Coupling of fully automated chip electrospray to Fourier transform ion cyclotron resonance mass spectrometry for high-performance glycoscreening and sequencing.

Institute for Medical Physics and Biophysics, University of Münster, Robert Koch Str. 31, 48149 Münster, Germany.
Rapid Communications in Mass Spectrometry (Impact Factor: 2.51). 02/2004; 18(24):3084-92. DOI: 10.1002/rcm.1733
Source: PubMed

ABSTRACT The NanoMate robot has been coupled to a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer at 9.4 T and implemented for the first time for complex carbohydrate analysis. It was optimized in the negative ion mode to achieve automated sample delivery on the chip along with increased sensitivity, ultra-high resolution and accurate mass determination. A novel bracket has been designed to allow a reliable mounting of the NanoMate to the Apollo electrospray ionization (ESI) source of an APEX II instrument. The notably higher efficiency of ionization for compositional mapping of complex mixtures and feasibility for fragmentation analysis of components by sustained off-resonance irradiation collision-induced tandem mass spectrometry (SORI-CID MS2) has been demonstrated on a glycoconjugate mixture containing O-glycosylated sialylated peptides from urine of a patient suffering from a hereditary N-acetylhexosaminidase deficiency (Schindler's disease), previously analyzed by capillary-based nanoESI-FTICRMS, and of a healthy control person. Due to its potential to generate highly charged ionic species, reduce the in-source fragmentation, increase sensitivity, reproducibility and ionization efficiency, along with the ability to generate a sustained and constant electrospray, this method can be considered as a new platform for advanced glycomics.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A high-throughput approach for biomolecule analysis is demonstrated for a mixture of peptides from tryptic digest of four proteins as well as a tryptic digests of human plasma. In this method a chip based electrospray autosampler coupled to a hybrid ion mobility (IMS) mass spectrometer (MS) is utilized to achieve rapid sample analysis. This high-throughput measurement is realized by exploiting the direct infusion capability of the chip based electrospray with its rapid sample manipulating capability as well as a high sensitive IMS-MS with a recently developed IMS-IMS separation technique that can be multiplexed to provide greater throughput. From replicate IMS-MS runs of known mixtures, the average uncertainty of peak intensities is determined to be +/-7% (relative standard deviation), and a detection limit in the low attomole range is established. The method is illustrated by analyzing 124 human plasma protein samples in duplicate, a measurement that required 16.5 h. Current limitations as well as implications of the high-throughput approach for complex biological sample analysis are discussed.
    Journal of Proteomics 07/2008; 71(3):318-31. · 4.09 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent developments in bioanalytical instrumentation, MS detection, and computational data analysis approaches have provided researchers with capabilities for interrogating the complex cellular glycoproteome, to help gain a better insight into the cellular and physiological processes that are associated with a disease and to facilitate the efforts centered on identifying disease-specific biomarkers. This review describes the progress achieved in the characterization of protein glycosylation by using advanced capillary and microfluidic MS technologies. The major steps involved in large-scale glycoproteomic analysis approaches are discussed, with special emphasis given to workflows that have evolved around complex MS detection functions. In addition, quantitative analysis strategies are assessed, and the bioinformatics aspects of glycoproteomic data processing are summarized. The developments in commercial and custom fabricated microfluidic front-end platforms to ESI- and MALDI-MS instrumentation, for addressing major challenges in carbohydrate analysis such as sensitivity, throughput, and ability to perform structural characterization, are further evaluated and illustrated with relevant examples.
    Electrophoresis 01/2011; 32(1):14-29. · 3.26 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Membrane proteomic analysis has been proven to be a promising tool for identifying new and specific biomarkers that can be used for prognosis and monitoring of various cancers. Membrane proteins are of great interest particularly those with functional domains exposed to the extracellular environment. Integral membrane proteins represent about one-third of the proteins encoded by the human genome and assume a variety of key biological functions, such as cell-to-cell communication, receptor-mediated signal transduction, selective transport, and pharmacological actions. More than two-thirds of membrane proteins are drug targets, highlighting their immensely important pharmaceutical significance. Most plasma membrane proteins and proteins from other cellular membranes have several PTMs; for example, glycosylation, phosphorylation, and nitrosylation, and moreover, PTMs of proteins are known to play a key role in tumor biology. These modifications often cause change in stoichiometry and microheterogeneity in a protein molecule, which is apparent during electrophoretic separation. Furthermore, the analysis of glyco- and phosphoproteome of cell membrane presents a number of challenges mainly due to their low abundance, their large dynamic range, and the inherent hydrophobicity of membrane proteins. Under pathological conditions, PTMs, such as phosphorylation and glycosylation are frequently altered and have been recognized as a potential source for disease biomarkers. Thus, their accurate differential expression analysis, along with differential PTM analysis is of paramount importance. Here we summarize the current status of membrane-based biomarkers in various cancers, and future perspective of membrane biomarker research.
    Proteomics 08/2012; 12(19-20):3085-104. · 4.43 Impact Factor