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May 15, 2012 (Vol. 32, No. 10)

Maximizing Mass Spec's Potential

  • Yes to N- and O-

    Click Image To Enlarge +
    Fragment ion spectra of the proteinase K-generated O-glycopeptide A276-S290 with two identical O-glycans from asialofetuin. A fragment ion spectrum (upper panel; MS2) of the protonated precursor at m/z 990.9 ([M+2H]2+) (inset), and a corresponding MS3 spectrum of m/z 1615.7 ([M+H]+; lower panel) are shown. The proposed peptide structure is indicated on top of the MS3 spectrum. Light square, N-Acetylgalactosamine; light circle, galactose. [Leiden University Medical Center]

    Some glycoproteins are trickier to study than others. Smaller, less complex molecules are easier to analyze by mass spectrometry, and so it would seem that it would be better to study the “glyco” part separately from the “protein” part of a glycoprotein. But unlike N-glycans (attached to asparagine), there is no enzyme that will specifically release all O-glycans (attached to serine or threonine) from the peptide backbone, so tedious chemical means need to be used, which are accompanied by complicating side reactions.

    An alternative and increasingly popular approach for studying protein glycosylation is, therefore, the analysis of glycopeptides generated by proteolytic cleavage of glycoproteins.

    A recent MS-based metabolomic study of urine showed that an O-glycopeptide was the discriminator between the healthy and diseased state of urinary tract infected patients. That stimulated Gerhild Zauner, Ph.D., researcher at the Leiden University Medical Center in the Netherlands, to take a closer look at the glycopeptides formed by enzymatic digestion of human fibrinogen’s backbone.

    The advantage of such an approach is that the glycan portion remains attached to a peptide, yielding information on the attachment site—information that is lost when releasing the glycans. “Very often you want to have information about where the glycan is attached to the protein in order to make some sense of function or protein-protein interaction.”

    Yet a specific proteinase like trypsin will often lead to long peptide stretches that may carry multiple modifications such as N- and O-glycans that can complicate analysis by MS. Therefore, “it is normally difficult to see O-glycopeptides in a trypic digest,” Dr. Zauner explained. So they opted to do a more extended study with the nonspecific Proteinase K, which can cut the backbone into much smaller pieces.

    Dr. Zauner and colleagues had previously established a protocol to look at proteinase K-generated N- and O-glycopeptides, in which performing nanoLC-MS analysis using a hydrophilic interaction liquid chromatography (HILIC) column gave a clear separation of N- from O-glycopeptides. The same was found to be the case for peptides from human fibrinogen. After running the fractions through reverse-phase LC-MS, they discovered O-glycopeptides that had not been described previously.

    Because Dr. Zauner didn’t know what the proteinase K fragments would be ahead of time, she “had to annotate the results by hand,” she said. As techniques to analyze O-linked glycopeptides become more widespread, instrument companies and others are developing software tools to automate the peptide and glycan assignments of glycopeptides, but for now “it’s a very time-consuming process.”

  • The Best of All Worlds

    Even when software exists, it doesn’t always do everything a researcher needs it to.

    Mass spec is often called upon to examine protein biomarkers found in biological fluids such as blood and spinal fluid, and it relies on sophisticated algorithms to do so. But “no one single method works perfectly to find the exact quantification,” said Jean Gao, Ph.D., of the University of Texas at Arlington.

    The approaches currently used in proteomics apply techniques such as spectral counting, chromatographic peak area, peptide count, or sequence coverage. Yet these different methods will often produce paradoxical results.

    Dr. Gao and her colleagues have been looking at the pros and cons of different approaches, and “have developed more efficient ways to integrate those different quantification methods, to obtain a more robust algorithm.” They take the measured values from each of the various methods and treat them as a feature, combining them as a vector in the new multivariate algorithm.

    The data integration technique has previously been used with other technology, but not for mass spectrometry as far as Dr. Gao is aware. The advantage of high-resolution MS, she says, is that it provides more of a global view in the search for distinguishable biomarkers.

    Dr. Gao and her collaborators look into subgroups of proteins that they expect to work together—those that are able to bind to albumin, for example—and compare their abundance in normal and diseased samples. The eventual clinical goal is to find how the levels of biomarkers change, she said, to discover how these proteins are contributing to the disease stages of different patients.

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