Browse
Submit Data
Databases
API
Help

Dataset Information

374 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantitative analysis and prediction of protein glycation (SystemsX Project)

ABSTRACT: Glycated proteins identified in human plasma by HCD-MS2 and CID-MS3 analysis with the experiment for predictive analysis

INSTRUMENT(S): LTQ Orbitrap, instrument model, LTQ Orbitrap XL

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: MARIA RAMIREZ

PROVIDER: PRD000346 | Pride | 2010-12-03

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Similar Datasets

GNPS Toronamide high-resolution MS2 and MS3

Project description:High-resolution targeted and DDA MS2 and MS3 experiments of Toronamide. (Orbitrap readout with HCD and CID)

2020-01-05 | MSV000084754 | GNPS

TMT data from ovarian cancer cells

Project description:In this project we want to compare ovarian cell cancer treated or non treated with cis-platinum. As acquisition strategy we have used a Real Time Search MS3 method in an Orbitrap Eclipse. The acquisition cycle began with an MS1 scanwhere the most intense ions were selected for fragmentation in the ion trap using CID. MS2 spectra were searched in real time with data acquisition using the sp-human database. MS2 spectra with an Xcorr greater than or equal to 1 and less than 10 ppm precursor mas error, triggered the submission of an MS3 spectrum to the instrument. MS3 spectrum, were collected using the multinotch MS3-based TMT method, in a way were ten MS2 fragment ions were captured in the MS3 precursor population using isolation waveforms with multiple frequency notches

2023-05-04 | PXD041002 | Pride

Glycoroteomics profiling of amyloid precursor protein

Project description:We developed TMMF strategy (Targeted MS strategy combined with Multi-Fragmentation) which provided plenty information of targeted glycopeptides based on complementary MS2 spectra from HCD, ETD and CID in a single MS run.

2021-03-12 | PXD024705 | iProX

pFAIMS: An optimized workflow for quantitative multiplexed phosphorylation analysis using high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS)

Project description:Protein phosphorylation is vital for the regulation of cellular signaling. Isobaric tag-based proteomic techniques, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the overall low stoichiometry of protein phosphorylation constrains the analytical depth of phosphopeptide analysis by mass spectrometry, thereby requiring robust and sensitive workflows. Here we evaluate and optimize high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) coupled to Orbitrap Tribrid mass spectrometers for the analysis of TMT10plex-labeled phosphopeptides. We determined that using FAIMS-SPS-MS3 with three compensation voltages (CV) in a single method minimizes inter-CV overlap and maximizes peptide coverage (e.g., CV=-40V/-60V/-80V) and that consecutive analyses using CID-MSA and HCD fragmentation at the MS2 stage increases the depth of phosphorylation analysis.

2020-01-10 | PXD014593 | Pride

Optimized TMT-based quantitative cross-linking mass spectrometry strategy for large-scale interactomic studies

Project description:Cross-linking mass spectrometry is a powerful method for the investigation of protein-protein interactions from highly complex samples. XL-MS combined with tandem mass tag labeling holds the promise of large-scale PPI quantification. However, a robust and efficient TMT-based XL-MS quantification method has not yet been established due to the lack of a benchmarking dataset and thorough evaluation of various MS parameters. To tackle these limitations, we generate a two-interactome dataset by spiking-in TMT-labeled cross-linked E. coli lysate into TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Using this benchmarking dataset, we assess the efficacy of cross-link identification and accuracy of cross-link quantification using different MS acquisition strategies. For identification, we compare various MS2- and MS3-based XL-MS methods, and optimize stepped HCD energies for TMT-labeled cross-links. We observed a need for notably higher fragmentation energies compared to unlabeled cross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3- and synchronous precursor selection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vast number of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexed quantitative PPI characterization from complex biological systems.

2022-04-07 | PXD031114 | Pride

Bovine protein glycation sites in different milk products

Project description:Here we studied the glycation of bovine milk proteins by lactose as dominant sugar in milk and hexoses using tandem mass spectrometry (CID and ETD mode). In a bottom-up proteomics approach after enriching glycated peptides by boronate affinity chromatography, first we could identify 260 lactosylated peptides corresponding to 124 lactosylation sites in 28 bovine milk proteins in raw milk, raw colostrum, three brands of pasteurized milk, three brands of UHT milk, and five brands of infant formula. The same regular and additionally two lactose-free milk products (pasteurized and UHT milk) where lactose is enzymatically cleaved into the more reactive hexoses were analyzed in terms of hexosylation sites that resulted in identification of 124 hexosylated tryptic peptides corresponding to 86 glycation sites in 17 bovine milk proteins. In quantitative terms glycation increased from raw milk to pasteurized milk to UHT milk and infant formula, i.e., with the harsher processing conditions. Lactose-free milk contained significantly higher hexosylation degrees than the corresponding regular milk product.

2016-01-11 | PXD003054 | Pride

GNPS Phenolic standard compounds by direct-infusion negative ESI tandem Orbitrap MS

Project description:This dataset consists of fragmentation data (MS2, MS3) obtained from a set of 14 standard compounds. The standards were measured in 2017 in negative ESI mode at collision energies from 10-40 (CID, N2) and 30-130 (HCD, N2). Each MS/MS spectrum was obtained by averaging 150 scans. For some product ions, also MS3 were acquired. See the upcoming manuscript for further details.

2021-03-31 | MSV000087133 | GNPS

Identify Yeast Proteasome Cross-links with Multiple Ion Fragmentation Methods

Project description:Use of EThcD, CID, HCD and high energy HCD to identify protein cross-links

2020-06-18 | PXD018310 | Pride

Engineered chemotaxis core signaling units

Project description:Identificaiton of bacterial chemoreceptors by DSSO-based MS2-MS3 method.

2021-09-09 | PXD019599 | Pride

Benchmarking LFQ, SILAC and MS2/MS3-based TMT quantification strategies for large-scale phosphoproteomics

Project description:Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible and multiplexed quantification remains challenging especially for analysis of post-translational modifications (PTMs), such as phosphorylation. Here we compared the most popular quantification techniques for phosphoproteomics in context of cell-signaling studies: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS2- and MS3-measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide-ratios, we found LFQ and SILAC to be the most accurate techniques. MS2-based TMT suffered from substantial ratio compression, which MS3-based TMT could partly rescue. However, when analyzing phosphoproteome changes in the DNA damage response (DDR), we found that MS3-based TMT was outperformed by MS2-based TMT as it identified most significantly regulated phosphopeptides due to its higher precision and higher number of identifications. Finally, we show that the high accuracy of MS3-based TMT is crucial for determination of phosphorylation site stoichiometry using a novel multiplexing-dependent algorithm.

2018-03-13 | PXD007145 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data