报告题目:GIPS: Towards automatic identification of glycan branching by using intelligent ion peakselection in multiple-stage mass spectrometry
报告人:卜东波 研究员
报告时间:2015年11月11日(周三)10:00
报告地点:逸夫楼C座314会议室
摘要: Glycanidentification has long been hampered by the the isomeric nature andcomplicated branching structures of glycans. Multiple-stage mass spectrometry(MS^n) is a promising glycan identification technique as it providesinformation for various fragments of glycan structures. However, one challengefor using this technique for automatic identification is the fact that ion peakselection is problematic, i.e., selection of an ion peak to feed into the massspectrometer to generate the next-stage spectrum is not trivial. Here wepropose an intelligent ion peak selection strategy (called GIPS) to facilitatethe automatic identification of glycan branching. Unlike the common strategybased on visual selection where ion peaks with the highest intensity are chosenmanually, GIPS selects the ion peak with the highest distinguishing power tominimize the number of MS^n experiments required to distinguish between theactual glycan and candidate glycans. Here, the distinguishing power of ions arecalculated using a hierarchical Bayesian model that incorporates information ofall stages of mass spectra of the glycan sample. Our results based on 7 glycanstandards suggest that GIPS correctly distinguished the actual glycans usingMS3 spectra. In contrast, the visualization-based strategy failed on 2 samples,and usually required more stages of mass spectra experiments compared to GIPS.Crucially, two isomeric glycan samples, Man7D1 and Man7D3, were correctlydistinguished by GIPS but not by the visualization-based strategy,demonstrating the advantages of GIPS over the visual method in distinguishingisomeric glycans. As practical applications, we successfully applied GIPSprotocol to identify the glycan mixtures extracted from glycoproteins RNaseB andIgG, where the identification results were confirmed using CE technique. Insummary, the combination of MS^n technique and GIPS protocol greatlyfacilitates the automatic identification of glycan branching structures, and atthe same time reduces time and cost of glycan identification.
The speaker would also like togive a brief introduction to his works on protein tertiary structure prediction.
报告人简介:Dr. Bu received his Ph. D. degree from theInstitute of Computing Technology, Chinese Academy of Sciences in 2001. He wasa post-doctoral scholar and visiting scholar at the University of Waterloo from2006 to 2008. His research interests include algorithms in the field ofbioinformatics, especially on proteins tertiary structure prediction, genomeassembly, and glycan/peptide identification using mass spectrometry. Hedeveloped FALCON@home, a server for protein structure prediction, which wasranked 3rd in CASP8, and 9th in CASP11.