Evidence map›Paper›PMID 38383636›Full record

ReviewFEMS microbiology reviews2024

Towards a rational approach to promoter engineering: understanding the complexity of transcription initiation in prokaryotes.

Cara Deal, Lien De Wannemaeker, Marjan De Mey

Abstract readReview
In one paragraph

Review in FEMS microbiology reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  7. Review
  8. Article
  9. A fluorescent reporter system for trackingFrontiers in microbiology · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. 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

3 authors.

Cara DealCentre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium.
Lien De WannemaekerCentre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium.
Marjan De MeyCentre for Synthetic Biology, Ghent University. Coupure Links 653, BE-9000 Ghent, Belgium.ORCID 0000-0002-8134-9436

Funding

Flanders 1156121NHorizon Europe project 101081782Special Research Fund iBOF/21/092
6 · The paper itself

Abstract

Promoter sequences are important genetic control elements. Through their interaction with RNA polymerase they determine transcription strength and specificity, thereby regulating the first step in gene expression. Consequently, they can be targeted as elements to control predictability and tuneability of a genetic circuit, which is essential in applications such as the development of robust microbial cell factories. This review considers the promoter elements implicated in the three stages of transcription initiation, detailing the complex interplay of sequence-specific interactions that are involved, and highlighting that DNA sequence features beyond the core promoter elements work in a combinatorial manner to determine transcriptional strength. In particular, we emphasize that, aside from promoter recognition, transcription initiation is also defined by the kinetics of open complex formation and promoter escape, which are also known to be highly sequence specific. Significantly, we focus on how insights into these interactions can be manipulated to lay the foundation for a more rational approach to promoter engineering.

Indexed as

DNA-Directed RNA PolymerasesTranscription, GeneticDNAGene Expression RegulationPromoter Regions, GeneticSigma FactorDNADNA-Directed RNA PolymerasesSigma Factorpromoter engineeringpromoter sequencesigma factorssynthetic biologytranscription initiation

Identifiers

PMID38383636
PMCPMC10911233

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.