolpyruvate carboxykinase (EC 4.1.1.49), pyruvate carboxylase (EC 6.4.1.1), pyruvate kinase (EC 2.7.1.40), l-serine hydroxymethyltransferase (EC 2.1.2.1), threonine aldolase (EC 4.1.2.5), threonine dehydratase (EC 4.3.1.19); transketolase (EC 2.2.1.1), transaldolase (EC 2.2.1.2).

Increased dosage of AOX1 promoter-regulated expression cassettes leads to transcription attenuation of the methanol metabolism in Pichia pastoris

The methanol-regulated alcohol oxidase promoter (P_AOX1) of Pichia pastoris is one of the strongest promoters for heterologous gene expression in this methylotrophic yeast. Although increasing gene dosage is one of the most common strategies to increase recombinant protein productivities, the increase of gene dosage of Rhizopus oryzae lipase (ROL) in P. pastoris has been previously shown to reduce cell growth, lipase production and substrate consumption in high-copy strains. To better assess that physiological response, transcriptomics analysis was performed of a subset of strains with 1 to 15 ROL copies. The macroscopic physiological parameters confirm that growth yield and carbon uptake rate are gene dosage dependent, and were supported by the transcriptomic data, showing the impact of increased dosage of AOX1 promoter-regulated expression cassettes on P. pastoris physiology under steady methanolic growth conditions. Remarkably, increased number of cassettes led to transcription attenuation of the methanol metabolism and peroxisome biogenesis in P. pastoris, concomitant with reduced secretion levels of the heterologous product. Moreover, our data also point to a block in ROL mRNA translation in the higher ROL-copies constructs, while the low productivities of multi-copy strains under steady growth conditions do not appear to be directly related to UPR and ERAD induction.

A comparative study of glycerol and sorbitol as co-substrates in methanol-induced cultures of Pichia pastoris: temperature effect and scale-up simulation

The production of recombinant proteins by Pichia pastoris under AOX1 promoter is usually performed using methanol together with either glycerol or sorbitol as co-substrate. Although both co-substrates have been widely used, comparative studies are scarce. In addition, these comparisons have been performed at different specific growth rate (µ) that it is well known that has an important effect on productivity. Thus, the effect of using these co-substrates on the production of Rhyzopus oryzae lipase (ROL) by P. pastoris was compared in continuous cultures growing at the same µ at either 22 or 30 °C. Results show that using glycerol as co-substrate led to higher volumetric productivities, and lower specific and volumetric methanol consumption rates. Scale-up simulation with 10–10,000 L bioreactor sizes indicated that glycerol produced the highest volumetric productivity of ROL with lower aeration requirements. Therefore, glycerol rises as a better option than sorbitol in ROL production.

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis

BACKGROUND

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios.

RESULTS

Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples.

CONCLUSIONS

The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

Sparse (13)C labelling for solid-state NMR studies of P. pastoris expressed eukaryotic seven-transmembrane proteins

We demonstrate a novel sparse (13)C labelling approach for methylotrophic yeast P. pastoris expression system, towards solid-state NMR studies of eukaryotic membrane proteins. The labelling scheme was achieved by co-utilizing natural abundance methanol and specifically (13)C labelled glycerol as carbon sources in the expression medium. This strategy improves the spectral resolution by 1.5 fold, displays site-specific labelling patterns, and has advantages for collecting long-range distance restraints for structure determination of large eukaryotic membrane proteins by solid-state NMR.

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

Motivation

Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented.

Results

In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models.

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.

Effect of dilution rate and methanol-glycerol mixed feeding on heterologous Rhizopus oryzae lipase production with Pichia pastoris Mut(+) phenotype in continuous culture

The induction using substrate mixtures is an operational strategy for improving the productivity of heterologous protein production with Pichia pastoris. Glycerol as a cosubstrate allows for growth at a higher specific growth rate, but also has been reported to be repressor of the expression from the AOX1 promoter. Thus, further insights about the effects of glycerol are required for designing the induction stage with mixed substrates. The production of Rhizopus oryzae lipase (ROL) was used as a model system to investigate the application of methanol-glycerol feeding mixtures in fast metabolizing methanol phenotype. Cultures were performed in a simple chemostat system and the response surface methodology was used for the evaluation of both dilution rate and methanol-glycerol feeding composition as experimental factors. Our results indicate that productivity and yield of ROL are strongly affected by dilution rate, with no interaction effect between the involved factors. Productivity showed the highest value around 0.04-0.06 h(-1) , while ROL yield decreased along the whole dilution rate range evaluated (0.03-0.1 h(-1) ). Compared to production level achieved with methanol-only feeding, the highest specific productivity was similar in mixed feeding (0.9 UA g-biomass(-1) h(-1) ), but volumetric productivity was 70% higher. Kinetic analysis showed that these results are explained by the effects of dilution rate on specific methanol uptake rate, instead of a repressor effect caused by glycerol feeding. It is concluded that despite the effect of dilution rate on ROL yield, mixed feeding strategy is a proper process option to be applied to P. pastoris Mut(+) phenotype for heterologous protein production.

Validation of an FBA model for Pichia pastoris in chemostat cultures

Background

Constraint-based metabolic models and flux balance analysis (FBA) have been extensively used in the last years to investigate the behavior of cells and also as basis for different industrial applications. In this context, this work provides a validation of a small-sized FBA model of the yeast Pichia pastoris. Our main objective is testing how accurate is the hypothesis of maximum growth to predict the behavior of P. pastoris in a range of experimental environments.

Results

A constraint-based model of P. pastoris was previously validated using metabolic flux analysis (MFA). In this paper we have verified the model ability to predict the cells behavior in different conditions without introducing measurements, experimental parameters, or any additional constraint, just by assuming that cells will make the best use of the available resources to maximize its growth. In particular, we have tested FBA model ability to: (a) predict growth yields over single substrates (glucose, glycerol, and methanol); (b) predict growth rate, substrate uptakes, respiration rates, and by-product formation in scenarios where different substrates are available (glucose, glycerol, methanol, or mixes of methanol and glycerol); (c) predict the different behaviors of P. pastoris cultures in aerobic and hypoxic conditions for each single substrate. In every case, experimental data from literature are used as validation.

Conclusions

We conclude that our predictions based on growth maximisation are reasonably accurate, but still far from perfect. The deviations are significant in scenarios where P. pastoris grows on methanol, suggesting that the hypothesis of maximum growth could be not dominating in these situations. However, predictions are much better when glycerol or glucose are used as substrates. In these scenarios, even if our FBA model is small and imposes a strong assumption regarding how cells will regulate their metabolic fluxes, it provides reasonably good predictions in terms of growth, substrate preference, product formation, and respiration rates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-014-0142-y) contains supplementary material, which is available to authorized users.

Biomarkers to evaluate the effects of temperature and methanol on recombinant Pichia pastoris

Pichia pastoris is methylotrophic yeast used as an efficient expression system for heterologous protein production. In order to evaluate the effects of temperature (10 and 30 °C) and methanol (1 and 3% (v/v)) on genetically-modified Pichia pastoris, different biomarkers were evaluated: Heat stress (HSF-1 and Hsp70), oxidative stress (OGG1 and TBARS) and antioxidant (GLR). Three yeast cultures were performed: 3X = 3% methanol-10 °C, 4X = 3% methanol-30 °C, and 5X = 1% methanol-10°C. The expression level of HIF-1α, HSF-1, HSP-70 and HSP-90 biomarkers were measured by Western blot and in situ detection was performed by immunocytochemistry. Ours results show that at 3% methanol −30 °C there is an increase of mitochondrial OGG1 (mtOGG1), Glutathione Reductase (GLR) and TBARS. In addition, there was a cytosolic expression of HSF-1 and HSP-70, which indicates a deprotection against nucleolar fragmentation (apoptosis). On the other hand, at 3% methanol −10 °C and 1% and at methanol −10 °C conditions there was nuclear expression of OGG1, lower levels of TBARS and lower expression of GLR, cytosolic expression of HSF-1 and nuclear expression HSP-70. In conclusion, our results suggest that 3% methanol-30 °C is a condition that induces a strong oxidative stress and risk factors of apoptosis in modified-genetically P. pastoris.

HSF-1, HIF-1 and HSP90 expression on recombinant Pichia pastoris under fed-batch fermentation

Pichia pastoris is a methylotrophic yeast used as an efficient expression system for heterologous protein production as compared to other expression systems. Considering that every cell must respond to environmental changes to survive and differentiate, determination of endogenous protein related to heat stress responses and hypoxia, it would necessary to establish the temperature and methanol concentration conditions for optimal growth. The aim of this study is characterize the culture conditions through the putative biomarkers in different conditions of temperature and methanol concentration. Three yeast cultures were performed: 3X = 3% methanol −10 °C, 4X = 3% methanol −30 °C, and 5X = 1% methanol −10 °C. The expression level of HIF-1α, HSF-1, HSP-70 and HSP-90 biomarkers were measured by Western blot and in situ detection was performed by immunocytochemistry. The western blot results of HIF-1α and HSP-90 did not indicate statistically significant in the culture conditions studied. Respect to biomarkers location, HIF-1α and HSP-90 presented differences between cultures. In conclusion, the results suggest the cultures in a hypoxic condition produce a high density and yeast cells smaller. Beside the high density would not necessary related with a high production of recombinant proteins in modified-genetically P. pastoris.

Impacts of high β-galactosidase expression on central metabolism of recombinant Pichia pastoris GS115 using glucose as sole carbon source via (13)C metabolic flux analysis

The yeast Pichia pastoris GS115 is a widely used microbial cell factory for the production of heterologous protein. In order to reveal the impacts of high heterologous protein expression on the central metabolism of Pichia pastoris GS115 using glucose as sole carbon source, we engineered a high β-galactosidase expression strain P. pastoris G1HL and a low expression control strain P. pastoris GHL through controlling the initiation strength of constitutive promoter pGAP. The carbon flux distributions in these two strains were quantified via (13)C metabolic flux analysis. Compared to the control strain, G1HL showed a lower growth rate, a higher flux through glycolysis pathway, a higher flux through pentose phosphate pathway, and a lower flux through by-products secretion pathway. The metabolic flux redistribution in G1HL was thought to compensate the increased redox cofactors and energy demands caused by the high protein expression. Although the fluxes through Krebs cycle in two engineered strains were almost the same, they were significantly lower than those in wild strain. The enhanced expression of β-galactosidase by glutamate supplementation demonstrated the potential of P. pastoris GS115 to catabolize more carbon through the Krebs cycle for even higher protein expression. In conclusion, our work indicates that P. pastoris GS115 can readjusts the central metabolism for higher heterologous protein expression and provides strategies for strain development or process optimization for enhancing production of heterologous protein.

Labelling analysis for ¹³C MFA using NMR spectroscopy

NMR spectroscopy is an efficient method for analyzing (13)C labelling of cellular metabolites. The strength of it is especially the ability to provide direct quantitative positional information on the (13)C labelling status of carbon atoms in metabolites. NMR spectroscopic methods allow also for detection of contiguously (13)C-labelled fragments in the carbon backbones of the metabolites. Furthermore, the recent developments of NMR spectroscopy hardware have substantially improved the sensitivity of the methods. In this chapter we describe a method for analyzing the (13)C labelling of the biomass amino acids for metabolic flux analysis, sample preparation for NMR spectroscopy, acquiring and processing the NMR spectra, and extracting the (13)C labelling information from the NMR data. Different NMR methods are applied depending on the (13)C labelling strategy chosen. These strategies include uniform (13)C labelling, positional (13)C labelling, or a combination of both. Not only the preparation of sample for analysis of (13)C labelling in proteinogenic amino acids in biomass is described, but also the necessary modifications to the method when analysis of (13)C labelling in free metabolic intermediates is of interest. Finally the strategies for using the different NMR-detected (13)C labelling data in (13)C MFA are discussed.

¹³C-based metabolic flux analysis of recombinant Pichia pastoris

Overexpression of a foreign protein may negatively affect several cell growth parameters, as well as cause cellular stress. Central (or core) metabolism plays a crucial role since it supplies energy, reduction equivalents, and precursor molecules for the recombinant product, cell's maintenance, and growth needs. However, the number of quantitative physiology studies of the impact of recombinant protein production on the central metabolic pathways of yeast cell factories has been traditionally rather limited, thereby hampering the application of rational strain engineering strategies targeting central metabolism.The development and application of quantitative physiology and modelling tools and methodologies is allowing for a systems-level understanding of the effect of bioprocess parameters such as growth rate, temperature, oxygen availability, and substrate(s) choice on metabolism, and its subsequent interactions with recombinant protein synthesis, folding, and secretion.Here, we review the recent developments and applications of (13)C-based metabolic flux analysis ((13)C-MFA) of Pichia pastoris and the gained understanding of the metabolic behavior of this yeast in recombinant protein production bioprocesses. We also discuss the potential of multilevel studies integrating (13)C-MFA with other omics analyses, as well as future perspectives on the metabolic modelling approaches to study and design metabolic engineering strategies for improved protein production.

¹³C-based metabolic flux analysis in yeast: the Pichia pastoris case

Metabolic flux analysis based on tracing patterns of stable isotopes, particularly (13)C, comprises a set of methodologies to experimentally quantify intracellular biochemical reaction rates, i.e., to measure carbon flux distributions through a metabolic network. This allows quantifying the response of a metabolic network to an environmental or genetic perturbation (i.e., the metabolic phenotype). Here, we describe a protocol based on growing yeast on a (13)C-labelled substrate and subsequent NMR detection of (13)C-patterns in proteinogenic amino acids. To calculate metabolic fluxes, we describe two complementary mathematical approaches using available software; namely, an approach based on the estimation of local ratios in network nodes, and a method based on a global iterative fitting approach. Furthermore, we consider specificities of these protocols for their application to the yeast Pichia pastoris growing on multicarbon substrates other than glucose (glycerol), as well as the case when methanol is used as co-substrate in combination with glucose or glycerol.

Pathway analysis of Pichia pastoris to elucidate methanol metabolism and its regulation for production of recombinant proteins

This research rationally analyzes metabolic pathways of Pichia pastoris to study the metabolic flux responses of this yeast under methanol metabolism. A metabolic model of P. pastoris was constructed and analyzed by elementary mode analysis (EMA). EMA was used to comprehensively identify the cell's metabolic flux profiles and its underlying regulation mechanisms for the production of recombinant proteins from methanol. Change in phenotypes and flux profiles during methanol adaptation with varying feed mixture of glycerol and methanol was examined. EMA identified increasing and decreasing fluxes during the glycerol-methanol metabolic shift, which well agreed with experimental observations supporting the validity of the metabolic network model. Analysis of all the identified pathways also led to the determination of the metabolic capacities as well as the optimum metabolic pathways for recombinant protein synthesis during methanol induction. The network sensitivity analysis revealed that the production of proteins can be improved by manipulating the flux ratios at the pyruvate branch point. In addition, EMA suggested that protein synthesis is optimum under hypoxic culture conditions. The metabolic modeling and analysis presented in this study could potentially form a valuable knowledge base for future research on rational design and optimization of P. pastoris by determining target genes, pathways, and culture conditions for enhanced recombinant protein synthesis. The metabolic pathway analysis is also of considerable value for production of therapeutic proteins by P. pastoris in biopharmaceutical applications.

Perdeuteration and methyl-selective (1)H, (13)C-labeling by using a Kluyveromyces lactis expression system

The production of stable isotope-labeled proteins is critical in structural analyses of large molecular weight proteins using NMR. Although prokaryotic expression systems using Escherichia coli have been widely used for this purpose, yeast strains have also been useful for the expression of functional eukaryotic proteins. Recently, we reported a cost-effective stable isotope-labeled protein expression using the hemiascomycete yeast Kluyveromyces lactis (K. lactis), which allow us to express exogenous proteins at costs comparable to prokaryotic expression systems. Here, we report the successful production of highly deuterated (>90 %) protein in the K. lactis system. We also examined the methyl-selective (1)H, (13)C-labeling of Ile, Leu, and Val residues using commonly used amino acid precursors. The efficiency of (1)H-(13)C-incorporation varied significantly based on the amino acid. Although a high level of (1)H-(13)C-incorporation was observed for the Ile δ1 position, (1)H, (13)C-labeling rates of Val and Leu methyl groups were limited due to the mitochondrial localization of enzymes involved in amino acid biosynthesis and the lack of transporters for α-ketoisovalerate in the mitochondrial membrane. In line with this notion, the co-expression with branched-chain-amino-acid aminotransferase in the cytosol significantly improved the incorporation rates of amino acid precursors. Although it would be less cost-effective, addition of (13)C-labeled valine can circumvent problems associated with precursors and achieve high level (1)H, (13)C-labeling of Val and Leu. Taken together, the K. lactis system would be a good alternative for expressing large eukaryotic proteins that need deuteration and/or the methyl-selective (1)H, (13)C-labeling for the sensitive detection of NMR resonances.

Towards better understanding of an industrial cell factory: investigating the feasibility of real-time metabolic flux analysis in Pichia pastoris

Background

Novel analytical tools, which shorten the long and costly development cycles of biopharmaceuticals are essential. Metabolic flux analysis (MFA) shows great promise in improving our understanding of the metabolism of cell factories in bioreactors, but currently only provides information post-process using conventional off-line methods. MFA combined with real time multianalyte process monitoring techniques provides a valuable platform technology allowing real time insights into metabolic responses of cell factories in bioreactors. This could have a major impact in the bioprocessing industry, ultimately improving product consistency, productivity and shortening development cycles.

Results

This is the first investigation using Near Infrared Spectroscopy (NIRS) in situ combined with metabolic flux modelling which is both a significant challenge and considerable extension of these techniques. We investigated the feasibility of our approach using the industrial workhorse Pichia pastoris in a simplified model system. A parental P. pastoris strain (i.e. which does not synthesize recombinant protein) was used to allow definition of distinct metabolic states focusing solely upon the prediction of intracellular fluxes in central carbon metabolism. Extracellular fluxes were determined using off-line conventional reference methods and on-line NIR predictions (calculated by multivariate analysis using the partial least squares algorithm, PLS). The results showed that the PLS-NIRS models for biomass and glycerol were accurate: correlation coefficients, R², above 0.90 and the root mean square error of prediction, RMSEP, of 1.17 and 2.90 g/L, respectively. The analytical quality of the NIR models was demonstrated by direct comparison with the standard error of the laboratory (SEL), which showed that performance of the NIR models was suitable for quantifying biomass and glycerol for calculating extracellular metabolite rates and used as independent inputs for the MFA (RMSEP lower than 1.5 × SEL). Furthermore, the results for the MFA from both datasets passed consistency tests performed for each steady state, showing that the precision of on-line NIRS is equivalent to that obtained by the off-line measurements.

Conclusions

The findings of this study show for the first time the potential of NIRS as an input generating for MFA models, contributing to the optimization of cell factory metabolism in real-time.

Glucose-methanol co-utilization in Pichia pastoris studied by metabolomics and instationary ¹³C flux analysis

Background

Several studies have shown that the utilization of mixed carbon feeds instead of methanol as sole carbon source is beneficial for protein production with the methylotrophic yeast Pichia pastoris. In particular, growth under mixed feed conditions appears to alleviate the metabolic burden related to stress responses triggered by protein overproduction and secretion. Yet, detailed analysis of the metabolome and fluxome under mixed carbon source metabolizing conditions are missing. To obtain a detailed flux distribution of central carbon metabolism, including the pentose phosphate pathway under methanol-glucose conditions, we have applied metabolomics and instationary ¹³C flux analysis in chemostat cultivations.

Results

Instationary ¹³C-based metabolic flux analysis using GC-MS and LC-MS measurements in time allowed for an accurate mapping of metabolic fluxes of glycolysis, pentose phosphate and methanol assimilation pathways. Compared to previous results from NMR-derived stationary state labelling data (proteinogenic amino acids, METAFoR) more fluxes could be determined with higher accuracy. Furthermore, using a thermodynamic metabolic network analysis the metabolite measurements and metabolic flux directions were validated. Notably, the concentration of several metabolites of the upper glycolysis and pentose phosphate pathway increased under glucose-methanol feeding compared to the reference glucose conditions, indicating a shift in the thermodynamic driving forces. Conversely, the extracellular concentrations of all measured metabolites were lower compared with the corresponding exometabolome of glucose-grown P. pastoris cells.

The instationary ¹³C flux analysis resulted in fluxes comparable to previously obtained from NMR datasets of proteinogenic amino acids, but allowed several additional insights. Specifically, i) in vivo metabolic flux estimations were expanded to a larger metabolic network e.g. by including trehalose recycling, which accounted for about 1.5% of the glucose uptake rate; ii) the reversibility of glycolytic/gluconeogenesis, TCA cycle and pentose phosphate pathways reactions was estimated, revealing a significant gluconeogenic flux from the dihydroxyacetone phosphate/glyceraldehydes phosphate pool to glucose-6P. The origin of this finding could be carbon recycling from the methanol assimilatory pathway to the pentose phosphate pool. Additionally, high exchange fluxes of oxaloacetate with aspartate as well as malate indicated amino acid pool buffering and the activity of the malate/Asp shuttle; iii) the ratio of methanol oxidation vs utilization appeared to be lower (54 vs 79% assimilated methanol directly oxidized to CO₂).

Conclusions

In summary, the application of instationary ¹³C-based metabolic flux analysis to P. pastoris provides an experimental framework with improved capabilities to explore the regulation of the carbon and energy metabolism of this yeast, particularly for the case of methanol and multicarbon source metabolism.

Metabolic reconstruction and flux analysis of industrial Pichia yeasts

Pichia yeasts have been recognized as important microbial cell factories in the biotechnological industry. Notably, the Pichia pastoris and Pichia stipitis species have attracted much research interest due to their unique cellular physiology and metabolic capability: P. pastoris has the ability to utilize methanol for cell growth and recombinant protein production, while P. stipitis is capable of assimilating xylose to produce ethanol under oxygen-limited conditions. To harness these characteristics for biotechnological applications, it is highly required to characterize their metabolic behavior. Recently, following the genome sequencing of these two Pichia species, genome-scale metabolic networks have been reconstructed to model the yeasts' metabolism from a systems perspective. To date, there are three genome-scale models available for each of P. pastoris and P. stipitis. In this mini-review, we provide an overview of the models, discuss certain limitations of previous studies, and propose potential future works that can be conducted to better understand and engineer Pichia yeasts for industrial applications.

Batch and fed-batch growth of Pichia pastoris under increased air pressure

Pichia pastoris CBS 2612 behavior under air pressures of 1, 3 and 5 bar in culture media of glycerol (pure and crude) and methanol was studied. Generally, the increase in oxygen transfer rate due to the increase of total pressure improved cellular growth for all carbon sources and for batch and fed-batch processes with different feeding rate strategies. In batch cultures, 1.4-, 1.2-, and 1.5-fold improvement in biomass production was obtained with the increase of air pressure up to 5 bar, using methanol, pure glycerol, and crude glycerol, respectively. The increase of air pressure to 5 bar using exponential feeding rate led to 1.4-fold improvement in biomass yield per glycerol mass consumed, for crude and pure glycerol. The current low cost of crude glycerol from the biodiesel production together with the present results shows the possibility of improving cell mass production of P. pastoris using increased air pressure.

Metabolic flux ratio analysis and multi-objective optimization revealed a globally conserved and coordinated metabolic response of E. coli to paraquat-induced oxidative stress

The ability of a microorganism to adapt to changes in the environment, such as in nutrient or oxygen availability, is essential for its competitive fitness and survival. The cellular objective and the strategy of the metabolic response to an extreme environment are therefore of tremendous interest and, thus, have been increasingly explored. However, the cellular objective of the complex regulatory structure of the metabolic changes has not yet been fully elucidated and more details regarding the quantitative behaviour of the metabolic flux redistribution are required to understand the systems-wide biological significance of this response. In this study, the intracellular metabolic flux ratios involved in the central carbon metabolism were determined by fractional (13)C-labeling and metabolic flux ratio analysis (MetaFoR) of the wild-type E. coli strain JM101 at an oxidative environment in a chemostat. We observed a significant increase in the flux through phosphoenolpyruvate carboxykinase (PEPCK), phosphoenolpyruvate carboxylase (PEPC), malic enzyme (MEZ) and serine hydroxymethyltransferase (SHMT). We applied an ε-constraint based multi-objective optimization to investigate the trade-off relationships between the biomass yield and the generation of reductive power using the in silico iJR904 genome-scale model of E. coli K-12. The theoretical metabolic redistribution supports that the trans-hydrogenase pathway should not play a direct role in the defence mounted by E. coli against oxidative stress. The agreement between the measured ratio and the theoretical redistribution established the significance of NADPH synthesis as the goal of the metabolic reprogramming that occurs in response to oxidative stress. Our work presents a framework that combines metabolic flux ratio analysis and multi-objective optimization to investigate the metabolic trade-offs that occur under varied environmental conditions. Our results led to the proposal that the metabolic response of E. coli to paraquat-induced oxidative stress is globally conserved and coordinated.

Quantitative metabolomics analysis of amino acid metabolism in recombinant Pichia pastoris under different oxygen availability conditions

Background

Environmental and intrinsic stress factors can result in the global alteration of yeast physiology, as evidenced by several transcriptional studies. Hypoxia has been shown to have a beneficial effect on the expression of recombinant proteins in Pichia pastoris growing on glucose. Furthermore, transcriptional profiling analyses revealed that oxygen availability was strongly affecting ergosterol biosynthesis, central carbon metabolism and stress responses, in particular the unfolded protein response. To contribute to the better understanding of the effect and interplay of oxygen availability and foreign protein secretion on central metabolism, a first quantitative metabolomic analysis of free amino acids pools in a recombinant P. pastoris strain growing under different oxygen availability conditions has been performed.

Results

The values obtained indicate significant variations in the intracellular amino acid pools due to different oxygen availability conditions, showing an overall increase of their size under oxygen limitation. Notably, even while foreign protein productivities were relatively low (about 40–80 μg Fab/g_DCW·h), recombinant protein production was found to have a limited but significant impact on the intracellular amino acid pools, which were generally decreased in the producing strain compared with the reference strain. However, observed changes in individual amino acids pools were not correlated with their corresponding relative abundance in the recombinant protein sequence, but to the overall cell protein amino acid compositional variations.

Conclusions

Overall, the results obtained, combined with previous transcriptomic and proteomic analyses provide a systematic metabolic fingerprint of the oxygen availability impact on recombinant protein production in P. pastoris.

A dynamic fed batch strategy for a Pichia pastoris mixed feed system to increase process understanding

Mixed substrate feeding strategies are frequently investigated to enhance the productivity of recombinant Pichia pastoris processes. For this purpose, numerous fed batch experiments or time-consuming continuous cultivations are required to optimize control parameters such as the substrate mixing ratio and the applied methanol concentration. In this study, we decoupled the feeding of methanol and glycerol in a mixed substrate fed batch environment to gain process understanding for a recombinant P. pastoris Muts strain producing the model enzyme horseradish peroxidase. Specific substrate uptake rates (qs) were controlled separately, and a stepwise increased qGly-control scheme was applied to investigate the effect of various substrate fluxes on the culture. The qs-controlled strategy allowed a parallel characterization of the metabolism and the recombinant protein expression in a fed batch environment. A critical-specific glycerol uptake rate was determined, where a decline of the specific productivity occurred, and a time-dependent acceleration of protein expression was characterized with the dynamic fed batch approach. Based on the observations on recombinant protein expression, propositions for an optimal feeding design to target maximal productivities were stated. Thus, the dynamic fed batch strategy was found to be a valuable tool for both process understanding and optimization of product formation for P. pastoris in a mixed substrate environment.

Metabolic flux profiling of recombinant protein secreting Pichia pastoris growing on glucose:methanol mixtures

Background

The methylotrophic yeast Pichia pastoris has emerged as one of the most promising yeast hosts for the production of heterologous proteins. Mixed feeds of methanol and a multicarbon source instead of methanol as sole carbon source have been shown to improve product productivities and alleviate metabolic burden derived from protein production. Nevertheless, systematic quantitative studies on the relationships between the central metabolism and recombinant protein production in P. pastoris are still rather limited, particularly when growing this yeast on mixed carbon sources, thus hampering future metabolic network engineering strategies for improved protein production.

Results

The metabolic flux distribution in the central metabolism of P. pastoris growing on a mixed feed of glucose and methanol was analyzed by Metabolic Flux Analysis (MFA) using ¹³C-NMR-derived constraints. For this purpose, we defined new flux ratios for methanol assimilation pathways in P. pastoris cells growing on glucose:methanol mixtures. By using this experimental approach, the metabolic burden caused by the overexpression and secretion of a Rhizopus oryzae lipase (Rol) in P. pastoris was further analyzed. This protein has been previously shown to trigger the unfolded protein response in P. pastoris. A series of ¹³C-tracer experiments were performed on aerobic chemostat cultivations with a control and two different Rol producing strains growing at a dilution rate of 0.09 h⁻¹ using a glucose:methanol 80:20 (w/w) mix as carbon source.

The MFA performed in this study reveals a significant redistristribution of carbon fluxes in the central carbon metabolism when comparing the two recombinant strains vs the control strain, reflected in increased glycolytic, TCA cycle and NADH regeneration fluxes, as well as higher methanol dissimilation rates.

Conclusions

Overall, a further ¹³C-based MFA development to characterise the central metabolism of methylotrophic yeasts when growing on mixed methanol:multicarbon sources has been implemented, thus providing a new tool for the investigation of the relationships between central metabolism and protein production. Specifically, the study points at a limited but significant impact of the conformational stress associated to secretion of recombinant proteins on the central metabolism, occurring even at modest production levels.