Evidence map›Paper›PMID 26275208›Full record

ArticlePLoS computational biology2015

Controlled Measurement and Comparative Analysis of Cellular Components in E. coli Reveals Broad Regulatory Changes in Response to Glucose Starvation.

John R Houser, Craig Barnhart, Daniel R Boutz, Sean M Carroll, Aurko Dasgupta, Joshua K Michener, Brittany D Needham, Ophelia Papoulas, Viswanadham Sridhara, Dariya K Sydykova and 5 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Translation accuracy in E. coli.Nucleic acids research · 2026
    Article
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  3. Review
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  11. Metabolites Potentiate Nitrofurans in Nongrowing Escherichia coli.Antimicrobial agents and chemotherapy · 2021
    Article
  12. Article
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  20. 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

15 authors.

John R HouserInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Craig BarnhartInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Daniel R BoutzInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Sean M CarrollDepartment of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America.
Aurko DasguptaInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Joshua K MichenerDepartment of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America.
Brittany D NeedhamInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Ophelia PapoulasInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Viswanadham SridharaCenter for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America.
Dariya K SydykovaInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America.
Christopher J MarxDepartment of Organismic and Evolutionary Biology, Harvard University, Boston, Massachusetts, United States of America; Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Boston, Massachusetts, United States of America; Department of Biological Sciences, University of Idaho, Moscow, Idaho, United States of America; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho, United States of America.
M Stephen TrentInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America; Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, Georgia, United States of America.
Jeffrey E BarrickInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, United States of America.
Edward M MarcotteInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, United States of America.
Claus O WilkeInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, United States of America; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, United States of America; Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America.

Funding

Next-Generation Proteomics: Massively Parallel Single-Molecule Protein IdentificaDP1GM106408 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI MARCOTTE, EDWARD M · 2012 to 2016
$3.8M
NIGMS NIH HHS DP1 GM106408
6 · The paper itself

Abstract

How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E. coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E. coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E. coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Indexed as

AlgorithmsEscherichia coliGene Expression ProfilingGene Expression Regulation, BacterialGlucoseSystems BiologyGlucose

Identifiers

PMID26275208
PMCPMC4537216

What OpenQuestion holds

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Registered trials

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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.