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

Research output: Contribution to journalArticleAcademicpeer-review


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.

Original languageEnglish
Pages (from-to)2490-502
Number of pages13
JournalMolecular & Cellular Proteomics
Issue number9
Publication statusPublished - Sept 2014


  • Algorithms
  • Carbohydrate Sequence
  • Heparitin Sulfate
  • Sequence Analysis
  • Tandem Mass Spectrometry


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