Dataset Information

Experimental determination of translational starts using peptide mass mapping and tandem mass spectrometry within the proteome of Mycobacterium tuberculosis.

ABSTRACT: Identification of protein translation start sites is largely a bioinformatics exercise, with relatively few confirmed by N-terminal sequencing. Translation start site determination is critical for defining both the protein sequence and the upstream DNA which may contain regulatory motifs. It is demonstrated here that translation start sites can be determined during routine protein identification, using MALDI-MS and MS/MS data to select the correct N-terminal sequence from a list of alternatives generated in silico. Applying the method to 13 proteins from Mycobacterium tuberculosis, 11 predicted translational start sites were confirmed, and two reassigned. The authors suggest that these data (be they confirmation or reassignments) are important for the annotation of both this genome and those of organisms with related genes. It was also shown that N-acetylation, reported to be rare in prokaryotes, was present in three of the 13 proteins (23 %), suggesting that in the mycobacteria this modification may be common, and an important regulator of protein function, although more proteins need to be analysed. This method can be performed with little or no additional experimental work during proteomics investigations.

SUBMITTER: Rison SCG

PROVIDER: S-EPMC2884946 | biostudies-literature | 2007 Feb

REPOSITORIES: biostudies-literature

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Experimental determination of translational starts using peptide mass mapping and tandem mass spectrometry within the proteome of Mycobacterium tuberculosis.

Rison Stuart C G SCG Mattow Jens J Jungblut Peter R PR Stoker Neil G NG

Microbiology (Reading, England) 20070201 Pt 2

Identification of protein translation start sites is largely a bioinformatics exercise, with relatively few confirmed by N-terminal sequencing. Translation start site determination is critical for defining both the protein sequence and the upstream DNA which may contain regulatory motifs. It is demonstrated here that translation start sites can be determined during routine protein identification, using MALDI-MS and MS/MS data to select the correct N-terminal sequence from a list of alternatives ...[more]

PMID: 17259624

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Project description:MotivationA post-translational modification (PTM) is a chemical modification of a protein that occurs naturally. Many of these modifications, such as phosphorylation, are known to play pivotal roles in the regulation of protein function. Henceforth, PTM perturbations have been linked to diverse diseases like Parkinson's, Alzheimer's, diabetes and cancer. To discover PTMs on a genome-wide scale, there is a recent surge of interest in analyzing tandem mass spectrometry data, and several unrestrictive (so-called 'blind') PTM search methods have been reported. However, these approaches are subject to noise in mass measurements and in the predicted modification site (amino acid position) within peptides, which can result in false PTM assignments.ResultsTo address these issues, we devised a machine learning algorithm, PTMClust, that can be applied to the output of blind PTM search methods to improve prediction quality, by suppressing noise in the data and clustering peptides with the same underlying modification to form PTM groups. We show that our technique outperforms two standard clustering algorithms on a simulated dataset. Additionally, we show that our algorithm significantly improves sensitivity and specificity when applied to the output of three different blind PTM search engines, SIMS, InsPecT and MODmap. Additionally, PTMClust markedly outperforms another PTM refinement algorithm, PTMFinder. We demonstrate that our technique is able to reduce false PTM assignments, improve overall detection coverage and facilitate novel PTM discovery, including terminus modifications. We applied our technique to a large-scale yeast MS/MS proteome profiling dataset and found numerous known and novel PTMs. Accurately identifying modifications in protein sequences is a critical first step for PTM profiling, and thus our approach may benefit routine proteomic analysis.AvailabilityOur algorithm is implemented in Matlab and is freely available for academic use. The software is available online from http://genes.toronto.edu.

Dataset Information

Experimental determination of translational starts using peptide mass mapping and tandem mass spectrometry within the proteome of Mycobacterium tuberculosis.

Publications

Experimental determination of translational starts using peptide mass mapping and tandem mass spectrometry within the proteome of Mycobacterium tuberculosis.

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