Evidence map›Paper›PMID 37292769›Full record

ArticlebioRxiv : the preprint server for biology2023

"Ghost" fragment ions in structure and site-specific glycoproteomics analysis.

Diana Campos, Michael Girgis, Qiang Yang, Guanghui Zong, Radoslav Goldman, Lai-Xi Wang, Miloslav Sanda

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Diana CamposMax-Planck-Institut fuer Herz- und Lungenforschung, Ludwigstrasse 43, Bad Nauheim, 61231, Germany.
Michael GirgisDepartment of Bioengineering, College of Engineering and Computing, George Mason University, Fairfax, VA, USA.
Qiang YangGlycoT Therapeutics, College Park, MD, USA.
Guanghui ZongDepartment of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742.
Radoslav GoldmanDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, D.C.
Lai-Xi WangDepartment of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742.
Miloslav SandaMax-Planck-Institut fuer Herz- und Lungenforschung, Ludwigstrasse 43, Bad Nauheim, 61231, Germany.

Funding

LC-MS Analysis of Site Specific Protein GlycoformsU01CA230692 · NCI · GEORGETOWN UNIVERSITY · PI EDWARDS, NATHAN J, GOLDMAN, RADOSLAV · 2018 to 2020
$1.3M
NCI NIH HHS U01 CA230692
6 · The paper itself

Abstract

Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties, however, specificity of these fragments has never been examined closely. Here, we investigated fragmentation specificity using synthetic stable isotope-labelled glycopeptide standards. These standards were isotopically labelled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent the misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements. Graphical abstract:

Identifiers

PMID37292769
PMCPMC10245710

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.