Evidence map›Paper›PMID 33136197›Full record

ReviewJournal of industrial microbiology & biotechnology2020

The future of self-selecting and stable fermentations.

Peter Rugbjerg, Lisbeth Olsson

Abstract readReview
In one paragraph

Review in Journal of industrial microbiology & biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Practical genetic control strategies for industrial bioprocesses.Journal of industrial microbiology & biotechnology · 2022
    Review
  13. Article
  14. Frontiers in microbiology · 2022
    Article
  15. Review
  16. Article
  17. Introduction to the Special Issue on "Recent Advances in Fermentation Technology 2020".Journal of industrial microbiology & biotechnology · 2020
    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

2 authors.

Peter RugbjergEnduro Genetics ApS, Copenhagen, Denmark. pr@endurogenetics.com.ORCID http://orcid.org/0000-0003-2561-5063
Lisbeth OlssonDepartment of Biology and Biological Engineering, Industrial Biotechnology, Chalmers University of Technology, Gothenburg, Sweden.ORCID http://orcid.org/0000-0002-0827-5442

Funding

Novo Nordisk Fonden NNF19OC0055044
6 · The paper itself

Abstract

Unfavorable cell heterogeneity is a frequent risk during bioprocess scale-up and characterized by rising frequencies of low-producing cells. Low-producing cells emerge by both non-genetic and genetic variation and will enrich due to their higher specific growth rate during the extended number of cell divisions of large-scale bioproduction. Here, we discuss recent strategies for synthetic stabilization of fermentation populations and argue for their application to make cell factory designs that better suit industrial needs. Genotype-directed strategies leverage DNA-sequencing data to inform strain design. Self-selecting phenotype-directed strategies couple high production with cell proliferation, either by redirected metabolic pathways or synthetic product biosensing to enrich for high-performing cell variants. Evaluating production stability early in new cell factory projects will guide heterogeneity-reducing design choices. As good initial metrics, we propose production half-life from standardized serial-passage stability screens and production load, quantified as production-associated percent-wise growth rate reduction. Incorporating more stable genetic designs will greatly increase scalability of future cell factories through sustaining a high-production phenotype and enabling stable long-term production.

Indexed as

FermentationMetabolic EngineeringEvolutionary stabilityGenetic heterogeneityMetabolic burdenPhenotypic heterogeneityProduction loadProduction robustnessProduction stability

Identifiers

PMID33136197
PMCPMC7695646

What OpenQuestion holds

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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.