Altered glycosylation is a common feature of cancer cells and certain changes of glycan structures are well-known maker for tumour progression.  Alterations in glycosylation have been proposed to participate in cell adhesion, receptor activation, cell differentiations and tissue morphogenesis.  The identification and characterization of new functions of disease-associated sugar chains is one of the central aims of the emerging high throughput glycomics projects.  Since vast amounts of scientific data are generated, informatics support is required to store and order the primary data, categorise and annotate assigned data and extract the relevant information important for biomedical applications.  Although many of the data-handling, data-storage and primary statistical analysis can be adopted from proteomics analyses aiming to define marker proteins, glycomics analysis implies several new challenges.  These are mainly due to the high structural complexity of carbohydrate structures and the diversity of glycans.  Although the same glycosylation machinery is available to all proteins in a given cell, most glycoproteins emerge with characteristic glycosylation patterns and heterogeneous populations of glycans at each glycosylation site, which may be significantly altered in the diseased stage.  Analysis of these carbohydrates has proven difficult in the past.  However, modern analytical methods such as mass spectrometry have the ability to elucidate most structural details at the concentration levels required for glycomics.
  The lesson to learn from proteomics projects is that comprehensive databases of all carbohydrate structures which can occur in the analysed tissue are an important requirement for a fast, automatic and reliable analysis of all involved structures.  However, in comparison to the proteomic area, the compilation of data collections for carbohydrates and the development of appropriate bioinformatics tools have lagged behind.  In proteomics projects, peptide mass fingerprinting is a routinely used technique suitable for rapid protein identification.  This involves the generation of peptides from proteins using residuespecific enzymes, the determination of peptide masses by spectrometric techniques, and the matching of these masses against theoretical peptide libraries generated from protein sequence databases to create a list of likely protein identifications.  A similar service for glycomics - a glycofragment mass fingerprinting tool - is highly desired.  It will automate the manual, labour intensive interpretation of oligosaccharide fragmentation.
  The current status of the worldwide available resources to establish glycofragment mass fingerprinting tools and other MS based approaches for automatic detection of glycan structures will be reviewed.  One of the main bottlenecks of the development of efficient scoring algorithms is the lack of high quality experimental data of MS spectra of glycans, where an unambiguous assignment of peaks to structural data is provided.
  Some of the described tools are part of the EUROCarbDB (www.eurocarbdb.org) project, which aims to create the foundations for databases and bioinformatics tools in the realm of glycobiology and glycomics.  It will establish the technical framework for bottom to top initiative where all interested research groups can feed in their primary data.


References;

Lutteke T, Bohne-Lang A, Loss A, Goetz T, Frank M, von der Lieth CW.
GLYCOCIENCES.de: An Internet Portal to Support Glycomics and Glycobiology Research.
Glycobiology (2005 Oct 20). [Epub ahead of print]

Joshi HJ, Harrison MJ, Schulz BL, Cooper CA, Packer NH, Karlsson NG.
Development of a mass fingerprinting tool for automated interpretation of oligosaccharide fragmentation data.
Proteomics, 4(6),1650-64 (2004).

Lohmann KK, von der Lieth CW.
GlycoFragment and GlycoSearchMS: web tools to support the interpretation of mass spectra of complex carbohydrates.
Nucleic Acids Res., 32(Web Server issue), W261-6 (2004).