PXD008562

PXD008562 is an original dataset announced via ProteomeXchange.

Title	Displacement Chromatography Mode – High protein sequence coverages and identification rates for low µg-range proteomics using online 2D-LC-MS
Description	In bottom-up proteomics, the complexity of proteomes is still a challenge. For deep proteome profiling, multi-dimensional separation strategies and large initial protein amounts are required. Here, we report on an online 2D-LC-MS/MS approach applying strong cation exchange chromatography (SCX) in displacement chromatography mode (DCM) as the first dimension of separation. This method enables a comprehensive analysis of proteomes in the low µg-range (5 µg). The first detailed comparison of DCM with conventionally used gradient chromatography mode (GCM) highlights a significantly better separation efficiency with DCM. Especially for peptides with a net-charge state (NCS) of +2, which represents the majority of tryptic peptides in mammalian proteomes, DCM provides a significantly better separation. These peptides were separated over several fractions in DCM, which is not possible to achieve in GCM due to theirs low affinity towards the SCX column. The better separation in DCM results not only in a considerably higher reproducibility (Pearson’s r=0.93), but significantly increases identification rates of both peptides and proteins. For peptides with a low NCS, DCM achieved a 2.6-fold increase in identified peptides. In total, DCM provides a 1.5-fold increase in peptide identifications and a 1.7-fold increase of protein identifications. The number of identified unique peptides per protein and the protein sequence coverages were significantly higher in DCM compared to GCM providing more reliable quantitative results. The higher sequence coverage are of interest for applications such as proteogenomics, where it is important to have high protein sequence coverages to identify single amino acid variants and splice-junction peptides.
HostingRepository	PRIDE
AnnounceDate	2024-10-22
AnnouncementXML	Submission_2024-10-22_04:12:41.811.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Marcel Kwiatkowski
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Orbitrap Fusion

Revision	Datetime	Status	ChangeLog Entry
0	2018-01-02 01:06:15	ID requested
1	2018-10-17 00:21:59	announced
⏵ 2	2024-10-22 04:12:45	announced	2024-10-22: Updated project metadata.

Kwiatkowski M, Kr, ö, sser D, Wurlitzer M, Steffen P, Barcaru A, Krisp C, Horvatovich P, Bischoff R, Schl, ü, ter H, Application of Displacement Chromatography to Online Two-Dimensional Liquid Chromatography Coupled to Tandem Mass Spectrometry Improves Peptide Separation Efficiency and Detectability for the Analysis of Complex Proteomes. Anal Chem, 90(16):9951-9958(2018) [pubmed]

10.1021/acs.analchem.8b02189;

curator keyword: Technical

submitter keyword: proteomics,displacement chromatography, online 2D-LC-MS

Hartmut Schlüter
contact affiliation	Mass Spectrometric Proteomics, Institute of Clinical Chemistry, University Medical Center Hamburg-Eppendorf.
contact email	h.schluet@uke.de
lab head
Marcel Kwiatkowski
contact affiliation	University of Groningen
contact email	m.d.kwiatkowski@rug.nl
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/2018/10/PXD008562

PRIDE project URI

• PRIDE
  1. PXD008562
     1. Label: PRIDE project
     2. Name: Displacement Chromatography Mode – High protein sequence coverages and identification rates for low µg-range proteomics using online 2D-LC-MS