Proteomic analysis of subarachnoid hemorrhage - liquid phase isoelectric focusing in complex protein sample

Joanna Hajduk, Bartosz Sokół, Agata Swiatly, Jan Matysiak, Piotr Nowicki, Ewa Garbiec, Norbert Wąsik, Roman Jankowski, Zenon J. Kokot
2016 Journal of Medical Science  
The aim of this study was to present the proteomic approach based on liquid phase isoelectric focusing fractionation coupled to nLC-MALDI-TOF/TOF-MS/MS analysis to characterize cerebrospinal fluid from control patients and those suffering from subarachnoid hemorrhage. The new perspective in characterization of this brain neuropathology are in constant demand to point a valuable panel of indicators which could improve the treatment outcome.Methods: The cerebrospinal fluid samples were applied to
more » ... a commercial liquid phase isoelectric focusing apparatus and separated into 10 fractions by pI. Further, the untargeted mass spectrometry investigations were performed with data dependent acquisition mode for full-scan MS analysis with subsequently MS/MS fragmentation by using nLC-MALDI-TOF/TOF-MS/MS.Results: In total, the detection of 1664 and 2187 unique tryptic peptides provided biological evidence for 134 and 271 proteins in control and subarachnoid hemorrhage sample, respectively. The interpretation of liquid phase separation was performed by intersection analysis of two items between groups of ten fractions. The cumulative intersection exploration revealed the highest concentration of the detected components in the middle fractions of the focusing chamber, whereas the gradual dilution appeared on its extreme.Conclusions: The employed strategy ensured overall screening of investigated material presenting the proteins abundance in the current state of analysis. Few proteins such as proenkephalin A, peroxiredoxin-6, cathepsin B, thrombospondin-1, glial fibrillary acidic protein and α – spectrin were recognized as potential indicators, according to literature, pointing the possibility for its monitoring in further studies as panel of valuable biomarkers.
doi:10.20883/jms.2016.139 fatcat:qyq4hk5kavd2dmcko7bwfuup3u