scholarly journals Post-translational modification of nucleoid-associated proteins: an extra layer of functional modulation in bacteria?

2018 ◽  
Vol 46 (5) ◽  
pp. 1381-1392 ◽  
Author(s):  
Ivar W. Dilweg ◽  
Remus T. Dame
Keyword(s):  
Mass Spectrometry ◽  
Genetic Information ◽  
Structural Integrity ◽  
Mass Spectrometry Data ◽  
Post Translational Modification ◽  
Functional Importance ◽  
Widespread Occurrence ◽  
Associated Proteins ◽  
Chromatin Folding ◽  
Functional Modulation

Post-translational modification (PTM) of histones has been investigated in eukaryotes for years, revealing its widespread occurrence and functional importance. Many PTMs affect chromatin folding and gene activity. Only recently the occurrence of such modifications has been recognized in bacteria. However, it is unclear whether PTM of the bacterial counterparts of eukaryotic histones, nucleoid-associated proteins (NAPs), bears a comparable significance. Here, we scrutinize proteome mass spectrometry data for PTMs of the four most abundantly present NAPs in Escherichia coli (H-NS, HU, IHF and FIS). This approach allowed us to identify a total of 101 unique PTMs in the 11 independent proteomic studies covered in this review. Combined with structural and genetic information on these proteins, we describe potential effects of these modifications (perturbed DNA-binding, structural integrity or interaction with other proteins) on their function.

scholarly journals MoMo: discovery of statistically significant post-translational modification motifs

2018 ◽  
Vol 35 (16) ◽  
pp. 2774-2782 ◽  
Author(s):  
Alice Cheng ◽  
Charles E Grant ◽  
William S Noble ◽  
Timothy L Bailey
Keyword(s):  
Mass Spectrometry ◽  
Motif Discovery ◽  
Source Code ◽  
Web Server ◽  
Software Tool ◽  
Mass Spectrometry Data ◽  
Supplementary Information ◽  
Post Translational Modification ◽  
Statistical Confidence ◽  
Confidence Estimates

Abstract Motivation Post-translational modifications (PTMs) of proteins are associated with many significant biological functions and can be identified in high throughput using tandem mass spectrometry. Many PTMs are associated with short sequence patterns called ‘motifs’ that help localize the modifying enzyme. Accordingly, many algorithms have been designed to identify these motifs from mass spectrometry data. Accurate statistical confidence estimates for discovered motifs are critically important for proper interpretation and in the design of downstream experimental validation. Results We describe a method for assigning statistical confidence estimates to PTM motifs, and we demonstrate that this method provides accurate P-values on both simulated and real data. Our methods are implemented in MoMo, a software tool for discovering motifs among sets of PTMs that we make available as a web server and as downloadable source code. MoMo re-implements the two most widely used PTM motif discovery algorithms—motif-x and MoDL—while offering many enhancements. Relative to motif-x, MoMo offers improved statistical confidence estimates and more accurate calculation of motif scores. The MoMo web server offers more proteome databases, more input formats, larger inputs and longer running times than the motif-x web server. Finally, our study demonstrates that the confidence estimates produced by motif-x are inaccurate. This inaccuracy stems in part from the common practice of drawing ‘background’ peptides from an unshuffled proteome database. Our results thus suggest that many of the papers that use motif-x to find motifs may be reporting results that lack statistical support. Availability and implementation The MoMo web server and source code are provided at http://meme-suite.org. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MoMo: Discovery of post-translational modification motifs

2017 ◽  
Author(s):  
Alice Cheng ◽  
Charles E. Grant ◽  
Timothy L. Bailey ◽  
William Stafford Noble
Keyword(s):  
Mass Spectrometry ◽  
Source Code ◽  
Software Tool ◽  
Mass Spectrometry Data ◽  
Supplementary Information ◽  
Biological Functions ◽  
Post Translational Modification ◽  
Post Translational Modifications ◽  
Sequence Patterns ◽  
Supplementary Material

AbstractMotivationPost-translational modifications (PTMs) of proteins are associated with many significant biological functions and can be identified in high throughput using tandem mass spectrometry. Many PTMs are associated with short sequence patterns called “motifs” that help localize the modifying enzyme. Accordingly, many algorithms have been designed to identify these motifs from mass spectrometry data.ResultsMoMo is a software tool for identifying motifs among sets of PTMs. The program re-implements two previously described algorithms, Motif-X and MoDL, packaging them in a web-accessible user interface. In addition to reading sequence files in FASTA format, MoMo is capable of directly parsing output files produced by commonly used mass spectrometry search engines. The resulting motifs are presented to the user in an HTML summary with motif logos and linked text files in MEME motif format.AvailabilitySource code and web server available at http://[email protected] and [email protected] informationSupplementary figures are available at Bioinformatics online.

scholarly journals The phospho-docking protein 14-3-3 regulates microtubule-associated proteins in oocytes including the chromosomal passenger Borealin

2021 ◽  
Author(s):  
Charlotte Repton ◽  
C Fiona Cullen ◽  
Mariana FA Costa ◽  
Christos Spanos ◽  
Juri Rappsilber ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Regulatory Mechanism ◽  
Mass Spectrometry Data ◽  
Quantitative Mass Spectrometry ◽  
Microtubule Associated Proteins ◽  
Chromosomal Passenger ◽  
Associated Proteins ◽  
And Function ◽  
Systematic Identification ◽  
Docking Protein

Global regulation of spindle-associated proteins is crucial in oocytes due to the absence of centrosomes and their very large cytoplasmic volume, but little is known about how this is achieved beyond involvement of the Ran-importin pathway. We previously uncovered a novel regulatory mechanism in Drosophila oocytes, in which the phospho-docking protein 14-3-3 suppresses microtubule binding of Kinesin-14/Ncd away from chromosomes. Here we report systematic identification of microtubule-associated proteins regulated by 14-3-3 from Drosophila oocytes. Proteins from ovary extract were co-sedimented with microtubules in the presence or absence of a 14-3-3 inhibitor. Through quantitative mass-spectrometry, we identified proteins or complexes whose ability to binding microtubules is suppressed by 14-3-3, including the chromosomal passenger complex (CPC), the centralspindlin complex and Kinesin-14/Ncd. We showed that 14-3-3 binds to the disordered region of Borealin, and this binding is regulated differentially by two phosphorylations on Borealin. Mutations at these two phospho-sites compromised normal Borealin localisation and centromere bi-orientation in oocytes, showing that phospho-regulation of 14-3-3 binding is important for Borealin localisation and function. The mass spectrometry data are available from ProteomeXchange, identifier ID to be provided when available, PXD000xxx.

scholarly journals MoMo: Discovery of statistically significant post-translational modification motifs

2018 ◽  
Author(s):  
Alice Cheng ◽  
Charles E. Grant ◽  
William S. Noble ◽  
Timothy L. Bailey
Keyword(s):  
Mass Spectrometry ◽  
Motif Discovery ◽  
Web Server ◽  
Software Tool ◽  
Real Data ◽  
Mass Spectrometry Data ◽  
Post Translational Modification ◽  
Statistical Confidence ◽  
Proteome Database ◽  
Confidence Estimates

AbstractMotivationPost-translational modifications (PTMs) of proteins are associated with many significant biological functions and can be identified in high throughput using tandem mass spectrometry. Many PTMs are associated with short sequence patterns called “motifs” that help localize the modifying enzyme. Accordingly, many algorithms have been designed to identify these motifs from mass spectrometry data. Accurate statistical confidence estimates for discovered motifs are critically important for proper interpretation and in the design of downstream experimental validation.ResultsWe describe a method for assigning statistical confidence estimates to PTM motifs, and we demonstrate that this method provides accurate p-values on both simulated and real data. Our methods are implemented in MoMo, a software tool for discovering motifs among sets of PTMs that we make available as a web server and as downloadable source code. MoMo reimplements the two most widely used PTM motif discovery algorithms—motif-x and MoDL—while offering many enhancements. Relative to motif-x, MoMo offers improved statistical confidence estimates and more accurate calculation of motif scores. The MoMo web server offers more proteome databases, more input formats, larger inputs and longer running times than the motif-x web server. Finally, our study demonstrates that the confidence estimates produced by motif-x are inaccurate. This inaccuracy stems in part from the common practice of drawing “background” peptides from an unshuffled proteome database. Our results thus suggest that many of the hundreds of papers that use motif-x to find motifs may be reporting results that lack statistical support.Availabilityhttp://[email protected]

Dicarbonyl derived post-translational modifications: chemistry bridging biology and aging-related disease

2020 ◽  
Vol 64 (1) ◽  
pp. 97-110
Author(s):  
Christian Sibbersen ◽  
Mogens Johannsen
Keyword(s):  
Mass Spectrometry ◽  
Future Research ◽  
Amino Acid Residues ◽  
Post Translational Modification ◽  
Dicarbonyl Compounds ◽  
Protein Targets ◽  
Post Translational Modifications ◽  
Reactive Protein ◽  
Glycation End Products ◽  
Direct Mass Spectrometry

Abstract In living systems, nucleophilic amino acid residues are prone to non-enzymatic post-translational modification by electrophiles. α-Dicarbonyl compounds are a special type of electrophiles that can react irreversibly with lysine, arginine, and cysteine residues via complex mechanisms to form post-translational modifications known as advanced glycation end-products (AGEs). Glyoxal, methylglyoxal, and 3-deoxyglucosone are the major endogenous dicarbonyls, with methylglyoxal being the most well-studied. There are several routes that lead to the formation of dicarbonyl compounds, most originating from glucose and glucose metabolism, such as the non-enzymatic decomposition of glycolytic intermediates and fructosyl amines. Although dicarbonyls are removed continuously mainly via the glyoxalase system, several conditions lead to an increase in dicarbonyl concentration and thereby AGE formation. AGEs have been implicated in diabetes and aging-related diseases, and for this reason the elucidation of their structure as well as protein targets is of great interest. Though the dicarbonyls and reactive protein side chains are of relatively simple nature, the structures of the adducts as well as their mechanism of formation are not that trivial. Furthermore, detection of sites of modification can be demanding and current best practices rely on either direct mass spectrometry or various methods of enrichment based on antibodies or click chemistry followed by mass spectrometry. Future research into the structure of these adducts and protein targets of dicarbonyl compounds may improve the understanding of how the mechanisms of diabetes and aging-related physiological damage occur.

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction

Nonparametric Pre-Processing Methods and Inference Tools for Analyzing Time-of-Flight Mass Spectrometry Data.

2007 ◽  
Vol 3 (2) ◽  
pp. 127-147 ◽  
Author(s):  
Anestis Antoniadis ◽  
Jeremie Bigot ◽  
Sophie Lambert-Lacroix ◽  
Frederique Letue
Keyword(s):  
Mass Spectrometry ◽  
Time Of Flight ◽  
Mass Spectrometry Data ◽  
Processing Methods ◽  
Flight Mass Spectrometry

scholarly journals N-Terminomics Strategies for Protease Substrates Profiling

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4699
Author(s):  
Mubashir Mintoo ◽  
Amritangshu Chakravarty ◽  
Ronak Tilvawala
Keyword(s):  
Mass Spectrometry ◽  
Protease Activity ◽  
Viral Infections ◽  
Mass Spectrometry Analysis ◽  
Post Translational Modification ◽  
Spectrometry Analysis ◽  
Physiological Conditions ◽  
Inflammatory Conditions ◽  
Biological Mixtures

Proteases play a central role in various biochemical pathways catalyzing and regulating key biological events. Proteases catalyze an irreversible post-translational modification called proteolysis by hydrolyzing peptide bonds in proteins. Given the destructive potential of proteolysis, protease activity is tightly regulated. Dysregulation of protease activity has been reported in numerous disease conditions, including cancers, neurodegenerative diseases, inflammatory conditions, cardiovascular diseases, and viral infections. The proteolytic profile of a cell, tissue, or organ is governed by protease activation, activity, and substrate specificity. Thus, identifying protease substrates and proteolytic events under physiological conditions can provide crucial information about how the change in protease regulation can alter the cellular proteolytic landscape. In recent years, mass spectrometry-based techniques called N-terminomics have become instrumental in identifying protease substrates from complex biological mixtures. N-terminomics employs the labeling and enrichment of native and neo-N-termini peptides, generated upon proteolysis followed by mass spectrometry analysis allowing protease substrate profiling directly from biological samples. In this review, we provide a brief overview of N-terminomics techniques, focusing on their strengths, weaknesses, limitations, and providing specific examples where they were successfully employed to identify protease substrates in vivo and under physiological conditions. In addition, we explore the current trends in the protease field and the potential for future developments.

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