Dataset Information

Bloodstream infection N-glycoproteomics

ABSTRACT: Here we have performed targeted quantitative N-glycoproteomics from plasma samples of patients with confirmed positive blood culture together with age and sex matched febrile controls with negative blood culture reports. Three hundred and sixty eight potential N-glycopeptides were quantified by mass spectrometry and 149 were further selected for identification. Twenty four N-glycopeptides were identified with high confidence together with elucidation of the peptide sequence, N-glycosylation site, glycan composition and proposed glycan structures. these N-glycopeptides can be used as potential biomarkers of bloodstream infection.

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: Sakari Joenväärä

LAB HEAD: Risto Renkonen

PROVIDER: PXD009048 | Pride | 2018-04-09

REPOSITORIES: pride

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Dataset's files

Source:

			Action	DRS
	20151117_KUUSELA_01a.raw.zip	Raw
	20151117_KUUSELA_01b.raw.zip	Raw
	20151117_KUUSELA_01bMS2.raw.zip	Raw
	20151117_KUUSELA_01c.raw.zip	Raw
	20151117_KUUSELA_02a.raw.zip	Raw

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Publications

Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients.

Joenvaara Sakari S Saraswat Mayank M Kuusela Pentti P Saraswat Shruti S Agarwal Rahul R Kaartinen Johanna J Järvinen Asko A Renkonen Risto R

PloS one 20180329 3

Bloodstream infections are associated with high morbidity and mortality with rates varying from 10-25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infecti ...[more]

PMID: 29596458

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Project description:Large-scale identification of N-linked intact glycopeptides by liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) in human serum is challenging due to the wide dynamic range of serum protein abundances, the lack of a complete serum N-Glycan database and the existence of non-specifically digested peptides and numerous modifications. In this regard, a spectral library search method was presented for serum N-linked intact glycopeptides identification with target-decoy and motif-specific false discovery rate (FDR) control. Low-abundant glycoproteins were firstly separated from high-abundant proteins by acetonitrile (ACN) precipitation. After digestion, the N-linked intact glycopeptides were enriched by hydrophilic interaction liquid chromatography (HILIC) column and a portion of the enriched N-linked intact glycopeptides were processed by N-Glycosidase F (PNGase F) to generate de-glycopeptides. Both N-linked intact glycopeptides and de-glycopeptides were analyzed by LC-MS/MS. From N-linked de-glycopeptides datasets, 764 N-linked glycoproteins, 1,699 N-linked glycosites and 3,328 unique N-linked de-glycopeptides were identified. The spectra of these N-linked de-glycopeptides were utilized for N-linked de-glycopeptides library construction and identification of N-linked intact glycopeptides. Four types of N-linked glycosylation motifs (NXS/T/C/V, X≠P) were used to recognize the N-linked de-glycopeptides, and two different N-Glycan mass databases including 27 modified N-Glycan masses and 712 unmodified N-Glycan masses were combined and utilized during spectral library search for identification of N-linked intact glycopeptides. In total, from the N-linked intact glycopeptides datasets, 526 N-linked glycoproteins, 1,036 N-linked glycosites, 22,677 N-linked intact glycopeptides and 738 N-Glycan masses were identified under 1% FDR, representing the most in-depth serum N-glycoproteome identified by LC-MS/MS at N-linked intact glycopeptide level and N-linked de-glycopeptides level.