Automating Mass Spectrometry-Based Quantitative Glycomics using Tandem Mass Tag (TMT) Reagents with SimGlycan
Poster Dec 22, 2016
Ningombam Sanjib Meitei; Arun Apte; Sergei Snovida; Julian Saba; John Rogers
One of the emerging trends in glycomics research is the innovation related to accurate MS based quantitative analysis of glycans. Recently, we have introduced aminoxyTMT Reagents, which enable efficient relative quantitation of carbohydrates, improved labeled-glycan ionization efficiency and increased analytical throughput. These reagents can be used for quantitative analysis of native N-glycans by direct or LC-coupled ESI-MS. However, unlike for proteomics, one of the major challenges left unaddressed is the lack of informatics tools to automate the qualitative and quantitative analysis protocols. These protocols include identification/quantitation of glycans using MS/MS data and differential analysis across biological samples. SimGlycan software is redesigned to streamline such protocols of the quantitation of labeled-glycoforms derived from complex mixtures.
Tryptic digests of several standard glycoproteins and monoclonal antibodies were treated with PNGase F glycosidase to release N-glycans. Following reversed-phase and graphitized carbon extraction/desalting steps, the glycans were labeled with oxyTMT reagents according to an optimized protocol. Labeled glycans were analysed using Velos Pro mass spectrometer (Thermo Scientific) in the positive ion mode to acquire trap-HCD MS/MS fragmentation. Data was subjected to SimGlycan to identify structure of the sample glycans. Post identification, we assign TMT 130.13 ion as the control The program allows custom setting of reporter ions correction factors, calculates sum/average/median of the reporter ion intensities, number of MS/MS spectra which identifies a glycan. Different types of chart facilitate glycan differential analysis across samples.
TMT reporter ion peak cluster was one of the most intense features in the MS2 spectra for all doubly-charged precursors that contained one sodium and one proton adduct. In order to test the performance of the software, HCD spectra were acquired on five high-mannose glycans. HCD fragmentation of high-mannose glycan precursors viz. 780, 861, 942, 1023 and 1124 m/z produced abundant TMT reporter ions, as well as Y/B/A-type ions. The MS/MS data was subjected to SimGlycan for structural identification. The program identifies N-glycan with carbohydrate residues (GlcNAc)2(Man)5 for the precursor m/z value 780, N-glycan (GlcNAc)2(Man)6 for 861, N-glycan (GlcNAc)2(Man)7 for 942, N-glycan (GlcNAc)2(Man)8 for 1023 and N-glycan with (GlcNAc)2(Man)9 for 1124, which is a correct assignment for all high-mannose glycans present in the sample. Majority of the ions with intact TMT tag carry Na adduct and are generally the outcome of two glycosidic cleavages towards reducing end. The program enables the quantitation by measuring reporter ion peak intensities. In order to nullify the interference of other nearby peaks onto TMT reporter ions, we set a custom correction factor. Statistics calculated as a measure of the relative amount/expression level of each glycan present in the samples constitute sum/average/median/standard deviation of the reporter ion intensities, ratio sum/average/median intensity of each TMT ion and the control TMT 130.13 ion, Log2 relative expressions of these ratios, number of MS/MS spectra which identifies each glycan. Differential analysis and data visualization are facilitated through different charts. Heat map displays relative intensities of TMT reporter ions for each identified glycan. Cluster dot plot shows Log2 expression levels of a glycan at different TMT reporter ions. The performance of the software for several standard glycoproteins and monoclonal antibodies were also examined in these studies.