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Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement.

Chung BK, Selvarasu S, Andrea C, Ryu J, Lee H, Ahn J, Lee H, Lee DY - Microb. Cell Fact. (2010)

Bottom Line: Pichia pastoris has been recognized as an effective host for recombinant protein production.Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins.This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

View Article: PubMed Central - HTML - PubMed

Affiliation: NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 28 Medical Drive, #05-01, 117456, Singapore. cheld@nus.edu.sg.

ABSTRACT

Background: Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.

Results: A fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified.

Conclusion: The genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

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Related in: MedlinePlus

Flux and flux-sum distributions for different carbon sources. Growth rate, flux and flux-sum values were generated based on individual carbon source uptake rate of 1 C-mmol/gDCW-hr. The color intensity of the lines in the central carbon metabolic network corresponds to the flux values. Precursor metabolites are in blue and the building blocks derived from each of them are specified in the text boxes. The heat-maps on the left and right illustrate the flux and flux-sum distributions, respectively. Similarly, the color intensity corresponds to the flux or flux-sum values normalized with respect to the maximum for each reaction or metabolite.
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Figure 5: Flux and flux-sum distributions for different carbon sources. Growth rate, flux and flux-sum values were generated based on individual carbon source uptake rate of 1 C-mmol/gDCW-hr. The color intensity of the lines in the central carbon metabolic network corresponds to the flux values. Precursor metabolites are in blue and the building blocks derived from each of them are specified in the text boxes. The heat-maps on the left and right illustrate the flux and flux-sum distributions, respectively. Similarly, the color intensity corresponds to the flux or flux-sum values normalized with respect to the maximum for each reaction or metabolite.

Mentions: Based on the first criterion of high growth yield, glycerol is the most promising candidate for recombinant protein production, followed by sorbitol (Figure 5). Generally, high utilization of the central metabolism can lead to increased production of various precursors, which can further synthesize building blocks required for the biomass. However, the resulting flux distributions indicated that the utilization of central carbon metabolism is the highest for methanol uptake despite yielding the lowest growth rate. We can understand this observation by examining gaseous exchange rates and ATP flux-sum for methanol utilization. The significantly higher turnover rate of ATP and gaseous exchange rates suggest that much of the resources have been diverted to energy generation during methanol utilization. The low respiratory quotient resulting from this diversion of resources is consistent with findings from several experimental studies [38,44]. Hence, the higher utilization of central metabolism is a consequence of the high energy requirement of methanol metabolism in P. pastors.


Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement.

Chung BK, Selvarasu S, Andrea C, Ryu J, Lee H, Ahn J, Lee H, Lee DY - Microb. Cell Fact. (2010)

Flux and flux-sum distributions for different carbon sources. Growth rate, flux and flux-sum values were generated based on individual carbon source uptake rate of 1 C-mmol/gDCW-hr. The color intensity of the lines in the central carbon metabolic network corresponds to the flux values. Precursor metabolites are in blue and the building blocks derived from each of them are specified in the text boxes. The heat-maps on the left and right illustrate the flux and flux-sum distributions, respectively. Similarly, the color intensity corresponds to the flux or flux-sum values normalized with respect to the maximum for each reaction or metabolite.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2908565&req=5

Figure 5: Flux and flux-sum distributions for different carbon sources. Growth rate, flux and flux-sum values were generated based on individual carbon source uptake rate of 1 C-mmol/gDCW-hr. The color intensity of the lines in the central carbon metabolic network corresponds to the flux values. Precursor metabolites are in blue and the building blocks derived from each of them are specified in the text boxes. The heat-maps on the left and right illustrate the flux and flux-sum distributions, respectively. Similarly, the color intensity corresponds to the flux or flux-sum values normalized with respect to the maximum for each reaction or metabolite.
Mentions: Based on the first criterion of high growth yield, glycerol is the most promising candidate for recombinant protein production, followed by sorbitol (Figure 5). Generally, high utilization of the central metabolism can lead to increased production of various precursors, which can further synthesize building blocks required for the biomass. However, the resulting flux distributions indicated that the utilization of central carbon metabolism is the highest for methanol uptake despite yielding the lowest growth rate. We can understand this observation by examining gaseous exchange rates and ATP flux-sum for methanol utilization. The significantly higher turnover rate of ATP and gaseous exchange rates suggest that much of the resources have been diverted to energy generation during methanol utilization. The low respiratory quotient resulting from this diversion of resources is consistent with findings from several experimental studies [38,44]. Hence, the higher utilization of central metabolism is a consequence of the high energy requirement of methanol metabolism in P. pastors.

Bottom Line: Pichia pastoris has been recognized as an effective host for recombinant protein production.Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins.This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

View Article: PubMed Central - HTML - PubMed

Affiliation: NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 28 Medical Drive, #05-01, 117456, Singapore. cheld@nus.edu.sg.

ABSTRACT

Background: Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.

Results: A fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified.

Conclusion: The genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

Show MeSH
Related in: MedlinePlus