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Targeted analysis of glycomics liquid chromatography/mass spectrometry data.

ABSTRACT: Hydrophilic interaction chromatography (HILIC) liquid chromatography/mass spectrometry (LC/MS) is appropriate for all native and reductively aminated glycan classes. HILIC carries the advantage that retention times vary predictably according to oligosaccharide composition. Chromatographic conditions are compatible with sensitive and reproducible glycomics analysis of large numbers of samples. The data are extremely useful for quantitative profiling of glycans expressed in biological tissues. With these analytical developments, the rate-limiting factor for widespread use of HILIC LC/MS in glycomics is the analysis of the data. In order to eliminate this problem, a Java-based open source software tool, Manatee, was developed for targeted analysis of HILIC LC/MS glycan datasets. This tool uses user-defined lists of compositions that specify the glycan chemical space in a given biological context. The program accepts high-resolution LC/MS data using the public mzXML format and is capable of processing a large data file in a few minutes on a standard desktop computer. The program allows mining of HILIC LC/MS data with an output compatible with multivariate statistical analysis. It is envisaged that the Manatee tool will complement more computationally intensive LC/MS processing tools based on deconvolution and deisotoping of LC/MS data. The capabilities of the tool were demonstrated using a set of HILIC LC/MS data on organ-specific heparan sulfates.

SUBMITTER: Dreyfuss JM

PROVIDER: S-EPMC3254673 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Targeted analysis of glycomics liquid chromatography/mass spectrometry data.

Dreyfuss Jonathan M JM Jacobs Christopher C Gindin Yevgeniy Y Benson Gary G Staples Gregory O GO Zaia Joseph J

Analytical and bioanalytical chemistry 20101016 2

Hydrophilic interaction chromatography (HILIC) liquid chromatography/mass spectrometry (LC/MS) is appropriate for all native and reductively aminated glycan classes. HILIC carries the advantage that retention times vary predictably according to oligosaccharide composition. Chromatographic conditions are compatible with sensitive and reproducible glycomics analysis of large numbers of samples. The data are extremely useful for quantitative profiling of glycans expressed in biological tissues. Wit ...[more]

PMID: 20953780

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Project description:BACKGROUND: Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are the detection of peptide features in the mass spectra and the alignment of samples by correcting for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists only for peptide identification algorithms but no data that represents a ground truth for the evaluation of feature detection, alignment and filtering algorithms. RESULTS: We present LC-MSsim, a simulation software for LC-ESI-MS experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS data set using a predictor for the retention time of the peptides and a model for peak shapes and elution profiles of the mass spectral peaks. Our software also offers the possibility to add contaminants, to change the background noise level and includes a model for the detectability of peptides in mass spectra. After the simulation, LC-MSsim writes the simulated data to mzData, a public XML format. The software also stores the positions (monoisotopic m/z and retention time) and ion counts of the simulated ions in separate files. CONCLUSION: LC-MSsim generates simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm developers can match the results of feature detection and alignment algorithms against the simulated ion lists and meaningful error rates can be computed. We anticipate that LC-MSsim will be useful to the wider community to perform benchmark studies and comparisons between computational tools.

Dataset Information

Targeted analysis of glycomics liquid chromatography/mass spectrometry data.

Publications

Targeted analysis of glycomics liquid chromatography/mass spectrometry data.

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