Multiple Sclerosis (MS) is the most common disabling neurologic disease of young people. The pathological course of MS is heterogeneous in clinical manifestations, response to therapies and outcome, in addition to distinctive clinical courses. For relapsing remitting multiple sclerosis (RRMS) there is need to identify accurately relapse , defined as new or worsening clinical symptoms associated with an acute inflammatory demyelinating event which is followed by remission, in order to diagnose and classify the clinical course as well as to guide patient management reliable. In this study, the protein composition of Extracellular Vesicles, purified from plasma and cerebrospinal fluid (CSF) samples of RRMS patients with relapse and in remission, were evaluated through a proteomic approach to identify candidate biomarkers for MS relapse.
Proteins extracted from each sample were loaded on a gradient polyacrylamide gel, run in MOPS buffer and stained with the colloidal blue staining kit.
Each gel lane was cut into at least 10 contiguous slices, which were subjected to trypsin digestion after reduction and alkylation steps. The resulting peptide mixtures were separated by a nanoflow reversed phase liquid chromatography tandem mass spectrometry using an Ultimate 3000 HPLC connected with a linear ion trap (LTQ XL, ThermoElectron, San Jose, CA, USA) equipped with a nano electrospray ion source (ESI). Peptides were desalted in a trap column and separated in a 10 cm long reverse phase column slurry packed in house with 5 um, 200 A pore size C18 resin.
Peptides were eluted using a 50 minutes linear gradient from 4 to 80% buffer B (95% acetonitrile and 0.1% formic acid) while buffer A was constituted by 5% acetonitrile and 0.1% formic acid, at 300 nL/min flow rate. Peptide separation was preceded by a 5 min equilibration step at 4% buffer B and followed by 3 min washing step at 90% buffer B and an additional 10 min equilibration period. Analyses were performed in positive mode with high voltage potential at around 1.7 kV. Full MS spectra (m/z 400 to 2000 mass range) were acquired in a data dependent mode in which each full MS scan was followed by five MS/MS scans; the five most abundant molecular ions were dynamically selected and fragmented by collision induced dissociation, using a normalized collision energy of 35%. Target ions already fragmented were dynamically excluded for 45 s.
Tandem mass spectra from plasma sample were matched against the Homo Sapiens protein Swiss Prot database and through the SEQUEST algorithm incorporated in the Bioworks software (version 3.3, Thermo Electron). The following match parameters were considered: fully tryptic cleavage constraints (one miss cleavage allowed), static cysteine carbamidomethylation, and variable methionine oxidation. Precursor and fragment ions were searched with 1.5 and 1 Da tolerance, respectively. A peptide has been considered legitimately identified when it achieved cross correlation scores of 1.8, 2.5 and 3 for 1, 2 and 3 peptide charge state, respectively, and peptide probability cut off of P < 0.001. Proteins were identified with at least two peptides.
For CSF samples tandem mass spectra were investigated using Proteome Discoverer 1.4 (Thermo Fisher Scientific).Spectral matches were filtered using Percolator node, based on q values, with 1% false discovery rate (FDR). Only master proteins were taken into account and only specific trypsin cleavages with two miscleavages were admitted. Cysteine carbamydomethylation was set as static modification, while methionine oxidation was set as variable modifications.
[doi:10.25345/C59C6SB2B]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: multiple sclerosis ; extracellular vesicles ; proteomics ; plasma ; cerebrospinal fluid
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Marialuisa Casella, Istituto Superiore Sanita, Italy |
Submitting User: | Marialuisa_PX |
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