Evidence map›Paper›PMID 28686609›Full record

ArticlePloS one2017

Self-consistent theory of transcriptional control in complex regulatory architectures.

Jasper Landman, Robert C Brewster, Franz M Weinert, Rob Phillips, Willem K Kegel

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

10 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. A synthetic synthesis to explore animal evolution and development.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Review
  7. Anticipating response function in gene regulatory networks.Journal of the Royal Society, Interface · 2021
    Article
  8. Massively parallel CRISPRi assays reveal concealed thermodynamic determinants of dCas12a binding.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  9. Article
  10. 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

5 authors at 3 institutions in 3 countries.

Jasper LandmanVan 't Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands.ORCID http://orcid.org/0000-0003-4871-7206
Robert C BrewsterProgram in Systems Biology, University of Massachusetts Medical School, Worcester, MA 01605, United States of America.
Franz M WeinertDepartment of Applied Physics, California Institute of Technology, Pasadena, California, United States of America.
Rob PhillipsDepartment of Applied Physics, California Institute of Technology, Pasadena, California, United States of America.
Willem K KegelVan 't Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands.
California Institute of Technology · USUtrecht University · NLUniversity of Massachusetts Chan Medical School · US

Funding

NIH Director's Pioneer Award (RMI)DP1OD000217 · OD · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI PHILLIPS, ROB · 2004 to 2008
$4.0M
Single-Molecule and Single-Cell Analysis of Transcription Factor-DNA ComplexesR01GM085286 · NIGMS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI PHILLIPS, ROB · 2009 to 2015
$2.8M
NIGMS NIH HHS R01 GM085286NIH HHS DP1 OD000217
6 · The paper itself

Abstract

Individual regulatory proteins are typically charged with the simultaneous regulation of a battery of different genes. As a result, when one of these proteins is limiting, competitive effects have a significant impact on the transcriptional response of the regulated genes. Here we present a general framework for the analysis of any generic regulatory architecture that accounts for the competitive effects of the regulatory environment by isolating these effects into an effective concentration parameter. These predictions are formulated using the grand-canonical ensemble of statistical mechanics and the fold-change in gene expression is predicted as a function of the number of transcription factors, the strength of interactions between the transcription factors and their DNA binding sites, and the effective concentration of the transcription factor. The effective concentration is set by the transcription factor interactions with competing binding sites within the cell and is determined self-consistently. Using this approach, we analyze regulatory architectures in the grand-canonical ensemble ranging from simple repression and simple activation to scenarios that include repression mediated by DNA looping of distal regulatory sites. It is demonstrated that all the canonical expressions previously derived in the case of an isolated, non-competing gene, can be generalised by a simple substitution to their grand canonical counterpart, which allows for simple intuitive incorporation of the influence of multiple competing transcription factor binding sites. As an example of the strength of this approach, we build on these results to present an analytical description of transcriptional regulation of the lac operon.

Indexed as

Binding SitesDNA-Binding ProteinsEscherichia coliGene Expression Regulation, BacterialGene Regulatory NetworksLac OperonModels, TheoreticalProtein BindingTranscription FactorsDNA-Binding ProteinsTranscription Factors

Identifiers

PMID28686609
PMCPMC5501422
OpenAlexW2730999832

What OpenQuestion holds

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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.