Evidence map›Paper›PMID 31578326›Full record

ArticleNature communications2019

Systematic identification of metabolites controlling gene expression in E. coli.

Martin Lempp, Niklas Farke, Michelle Kuntz, Sven Andreas Freibert, Roland Lill, Hannes Link

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

62 citing papers in PubMed, 119 citations in OpenAlex.

  1. Review
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  5. A systems-level atlas of carbon-response transcriptional states inProceedings of the National Academy of Sciences of the United States of America · 2026
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  10. Journal of bacteriology · 2025
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  18. Review
  19. Review
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2 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Martin LemppMax Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany.
Niklas FarkeMax Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany.
Michelle KuntzMax Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany.
Sven Andreas FreibertInstitut für Zytobiologie und Zytopathologie, Philipps-Universität Marburg, 35033, Marburg, Germany.ORCID http://orcid.org/0000-0002-8521-2963
Roland LillInstitut für Zytobiologie und Zytopathologie, Philipps-Universität Marburg, 35033, Marburg, Germany.ORCID http://orcid.org/0000-0002-8345-6518
Hannes LinkMax Planck Institute for Terrestrial Microbiology, Marburg, 35043, Germany. hannes.link@synmikro.mpi-marburg.mpg.de.ORCID http://orcid.org/0000-0002-6677-555X
Max Planck Institute for Terrestrial Microbiology · DEPhilipps University of Marburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolism controls gene expression through allosteric interactions between metabolites and transcription factors. These interactions are usually measured with in vitro assays, but there are no methods to identify them at a genome-scale in vivo. Here we show that dynamic transcriptome and metabolome data identify metabolites that control transcription factors in E. coli. By switching an E. coli culture between starvation and growth, we induce strong metabolite concentration changes and gene expression changes. Using Network Component Analysis we calculate the activities of 209 transcriptional regulators and correlate them with metabolites. This approach captures, for instance, the in vivo kinetics of CRP regulation by cyclic-AMP. By testing correlations between all pairs of transcription factors and metabolites, we predict putative effectors of 71 transcription factors, and validate five interactions in vitro. These results show that combining transcriptomics and metabolomics generates hypotheses about metabolism-transcription interactions that drive transitions between physiological states.

Indexed as

Gene Expression Regulation, BacterialMetabolomeTranscriptomeEscherichia coliEscherichia coli ProteinsGene Expression ProfilingGene Regulatory NetworksKineticsMetabolomicsTranscription FactorsEscherichia coli ProteinsTranscription Factors

Identifiers

PMID31578326
PMCPMC6775132
OpenAlexW2978408091

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.