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LC-MS/MS data characterising cell surface glycoproteins from chondrogenic progenitor cells and mesenchymal stem cells

dataset
posted on 2019-06-21, 10:38 authored by Csaba Matta, Christopher M. Fellows, Nicolai Miosge, James E. Dixon, Susan Liddell, Julia Smith, Ali Mobasheri
This dataset contains LC-MS/MS data generated from chondrogenic progenitor cell (CPC) and mesenchymal stem cell (MSC) surface glycoproteins, enriched with an aminooxy-biotin-based glycocapture technique. Together these results provide proteomic data on the surfaceome of two closely related cell types relevant to cartilage biology and osteoarthritis.

Data were generated with a Dionex Ultimate 3000 RSLCnano liquid chromatography (LC) system coupled with a Bruker Impact II QTOF mass spectroscopy (MS) instrument with CaptiveSpray nanoBooster source. MS acquisition rate was 5 Hz, followed by 10–20 Hz MS2 acquisition rate, depending on precursor intensity. The 20 most intense ions from each MS scan were selected for fragmentation. LC-MS/MS analysis was performed in 3 biological replicates for each sample.

For each replicate, 4 files are provided:

.baf file - A binary file in the Bruker proprietary data format, directly output from the MS instrument.
.xml file - Peak list in an XML-based format.
.mgf file - Peak list compiled in to the Mascot Generic Format (MGF).
.mzid file - MZidentML search result file generated using Mascot 2.6.

The first 3 letters of each file name indicate the cell type from which the data was generated (CPC or MSC), each with three technical replicates.

Funding

Marie Skłodowska-Curie Intra-European Fellowship for career development (project number: 625746; acronym: CHONDRION; FP7-PEOPLE-2013-IEF), European Commission Framework 7 programme (EU FP7; HEALTH.2012.2.4.5-2, project number 305815, Novel Diagnostics and Biomarkers for Early Identification of Chronic Inflammatory Joint Diseases), Deanship of Scientific Research (DSR), King AbdulAziz University (grant no. 1-141/1434 HiCi), Arthritis Research UK Centre for Sport, Exercise, and Osteoarthritis, funded by Arthritis Research UK (Grant Reference Number: 20194) and European Social Fund according to the activity ‘Improvement of researchers’ qualification by implementing world-class R&D projects’ of Measure No. 09.3.3-LMT-K-712 (grant application code: 09.3.3-LMT-K-712-01-0157, agreement No. DOTSUT-215).

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