Evidence map›Paper›PMID 33645919›Full record

ArticleMicrobial biotechnology2021

Integrating continuous hypermutation with high-throughput screening for optimization of cis,cis-muconic acid production in yeast.

Emil D Jensen, Francesca Ambri, Marie B Bendtsen, Alex A Javanpour, Chang C Liu, Michael K Jensen, Jay D Keasling

Open access · goldAbstract read
In one paragraph

Article in Microbial biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. MutaT7ACS synthetic biology · 2024
    Article
  7. Article
  8. Evolution and synthetic biology.Current opinion in microbiology · 2023
    Review
  9. Review
  10. Review
  11. Article
  12. In vivo hypermutation and continuous evolution.Nature reviews. Methods primers · 2022
    Article
  13. Article
  14. 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

7 authors at 3 institutions in 3 countries.

Emil D JensenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.
Francesca AmbriNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.
Marie B BendtsenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.
Alex A JavanpourDepartment of Biomedical Engineering, University of California, Irvine, Irvine, CA, 92697, USA.
Chang C LiuDepartment of Biomedical Engineering, University of California, Irvine, Irvine, CA, 92697, USA.
Michael K JensenNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.ORCID 0000-0001-7574-4707
Jay D KeaslingNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.
Novo Nordisk Foundation · DKUniversity of California, Irvine · USLawrence Berkeley National Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Directed evolution is a powerful method to optimize proteins and metabolic reactions towards user-defined goals. It usually involves subjecting genes or pathways to iterative rounds of mutagenesis, selection and amplification. While powerful, systematic searches through large sequence-spaces is a labour-intensive task, and can be further limited by a priori knowledge about the optimal initial search space, and/or limits in terms of screening throughput. Here, we demonstrate an integrated directed evolution workflow for metabolic pathway enzymes that continuously generate enzyme variants using the recently developed orthogonal replication system, OrthoRep and screens for optimal performance in high-throughput using a transcription factor-based biosensor. We demonstrate the strengths of this workflow by evolving a rate-limiting enzymatic reaction of the biosynthetic pathway for cis,cis-muconic acid (CCM), a precursor used for bioplastic and coatings, in Saccharomyces cerevisiae. After two weeks of simply iterating between passaging of cells to generate variant enzymes via OrthoRep and high-throughput sorting of best-performing variants using a transcription factor-based biosensor for CCM, we ultimately identified variant enzymes improving CCM titers > 13-fold compared with reference enzymes. Taken together, the combination of synthetic biology tools as adopted in this study is an efficient approach to debottleneck repetitive workflows associated with directed evolution of metabolic enzymes.

Indexed as

High-Throughput Screening AssaysSaccharomyces cerevisiaeSorbic AcidSynthetic Biologymuconic acidSorbic Acid

Identifiers

PMID33645919
PMCPMC8601171
OpenAlexW3135633117

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.