Evidence map›Paper›PMID 20594333›Full record

ArticleMicrobial cell factories2010

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

Bevan Ks Chung, Suresh Selvarasu, Camattari Andrea, Jimyoung Ryu, Hyeokweon Lee, Jungoh Ahn, Hongweon Lee, Dong-Yup Lee

Abstract read
In one paragraph

Article in Microbial cell factories, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

53 citing papers in PubMed.

  1. Systematic optimization ofEngineering microbiology · 2026
    Review
  2. Metabolic engineering ofApplied and environmental microbiology · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Genetic tools for metabolic engineering ofEngineering microbiology · 2023
    Review
  8. Article
  9. Review
  10. Development of synthetic biology tools to engineerSynthetic and systems biotechnology · 2021
    Review
  11. Article
  12. Article
  13. Review
  14. Genome-scale metabolic reconstruction of the non-model yeastMetabolic engineering communications · 2020
    Article
  15. Review
  16. Frontiers in microbiology · 2020
    Review
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Bevan Ks ChungNUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, 28 Medical Drive, #05-01, 117456, Singapore. cheld@nus.edu.sg.
Suresh Selvarasu
Camattari Andrea
Jimyoung Ryu
Hyeokweon Lee
Jungoh Ahn
Hongweon Lee
Dong-Yup Lee

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPichia 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.

resultsA 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.

conclusionThe 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.

Indexed as

Genome, FungalButylene GlycolsMetabolic Networks and PathwaysMethanolPhenotypePichiaRecombinant Proteins2,3-butylene glycolButylene GlycolsMethanolRecombinant Proteins

Identifiers

PMID20594333
PMCPMC2908565

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.