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BMC Genomics. 2017 Apr 17;18(1):301. doi: 10.1186/s12864-017-3676-8.

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

Author information

1
Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.
2
Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.
3
Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.
4
College of Pharmacy, The University of Texas at Austin, Austin, Texas, USA.
5
Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA.
6
Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA. wilke@austin.utexas.edu.
7
Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA. wilke@austin.utexas.edu.
8
Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA. wilke@austin.utexas.edu.

Abstract

BACKGROUND:

Post-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.

RESULTS:

We 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.

CONCLUSIONS:

Unbiased 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.

KEYWORDS:

Post-translational modification; Prokaryote; Proteomics

PMID:
28412930
PMCID:
PMC5392934
DOI:
10.1186/s12864-017-3676-8
[Indexed for MEDLINE]
Free PMC Article

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