Dataset Information

TagGraph re-analysis of a lung proteome (Peptide Atlas PAe001771), which was a component of the Wilhelm et al human proteome map

ABSTRACT: Thousands of protein post-translational modifications (PTMs) dynamically impact nearly all cellular functions. Although mass spectrometry is suited to PTM identification, it has historically been biased towards a few with established enrichment procedures. To measure all possible PTMs across diverse proteomes, software must overcome two fundamental challenges: intractably large search spaces and difficulty distinguishing correct from incorrect identifications. Here, we describe TagGraph, software that overcomes both challenges with a string-based search method that is orders of magnitude faster than current approaches, and a probabilistic validation model optimized for PTM assignments. When applied to a human proteome map, TagGraph triples confident identifications while revealing thousands of modification types spanning nearly one million sites across the proteome. We show new contexts for highly abundant yet understudied PTMs such as proline hydroxylation. TagGraph expands our ability to survey the full proteomic landscape of PTMs, shedding new light on their tissue-specific functions.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung

SUBMITTER: Joshua Elias

LAB HEAD: Joshua E Elias

PROVIDER: PXD008902 | Pride | 2019-03-12

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	Roche_human_lung_001.RAW	Raw
	Roche_human_lung_001.mzXML	Mzxml
	Roche_human_lung_002.RAW	Raw
	Roche_human_lung_002.mzXML	Mzxml
	Roche_human_lung_003.RAW	Raw

Items per page:

1 - 5 of 102

Publications

TagGraph reveals vast protein modification landscapes from large tandem mass spectrometry datasets.

Devabhaktuni Arun A Lin Sarah S Zhang Lichao L Swaminathan Kavya K Gonzalez Carlos G CG Olsson Niclas N Pearlman Samuel M SM Rawson Keith K Elias Joshua E JE

Nature biotechnology 20190401 4

Although mass spectrometry is well suited to identifying thousands of potential protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based ...[more]

PMID: 30936560

Similar Datasets

Project description:Peptides displayed by MHC molecules on a cell’s surface, referred to as its immunopeptidome, play an important role in the adaptive the immune response. Antigen processing for MHC class I presentation is a ubiquitous pathway present in all nucleated cells which generate and present peptides of both self and non-self origin. Peptides with post-translational modifications (PTMs) are one of the classes of peptides presented by MHC class I molecules. However, due to the high background of self-peptides presented by the cells, the diversity of peptides with post-translational modifications is not well reported. In this study, we have carried out MHC Class I immunopeptidomics analysis on Jurkat and A375 cell lines to characterize the diversity of post-translational modifications among MHC class I peptides. Using high resolution mass spectrometry, we identified 25,761 MHC-bound peptides across both the cell lines using Bolt and Sequest search engines. High specificity of the enrichment method is demonstrated by identifying ~90% of the peptides with typical length distribution of 8-12 aa and enriched motifs within those peptides similar to the binding motifs of MHC alleles. Among the MHC-bound peptides, we identified phosphorylation as a major post-translational modification followed by deamidation. We observed site-specific localization of these post-translational modifications, at position P4 for phosphorylated peptides and position P3 for deamidated peptides. We identified a smaller number of peptides with acetylated and methylated lysine, possibly due to very low stoichiometric levels of these post-translational modifications compared to phosphorylation and deamidation. Using PEAKS de novo sequencing algorithm, we identified spliced peptides that account for ~5-7% of MHC-bound peptides across the two cell lines. These peptides share similar features with respect to normal MHC-bound peptides such as peptide length distribution and binding motifs. We validated the identification of several post-translationally modified peptides and spliced peptides using synthetic peptide sequences. In conclusion, our study demonstrates unbiased identification of these low stoichiometric PTMs and unusual spliced peptides using high resolution mass spectrometry.