In-depth Exploration of Cerebrospinal Fluid by Combining Peptide Ligand Library Treatment and Label-free Protein Quantification

Abstract

Cerebrospinal fluid (CSF) is the biological fluid in closest contact with the brain and thus contains proteins of neural cell origin. Hence, CSF is a biochemical window into the brain and is particularly attractive for the search for biomarkers of neurological diseases. However, as in the case of other biological fluids, one of the main analytical challenges in proteomic characterization of the CSF is the very wide concentration range of proteins, largely exceeding the dynamic range of current analytical approaches. Here, we used the combinatorial peptide ligand library technology (ProteoMiner) to reduce the dynamic range of protein concentration in CSF and unmask previously undetected proteins by nano-LC-MS/MS analysis on an LTQ-Orbitrap mass spectrometer. This method was first applied on a large pool of CSF from different sources with the aim to better characterize the protein content of this fluid, especially for the low abundance components. We were able to identify 1212 proteins in CSF, and among these, 745 were only detected after peptide library treatment. However, additional difficulties for clinical studies of CSF are the low protein concentration of this fluid and the low volumes typically obtained after lumbar puncture, precluding the conventional use of ProteoMiner with large volume columns for treatment of patient samples. The method has thus been optimized to be compatible with low volume samples. We could show that the treatment is still efficient with this miniaturized protocol and that the dynamic range of protein concentration is actually reduced even with small amounts of beads, leading to an increase of more than 100% of the number of identified proteins in one LC-MS/MS run. Moreover, using a dedicated bioinformatics analytical work flow, we found that the method is reproducible and applicable for label-free quantification of series of samples processed in parallel. Molecular & Cellular Proteomics 9:1006 -1021, 2010.

Proteolipidic Composition of Exosomes Changes during Reticulocyte Maturation

“…4 as well as two others prepared with exosome samples obtained through completely independent productions were used for separate proteomic determinations of the protein composition of the exosomes via MS/MS mass spectrometry. Analysis of quantitative changes in protein abundance was performed by a label-free spectral count method using the MFPaQ software developed in-house (22,23). An initial preliminary analysis was performed on a QSTAR Pulsar XL machine and two others on an LTQ-Orbitrap, a more sensitive machine.…”

“…Proteins were visualized by Coomassie Blue staining, and each lane was cut into 10 slices and subjected to in-gel tryptic digestion. For the initial preliminary analysis, the tryptic digests were analyzed by nanoLC-MS/MS using a Qq-Tof mass spectrometer (QSTAR Pulsar XL, Applied Biosystems, Foster City, CA), and the two subsequent analyses were run on an UltiMate 3000 system (Dionex, Amsterdam, The Netherlands) coupled to an LTQ-Orbitrap XL mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) as described previously (22), except that peptides were eluted using a 0 -50% gradient of solvent B during 55 min at a 300 nl/min flow rate. Mascot (2.3.01) was used to automatically extract peak lists from .raw files.…”

Bacterial protein-O-mannosylating enzyme is crucial for virulence ofMycobacterium tuberculosis

“…NanoLC-MS/MS analyses were performed on an Ultimate3000 system (Dionex) coupled to an LTQ-Orbitrap XL or an ETD-enabled LTQ Orbitrap Velos mass spectrometer (Thermo Fisher Scientific), respectively, for CID or ETD experiments. Data analysis and database searches were performed according to journal guidelines using Mascot Daemon against actinobacteria entries in Sprot-Trembl_20090707 database and the in-house developed software MFPaQ v4.0.0 (31,32). The detection of peak signatures corresponding to carbohydrate neutral loss in CID MS/MS spectra has been performed using an in-house developed Perl script.…”

GRK2 Protein-mediated Transphosphorylation Contributes to Loss of Function of μ-Opioid Receptors Induced by Neuropeptide FF (NPFF2) Receptors

“…The following relative abundance ratios 1DMe/CTRL, DAMGO/ CTRL, and DAMGO/1DMe were calculated by computing the peak area ratio of all MOP receptor peptides containing phosphorylation site(s) for pairwise comparison. Peak areas were automatically measured from extracted ion chromatograms of each peptide (sum of all observed charge states) in the nano-LC-MS raw file using the label-free module of the in-house developed MFPaQ version 4.0.0 software (43). To calibrate the amounts of MOP receptor in the three treatment conditions, a normalization of the calculated ratios was performed.…”