The methylotrophic yeast Pichia pastoris is widely used in the manufacture of industrial enzymes and pharmaceuticals. Like most biotechnological production hosts, P. pastoris is heterotrophic and grows on organic feedstocks that have competing uses in the production of food and animal feed. In a step toward more sustainable industrial processes, we describe the conversion of P. pastoris into an autotroph that grows on CO 2 . By addition of eight heterologous genes and deletion of three Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:
BackgroundSome 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.ResultsIn 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.ConclusionsTaken 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 materialThe online version of this article (doi:10.1186/s12915-015-0186-5) contains supplementary material, which is available to authorized users.
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.
Quantitative metabolic profiling is preceded by dedicated sample preparation protocols. These multistep procedures require detailed optimization and thorough validation. In this work, a uniformly (13)C-labeled (U(13)C) cell extract was used as a tool to evaluate the recoveries and repeatability precisions of the cell extraction and the extract treatment. A homogenous set of biological replicates (n = 15 samples of Pichia pastoris) was prepared for these fundamental experiments. A range of less than 30 intracellular metabolites, comprising amino acids, nucleotides, and organic acids were measured both in monoisotopic (12)C and U(13)C form by LC-MS/MS employing triple quadrupole MS, reversed phase chromatography, and HILIC. Recoveries of the sample preparation procedure ranging from 60 to 100% and repeatability precisions below 10% were obtained for most of the investigated metabolites using internal standardization approaches. Uncertainty budget calculations revealed that for this complex quantification task, in the optimum case, total combined uncertainty of 12% could be achieved. The optimum case would be represented by metabolites, easy to extract from yeast with high and precise recovery. In other cases the total combined uncertainty was significantly higher.
Metabolic flux analysis implies mass isotopomer distribution analysis and determination of mass isotopologue fractions (IFs) of proteinogenic amino acids of cell cultures. In this work, for the first time, this type of analysis is comprehensively investigated in terms of measurement uncertainty by calculating and comparing budgets for different mass spectrometric techniques. The calculations addressed amino acids of Pichia pastoris grown on 10% uniformly (13)C labeled glucose. Typically, such experiments revealed an enrichment of (13)C by at least one order of magnitude in all proteinogenic amino acids. Liquid chromatography-time-of-flight mass spectrometry (LC-TOFMS), liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) analyses were performed. The samples were diluted to fit the linear dynamic range of the mass spectrometers used (10 μM amino acid concentration). The total combined uncertainties of IFs as well as the major uncertainty contributions affecting the IFs were determined for phenylalanine, which was selected as exemplary model compound. A bottom-up uncertainty propagation was performed according to Quantifying Uncertainty in Analytical Measurement and using the Monte Carlo method by considering all factors leading to an IF, i.e., the process of measurement and the addition of (13)C-glucose. Excellent relative expanded uncertainties (k = 1) of 0.32, 0.75, and 0.96% were obtained for an IF value of 0.7 by LC-MS/MS, GC-MS, and LC-TOFMS, respectively. The major source of uncertainty, with a relative contribution of 20-80% of the total uncertainty, was attributed to the signal intensity (absolute counts) uncertainty calculated according to Poisson counting statistics, regardless which of the mass spectrometry platforms was used. Uncertainty due to measurement repeatability was of importance in LC-MS/MS, showing a relative contribution up to 47% of the total uncertainty, whereas for GC-MS and LC-TOFMS the average contribution was lower (30 and 15%, respectively). Moreover, the IF actually present also depends on the isotopic purity of the carbon sources. Therefore, in the uncertainty calculation a carbon source purity factor was introduced and a minor contribution to the total uncertainty was observed. The results obtained by uncertainty calculation performed according to the Monte Carlo method were in agreement with the uncertainty value of the Kragten approach and showed a Gaussian distribution.
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