Background-We sought to perform a systematic lipid analysis of atherosclerotic plaques using emerging mass spectrometry techniques. Methods and Results-A chip-based robotic nanoelectrospray platform interfaced to a triple quadrupole mass spectrometer was adapted to analyze lipids in tissue sections and extracts from human endarterectomy specimens by shotgun lipidomics. Eighteen scans for different lipid classes plus additional scans for fatty acids resulted in the detection of 150 lipid species from 9 different classes of which 24 were detected in endarterectomies only. Further analyses focused on plaques from symptomatic and asymptomatic patients and stable versus unstable regions within the same lesion. Polyunsaturated cholesteryl esters with long-chain fatty acids and certain sphingomyelin species showed the greatest relative enrichment in plaques compared to plasma and formed part of a lipid signature for vulnerable and stable plaque areas in a systems-wide network analysis. In principal component analyses, the combination of lipid species across different classes provided a better separation of stable and unstable areas than individual lipid classes.
Conclusions-This
Gangliosides (GGs), involved in malignant alteration and tumor progression/invasiveness, are considered as tumor biomarkers or therapeutic targets. Here, we describe the first systematic GG composition characterization in human gliosarcoma versus normal brain tissue using our recently developed mass spectrometry (MS) methods, based on nano-electrospray (nano-ESI), Fourier-transform ion cyclotron resonance (FT-ICR), and chip nano-ESI quadrupole time-of-flight (QTOF), complemented by thin-layer chromatographic (TLC) analysis and quantification. Combined MS enabled detection and structural assignment of 73 distinct GG species: many more than reported so far for investigated gliomas. Apart from the 7.4-times lower total GG content, gliosarcoma contained all major brain-associated species, however, in very altered proportions, exhibiting a highly distinctive pattern: GD3 (48.9%)>GD1a/nLD1>GD2/GT3>GM3>GT1b>GM2>GM1a/GM1b/nLM1>LM1>GD1b>GQ1b. MS also revealed abundant O-Ac-GD3; its sequencing provided structural evidence to postulate a novel O-Ac-GD3 isomer O-acetylated at the inner Neu5Ac-residue, previously not structurally confirmed. The high sensitivity and mass accuracy permitted the assignment of unusual minor species: GM4, Hex-HexNAc-nLM1, Gal-GD1, Fuc-GT1, GalNAc-GT1, O-Ac-GM3, di- O-Ac-GD3O-Ac-GD3, and O-Ac-GT3, not previously reported as glioma-associated. The gliosarcoma-expressed GA2 might represent a marker distinguishing astrocytic from oligodendroglial tumors. This is, to our knowledge, so far the most complete GG composition characterization of certain glioma, which demonstrates that our MS-based approach could provide essential structural information relevant to glycosphingolipid role(s) in brain tumor biology, differential diagnosis/prognosis and novel treatment concepts.
Carbohydrates represent a major class of biopolymers, which occur in nature either as oligosaccharides or glycoconjugates, in which the sugar moiety is linked to proteins or lipids. The significance of mass spectrometry for highly sensitive analysis of complex carbohydrates increased after the introduction of the electrospray ionization and matrix assisted laser desorption/ionization methods and the possibility of tandem MS for sequencing of single molecular species in complex mixtures. Rapid and sensitive characterization of carbohydrates in biological systems by automated nanoscale liquid delivery and chip-based electrospray interface techniques have not been developed so far. In this contribution, the implementation and optimization of a fully automated chip-based nanoelectrospray assembly (NanoMate system), operating in the negative ion mode, in combination with QTOF-tandem MS for mapping/sequencing and computer-assisted structure assignment for carbohydrate components in complex mixtures is presented.
The introduction of chip-based electrospray (ESI) ion sources into biological mass spectrometry (MS) addressed the fundamental issue of how to analyze minute amounts of complex biological systems. The automation of sample delivery into the MS combined with the chip-based ESI allows for high quality bioanalysis in a high-throughput fashion. These advantages have already been demonstrated in proteomics, direct screening of drugs and drug discovery. As part of our continuing effort to implement automated chip-based mass spectrometry into the field of complex carbohydrate analysis, we hereby report the development of a chipESI MS and MS/MS methodology for the screening of gangliosides. A strategy to characterize a complex ganglioside mixture from human cerebellar tissue, by automated ESIchip-quadrupole time-of-flight (QTOF) MS and MS/MS is presented here. The feasibility of this method, and the general experimental requirements for automated chipESI MS analysis of these carbohydrate species is
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