N-Glycopeptide Identification from CID Tandem Mass Spectra using Glycan Databases and False Discovery Rate Estimation Kevin B. Chandler, Petr Pompach, Radoslav Goldman, Nathan J. Edwards Georgetown University, Department of Biochemistry and Molecular & Cellular Biology, Washington, DC Over half of all proteins are glycosylated (this rate is higher for secreted, cell-surface and extracellular matrix proteins) Glycosylation mediates cell-cell & cell-matrix interactions N-linked glycosylation is enzyme-directed, occurs on Asn residues within the motif NXS/T (X ≠ Pro) Tandem mass spectrometry (MS/MS) is used to study protein glycosylation; however, there are few software tools to aid in processing and interpretation of large glycopeptide MS/MS datasets, and manual interpretation of datasets is time consuming Introduction and Background GlycoPeptideSearch Software – Glycopeptide Discovery Workflow 1. Ranzinger, Herget, von der Lieth, Frank. Nucleic Acids Res. 39(Database issue):D (2011). 2. Fujimura, Shinohara, Tossot, Pang, Kurogochi, Saito, Arai, Sadilek, Murayama, Dell, Nishimura, Hakomori. Int. J. Cancer 122:39–49 (2008). 3. Goldberg, Sutton-Smith, Paulson, Dell. Proteomics 5: (2005). 4. Pompach, Chandler, Lan, Edwards, Goldman. J.Proteome Res. 11 (3); (2012). References Acknowledgements Kevin B Chandler is supported by a Graduate Research Fellowship from the National Science Foundation. Nathan J Edwards is supported, in part, by NIH/NCI/CPTI grant CA Rado slav Goldman is supported by NCI’s R01 CA and CA GlycoPeptideSearch Scheme MS/MS Spectra w/ glycan oxonium ion (204, 366) peaks w/ 2+ “peptide” peaks GlycomeDB Distinct Glycopeptides x LC-MS/MS Proteolytic digest of Haptoglobin with trypsin and GluC Hydrophilic interaction liquid chromatography (HILIC) of glycopeptides Eleven glycopeptide fractions analyzed by nanoC18 RP LC-MS/MS using a Q-STAR Elite mass-spectrometer. IDA: Four most abundant ions with 20 sec exclusion. 15,780 MS and 3,288 MS/MS spectra (msconvert) Test Dataset (Haptoglobin Glycopeptides) Automated in silico digestion (Trypsin, GluC) of user-submitted protein sequence & N-glycosylation site ID Fixed (carbamidomethylation) & variable modifications (Methionine oxidation) considered Spectra filtered for glycan oxonium ions & peptide + N-linked core fragments & mass-lookup in GlycomeDB (glycan database) Isotope Cluster Scoring performed on precursor ion Decoy (non-motif containing) peptides submitted to search to enable estimation of the False Discovery Rate Open format (XML) spectra input and Excel output. Methods: GlycoPeptideSearch Software We hypothesize that N-glycopeptide MS/MS data interpretation can be automated by adopting an algorithm that uses (1) oxonium marker ions and intact peptide peak filters, (2) the sequence(s) of the protein(s) of interest and (3) mass-matching to publicly available glycan databases to match glycan-peptide pairs to glycopeptide MS/MS spectra. The aim of this research is to develop a novel software tool for rapid interpretation of glycopeptide MS/MS datasets to facilitate the study of glycoprotein microheterogeneity Hypothesis and Aims Controlling Error Using Spectra Filters and Hit Filters FDR Determination Decoy Peptides (without motif) GPS Target and Decoy Spectra Hits FDR Target Peptides (with NXS/T) 52 glycan-peptide pairs matched 263 spectra (3.9% FDR). 52% (136) of filtered spectra matched a single glycopeptide pair ( 1 peptide. 27 distinct non-isobaric glycans at 4 sites were discovered, consistent with published reports 2. Conclusion: Using characteristics of glycopeptide spectra including oxonium ions and intact peptide peaks, it is possible to automate glycopeptide CID MS/MS data interpretation with low false discovery. Results and Conclusion Summary of Haptoglobin Glycopeptides Sample MS/MS Spectrum: Fraction 17, Scan 1407