automated glycan structural isomer differentiation using ... · automated glycan structural isomer...
TRANSCRIPT
Automated Glycan Structural Isomer Differentiation Using SimGlycan Software Julian Saba1, Arun Apte2, Ningombam Sanjib Meitei2, and Rosa Viner1 1Thermo Fisher Scientific, San Jose, CA, 2PREMIER Biosoft, Palo Alto, CA
Application Note: 516
Key Words
•Glycans
•VelosPro
•SimGlycan
•MultistageFragmentation
•GlycanStructuralIsomer
IntroductionCurrently, glycans are attracting attention from the scien-tific community as potential biomarkers or as post-transla-tional modifications (PTMs) of therapeutic proteins.1,2 For example, glycans on the surface of cells mediate interac-tions between cells and define cellular identities within complex tissues at all stages of animal life. In addition, specific glycan structures control the activities of the pro-teins to which they are attached, adding a post-transcrip-tional, post-translational layer of regulation onto protein function. Many glycans show disease-related expression level changes.3,4 In some instances, the function of specific cell-surface signaling molecules requires the elucidation of an exact glycan structure at a precise site on an appropri-ate protein. However, the complex branching and isomeric nature of glycans pose significant analytical challenges to the identification of these structures.
Mass spectrometry (MS) has emerged as one of the most powerful tools for the structural elucidation of glycans.5-7 This is due to its sensitivity of detection and its ability to analyze complex mixtures of glycans derived from a variety of organisms and cell lines. However, there are some drawbacks to using MS-based approaches. Mass spectrometers generate large volumes of data. Currently, processing of data from glycans is mostly done manually, which makes it tedious and time-consuming. In addition to the characterization of the sugar sequence, the analysis must elucidate branching, linkages between monosac-charide units, anomeric configuration, and the location of possible sulfate or phosphate groups.5 The lack of reliable bioinformatics tools to simplify and expedite the elucida-tion of glycan structures is the biggest bottleneck in MS-based approaches.
The challenges of MS-based glycomics are further com-pounded by the need for multistage fragmentation (MSn). This is a critical tool for glycan structure elucidation8-11, as it allows for determination of structural heterogeneity and differentiation of isomers. However, it is complicated by the large number of spectra generated for a single structure. It is very common that one must acquire six or seven levels of fragmentation (MS6 or MS7) to differentiate potential glycan structural isomers.
SimGlycan™ software from PREMIER Biosoft provides support for glycan identification and structural elucida-tion.12 It accepts raw data files from Thermo Scientific mass spectrometers and elucidates the associated glycan structure with high accuracy using database searching and scoring techniques. MS/MS data are searched against the SimGlycan software’s database containing theoretical frag-mentation of over 9500 glycans. Each proposed structure is assigned a score to reflect how closely it matches with the experimental data. Other relevant biological informa-tion for the proposed glycan structures, such as the glycan class, reaction, pathway, and enzyme, are also available via interactive links. To address the challenges of MSn data interpretation, SimGlycan software version 2.92 has been introduced to provide comprehensive support for MSn experiments performed on Thermo Scientific mass spectrometers.
In this note, we present for the first time an automated workflow for complete structural elucidation of glycans by combining MSn fragmentation and data processing using SimGlycan software.
GoalTo demonstrate the use of SimGlycan software for automated structural elucidation of MSn glycan spectra acquired on Thermo Scientific mass spectrometers.
Experimental Conditions
SamplePreparationChicken ovalbumin (1 mg, Sigma) was reduced, alkylated, and digested overnight with trypsin in 25 mM ammonium bicarbonate buffer (pH~8) at 37 ºC as described previ-ously.13 PNGase F solution (3 μL, Roche) was added to 200 μL of digested sample and the mixture was incubated for another 16 hours at 37 ºC.
Released glycans were separated from peptides using a Sep-Pak® C18 cartridge. The Sep-Pak C18 cartridge was conditioned by washing with acetonitrile, followed by water. PNGaseF-digested sample was loaded onto the car-tridge. The released glycans were eluted with 1% ethanol while peptides remained bound to the cartridge.
Released ovalbumin oligosaccharides were first puri-fied using porous graphite carbon column (PhyNexus) and then permethylated as described previously.9
MassSpectrometryAll MSn experiments were carried out on a Thermo Scientific Velos Pro linear ion trap mass spectrometer using direct infusion into a nanoelectrospray source. Details for the mass spectrometric settings and SimGlycan 2.92 search parameters are listed in Tables 1 and 2.
Table 1. Mass spectrometer settings
Source nano-ESI
Capillary Temperature 200 °C
S-lens RF Level 50%
Source Voltage 1.3 kV
Full MS Mass Range 150-2000 (m/z)
Scan Rate Enhanced
Maximum Injection Time Full MS 50 ms
MSn 50 ms
Isolation Width 3
Collision Energy 30
Activation Time 10 ms
Predictive AGC Enabled Yes
No. Microscans for Full MS 5
Target Value Full MS 3e4
Target Value MSn 3e4
Table 2. SimGlycan 2.92 search parameters
Ion Mode Positive
Adducts Sodium
Precursor Ion m/z Error Tolerance 0.8 Da
Spectrum Peak m/z Error Tolerance 0.8 Da
Chemical Derivatization Permethylated
Reducing Terminal Reduced
Include Substituents while Searching Glycans Yes
Class Glycoprotein
SubClass N-Glycan
Biological Source Chicken
Pathway Unknown
Search Structure All
Glycan Type All
Results and DiscussionAutomated structural interpretation of MSn glycan spectra were tested on glycans released from chicken ovalbumin (Figure 1). This was an ideal system to test the capabil-ity of SimGlycan software because the glycan content of ovalbumin has been characterized in depth.14 In parallel, we manually interpreted the MSn spectra and compared it with Glycome Technologies results presented at the 58th ASMS conference15 which provided a perfect control.
Figure 2a shows the MS profile of permethylated glycans derived from ovalbumin and analyzed on a Velos Pro mass spectrometer. This was an ideal instrument for these experiments as the dual-pressure ion trap and S-Lens
MS2
MSn
.... MS2 data
imported into SimGlycan
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MSn data imported into
SimGlycan
Confirmation of glycan
structure
MSn dataacquisition
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14
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MS2 data searched andscored against
SimGlycan database
Selection of glycan structure to match with
MSn data
Figure 1. Workflow for automated structural interpretation of MSn glycan spectra.
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MS2
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MS4
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Figure 2. (a) Ion trap (IT) mass spectrum of permethylated ovalbumin released glycans (labeled peaks correspond to Table 3). (b) IT MS/MS spectrum of the peak at m/z 1054.68. (c) Set of sequential MSn spectra acquired for peak at m/z 1054.68 (+2).
ion optics provide increased ion transmission along with better trapping and fragmentation efficiency, which are critical for performing MSn experiments. Table 3 shows all glycans identified in this study. Figure 2b shows the MS2 spectrum for a peak at m/z 1054.68 (+2) (#13 in Figure 2a), which was selected for software evaluation as it was interrogated before.15 Though it is possible to identify the different monosaccharides that make up the overall glycan composition, it is very difficult from the MS2 spectrum to determine linkages and branching. To fully characterize the glycan structure, sets of sequential MSn spectra were acquired for this precursor (Figure 2c) and SimGlycan soft-ware was used for data interpretation. The Velos Pro mass spectrometer was operated in “Enhanced Scan” profile mode for all MS experiments. The enhanced scan mode provides for higher resolution and allows charge-stage determination of precursors and fragment ions.
The initial step in data analysis is to import the MS2 spectrum into SimGlycan for automatic compositional identification. Based on the criteria selected, the SimGlycan software searches its database to match the MS2 data. If we were to strictly rely on MS2 data, then the MS/MS fragmentation pattern for m/z 1054.68 (+2) can be interpreted as a hybrid glycan with a bisecting GlcNAc from the top ranked glycan from SimGlycan database search results (Figure 3). Examination of the glycan list reported by SimGlycan software for the submitted MS2 spectrum shows additional glycan compositions having the same mass but ranked much lower. These glycans, though reported to have much lower probability of matching the submitted MS2 spectrum, could represent additional isomers that might be present, as not every major fragment in the spectra was assigned (Figure 2b).
To determine whether these glycans were additional isomers present in the sample, SimGlycan software was used to examine if any of the lower-ranked glycan struc-
tures matched the MSn fragmentation pathway. From the list generated by the software, we selected specific structures to compare with the MSn fragmentation pathway. Each succes-sive level of fragmentation was then brought in to match with the specific precursor selected for fragmentation in the previous level of MSn spectrum.
A
B
C
From our list, we selected the asialyl digalactosyl bian-tennary glycan to confirm or deny as an isomer. It was ranked much lower based on MS2 data, but had the same precursor mass as the top match (Figure 3, ranked 14 on the list). From the MS2 spectrum (Figure 2b) of m/z 1054.68 (+2) we selected the fragment ion at m/z 1623.25 (+1) for further fragmentation. The detection of this ion indicated the loss of Gal-GlcNAc from the non-reducing end of the asialyl digalactosyl biantennary glycan. Figures 2c and 4a show the MS3 spectra for this ion and the fragmentation match of this particular spectrum to the theoretical fragmentation of the selected structure. Of particular interest in the MS3 spectrum is the fragment ion at m/z 1159.93 (+1), which
corresponds to additional loss of Gal-GlcNAc structure. This is only possible from our selected asialyl digalactosyl biantennary glycan structure as additional loss is possible from the non-reducing end. Figure 4b shows the over-all sequential fragmentation pathway for the proposed structure and how it is only compatible with the selected structure and the set of sequential MSn spectra acquired in Figure 2c (1054.68→662.50). Figure 4c shows sequential (1054.68→1070.84 as in Figure 2c) fragmentation path-way for the hybrid glycan with the bisecting GlcNAc. This further confirms that this structure is also present in pre-cursor at m/z 1054.68 (+2). An additional hybrid glycan is identified for this precursor in Figure 4d (1054.68→621.59 as in Figure 1c). As illustrated in Figures 4b-d, SimGlycan software was able to resolve isobaric oligosaccharides and perform detailed characterization of selected structures.
Table 3 shows 2 other glycan structural isomers (la-beled as 5 and 9) identified by SimGlycan software using the approach described above. As well as differentiating structural isomers, MSn can be used to confidently eluci-date correct glycan structure when insufficient fragmenta-tion is generated at the MS2 level. For example, the peak at m/z 1422.92(+2) represents a single glycan structure. How-ever, the MS2 spectrum does not provide enough informa-tion to clearly elucidate the correct structure. In fact, sub-mission of MS2 data to SimGlycan resulted in an incorrect structure being ranked number one due to the absence of key fragment ions. The correct structure of this precursor is shown in Table 3 (labeled as 19). Figure 5 highlights the MSn sequential fragmentation pathway required for this glycan identification and the use of SimGlycan to interpret the MSn spectra.
1
14
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Figure 3. SimGlycan search results for ion trap MS/MS spectrum of precursor ion at m/z 1054.68 (+2). Symbolic representation of top-ranked and two lower-ranked glycans search results by SimGlycan software is shown.
b1 3
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- Loss of “H2O” for the particular carboydrate residue
- Loss of “Cross-ring” fragment for the particular carbohydrate residue
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MS7Figure 4. (a) Ion trap MS3 spectrum of precursor at m/z 1623.25 (+1). Symbolic representation of Y-type glycosidic fragments are shown. MSn fragmentation pathway for (b) (Gal)2(Man)3(GlcNAc)4 (c) (Man)5(GlcNAc)4 and (d) (Gal)(Man)4(GlcNAc)4.
A B C D
- Loss of “H2O” for the particular carboydrate residue
- Loss of “Cross-ring” fragment for the particular carbohydrate residue
MS2
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Figure 5. Ion trap MSn fragmentation pathway for precursor at m/z 1422.92 (+2).
Table 3. Structures of chicken ovalbumin N-linked released glycans identified in this study (structures drawn using GlycoWorkbench16)
Conclusion•Thecombinationofpermethylation,MSn, and
SimGlycan software enabled successful identification and differentiation of various structural isomers of chicken ovalbumin released glycans.
•Theoverallanalysistimewasreducedtomatterofminutes thus enabling truly automated, high-throughput data analysis.
•SimGlycansoftwaresimplifieddataanalysisbyprovidingcomprehensive support for performing MSn experiments on Thermo Scientific ion trap and ion trap/Orbitrap hybrid mass spectrometers.
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