1. Comparison of serum proteomics analysis using in-silico and in-gel fractionation Anna Drabik, Anna Bodzoń-Kułakowska, Piotr Suder, Marek Sierzęga, Jan Kulig, Jerzy Silberring 1 1 1 2 2 1,3 1 Department of Biochemistry and Neurobiology, Faculty of Materials Sciences and Ceramics, AGH University of Science and Technology, Mickiewicza 30 Ave, 30-059 Krakow, Poland 2 1st Department of Surgery, Jagiellonian University Medical College, 40 Kopernika Street, 31-501 Krakow, Poland 3 Center of Polymer and Carbon Materials, Polish Academy of Sciences, Sowinskiego 5 Str, 44-121 Gliwice, Poland Introduction The dynamic nature of the circulatory system and its constituents reflect physiological and pathological states of living organisms, therefore serum is the sample of choice for biomarker identification. Proteomic analysis of serum is a very challenging task, due to the vast number of proteins and broad range of concentrations in a given sample, which can vary by 12 orders of magnitude. The purpose of this study was to compare the most popular separation technique – one dimensional polyacrylamide gel electrophoresis with a new in-silico method of mass spectrometry data acquisition based on the scheduled precursor lists. SPL In-silico fractionation consists of series of the nanoLC-MS/MS runs. Peptides identified during initial capture process are excluded in the subsequent run. Highly abundant peptides are selected and identified during first analysis, while less abundant constituents of the mixture are selected and identified in the consecutive examination. Methods Contact: drabik@agh.edu.pl SPL results Conclusions and perspectives Human serum samples were purified using microspin C18 columns. One part of obtained fraction was separated by the one dimensional SDS-PAGE, and visualized with CBB. Gel lane after separation was cut into 10 pieces, subsequently reduced, alkylated, trypsin digested. The peptides were eluted from gel pieces and analyzed using nanoLc-MS/MS. The remaining part of C18 fraction was reduced, alkylated and trypsin digested. MS analysis of sample was consisting of two separate runs. After first run the exclusion precursor lists was generated and subjected to the second analysis. SDS-PAGE Ten samples were cut from the SDS-PAGE. 10 hours of nanoLC- MS/MS analysis were performed in order to identify 12 most abundant proteins. Two hours of nanoLC-MS/MS analysis were completed using the same sample. 11 most abundant proteins were identified compared to standard serum single nanoLC-MS/MS were only 5 most abundant proteins were detected. The effect of this technology improves protein identification scores and reveals information regarding the content of complex biological samples without the necessity of utilizing additional separation procedure. It is time and cost saving. Future more detailed human serum analysis might be represented by combination of fast and cheap prefractionation method with SPL mass spectrometry data acquisition technique.