PXD015987

PXD015987 is an original dataset announced via ProteomeXchange.

Title	An integrated MS data processing strategy for fast identification, in-depth and reproducible quantification of protein O-glycosylation in large cohorts of human urine samples
Description	Protein O-glycosylation has long been recognized to be closely associated with many diseases, particularly with tumor proliferation, invasion and metastasis. The ability to efficiently profile the variation of O-glycosylation in large-scale clinical samples provides an important approach for the development of biomarkers for cancer diagnosis and for therapeutic response evaluation. Therefore, mass spectrometry (MS)-based techniques for high throughput, in-depth and reliable elucidation of protein O-glycosylation in large clinical cohorts are in high demand. However, the wide existence of serine and threonine residues in the proteome and the tens of mammalian O-glycan types lead to extremely large searching space composed of millions of theoretical combinations of peptides and O-glycans for intact O-glycopeptide database searching. As a result, exceptionally long time is required for database searching which is a major obstacle in O-glycoproteome studies of large clinical cohorts. More importantly, due to the low abundance and poor ionization of intact O-glycopeptides and the stochastic nature of data-dependent MS2 acquisition, substantially elevated missing data levels are inevitable as the sample number increases, which undermines the quantitative comparison across samples. Therefore, we report a new MS data processing strategy that integrates glycoform-specific database searching, reference library-based MS1 feature matching and MS2 identification propagation for fast identification, in-depth and reproducible label-free quantification of O-glycosylation of human urinary proteins. This strategy increases the database searching speeds by up to 20-fold and leads to a 30-40% enhanced intact O-glycopeptide quantification in individual samples with an obviously improved reproducibility. In total, we obtained quantitative information for 1068 intact O-glycopeptides across 36 healthy human urine samples with a 30-40% reduction in the amount of missing data. This is currently the largest dataset of urinary O-glycoproteome and demonstrates the application potential of this new strategy in large-scale clinical investigations.
HostingRepository	PRIDE
AnnounceDate	2020-02-04
AnnouncementXML	Submission_2020-02-04_09:12:05.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Xinyuan Zhao
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	monohydroxylated residue; complex glycosylation; iodoacetamide derivatized residue
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2019-10-23 06:12:00	ID requested
⏵ 1	2020-02-04 09:12:07	announced

Zhao X, Zheng S, Li Y, Huang J, Zhang W, Xie Y, Qin W, Qian X, -Glycosylation in a Large Cohort of Human Urine Samples. Anal Chem, 92(1):690-698(2020) [pubmed]

submitter keyword: O-glycopeptide

urine

sialic acid

Weijie Qin
contact affiliation	National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, PR China
contact email	aunp_dna@126.com
lab head
Xinyuan Zhao
contact affiliation	National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, PR China
contact email	zhaoxinyuan@foxmail.com
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2020/02/PXD015987

PRIDE project URI

• PRIDE
  1. PXD015987
     1. Label: PRIDE project
     2. Name: An integrated MS data processing strategy for fast identification, in-depth and reproducible quantification of protein O-glycosylation in large cohorts of human urine samples