An Improved Approach for Glycan Structure Identification from HCD - PowerPoint PPT Presentation

Introduction Method Experiments An Improved Approach for Glycan Structure Identification from HCD MS/MS Spectra Weiping Sun, Yi Liu, Gilles Lajoie, Bin Ma and Kaizhong Zhang Department of Computer Science, Western University wsun63@uwo.ca October 3, 2016 1 / 18

Introduction Method Experiments Overview Introduction 1 Main Method 2 Experiments and Discussion 3 2 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Glycosylation One of the most important PTMs 70% human proteins are glycosylated 3 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Glycosylation One of the most important PTMs 70% human proteins are glycosylated Types of Glycosylation N-linked glycosylation – Attached to N(Asn) – Motif; core structure O-linked glycosylation – Linked to S/T, or hydroxylysine residues 3 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches MS-Based Glycoproteomic Analysis 4 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Tandem Mass Spectrometry Three common fragmentation techniques: CID: B- and Y-ions HCD: B- and Y-ions, as well as A- and X-ions ETD/ECD: C- and Z-ions 5 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Glycan Identification from HCD Spectrum 6 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Glycan Identification from HCD Spectrum 7 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Computational Approaches for Spectral Data Interpretation Database search – Search from a glycan database to find matched glycan candidates. Examples : GlycoSearchMS, GlycoWorkBench, MAGIC, GlycoMaster DB, etc. 8 / 18

Introduction Method Experiments Glycosylation Glycoproteomics Approaches Computational Approaches for Spectral Data Interpretation Database search – Search from a glycan database to find matched glycan candidates. Examples : GlycoSearchMS, GlycoWorkBench, MAGIC, GlycoMaster DB, etc. VS De novo sequencing – Computation does not rely on glycan database knowledge, instead the algorithms directly construct glycans from MS/MS. Examples : Glycan: STAT, GlyCH, StrOligo, etc. Glycopeptide: GlycoMaster, etc. 8 / 18

Introduction Method Experiments Mathematical Model Method Motivations De novo sequencing need high-quality mass spectra. Database search has the ability to obtain more reliable results. Our previous de novo sequencing method can at least provide useful structures. 9 / 18

Introduction Method Experiments Mathematical Model Method Glycan Database Search Problem Glycan: a labelled rooted unordered tree with bounded degree. Glycan database search problem : Input: - An MS/MS spectrum M - A glycan database D - A predefined mass error tolerance δ Output: A glycan structure T in D that satisfies, - |� T � + � P � + � H 2 O � + 1 − M p | ≤ δ ; - Matching score between M and T is maximized. 10 / 18

Introduction Method Experiments Mathematical Model Method Main Idea Use de novo sequencing result to filter glycans selected from database. 11 / 18

Introduction Method Experiments Mathematical Model Method Step 1: Peptide mass calculation 12 / 18

Introduction Method Experiments Mathematical Model Method Step 2: Glycan candidate selection and raw score calculation 1. Calculate glycan mass 2. Screen glycan database for possible glycan candidates 3. Calculate their raw score � � � S raw = α f ( m Bi , h Bi )+ β f ( m Y j , h Y j )+ θ f ( m I k , h I k ) 13 / 18

Introduction Method Experiments Mathematical Model Method Step 3: Filtration A list of de novo sequencing glycans: L n = { R 1 , R 2 , . . . , R m } A list of database glycans: L d = { Q 1 , Q 2 , . . . , Q n } 1 rank ( Rj ) S comp ( Q i , R j ) = S align ( Q i , R j ) × e S ( Q i ) = � K k =1 S comp ( Q i , R k ) × 1 K × S raw ( Q i ) 14 / 18

Introduction Method Experiments Dataset Results Dataset Protein samples: - Alpha-1-acid glycoprotein (Bovine) - Ovomucoid (Chicken) - Ig gamma-3 chain C region (Human) Thermo Scientific Orbitrap Elite hybrid mass spectrometer HCD fragmentation technique GlycoMaster DB was used for comparison 46 HCD spectra of glycopeptides were contained 15 / 18

Introduction Method Experiments Dataset Results Experimental Results Software program: GlycoNovoDB Table: Performance of De Novo Sequencing Algorithm and GlycoNovoDB Compared with GlycoMaster DB De Novo Sequencing Algorithm GlycoNovoDB Rank 1 Number Percentage(%) Number Percentage(%) 1 40 86.96 45 97.83 2 1 2.17 1 2.17 3 1 2.17 0 0.00 4 ∼ 10 1 2.17 0 0.00 > 10 2 4.35 0 0.00 can’t find 1 2.17 0 0.00 1 ”Rank” refers to the ranking status of the reference structure (the top glycan structure reported by GlycoMaster DB) in our results for a spectrum. 16 / 18

Introduction Method Experiments Dataset Results Experimental Results GlycoNovoDB can report more confident results than GlycoMaster DB. - There are 6 spectra that GlycoMaster DB reported more than one top-ranked glycans with the same score. - An example: 17 / 18

Introduction Method Experiments Acknowledgement Thank you! Questions? University of Western Ontario - Prof. Kaizhong Zhang - Prof. Gilles A. Lajoie - Dr. Weiping Sun - Dr. Yi Liu University of Waterloo - Prof. Bin Ma This work was supported in part by the NSERC Discovery Grant and a Discovery Accelerator Supplements Grant. 18 / 18