MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS

The study of N-linked glycosylation has long been complicated by a lack of bioinformatics tools. In particular, there is still a lack of fast and robust data processing tools for targeted (relative) quantitation. We have developed modular, high-throughput data processing software, MassyTools, that is capable of calibrating spectra, extracting data, and performing quality control calculations based on a user-defined list of glycan or glycopeptide compositions. Typical examples of output include relative areas after background subtraction, isotopic pattern-based quality scores, spectral quality scores, and signal-to-noise ratios. We demonstrated MassyTools’ performance on MALDI-TOF-MS glycan and glycopeptide data from different samples. MassyTools yielded better calibration than the commercial software flexAnalysis, generally showing 2-fold better ppm errors after internal calibration. Relative quantitation using MassyTools and flexAnalysis gave similar results, yielding a relative standard deviation (RSD) of the main glycan of ∼6%. However, MassyTools yielded 2- to 5-fold lower RSD values for low-abundant analytes than flexAnalysis. Additionally, feature curation based on the computed quality criteria improved the data quality. In conclusion, we show that MassyTools is a robust automated data processing tool for high-throughput, high-performance glycosylation analysis. The package is released under the Apache 2.0 license and is freely available on GitHub (https://github.com/Tarskin/MassyTools)

LaCyTools: A Targeted Liquid Chromatography–Mass Spectrometry Data Processing Package for Relative Quantitation of Glycopeptides

Bottom-up glycoproteomics by liquid chromatography–mass spectrometry (LC–MS) is an established approach for assessing glycosylation in a protein- and site-specific manner. Consequently, tools are needed to automatically align, calibrate, and integrate LC–MS glycoproteomics data. We developed a modular software package designed to tackle the individual aspects of an LC–MS experiment, called LaCyTools. Targeted alignment is performed using user defined <i>m</i>/<i>z</i> and retention time (<i>t</i>_r) combinations. Subsequently, sum spectra are created for each user defined analyte group. Quantitation is performed on the sum spectra, where each user defined analyte can have its own <i>t</i>_r, minimum, and maximum charge states. Consequently, LaCyTools deals with multiple charge states, which gives an output per charge state if desired, and offers various analyte and spectra quality criteria. We compared throughput and performance of LaCyTools to combinations of available tools that deal with individual processing steps. LaCyTools yielded relative quantitation of equal precision (relative standard deviation <0.5%) and higher trueness due to the use of MS peak area instead of MS peak intensity. In conclusion, LaCyTools is an accurate automated data processing tool for high-throughput analysis of LC–MS glycoproteomics data. Released under the Apache 2.0 license, it is freely available on GitHub (https://github.com/Tarskin/LaCyTools)

Overview of the IgG Fc <i>N</i>-glycosylation of seven different IVIg products.

<p>Data presented as mean, standard deviation (SD) and coefficient of variation (CV), numbers in the first row are the seven different IVIg products, (C) denotes an IVIg batch triplicate, and (S) an internal IgG standard.</p><p>Overview of the IgG Fc <i>N</i>-glycosylation of seven different IVIg products.</p

Dopant Enriched Nitrogen Gas Combined with Sheathless Capillary Electrophoresis–Electrospray Ionization-Mass Spectrometry for Improved Sensitivity and Repeatability in Glycopeptide Analysis

Over the last years, numerous strategies have been proposed to enhance both ionization efficiency and spray stability in electrospray ionization (ESI), in particular for nanospray applications. In nano-liquid chromatography–mass spectrometry (nano-LC–ESI-MS), a better ESI performance has been observed when a coaxial gas flow is added around the ESI emitter. Moreover, enrichment of the gas with an organic dopant has led to an improved desolvation and ionization efficiency with an overall enhanced sensitivity. In this study, the use of a dopant enriched nitrogen (DEN)-gas combined with sheathless capillary electrophoresis (CE)–ESI-MS was evaluated for glycopeptide analysis. Using acetonitrile as a dopant, an increased sensitivity was observed compared to conventional sheathless CE–ESI-MS. Up to 25-fold higher sensitivities for model glycopeptides were obtained, allowing for limits of detection unachieved by state-of-the-art nano-LC–ESI-MS. The effect of DEN-gas on the repeatability and intermediate precision was also investigated. When compared to previously reported nano-LC–ESI-MS measurements, similar values were found for CE–ESI-MS with DEN-gas. The enhanced repeatability fosters the use of DEN-gas sheathless CE–ESI-MS in protein glycosylation analysis, where precision is essential. The use of DEN-gas opens new avenues for highly sensitive sheathless CE–ESI-MS approaches in glycoproteomics research, by significantly improving sensitivity and precision