Evidence map›Paper›PMID 18836036›Full record

ArticleGenome research2009

Principles of transcriptional regulation and evolution of the metabolic system in E. coli.

Aswin S N Seshasayee, Gillian M Fraser, M Madan Babu, Nicholas M Luscombe

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed, 67 citations in OpenAlex.

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  16. Effect of database drift on network topology and enrichment analyses: a case study for RegulonDB.Database : the journal of biological databases and curation · 2016
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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

4 authors at 3 institutions in 2 countries.

Aswin S N SeshasayeeEMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, United Kingdom. aswin@ebi.ac.uk
Gillian M Fraser
M Madan Babu
Nicholas M Luscombe
European Bioinformatics Institute · GBMRC Laboratory of Molecular Biology · GBUniversity of Cambridge · GB

Funding

Biotechnology and Biological Sciences Research Council BB/E01075X/1Biotechnology and Biological Sciences Research Council BB/E011489/1Medical Research Council MC_U105185859
6 · The paper itself

Abstract

Organisms must adapt to make optimal use of the metabolic system in response to environmental changes. In the long-term, this involves evolution of the genomic repertoire of enzymes; in the short-term, transcriptional control ensures that appropriate enzymes are expressed in response to transitory extracellular conditions. Unicellular organisms are particularly susceptible to environmental changes; however, genome-scale impact of these modulatory effects has not been explored so far in bacteria. Here, we integrate genome-scale data to investigate the evolutionary trends and transcriptional control of metabolism in Escherichia coli K12. Globally, the regulatory system is organized in a clear hierarchy of general and specific transcription factors (TFs) that control differing ranges of metabolic functions. Further, catabolic, anabolic, and central metabolic pathways are targeted by distinct combinations of these TFs. Locally, enzymes catalyzing sequential reactions in a metabolic pathway are co-regulated by the same TFs. Regulation is more complex at junctions: General TFs control the overall activity of all connecting reactions, whereas specific TFs control individual enzymes. Divergent junctions play a special role in delineating metabolic pathways and decouple the regulation of incoming and outgoing reactions. We find little evidence for differential usage of isozymes, which are generally co-expressed in similar conditions, and thus are likely to reinforce the metabolic system through redundancy. Finally, we show that enzymes controlled by the same TFs have a strong tendency to co-evolve, suggesting a significant constraint to maintain similar regulatory regimes during evolution. Catabolic, anabolic, and central energy pathways evolve differently, emphasizing the role of the environment in shaping the metabolic system. Many of the observations also occur in yeast, and our findings may apply across large evolutionary distances.

Indexed as

Energy MetabolismEnzymesEscherichia coli K12Escherichia coli ProteinsEvolution, MolecularGenome, BacterialMetabolic Networks and PathwaysModels, BiologicalModels, GeneticTranscription FactorsTranscription, GeneticEnzymesEscherichia coli ProteinsTranscription Factors

Identifiers

PMID18836036
PMCPMC2612968
OpenAlexW2170580257

What OpenQuestion holds

Textmetadata
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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.