Capturing and identification of differentially expressed fucome by a gel free and label free approach

• A gel free and label free approach incorporating combinatorial peptide ligand library (CPLL) and a multicolumn platform was introduced.
• The approach allowed the capturing of differentially expressed fucosylated proteins (DEPs) in hepatocellular carcinoma (HCC).
• Seventy DEPs were identified in HCC serum treated by CPLL.

This research reports a proof-of-concept that describes an instrumental approach that is gel free and label free at both the separation and mass spectrometry ends for the capturing and identification of differentially expressed proteins (DEPs) in diseases, e.g., cancers. The research consists of subjecting/processing equalized and non-equalized (i.e., untreated) disease-free and hepatocellular carcinoma (HCC) human sera via a multicolumn platform for capturing/fractionating human serum fucome. The equalization was performed via the combinatorial peptide ligand library (CPLL) beads technology that ensured narrowing the protein concentration range, thus allowing the detection of low abundance proteins. The equalized and non-equalized disease-free and HCC sera were first fractionated online onto two lectin columns specific to fucose, namely Aleuria aurantia lectin (AAL) and Lotus tetragonolobus agglutinin (LTA) followed by the online fractionation of the lectin captured fucome by reversed phase chromatography. The online desalted fractions were first subjected to trypsinolysis and then to liquid chromatography–mass spectrometry (LC–MS/MS) analysis. In comparison with untreated serum, the CPLL treated serum is superior in terms of the total number of identified DEPs, which reflected an increased number of DEPs in a wide abundance range. The DEPs in HCC serum were found to be 70 and 40 in both LTA and AAL fractions for the serum treated by CPLL and untreated serum, respectively. In addition, the platform combined with the CPLL treatment was accomplished with virtually no sample loss and dilution as well as with no experimental biases and sample labeling when comparing the diseased-free and cancer sera using LC–MS/MS.