Dataset Information

Development of quantitative metabolomics for Pichia pastoris.

ABSTRACT: Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest of all metabolic activity and removal of extracellular metabolites, without causing leakage of metabolites from the cells. Five different procedures based on cold methanol quenching and cell separation by filtration were tested for metabolomics of Pichia pastoris regarding methanol content and temperature of the quenching solution as key parameters. Quantitative evaluation of these protocols was carried out through mass balance analysis, based on metabolite measurements in all sample fractions, those are whole broth, quenched and washed cells, culture filtrate and quenching and washing solution. Finally, the optimal method was used to study the time profiles of free amino acid and central carbon metabolism intermediates in glucose-limited chemostat cultures. Acceptable recoveries (>90%) were obtained for all quenching procedures tested. However, quenching at -27°C in 60% v/v methanol performed slightly better in terms of leakage minimization. We could demonstrate that five residence times under glucose limitation are enough to reach stable intracellular metabolite pools. Moreover, when comparing P. pastoris and S. cerevisiae metabolomes, under the same cultivation conditions, similar metabolite fingerprints were found in both yeasts, except for the lower glycolysis, where the levels of these metabolites in P. pastoris suggested an enzymatic capacity limitation in that part of the metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0308-1) contains supplementary material, which is available to authorized users.

SUBMITTER: Carnicer M

PROVIDER: S-EPMC3291848 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of quantitative metabolomics for Pichia pastoris.

Carnicer Marc M Canelas André B AB Ten Pierick Angela A Zeng Zhen Z van Dam Jan J Albiol Joan J Ferrer Pau P Heijnen Joseph J JJ van Gulik Walter W

Metabolomics : Official journal of the Metabolomic Society 20110421 2

Accurate, reliable and reproducible measurement of intracellular metabolite levels has become important for metabolic studies of microbial cell factories. A first critical step for metabolomic studies is the establishment of an adequate quenching and washing protocol, which ensures effective arrest of all metabolic activity and removal of extracellular metabolites, without causing leakage of metabolites from the cells. Five different procedures based on cold methanol quenching and cell separatio ...[more]

PMID: 22448155

Similar Datasets

Project description:BackgroundSeveral 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.ResultsInstationary 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 CO?).ConclusionsIn 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.

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

Development of quantitative metabolomics for Pichia pastoris.

Publications

Development of quantitative metabolomics for Pichia pastoris.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure