GlyQ-IQ: Glycomics Quintavariate-Informed Quantification with High-Performance Computing and GlycoGrid 4D Visualization

Journal Article · Sat May 31 00:00:00 EDT 2014 · Analytical Chemistry, 86(13):6268-6276

DOI:https://doi.org/10.1021/ac501492f· OSTI ID:1136598

Kronewitter, Scott R.; Slysz, Gordon W.; Marginean, Ioan; Hagler, Clay D.; Lamarche, Brian L.; Zhao, Rui; Harris, Myanna Y.; Monroe, Matthew E.; Polyukh, Christina A.; Crowell, Kevin L.; Fillmore, Thomas L.; Carlson, Timothy S.; Camp, David G.; Moore, Ronald J.; Payne, Samuel H.; Anderson, Gordon A.; Smith, Richard D.

Dense LC-MS datasets have convoluted extracted ion chromatograms with multiple chromatographic peaks that cloud the differentiation between intact compounds with their overlapping isotopic distributions, peaks due to insource ion fragmentation, and noise. Making this differentiation is critical in glycomics datasets because chromatographic peaks correspond to different intact glycan structural isomers. The GlyQ-IQ software is targeted chromatography centric software designed for chromatogram and mass spectra data processing and subsequent glycan composition annotation. The targeted analysis approach offers several key advantages to LC-MS data processing and annotation over traditional algorithms. A priori information about the individual target’s elemental composition allows for exact isotope profile modeling for improved feature detection and increased sensitivity by focusing chromatogram generation and peak fitting on the isotopic species in the distribution having the highest intensity and data quality. Glycan target annotation is corroborated by glycan family relationships and in source fragmentation detection. The GlyQ-IQ software is developed in this work (Part 1) and was used to profile N-glycan compositions from human serum LC-MS Datasets. The companion manuscript GlyQ-IQ Part 2 discusses developments in human serum N-glycan sample preparation, glycan isomer separation, and glycan electrospray ionization. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad N-glycan profile from a high resolution (100K/60K) nESI-LS-MS/MS dataset including CID and HCD fragmentation acquired on a Velos Pro Mass spectrometer. 101 glycan compositions and 353 isomer peaks were detected from a single sample. 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high resolution mass spectra and mass accuracies less than 7 ppm.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1136598
• Report Number(s): PNNL-SA-100272; 47418; KP1601010
• Journal Information: Analytical Chemistry, 86(13):6268-6276, Journal Name: Analytical Chemistry, 86(13):6268-6276
• Country of Publication: United States
• Language: English

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