Jansen Bas C, Reiding Karli R, Bondt Albert, Hipgrave Ederveen Agnes L, Palmblad Magnus, Falck David, Wuhrer Manfred
Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands.
Department of Rheumatology, Erasmus University Medical Center , 3000 CA Rotterdam, The Netherlands.
J Proteome Res. 2015 Dec 4;14(12):5088-98. doi: 10.1021/acs.jproteome.5b00658. Epub 2015 Nov 13.
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 ).
长期以来，缺乏生物信息学工具一直使N-糖基化的研究变得复杂。特别是，仍然缺乏用于靶向（相对）定量的快速且强大的数据处理工具。我们开发了模块化的高通量数据处理软件MassyTools，它能够校准光谱、提取数据，并根据用户定义的聚糖或糖肽组成列表进行质量控制计算。输出的典型示例包括背景扣除后的相对面积、基于同位素模式的质量分数、光谱质量分数和信噪比。我们展示了MassyTools在来自不同样品的MALDI-TOF-MS聚糖和糖肽数据上的性能。MassyTools的校准效果优于商业软件flexAnalysis，内部校准后的ppm误差通常低2倍。使用MassyTools和flexAnalysis进行相对定量得到了相似的结果，主要聚糖的相对标准偏差（RSD）约为6%。然而，对于低丰度分析物，MassyTools产生的RSD值比flexAnalysis低2至5倍。此外，基于计算出的质量标准进行特征整理提高了数据质量。总之，我们表明MassyTools是一种用于高通量、高性能糖基化分析的强大自动化数据处理工具。该软件包根据Apache 2.0许可发布，可在GitHub（https://github.com/Tarskin/MassyTools）上免费获取。
