Dataset Information

A375 melanoma cell line, Expanded database search comparisons

ABSTRACT: Thousands of protein post-translational modifications (PTMs) dynamically impact nearly all cellular functions. Mass spectrometry is well suited to PTM identification, but proteome-scale analyses are biased towards PTMs with existing enrichment methods. To measure the full landscape of PTM regulation, 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 orders of magnitude faster than current approaches, and probabilistic validation model optimized for PTM assignments. When applied to a human proteome map, TagGraph tripled confident identifications while revealing thousands of modification types on nearly one million sites spanning the proteome. We expand known sites by orders of magnitude for highly abundant yet understudied PTMs such as proline hydroxylation, and derive tissue-specific insight into these PTMs’ roles. TagGraph expands our ability to survey the full landscape of PTM function and regulation.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Melanocyte, Skin

SUBMITTER: Joshua Elias

LAB HEAD: Joshua E. Elias

PROVIDER: PXD005912 | Pride | 2019-03-12

REPOSITORIES: Pride

ACCESS DATA

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:Both genetic and environmental factors are implicated in Type 1 Diabetes (T1D). Since environmental factors can trigger epigenetic changes, we hypothesized that variations in histone posttranslational modifications (PTMs) at the promoter/enhancer regions of T1D susceptible genes may be associated with T1D. We therefore evaluated histone PTM variations at known T1D susceptible genes in blood cells from T1D patients versus healthy non-diabetic controls, and explored their connections to T1D. We used the chromatin-immunoprecipitation-linked-to-microarray approach to profile key histone PTMs, including H3-lysine-4 trimethylation (H3K4me3), H3K27me3, H3K9me3, H3K9 acetylation (H3K9Ac) and H4K16Ac at genes within the T1D susceptible loci in lymphocytes, and H3K4me3, H3K9me2, H3K9Ac and H4K16Ac at the IDDM1 region in monocytes of T1D patients and healthy controls separately. We screened for potential variations in histone PTMs using computational methods to compare datasets from T1D and controls. Interestingly, we observed marked variations in H3K9Ac levels at the upstream regions of HLA-DRB1 and HLA-DQB1 within the IDDM1 locus in T1D monocytes relative to controls. Additional experiments with THP-1 monocytes demonstrated increased expression of HLA-DRB1 and HLA-DQB1 in response to interferon- and TNF-treatment that were accompanied by changes in H3K9Ac at the same promoter regions as that seen in the patient monocytes. These results suggest that the H3K9Ac status of HLA-DRB1 and HLA-DQB1, two genes highly associated with T1D, may be relevant to their regulation and transcriptional response towards external stimuli. Thus, the promoter/enhancer architecture and chromatin status of key susceptible loci could be important determinants in their functional association to T1D susceptibility. We evaluated histone PTM variations at known T1D susceptible genes in blood cells from T1D patients versus healthy non-diabetic controls, and explored their connections to T1D. We used the ChIP-chip approach to profile key histone PTMs, including histone H3K4me3, H3K27me3, H3K9me3, H3K9 acetylation (H3K9Ac) and H4K16Ac, at genes within the T1D susceptible loci in lymphocytes.

Dataset Information

A375 melanoma cell line, Expanded database search comparisons

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure