Limits...
Systematic single-cell analysis of Pichia pastoris reveals secretory capacity limits productivity.

Love KR, Politano TJ, Panagiotou V, Jiang B, Stadheim TA, Love JC - PLoS ONE (2012)

Bottom Line: Here, with single-cell resolution, we systematically analysed the productivity of a series of Pichia pastoris strains that produce different proteins both constitutively and inducibly.We then developed a simple mathematical model describing the flux of folded protein through the ER.This combination of single-cell measurements and computational modelling shows that protein trafficking through the secretory machinery is often the rate-limiting step in single-cell production, and strategies to enhance the overall capacity of protein secretion within hosts for the production of heterologous proteins may improve productivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

ABSTRACT
Biopharmaceuticals represent the fastest growing sector of the global pharmaceutical industry. Cost-efficient production of these biologic drugs requires a robust host organism for generating high titers of protein during fermentation. Understanding key cellular processes that limit protein production and secretion is, therefore, essential for rational strain engineering. Here, with single-cell resolution, we systematically analysed the productivity of a series of Pichia pastoris strains that produce different proteins both constitutively and inducibly. We characterized each strain by qPCR, RT-qPCR, microengraving, and imaging cytometry. We then developed a simple mathematical model describing the flux of folded protein through the ER. This combination of single-cell measurements and computational modelling shows that protein trafficking through the secretory machinery is often the rate-limiting step in single-cell production, and strategies to enhance the overall capacity of protein secretion within hosts for the production of heterologous proteins may improve productivity.

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Model for steady-state distribution of protein trafficking through the ER in P. pastoris.(A) Schematic model for protein secretion that includes flux from the ER via both protein export and degradation. (B) Density plot of the relative rates of protein secretion by single cells compared to the relative amount of intracellular protein calculated with the kinetic model described in equations 2–4 under different relative median rates: kERAD>ksec (purple, r = 0.826); kERAD = ksec (green, r = 0.014); and kERAD<ksec (pink, r = −0.829) (n = 5,000 for each group; Pearson's correlation coefficient for protein production and secretion). (C) Density plot of the relative rates of protein secretion by single cells against the relative amount of intracellular protein for a representative model data set where median kERAD>ksec (left panel). Pearson's correlation coefficient for protein production and secretion in this population is 0.391. Blue shading indicates cells with rates of protein secretion greater than the median rate+2σ (high secretors). These data were replotted as a function of their rate parameters for secretion and degradation; units shown are s−1 (right panel). The median tsec was 80 min and median tERAD was 60 min, with a standard deviation of 10 min for each. (D) Distributions of the relative rates of protein secretion for model populations of cells producing proteins of low (green), intermediate (red), and high complexity (blue). The median tsec value was scaled by a multiplicative constant between 1 and 2 in order to reflect the additional time required to process proteins of higher complexity. (E) Plot of relative gene expression against the median rates of secretion for populations of cells generated using the kinetic model with varying levels of gene expression and protein complexity. Data were fit by linear regression (R2 = 0.983). kexp was multiplied by the relative mRNA expression level in each strain (Table 1), and tsec was scaled as noted in (D) for glycosylated Fc (medium complexity) and aglycosylated Fc (high complexity).
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pone-0037915-g004: Model for steady-state distribution of protein trafficking through the ER in P. pastoris.(A) Schematic model for protein secretion that includes flux from the ER via both protein export and degradation. (B) Density plot of the relative rates of protein secretion by single cells compared to the relative amount of intracellular protein calculated with the kinetic model described in equations 2–4 under different relative median rates: kERAD>ksec (purple, r = 0.826); kERAD = ksec (green, r = 0.014); and kERAD<ksec (pink, r = −0.829) (n = 5,000 for each group; Pearson's correlation coefficient for protein production and secretion). (C) Density plot of the relative rates of protein secretion by single cells against the relative amount of intracellular protein for a representative model data set where median kERAD>ksec (left panel). Pearson's correlation coefficient for protein production and secretion in this population is 0.391. Blue shading indicates cells with rates of protein secretion greater than the median rate+2σ (high secretors). These data were replotted as a function of their rate parameters for secretion and degradation; units shown are s−1 (right panel). The median tsec was 80 min and median tERAD was 60 min, with a standard deviation of 10 min for each. (D) Distributions of the relative rates of protein secretion for model populations of cells producing proteins of low (green), intermediate (red), and high complexity (blue). The median tsec value was scaled by a multiplicative constant between 1 and 2 in order to reflect the additional time required to process proteins of higher complexity. (E) Plot of relative gene expression against the median rates of secretion for populations of cells generated using the kinetic model with varying levels of gene expression and protein complexity. Data were fit by linear regression (R2 = 0.983). kexp was multiplied by the relative mRNA expression level in each strain (Table 1), and tsec was scaled as noted in (D) for glycosylated Fc (medium complexity) and aglycosylated Fc (high complexity).

Mentions: We next sought to develop a simple mechanistic model from first principles to understand how distinct subpopulations of cells with varied rates of secretion could arise. The flux of proteins through the ER is determined by the rates at which proteins transfer into the ER, and then out of the ER either by entering the secretory pathway or by being shuttled to the proteasome via ER-associated degradation (ERAD) [33]. We generated a mathematical model (Eqs. 2–4) to describe the steady-state distribution of folded proteins retained in the ER (Figure 4a):(2)(3)(4)where [ER] represents the concentration of folded protein present in the ER and kexp, kERAD, and ksec are the rate constants for protein flux into the ER, out of the ER to the proteasome, and out through the secretory pathway, respectively.


Systematic single-cell analysis of Pichia pastoris reveals secretory capacity limits productivity.

Love KR, Politano TJ, Panagiotou V, Jiang B, Stadheim TA, Love JC - PLoS ONE (2012)

Model for steady-state distribution of protein trafficking through the ER in P. pastoris.(A) Schematic model for protein secretion that includes flux from the ER via both protein export and degradation. (B) Density plot of the relative rates of protein secretion by single cells compared to the relative amount of intracellular protein calculated with the kinetic model described in equations 2–4 under different relative median rates: kERAD>ksec (purple, r = 0.826); kERAD = ksec (green, r = 0.014); and kERAD<ksec (pink, r = −0.829) (n = 5,000 for each group; Pearson's correlation coefficient for protein production and secretion). (C) Density plot of the relative rates of protein secretion by single cells against the relative amount of intracellular protein for a representative model data set where median kERAD>ksec (left panel). Pearson's correlation coefficient for protein production and secretion in this population is 0.391. Blue shading indicates cells with rates of protein secretion greater than the median rate+2σ (high secretors). These data were replotted as a function of their rate parameters for secretion and degradation; units shown are s−1 (right panel). The median tsec was 80 min and median tERAD was 60 min, with a standard deviation of 10 min for each. (D) Distributions of the relative rates of protein secretion for model populations of cells producing proteins of low (green), intermediate (red), and high complexity (blue). The median tsec value was scaled by a multiplicative constant between 1 and 2 in order to reflect the additional time required to process proteins of higher complexity. (E) Plot of relative gene expression against the median rates of secretion for populations of cells generated using the kinetic model with varying levels of gene expression and protein complexity. Data were fit by linear regression (R2 = 0.983). kexp was multiplied by the relative mRNA expression level in each strain (Table 1), and tsec was scaled as noted in (D) for glycosylated Fc (medium complexity) and aglycosylated Fc (high complexity).
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3369916&req=5

pone-0037915-g004: Model for steady-state distribution of protein trafficking through the ER in P. pastoris.(A) Schematic model for protein secretion that includes flux from the ER via both protein export and degradation. (B) Density plot of the relative rates of protein secretion by single cells compared to the relative amount of intracellular protein calculated with the kinetic model described in equations 2–4 under different relative median rates: kERAD>ksec (purple, r = 0.826); kERAD = ksec (green, r = 0.014); and kERAD<ksec (pink, r = −0.829) (n = 5,000 for each group; Pearson's correlation coefficient for protein production and secretion). (C) Density plot of the relative rates of protein secretion by single cells against the relative amount of intracellular protein for a representative model data set where median kERAD>ksec (left panel). Pearson's correlation coefficient for protein production and secretion in this population is 0.391. Blue shading indicates cells with rates of protein secretion greater than the median rate+2σ (high secretors). These data were replotted as a function of their rate parameters for secretion and degradation; units shown are s−1 (right panel). The median tsec was 80 min and median tERAD was 60 min, with a standard deviation of 10 min for each. (D) Distributions of the relative rates of protein secretion for model populations of cells producing proteins of low (green), intermediate (red), and high complexity (blue). The median tsec value was scaled by a multiplicative constant between 1 and 2 in order to reflect the additional time required to process proteins of higher complexity. (E) Plot of relative gene expression against the median rates of secretion for populations of cells generated using the kinetic model with varying levels of gene expression and protein complexity. Data were fit by linear regression (R2 = 0.983). kexp was multiplied by the relative mRNA expression level in each strain (Table 1), and tsec was scaled as noted in (D) for glycosylated Fc (medium complexity) and aglycosylated Fc (high complexity).
Mentions: We next sought to develop a simple mechanistic model from first principles to understand how distinct subpopulations of cells with varied rates of secretion could arise. The flux of proteins through the ER is determined by the rates at which proteins transfer into the ER, and then out of the ER either by entering the secretory pathway or by being shuttled to the proteasome via ER-associated degradation (ERAD) [33]. We generated a mathematical model (Eqs. 2–4) to describe the steady-state distribution of folded proteins retained in the ER (Figure 4a):(2)(3)(4)where [ER] represents the concentration of folded protein present in the ER and kexp, kERAD, and ksec are the rate constants for protein flux into the ER, out of the ER to the proteasome, and out through the secretory pathway, respectively.

Bottom Line: Here, with single-cell resolution, we systematically analysed the productivity of a series of Pichia pastoris strains that produce different proteins both constitutively and inducibly.We then developed a simple mathematical model describing the flux of folded protein through the ER.This combination of single-cell measurements and computational modelling shows that protein trafficking through the secretory machinery is often the rate-limiting step in single-cell production, and strategies to enhance the overall capacity of protein secretion within hosts for the production of heterologous proteins may improve productivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

ABSTRACT
Biopharmaceuticals represent the fastest growing sector of the global pharmaceutical industry. Cost-efficient production of these biologic drugs requires a robust host organism for generating high titers of protein during fermentation. Understanding key cellular processes that limit protein production and secretion is, therefore, essential for rational strain engineering. Here, with single-cell resolution, we systematically analysed the productivity of a series of Pichia pastoris strains that produce different proteins both constitutively and inducibly. We characterized each strain by qPCR, RT-qPCR, microengraving, and imaging cytometry. We then developed a simple mathematical model describing the flux of folded protein through the ER. This combination of single-cell measurements and computational modelling shows that protein trafficking through the secretory machinery is often the rate-limiting step in single-cell production, and strategies to enhance the overall capacity of protein secretion within hosts for the production of heterologous proteins may improve productivity.

Show MeSH
Related in: MedlinePlus