A Computational Framework for Heparan Sulfate Sequencing Using High-resolution Tandem Mass Spectra

Han Hu,Yu Huang,Yang Mao,Xiang Yu,Yongmei Xu,Jian Liu,Chengli Zong,Geert-Jan Boons,Cheng Lin,Yu Xia,Joseph Zaia

doi:10.1074/mcp.m114.039560

Abstract

Heparan sulfate (HS) is a linear polysaccharide expressed on cell surfaces, in extracellular matrices and cellular granules in metazoan cells. Through non-covalent binding to growth factors, morphogens, chemokines, and other protein families, HS is involved in all multicellular physiological activities. Its biological activities depend on the fine structures of its protein-binding domains, the determination of which remains a daunting task. Methods have advanced to the point that mass spectra with information-rich product ions may be produced on purified HS saccharides. However, the interpretation of these complex product ion patterns has emerged as the bottleneck to the dissemination of these HS sequencing methods. To solve this problem, we designed HS-SEQ, the first comprehensive algorithm for HS de novo sequencing using high-resolution tandem mass spectra. We tested HS-SEQ using negative electron transfer dissociation (NETD) tandem mass spectra generated from a set of pure synthetic saccharide standards with diverse sulfation patterns. The results showed that HS-SEQ rapidly and accurately determined the correct HS structures from large candidate pools.

Highlights

From the ‡Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA; §Center for Biomedical Mass Spectrometry, Department of Biochemistry, Boston University School of Medicine, Boston University, Boston, Massachusetts 02118, USA; ¶ Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599, USA; ʈDepartment of Bioengineering, Faculty of Engineering, McGill University, Montreal, Quebec H3A 0C3, Canada; **Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602
The results showed that Heparan sulfate (HS)-SEQ accurately recovered the correct HS sequences for 76% (19 out of 25) of the tested tandem mass spectra, and approached the correct sequences for the remainder
The preprocessing results are given in supplemental material S2–S3 and the modification distributions reported by HSSEQ are provided in supplemental material S1

Summary

Introduction

HS chains in determining the binding specificity between HS, growth factors, and growth factor receptors, and illustrate the potential of developing HS-based drugs and therapeutics (20 –23) In this context, effective methods for identifying sulfation patterns on HS chains are in high demand. A computational simulation method was explored to predict the fine structure and domain organization of HS sequence using information from enzymatic digestion and Golgi-based biosynthetic rules [38]. This model produced an “average” HS chain statistically and is valuable for guiding the selection of candidate sequences, yet it failed to pinpoint the positions of sulfate groups for a specific chain. The public tool Glycoworkbench (39 – 41) was developed to facilitate the assignment of monoisotopic peaks in tandem mass spectra of glycans, but it aided little in the identification of sulfated sites on the sequence scale

Methods

Results

Conclusion