Sialic Acid-focused Quantitative Mouse Serum Glycoproteomics by Multiple Reaction Monitoring Assay

Despite increasing importance of protein glycosylation, most of the large-scale glycoproteomics have been limited to profiling the sites of N-glycosylation. However, in-depth knowledge of protein glycosylation to uncover functions and their clinical applications requires quantitative glycoproteomics eliciting both peptide and glycan sequences concurrently. Here we describe a novel strategy for the multiplexed quantitative mouse serum glycoproteomics based on a specific chemical ligation, namely, reverse glycoblotting technique, focusing sialic acids and multiple reaction monitoring (MRM). LC-MS/MS analysis of de-glycosylated peptides identified 270 mouse serum peptides (95 glycoproteins) as sialylated glycopeptides, of which 67 glycopeptides were fully characterized by MS/MS analyses in a straightforward manner. We revealed the importance of a fragment ion containing innermost N-acetylglucosamine (GlcNAc) residue as MRM transitions regardless the sequence of the peptides. Versatility of the reverse glycoblotting-assisted MRM assays was demonstrated by quantitative comparison of 25 targeted glycopeptides from 16 proteins between mice with homo and hetero types of diabetes disease model.Clinical proteomics focusing on the identification and validation of biomarkers and the discovery of proteins as therapeutic targets is an emerging and highly important area of proteomics. Biomarkers are measurable indicators of a specific biological state (particularly one relevant to the risk of contraction) and the presence or the stage of disease, and are thus expected to be useful for the prediction, detection, and diagnosis of disease as well as to follow the efficacy, toxicology, and side effects of drug treatment, and to provide new functional insights into biological processes.At present, proteomics methods based on mass spectrometry (MS) have emerged as the preferred strategy for discovery of diagnostic, prognostic, and therapeutic protein biomarkers. Most biomarker discovery studies use unbiased, “identified-based” approaches that rely on high performance mass spectrometers and extensive sample processing. Semiquantitative comparisons of protein relative abundance between disease and control patient samples are used to identify proteins that are differentially expressed and, thus, to populate lists of potential biomarkers. De novo proteomics discovery experiments often result in tens to hundreds of candidate biomarkers that must be subsequently verified in serum. However, despite the large numbers of putative biomarkers, only a small number of them are passed through the development and validation process into clinical practice, and their rate of introduction is declining. The first non-standard abbreviation (MS above is standard) must be footnoted the same as the abbreviation footnote, and MRM must be the first abbreviation in the list because it is the one footnoted. After that the order does not matter.Targeted proteomics using multiple reaction monitoring (MRM)1 is emerging as a technology that complements the discovery capabilities of shotgun strategies as well as an alternative powerful novel MS-based approach to measure a series of candidate biomarkers (1–7). Therefore, MRM is expected to provide a powerful high throughput platform for biomarker validation, although clinical validation of novel biomarkers has been traditionally relying on immunoassays (8, 9). MRM exploits the unique capabilities of triple quadrupoles (QQQ) MS for quantitative analysis. In MRM, the first and the third quadrupoles act as filters to specifically select predefined m/z values corresponding to the peptide precursor ion and specific fragment ion of the peptide, whereas the second quadrupole serves as collision cell. Several such transitions (precursor/fragment ion pairs) are monitored over time, yielding a set of chromatographic traces with retention time and signal intensity for a specific transition as coordinates. These measurements have been multiplexed to provide 30 or more specific assays in one run. Such methods are slowly gaining acceptance in the clinical laboratory for the routine measurement of endogenous metabolites (10) (e.g. in screening newborns for a panel of inborn errors of metabolism) some drugs (11) (e.g. immunosuppressants), and the component analysis of sugars (12).One of the profound challenges in clinical proteomics is the need to handle highly complex biological mixtures. This complexity presents unique analytical challenges that are further magnified with the use of clinical serum/plasma samples to search for novel biomarkers of human disease. The serum proteome is composed of tens of thousands of unique proteins, of which concentrations may exceed 10 orders of magnitude. Protein glycosylation, one of the most common post-translational modifications, generates tremendous diversity, complexity, and heterogeneity of gene products. It changes the biological and physical properties of proteins, which include functions as signals or ligands to control their distribution, antigenicity, metabolic fate, stability, and solubility. Protein glycosylation, in particular by N-linked glycans, is prevalent in proteins destined for extracellular environments. These include proteins on the extracellular side of the plasma membrane, secreted proteins, and proteins contained in body fluids (such as blood serum, cerebrospinal fluid, urine, breast milk, saliva, lung lavage fluid, or pancreatic juice). Considering that such body fluids are most easily accessible for diagnostic and therapeutic purposes, it is not surprising that many clinical biomarkers and therapeutic targets are glycoproteins. These include, for example, cancer antigen 125 (CA125) in ovarian cancer, human epidermal growth factor receptor 2 (Her2/neu) in breast cancer, and prostate-specific antigen (PSA) in prostate cancer. In addition, changes in the extent of glycosylation and the structure of N-glycans or O-glycans attached to proteins on the cell surface and in body fluids have been shown to correlate with cancer and other disease states, highlighting the clinical importance of this modification as an indicator or effector of pathologic mechanisms (13–16). Thus, clinical proteomic platforms should have capability to provide protein glycosylation information as well as sufficient analytical depth to reliably detect and quantify specific proteins with sufficient accuracy and throughput.To improve the detection limits to the required sensitivities, one needs to dramatically reduce the complexity of the sera samples. For focused glycoproteomics, several techniques using lectins or antibodies enabling the large-scale identification of glycoproteins have recently been developed (17–19). Notably, Zhang et al. reported a method for the selective isolation of peptides based on chemical oxidation of the carbohydrate moiety and subsequent conjugation to a solid support using hydrazide chemistry (20–26). However, it is not possible to provide any structural information about N-glycans because the MS analysis is performed on peptides of which N-glycans are removed preferentially by treating with peptide N-glycanase (PNGase). In 2007, we developed a method for rapid enrichment analysis of peptides bearing sialylated N-glycans on the MALDI-TOF-MS platform (27). The method involves highly selective oxidation of sialic acid residues of glycopeptides to elaborate terminal aldehyde group and subsequent enrichment by chemical ligation with a polymer reagent, namely, reverse glycoblotting technique inspired from an original concept of glycoblotting method (28). This method, in principle, is capable identifying both glycan and peptide sequences concurrently. Recently, Nilsson et al. reported that glycopeptides from human cerebrospinal fluid can be enriched on the basis of the same principle as the reverse glycoblotting protocol, and captured glycopeptides were analyzed with ESI FT-ICR MS (29). Because it is well known that sialic acids play important roles in various biological processes including cell differentiation, immune response, and oncogenesis (30–34), our attention has been directed toward feasibility of the reverse glycoblotting technique in quantitative analysis of the specific glycopeptides carrying sialic acid(s) by combining with multiplexed MRM-based MS.