A semi-automatic modular framework for quantitative glycomics data analysis
MetadataShow full item record
Mass spectrometry (MS) based glycomics techniques are most often used to analyze free oligosaccharides that are chemically or enzymically released from glycoconjugates (e.g., glycoproteins, proteoglycans and glycolipids). However, improved MS methods for analyzing intact glycoconjugates are continuously being developed. Protein-linked N-glycans and O-glycans are typically released by enzymatic and chemical methods. MS is particularly advantageous for the analysis of complex glycan mixtures containing oligosaccharides that cannot be identified by HPLC alone due to the lack of authentic molecular standards. MS methods that provide accurate molecular mass values can afford direct information regarding the glycosyl residue composition of each glycan in the sample. However, several sets of isomeric glycans, each characterized by a distinct glycosyl composition and molecular mass, are often present in a sample being analyzed. The structure and abundance of each member of such an isomeric set cannot be determined by one-dimensional mass profiling techniques. More sophisticated methods such as multi-stage tandem MS (i.e., MSn) or combinations of MS with high-resolution separation techniques (e.g., HPLC-MS) are required to resolve the isomeric glycans in such samples. Although many MS based glycomics tools have been developed from different perspectives, no single tool or platform can fit all the needs for glycomics research. Thus, the integration of glycomics tools to satisfy the needs for a particular glycomics project or research group is a significant challenge. Currently existing software does not include a platform or framework (analogous to the Trans-Proteomic Pipeline (TPP) software for proteomics) that allows users to “personalize” processing of glycomics data according to the input file format and the research aims. Such software, which requires the ability to select and orchestrate the appropriate functional modules designed to accomplish specific aims in the glycomics domain, are required for automatic, high throughput analysis of glycomics data. We have developed a modular glycomics data processing environment and implemented some of its key components, which support semantically annotated data-exchange formats and workflow engines, enabling the development of interactive modules that perform well-defined data processing tasks. A workflow comprised of modules for data conversion, scaling, extraction, and quantification of rolling-trapping MS data was developed and implemented in this environment. This workflow was applied to experimental data, revealing sources of variation between replicates.