Evidence map›Paper›PMID 28302114›Full record

ArticleMicrobial cell factories2017

Implications of evolutionary engineering for growth and recombinant protein production in methanol-based growth media in the yeast Pichia pastoris.

Josef W Moser, Roland Prielhofer, Samuel M Gerner, Alexandra B Graf, Iain B H Wilson, Diethard Mattanovich, Martin Dragosits

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

21 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
  2. Living Microbial Drugs.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  3. Article
  4. Article
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  8. Advances in Metabolic Engineering ofJournal of fungi (Basel, Switzerland) · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Methanol biotransformation toward high-level production of fatty acid derivatives by engineering the industrial yeastProceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
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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

7 authors at 3 institutions in 1 country.

Josef W MoserDepartment of Chemistry, University of Natural Resources and Life Sciences, Muthgasse 11, 1190, Vienna, Austria.
Roland PrielhoferAustrian Centre of Industrial Biotechnology (ACIB), 1190, Vienna, Austria.
Samuel M GernerUniversity of Applied Sciences FH-Campus Wien, Bioengineering, Vienna, Austria.
Alexandra B GrafAustrian Centre of Industrial Biotechnology (ACIB), 1190, Vienna, Austria.
Iain B H WilsonDepartment of Chemistry, University of Natural Resources and Life Sciences, Muthgasse 11, 1190, Vienna, Austria.
Diethard MattanovichAustrian Centre of Industrial Biotechnology (ACIB), 1190, Vienna, Austria.
Martin DragositsDepartment of Chemistry, University of Natural Resources and Life Sciences, Muthgasse 11, 1190, Vienna, Austria. martin.dragosits@boku.ac.at.ORCID http://orcid.org/0000-0003-2522-8469
Austrian Centre of Industrial Biotechnology (Austria) · ATBOKU University · ATHochschule Campus Wien · AT

Funding

Austrian Science Fund FWF P 26210
6 · The paper itself

Abstract

backgroundPichia pastoris is a widely used eukaryotic expression host for recombinant protein production. Adaptive laboratory evolution (ALE) has been applied in a wide range of studies in order to improve strains for biotechnological purposes. In this context, the impact of long-term carbon source adaptation in P. pastoris has not been addressed so far. Thus, we performed a pilot experiment in order to analyze the applicability and potential benefits of ALE towards improved growth and recombinant protein production in P. pastoris.

resultsAdaptation towards growth on methanol was performed in replicate cultures in rich and minimal growth medium for 250 generations. Increased growth rates on these growth media were observed at the population and single clone level. Evolved populations showed various degrees of growth advantages and trade-offs in non-evolutionary growth conditions. Genome resequencing revealed a wide variety of potential genetic targets associated with improved growth performance on methanol-based growth media. Alcohol oxidase represented a mutational hotspot since four out of seven evolved P. pastoris clones harbored mutations in this gene, resulting in decreased Aox activity, despite increased growth rates. Selected clones displayed strain-dependent variations for AOX-promoter based recombinant protein expression yield. One particularly interesting clone showed increased product titers ranging from a 2.5-fold increase in shake flask batch culture to a 1.8-fold increase during fed batch cultivation.

conclusionsOur data indicate a complex correlation of carbon source, growth context and recombinant protein production. While similar experiments have already shown their potential in other biotechnological areas where microbes were evolutionary engineered for improved stress resistance and growth, the current dataset encourages the analysis of the potential of ALE for improved protein production in P. pastoris on a broader scale.

Indexed as

Directed Molecular EvolutionAlcohol OxidoreductasesBatch Cell Culture TechniquesBiotechnologyCloning, MolecularCulture MediaMethanolMutationPichiaPilot ProjectsPromoter Regions, GeneticRecombinant Proteinsalcohol oxidaseAlcohol OxidoreductasesCulture MediaMethanolRecombinant ProteinsExperimental evolutionMethanolPichia pastorisRecombinant protein

Identifiers

PMID28302114
PMCPMC5356285
OpenAlexW2595491014

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.