Changes in protein glycosylation are frequently identified in the context of diseases. Alterations in N-glycan profiles from blood plasma for example have been found to correlate with pathological states, such as diabetes type II, inflammation, liver cirrhosis/fibrosis and inbreast, pancreas, ovaries, prostate, stomach and lung cancer. Hence detailed information about the glycosylation status of a patient could be utilised in the context of personalised medicine when the correlation between glycan signatures, particular diseases and their treatment is understood.
In most clinical settings the glycosylation status of proteins is mostly disregarded due to the lack of tools that allow us to obtain this information in sufficient specificity and sensitivity within the standard capacities of a haematology or clinical laboratory. The development and availability of reliable, robust, rapid and sensitive workflows and technologies for sample preparation, data acquisition and automated analysis that can also be handled by non-glycobiologists represents a key step and requirement to introduce and establish glycomic and glycoproteomic parameters as routinely acquired clinical parameters.
We offer a novel method for determining the composition, connectivity and configuration of glycans by ion mobility-mass spectrometry (IM-MS) in negative ionization mode.
Figure 1: Structure and IM–MS data of trisaccharides 1–6.
a) The synthetic trisaccharides share the same disaccharide core, and differ merely in the composition, connectivity, or configuration of the last monosaccharide building block.
b) IM–MS drift-time distributions for trisaccharides 1–6 as [M-H]- ions. The values in Å2 correspond to the estimated CCSs in the drift gas nitrogen and represent averages of three independent measurements. Although compositional isomers cannot be distinguished, connectivity and configurational isomers are clearly identified on basis of their CCSs.
The drift time is used to calculate the rotationally averaged collision cross-section (CCS) of an ion in a specific drift gas. This CCS is a molecular property, which under controlled conditions is independent of instrument parameters and is correlated to the shape of an ion. As such, CCSs can be used as an additional identification parameter, and can be stored in databases, thereby enabling easier and more reliable structural assignment.
As the sample and time requirements of IM–MS are similar to those of a conventional mass spectrometry experiment, the additional information is obtained at no extra cost.
The combined analysis of intact glycan ions and their fragments to obtain characteristic CCS fingerprints is essential for the structural identification of glycans and glycoconjugates. Using connected m/z and CCS information in databases is key to simplify routine analyses.
Figure 2: Workflow of a tandem MS experiment followed by ion-mobility separation. The drift times of certain fragments (F) can be more characteristic than the intact precursor ions (P) and allow database supported structural identification.
The sample can contain even less than 0.1 % of the target carbohydrate as the high intensity measurements of the drift time value and m/z value enable the detection of the target carbohydrate and the determination of its structure. The direct investigation of diagnostic fragments arising from large macromolecules like glycoproteins is exceptionally useful for the rapid analysis of structural features of complex samples.
The offered database supported IM–MS method is a powerful tool which drastically improves the structural analysis and quality control of carbohydrates. Connectivity and configurational isomers can be separated efficiently with baseline resolution, and the relative content of isomeric impurities can be determined quickly and easily. To our knowledge, no other experimental technique can provide the same structural information as quickly and with such minimal sample consumption.
PCT priority application WO17/036545 filed 03.09.2015, nationalized in US in March 2018.
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