Automatic annotation of N-glycan species in MALDI-TOF-TOF spectra for rapid profiling and comparing

1. Indiana University Bloomington School of Informatics and Computing  Automatic annotation of N-glycan species in MALDI-TOF-TOF spectra for rapid profiling and comparing Chuan-Yih, Yu 2010.05.14 Capstone Advisor: Prof. Haixu Tang

2. Outline • Introduction • Glycoprotein, Monosaccharides, N-linked glycosylation, and Mass Spectrometry • Problem set • Goals • MultiNGlycan • Result • Future works

3. Introduction 1.Apweiler, R., H. Hermjakob, and N. Sharon, On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database.BiochimBiophysActa, 1999. 1473(1): p. 4-8 • Post-Translation Modification (PTM) • An enzyme-catalyzed change after synthesized • Acetylation, Cleavage, Glycosylation, Methylation, Phosphorylation, and Prenylation • 50% of all eukaryotic proteins are glycosylated1 [Apweiler, et al.] http://yahoo.brand.edgar-online.com/EFX_dll/EDGARpro.dll?FetchFilingHTML1?SessionID=WD8AC7y2l3h1FMr&ID=5101862

4. Glycosylation • N-linked glycosylation • Core structure – 2 GlcNac + 3 Man • Asn-X-Ser or Asn-X-Thr, X can be any but Pro (glycosylation  sequon) • Glycosylation before folding • O-linked glycosylation • Many different core structures • Serine or Threonine • Glycosylation after folding

5. N-linked glycosylation • Tree structure • Monosaccharides- building blocks of polysaccharide chain • Diverse linage – at most four branches • Three types of N-linked glycan tree • High mannose • Complex • Hybrid Graphs: Varki, A., Essentials of glycobiology. 2nd ed. 2009, Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press. xxix, 784 p

6. MALDI-TOF-TOF Graph:MALDI-TOF Mass Analysis. (2008, 11 16). Retrieved May 2, 2009, from The Protein Facility of the Iowa State University Office of Biotechnology www.protein.iastate.edu/maldi.html • Matrix-assisted laser desorption/ionization • Time of flight (TOF)

7. Problem Sets Glycopeptide isotope pattern overlap http://en.wikipedia.org/wiki/Carbon Graphs: Isotope Pattern Calculator v4.0 http://yanjunhua.tripod.com/pattern.htm

8. Problem Sets High-throughput glycans profiling http://www.functionalglycomics.org

9. Goals • Glycans profile correlation • Report scores for non-overlap and overlap profile • Glycans examination • Glycan profile comparison • Report significant glycan between groups • Glycans biomarker discovery

10. Glycans Profile Correlation 1.Krambeck, F.J. and M.J. Betenbaugh, A mathematical model of N-linked glycosylation.BiotechnolBioeng, 2005. 92(6): p. 711-28. 2.Rockwood, A., S. Van Orden, and R. Smith, Rapid Calculation of Isotope Distributions. Analytical Chemistry, 1995. 67: p. 2699-2704. • For each glycan combination • 412 different glycan combinations[Krambeck, et al. ]1 • Generate a theoretical isotope pattern • Calculate the correlation for following cases • Glycans • Glycans + Glycans, linear combination applied • Glycans + Unknown, linear combination applied • Mercury algorithm2 • Generate the unknown isotope pattern

11. Three Cases Glycans Theoretical isotope pattern Score 0.6 Glycans Experiment spectrum α β 0.8 Unknown α β 0.2

12. Glycan Profile Comparison HCC: Hepatocellular Carcinoma ( Cancer of liver) CLD: Chronic liver disease Graph: Ressom, H.W., et al., Analysis of MALDI-TOF mass spectrometry data for discovery of peptide and glycan biomarkers of hepatocellular carcinoma. J Proteome Res, 2008. 7(2): p. 603-10. • Multiple spectra comparison • Biomarker discovery • Given spectrum with several conditions • Find distinct glycans between samples

13. Concept Remove the least significant component. Repeat until all the score above threshold. 70% identical with a cutoff at 0.5 Health spectra (H1, H2, H3…Hk) Disease spectra (D1, D2, D3…Dk) 1.Hastie, T., et al., 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol, 2000. 1(2): p. RESEARCH0003

14. Multi N-Glycan 1.Pedrioli, P., et al., A Common Open Representation of Mass Spectrometry Data and its Application in a Proteomics Research Environment. Nature Biotechnology, 2004. 22(11): p. 1459-1466. • Software Requirements • .net framework 2.0 using C# • C++ runtime • R • Thermo Scientific Xcalibur • Input • Spectrum • Plain text (Peak list), mzXML1,RAW (Thermo Scientific raw file) • Glycans list • CSV file (User-defined) • Output • List of glycans with scores

15. Software Interface

16. Software features • Signal preprocessing provided • Subtracting background • Smoothing peak • Tolerating Mass Spectrometry accuracy • Flexible parameters incorporate actual experiment • Useful tools provides • Isotope pattern generator • Content rich output, multi-format supports • csv, text, html

17. Software screenshot Html result export

18. Software screenshot

19. Result Anoop M., Chuan-Yih Y., A Multi-PCA Approach to Glycan Biomarker Discovery using Mass Spectrometry Profile Data. I690 project, 2009 Fall Zhiqun T., et al., Identification of N-Glycan Serum Markers Associated with Hepatocellular Carcinoma from Mass Spectrometry Data. J Proteome Res, 2009 Ressom, H.W., et al., Analysis of MALDI-TOF mass spectrometry data for discovery of peptide and glycan biomarkers of hepatocellular carcinoma. J Proteome Res, 2008. 7(2): p. 603-10. • Data set • Liver Cancer : 73 individuals • Health: 78 individuals • 412 glycan structures are tested • Glycan criterion • Correlation score cut off < 0.5 • Present in 30% of total spectra

20. Result Overlap with 2192 Can’t find the glycan structure in CFG database Correlation score Filtered out

21. Result

22. Future Works Test on more clinical samples Verify the correlation between glycan modification which reported by MultiNGlycan with Hepatocellulararcinoma Perform these tasks on O-linked glycan Apply de novo glycan sequencing on reported glycan (ongoing)

23. References Anoop M., Chuan-Yih Y., A Multi-PCA Approach to Glycan Biomarker Discovery using Mass Spectrometry Profile Data. I690 project, 2009 Fall Apweiler, R., H. Hermjakob, and N. Sharon, On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database.BiochimBiophysActa, 1999. 1473(1): p. 4-8. DalitShental-Bechor and Yaakov Levy, Effect of glycosylation on protein folding: A close look at thermodynamic stabilization, PNAS June 11, 2008 Hastie, T., et al., ‘Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns. Genome Biol, 2000. 1(2): p. RESEARCH0003. Krambeck, F.J. and M.J. Betenbaugh, A mathematical model of N-linked glycosylation.BiotechnolBioeng, 2005. 92(6): p. 711-28. Pedrioli, P., et al., A Common Open Representation of Mass Spectrometry Data and its Application in a Proteomics Research Environment. Nature Biotechnology, 2004. 22(11): p. 1459-1466. Ressom, H.W., et al., Analysis of MALDI-TOF mass spectrometry data for discovery of peptide and glycan biomarkers of hepatocellular carcinoma. J Proteome Res, 2008. 7(2): p. 603-10. Rockwood, A., S. Van Orden, and R. Smith, Rapid Calculation of Isotope Distributions. Analytical Chemistry, 1995. 67: p. 2699-2704. Zhiqun, T., et al., Identification of N-glycan serum markers associated with hepatocellular carcinoma from mass spectrometry data. J Proteome Res, 2010. 9(1): p. 104-12. Varki, A., Essentials of glycobiology. 2nd ed. 2009, Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press. xxix, 784 p.

24. Acknowledge Advisor: Prof. Haixu Tang Co-worker: AnoopMayampurath Collaborator: YehiaMechref, Department of Chemistry COL Lab members This work will present in 26th May, 58th ASMS Conference Salt Lake City, Utah and submit to the Bioinformatics Application Notes.

25. Thank You