Evidence map›Paper›PMID 23388641›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Systematic measurement of transcription factor-DNA interactions by targeted mass spectrometry identifies candidate gene regulatory proteins.

Hamid Mirzaei, Theo A Knijnenburg, Bong Kim, Max Robinson, Paola Picotti, Gregory W Carter, Song Li, David J Dilworth, Jimmy K Eng, John D Aitchison and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. 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
3.0field-weighted citation impact, top 8% 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, 31 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Systems cell biology.The Journal of cell biology · 2014
    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

14 authors at 5 institutions in 3 countries.

Hamid MirzaeiInstitute for Systems Biology, Seattle, WA 98109, USA.
Theo A Knijnenburg
Bong Kim
Max Robinson
Paola Picotti
Gregory W Carter
Song Li
David J Dilworth
Jimmy K Eng
John D Aitchison
Ilya Shmulevich
Timothy Galitski
Ruedi Aebersold
Jeffrey Ranish
Institute for Systems Biology · USETH Zurich · CHThe Netherlands Cancer Institute · NLThe University of Texas Southwestern Medical Center · USUniversity of Zurich · CH

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI AITCHISON, JOHN D. · 2006 to 2016
$30.6M
Inference and Testing of Quantitative Models of Genetic InteractionK25GM079404 · NIGMS · JACKSON LABORATORY · PI CARTER, GREGORY W · 2007 to 2011
$545k
European Research Council 233226NHLBI NIH HHS N01-HV-8179NIGMS NIH HHS K25 GM079404NIGMS NIH HHS P50 GM076547PHS HHS P50 GMO76547
6 · The paper itself

Abstract

Regulation of gene expression involves the orchestrated interaction of a large number of proteins with transcriptional regulatory elements in the context of chromatin. Our understanding of gene regulation is limited by the lack of a protein measurement technology that can systematically detect and quantify the ensemble of proteins associated with the transcriptional regulatory elements of specific genes. Here, we introduce a set of selected reaction monitoring (SRM) assays for the systematic measurement of 464 proteins with known or suspected roles in transcriptional regulation at RNA polymerase II transcribed promoters in Saccharomyces cerevisiae. Measurement of these proteins in nuclear extracts by SRM permitted the reproducible quantification of 42% of the proteins over a wide range of abundances. By deploying the assay to systematically identify DNA binding transcriptional regulators that interact with the environmentally regulated FLO11 promoter in cell extracts, we identified 15 regulators that bound specifically to distinct regions along ∼600 bp of the regulatory sequence. Importantly, the dataset includes a number of regulators that have been shown to either control FLO11 expression or localize to these regulatory regions in vivo. We further validated the utility of the approach by demonstrating that two of the SRM-identified factors, Mot3 and Azf1, are required for proper FLO11 expression. These results demonstrate the utility of SRM-based targeted proteomics to guide the identification of gene-specific transcriptional regulators.

Indexed as

Gene Expression Regulation, FungalGenetic Association StudiesCell NucleusDNA-Binding ProteinsDNA, FungalMass SpectrometryPromoter Regions, GeneticProtein BindingProteomeRepressor ProteinsReproducibility of ResultsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTrans-ActivatorsTranscription FactorsDNA-Binding ProteinsDNA, FungalProteomeRepressor ProteinsSaccharomyces cerevisiae ProteinsTrans-ActivatorsTranscription Factors

Identifiers

PMID23388641
PMCPMC3587231
OpenAlexW2127059057

What OpenQuestion holds

Textmetadata
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.