Evidence map›Paper›PMID 32690010›Full record

ArticleMicrobial cell factories2020

Engineering transcription factor-based biosensors for repressive regulation through transcriptional deactivation design in Saccharomyces cerevisiae.

Chenxi Qiu, Xiaoxu Chen, Reheman Rexida, Yu Shen, Qingsheng Qi, Xiaoming Bao, Jin Hou

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2020. 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
1.3field-weighted citation impact, top 20% 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, 24 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Tailored UPRE2 variants for dynamic gene regulation in yeast.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Biosensor-CoupledmSystems · 2022
    Article
  10. Review
  11. D-Xylose Sensing inInternational journal of molecular sciences · 2021
    Review
  12. Review
  13. Biology · 2021
    Review
  14. Review
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 2 institutions in 1 country.

Chenxi QiuState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Xiaoxu ChenState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Reheman RexidaState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Yu ShenState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Qingsheng QiState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Xiaoming BaoState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China.
Jin HouState Key Laboratory of Microbial Technology, Shandong University, Binhai Road 72, Qingdao, 266237, People's Republic of China. houjin@sdu.edu.cn.ORCID http://orcid.org/0000-0001-6789-6057
Shandong University · CNQilu University of Technology · CN

Funding

National Key R&D Program of China 2019YFA0904900National Natural Science Foundation of China 31770101and 31970082
6 · The paper itself

Abstract

backgroundWith the development of engineering the microbial cell factories, biosensors have been used widely for regulation of cellular metabolism and high-throughput screening. However, most of the biosensors constructed in Saccharomyces cerevisiae are designed for transcriptional activation. Very few studies have dedicated to the development of genetic circuit for repressive regulation, which is also indispensable for the dynamic control of metabolism.

resultsIn this study, through transcriptional deactivation design, we developed transcription-factor-based biosensors to allow repressive regulation in response to ligand. Using a malonyl-CoA sensing system as an example, the biosensor was constructed and systematically engineered to optimize the dynamic range by comparing transcriptional activity of the activators, evaluating the positions and numbers of the operators in the promoter and comparing the effects of different promoters. A biosensor with 82% repression ratio was obtained. Based on this design principle, another two biosensors, which sense acyl-CoA or xylose and downregulate gene expression, were also successfully constructed.

conclusionsOur work systematically optimized the biosensors for repressive regulation in yeast for the first time. It provided useful framework to construct similar biosensors. Combining the widely reported biosensors for transcriptional activation with the biosensors developed here, it is now possible to construct biosensors with opposing transcriptional activities in yeast.

Indexed as

Biosensing TechniquesBacterial ProteinsDNA-Binding ProteinsGene Expression Regulation, FungalGenetic EngineeringMalonyl Coenzyme AMetabolic EngineeringPromoter Regions, GeneticProtein DomainsRecombinant Fusion ProteinsRepressor ProteinsSaccharomyces cerevisiaeTranscriptional ActivationTranscription FactorsXyloseBacterial ProteinsDNA-Binding ProteinsFadR protein, BacteriaMalonyl Coenzyme ARecombinant Fusion ProteinsRepressor ProteinsTranscription FactorsXyloseBiosensorsMed2Repressive regulationSaccharomyces cerevisiae

Identifiers

PMID32690010
PMCPMC7372789
OpenAlexW3042552100

What OpenQuestion holds

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LicenceCC BY
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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.