In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates

Ignacio Poblete-Castro, Danielle Binger, Andre Rodrigues, Judith Becker, Vitor A P Martins Dos Santos, Christoph Wittmann

Resultado de la investigación: Article

76 Citas (Scopus)

Resumen

Here, we present systems metabolic engineering driven by in-silico modeling to tailor Pseudomonas putida for synthesis of medium chain length PHAs on glucose. Using physiological properties of the parent wild type as constraints, elementary flux mode analysis of a large-scale model of the metabolism of P. putida was used to predict genetic targets for strain engineering. Among a set of priority ranked targets, glucose dehydrogenase (encoded by gcd) was predicted as most promising deletion target. The mutant P. putida Δ. gcd, generated on basis of the computational design, exhibited 100% increased PHA accumulation as compared to the parent wild type, maintained a high specific growth rate and exhibited an almost unaffected gene expression profile, which excluded detrimental side effects of the modification. A second mutant strain, P. putida Δ. pgl, that lacked 6-phosphogluconolactonase, exhibited a substantially decreased PHA synthesis, as was also predicted by the model. The production potential of P. putida Δ. gcd was assessed in batch bioreactors. The novel strain showed an increase of the PHA yield (+80%), the PHA titer (+100%) and cellular PHA content (+50%) and revealed almost unaffected growth and diminished by-product formation. It was thus found superior in all relevant criteria towards industrial production. Beyond the contribution to more efficient PHA production processes at reduced costs that might replace petrochemical plastics in the future, the study illustrates the power of computational prediction to tailor microbial strains for enhanced biosynthesis of added-value compounds.

Idioma originalEnglish
Páginas (desde-hasta)113-123
Número de páginas11
PublicaciónMetabolic Engineering
Volumen15
N.º1
DOI
EstadoPublished - 1 ene 2013

Huella dactilar

Metabolic engineering
Metabolic Engineering
Pseudomonas putida
Computer Simulation
6-phosphogluconolactonase
Glucose
Glucose 1-Dehydrogenase
Biosynthesis
Bioreactors
Systems engineering
Chain length
Metabolism
Gene expression
Petrochemicals
Byproducts
Fluxes
Plastics
Growth
Transcriptome
Costs

ASJC Scopus subject areas

  • Bioengineering
  • Biotechnology
  • Applied Microbiology and Biotechnology

Citar esto

Poblete-Castro, Ignacio ; Binger, Danielle ; Rodrigues, Andre ; Becker, Judith ; Martins Dos Santos, Vitor A P ; Wittmann, Christoph. / In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates. En: Metabolic Engineering. 2013 ; Vol. 15, N.º 1. pp. 113-123.
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abstract = "Here, we present systems metabolic engineering driven by in-silico modeling to tailor Pseudomonas putida for synthesis of medium chain length PHAs on glucose. Using physiological properties of the parent wild type as constraints, elementary flux mode analysis of a large-scale model of the metabolism of P. putida was used to predict genetic targets for strain engineering. Among a set of priority ranked targets, glucose dehydrogenase (encoded by gcd) was predicted as most promising deletion target. The mutant P. putida Δ. gcd, generated on basis of the computational design, exhibited 100{\%} increased PHA accumulation as compared to the parent wild type, maintained a high specific growth rate and exhibited an almost unaffected gene expression profile, which excluded detrimental side effects of the modification. A second mutant strain, P. putida Δ. pgl, that lacked 6-phosphogluconolactonase, exhibited a substantially decreased PHA synthesis, as was also predicted by the model. The production potential of P. putida Δ. gcd was assessed in batch bioreactors. The novel strain showed an increase of the PHA yield (+80{\%}), the PHA titer (+100{\%}) and cellular PHA content (+50{\%}) and revealed almost unaffected growth and diminished by-product formation. It was thus found superior in all relevant criteria towards industrial production. Beyond the contribution to more efficient PHA production processes at reduced costs that might replace petrochemical plastics in the future, the study illustrates the power of computational prediction to tailor microbial strains for enhanced biosynthesis of added-value compounds.",
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In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates. / Poblete-Castro, Ignacio; Binger, Danielle; Rodrigues, Andre; Becker, Judith; Martins Dos Santos, Vitor A P; Wittmann, Christoph.

En: Metabolic Engineering, Vol. 15, N.º 1, 01.01.2013, p. 113-123.

Resultado de la investigación: Article

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T1 - In-silico-driven metabolic engineering of Pseudomonas putida for enhanced production of poly-hydroxyalkanoates

AU - Poblete-Castro, Ignacio

AU - Binger, Danielle

AU - Rodrigues, Andre

AU - Becker, Judith

AU - Martins Dos Santos, Vitor A P

AU - Wittmann, Christoph

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Here, we present systems metabolic engineering driven by in-silico modeling to tailor Pseudomonas putida for synthesis of medium chain length PHAs on glucose. Using physiological properties of the parent wild type as constraints, elementary flux mode analysis of a large-scale model of the metabolism of P. putida was used to predict genetic targets for strain engineering. Among a set of priority ranked targets, glucose dehydrogenase (encoded by gcd) was predicted as most promising deletion target. The mutant P. putida Δ. gcd, generated on basis of the computational design, exhibited 100% increased PHA accumulation as compared to the parent wild type, maintained a high specific growth rate and exhibited an almost unaffected gene expression profile, which excluded detrimental side effects of the modification. A second mutant strain, P. putida Δ. pgl, that lacked 6-phosphogluconolactonase, exhibited a substantially decreased PHA synthesis, as was also predicted by the model. The production potential of P. putida Δ. gcd was assessed in batch bioreactors. The novel strain showed an increase of the PHA yield (+80%), the PHA titer (+100%) and cellular PHA content (+50%) and revealed almost unaffected growth and diminished by-product formation. It was thus found superior in all relevant criteria towards industrial production. Beyond the contribution to more efficient PHA production processes at reduced costs that might replace petrochemical plastics in the future, the study illustrates the power of computational prediction to tailor microbial strains for enhanced biosynthesis of added-value compounds.

AB - Here, we present systems metabolic engineering driven by in-silico modeling to tailor Pseudomonas putida for synthesis of medium chain length PHAs on glucose. Using physiological properties of the parent wild type as constraints, elementary flux mode analysis of a large-scale model of the metabolism of P. putida was used to predict genetic targets for strain engineering. Among a set of priority ranked targets, glucose dehydrogenase (encoded by gcd) was predicted as most promising deletion target. The mutant P. putida Δ. gcd, generated on basis of the computational design, exhibited 100% increased PHA accumulation as compared to the parent wild type, maintained a high specific growth rate and exhibited an almost unaffected gene expression profile, which excluded detrimental side effects of the modification. A second mutant strain, P. putida Δ. pgl, that lacked 6-phosphogluconolactonase, exhibited a substantially decreased PHA synthesis, as was also predicted by the model. The production potential of P. putida Δ. gcd was assessed in batch bioreactors. The novel strain showed an increase of the PHA yield (+80%), the PHA titer (+100%) and cellular PHA content (+50%) and revealed almost unaffected growth and diminished by-product formation. It was thus found superior in all relevant criteria towards industrial production. Beyond the contribution to more efficient PHA production processes at reduced costs that might replace petrochemical plastics in the future, the study illustrates the power of computational prediction to tailor microbial strains for enhanced biosynthesis of added-value compounds.

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KW - Pathway engineering

KW - Phosphogluconolactonase

KW - Polyhydroxyalkanoates

KW - Pseudomonas putida KT2440

KW - Systems metabolic engineering

KW - Transcriptome

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DO - 10.1016/j.ymben.2012.10.004

M3 - Article

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AN - SCOPUS:84871463200

VL - 15

SP - 113

EP - 123

JO - Metabolic Engineering

JF - Metabolic Engineering

SN - 1096-7176

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