Dataset Information

Macromolecular and elemental composition analysis and extracellular metabolite balances of Pichia pastoris growing at different oxygen levels.

ABSTRACT:

Background

Analysis of the cell operation at the metabolic level requires collecting data of different types and to determine their confidence level. In addition, the acquired information has to be combined in order to obtain a consistent operational view. In the case of Pichia pastoris, information of its biomass composition at macromolecular and elemental level is scarce particularly when different environmental conditions, such as oxygen availability or, genetic backgrounds (e.g. recombinant protein production vs. non production conditions) are compared.

Results

P. pastoris cells growing in carbon-limited chemostat cultures under different oxygenation conditions (% O2 in the bioreactor inlet gas: 21%, 11% and 8%, corresponding to normoxic, oxygen-limiting and hypoxic conditions, respectively), as well as under recombinant protein (antibody fragment, Fab) producing and non-producing conditions, were analyzed from different points of view. On the one hand, the macromolecular and elemental composition of the biomass was measured using different techniques at the different experimental conditions and proper reconciliation techniques were applied for gross error detection of the measured substrates and products conversion rates. On the other hand, fermentation data was analyzed applying elemental mass balances. This allowed detecting a previously missed by-product secreted under hypoxic conditions, identified as arabinitol (aka. arabitol). After identification of this C5 sugar alcohol as a fermentation by-product, the mass balances of the fermentation experiments were validated.

Conclusions

After application of a range of analytical and statistical techniques, a consistent view of growth parameters and compositional data of P. pastoris cells growing under different oxygenation conditions was obtained. The obtained data provides a first view of the effects of oxygen limitation on the physiology of this microorganism, while recombinant Fab production seems to have little or no impact at this level of analysis. Furthermore, the results will be highly useful in other complementary quantitative studies of P. pastoris physiology, such as metabolic flux analysis.

SUBMITTER: Carnicer M

PROVIDER: S-EPMC2799386 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Publications

Macromolecular and elemental composition analysis and extracellular metabolite balances of Pichia pastoris growing at different oxygen levels.

Carnicer Marc M Baumann Kristin K Töplitz Isabelle I Sánchez-Ferrando Francesc F Mattanovich Diethard D Ferrer Pau P Albiol Joan J

Microbial cell factories 20091209

<h4>Background</h4>Analysis of the cell operation at the metabolic level requires collecting data of different types and to determine their confidence level. In addition, the acquired information has to be combined in order to obtain a consistent operational view. In the case of Pichia pastoris, information of its biomass composition at macromolecular and elemental level is scarce particularly when different environmental conditions, such as oxygen availability or, genetic backgrounds (e.g. reco ...[more]

PMID: 20003217

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Project description:BackgroundThe 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.ResultsThe 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 redistribution 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.ConclusionsOverall, 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.

Project description:Yeasts are attractive expression platforms for many recombinant proteins, and there is evidence for an important interrelation between the protein secretion machinery and environmental stresses. While adaptive responses to such stresses are extensively studied in Saccharomyces cerevisiae, little is known about their impact on the physiology of Pichia pastoris. We have recently reported a beneficial effect of hypoxia on recombinant Fab secretion in P. pastoris chemostat cultivations. As a consequence, a systems biology approach was used to comprehensively identify cellular adaptations to low oxygen availability and the additional burden of protein production. Gene expression profiling was combined with proteomic analyses and the 13C isotope labelling based experimental determination of metabolic fluxes in the central carbon metabolism.The physiological adaptation of P. pastoris to hypoxia showed distinct traits in relation to the model yeast S. cerevisiae. There was a positive correlation between the transcriptomic, proteomic and metabolic fluxes adaptation of P. pastoris core metabolism to hypoxia, yielding clear evidence of a strong transcriptional regulation component of key pathways such as glycolysis, pentose phosphate pathway and TCA cycle. In addition, the adaptation to reduced oxygen revealed important changes in lipid metabolism, stress responses, as well as protein folding and trafficking.This systems level study helped to understand the physiological adaptations of cellular mechanisms to low oxygen availability in a recombinant P. pastoris strain. Remarkably, the integration of data from three different levels allowed for the identification of differences in the regulation of the core metabolism between P. pastoris and S. cerevisiae. Detailed comparative analysis of the transcriptomic data also led to new insights into the gene expression profiles of several cellular processes that are not only susceptible to low oxygen concentrations, but might also contribute to enhanced protein secretion.

Project description:Over the past three decades, due to the universal application of Pichia yeast in the fermentation industry as well as the establishment of Pichia pastoris fermentation process for more than 30 years, the technology of the whole process has become very mature and has now reached a stagnated period of growth. However, studies and research conducted on the genomics of the classic fermentation process and the uncovering of the biological phenomena in the fermentation process from the point of view of high-throughput gene or protein is still in its early stages, and there is still insufficient data within this field. First, in collaboration with Agilent Company, we designed and prepared an expression microarray that could be used for the detection of Pichia pastoris transcriptomics. The transcriptomic changes in the five key technology steps (time points), during the fermentation process of Pichia pastoris would then be detected with the aid of an expression microarray. The five key steps of technology described above formed two important biological processes, namely, the limiting carbon source replacement and secondly, the fermentative production of exogenous proteins. The biological phenomena involved in these two processes were displayed and analyzed at the transcriptional level. In addition to this, with regard to the most important function in the fermentation process of Pichia pastoris, oxid-reduction, the metabolic drift process was analyzed and the important genes that might dominate the changes in the metabolic flux were discovered creatively by using the function tree method in this paper. This study was undertaken from the point of view of the transcriptome and the biological phenomena in the fermemntation process of Pichia pastoris. Both of which, were thoroughly explained during this study. The hope is for many more researchers to optimize the strain fermentation process, to produce proteins at the genetic level, as well as providing and obtaining new perspectives and detailed scientific data for the continued development within this field.

Dataset Information

Macromolecular and elemental composition analysis and extracellular metabolite balances of Pichia pastoris growing at different oxygen levels.

Background

Results

Conclusions

Publications

Macromolecular and elemental composition analysis and extracellular metabolite balances of Pichia pastoris growing at different oxygen levels.

Similar Datasets

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