Evidence map›Paper›PMID 28412930›Full record

ArticleBMC genomics2017

Large-scale analysis of post-translational modifications in E. coli under glucose-limiting conditions.

Colin W Brown, Viswanadham Sridhara, Daniel R Boutz, Maria D Person, Edward M Marcotte, Jeffrey E Barrick, Claus O Wilke

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.8field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 44 citations in OpenAlex.

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  11. Ionizing Radiation-induced Proteomic Oxidation inMolecular & cellular proteomics : MCP · 2020
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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

7 authors at 2 institutions in 1 country.

Colin W BrownInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
Viswanadham SridharaCenter for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.
Daniel R BoutzInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
Maria D PersonInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
Edward M MarcotteInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
Jeffrey E BarrickInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
Claus O WilkeInstitute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA. wilke@austin.utexas.edu.ORCID 0000-0002-7470-9261
The University of Texas at Austin · USAustin College · US

Funding

Proteomics and model organism humanization to decode human geneticsR35GM122480 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI EDWARD M MARCOTTE · 2017 to 2026
$5.4M
The biophysical basis of translational selectionR01GM088344 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI BARRICK, JEFFREY EVAN, WILKE, CLAUS O · 2009 to 2023
$3.5M
NIGMS NIH HHS R01 GM088344NIGMS NIH HHS R35 GM122480
6 · The paper itself

Abstract

backgroundPost-translational modification (PTM) of proteins is central to many cellular processes across all domains of life, but despite decades of study and a wealth of genomic and proteomic data the biological function of many PTMs remains unknown. This is especially true for prokaryotic PTM systems, many of which have only recently been recognized and studied in depth. It is increasingly apparent that a deep sampling of abundance across a wide range of environmental stresses, growth conditions, and PTM types, rather than simply cataloging targets for a handful of modifications, is critical to understanding the complex pathways that govern PTM deposition and downstream effects.

resultsWe utilized a deeply-sampled dataset of MS/MS proteomic analysis covering 9 timepoints spanning the Escherichia coli growth cycle and an unbiased PTM search strategy to construct a temporal map of abundance for all PTMs within a 400 Da window of mass shifts. Using this map, we are able to identify novel targets and temporal patterns for N-terminal N α acetylation, C-terminal glutamylation, and asparagine deamidation. Furthermore, we identify a possible relationship between N-terminal N α acetylation and regulation of protein degradation in stationary phase, pointing to a previously unrecognized biological function for this poorly-understood PTM.

conclusionsUnbiased detection of PTM in MS/MS proteomics data facilitates the discovery of novel modification types and previously unobserved dynamic changes in modification across growth timepoints.

Indexed as

AcetylationChromatography, High Pressure LiquidEscherichia coliEscherichia coli ProteinsGlucosePeptidesProtein Processing, Post-TranslationalProteomicsTandem Mass SpectrometryEscherichia coli ProteinsGlucosePeptidesPost-translational modificationProkaryoteProteomics

Identifiers

PMID28412930
PMCPMC5392934
OpenAlexW2950409671

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.