Application of lectin microarray to crude samples: differential glycan profiling of lec mutants

We recently developed a novel system for lectin microarray based on the evanescent-field fluorescence-detection principle, by which even weak lectin-oligosaccharide interactions are detectable without a washing procedure. For its practical application, cell glycan analysis was performed for Chinese hamster ovary (CHO) cells and their glycan profile was compared with those of their glycosylation-defective Lec mutants. Each of the cell surface extracts gave a significantly different profile from that of the parental CHO cells in a manner reflecting denoted biosynthetic features. Hence, the developed lectin microarray system is considered to be fully applicable for differential glycan profiling of crude samples.     

Evanescent-field fluorescence-assisted lectin microarray: a new strategy for glycan profiling

Glycans have important roles in living organisms with their structural diversity. Thus, glycomics, especially aspects involving the assignment of functional glycans in a high-throughput manner, has been an emerging field in the postproteomics era. To date, however, there has been no versatile method for glycan profiling. Here we describe a new microarray procedure based on an evanescent-field fluorescence-detection principle, which allows sensitive, real-time observation of multiple lectin-carbohydrate interactions under equilibrium conditions. The method allows quantitative detection of even weak lectin-carbohydrate interactions (dissociation constant, K(d) > 10(-6) M) as fluorescent signals for 39 immobilized lectins. We derived fully specific signal patterns for various Cy3-labeled glycoproteins, glycopeptides and tetramethylrhodamine (TMR)-labeled oligosaccharides. The obtained results were consistent with the previous reports of glycoprotein and lectin specificities. We investigated the latter aspects in detail by frontal affinity chromatography, another profiling method. Thus, the developed lectin microarray should contribute to creation of a new paradigm for glycomics.     

Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal cancer (CRC). Following immunodepletion of the most abundant plasma proteins, the plasma N -linked glycoproteins were enriched using lectin affinity chromatography and subsequently further separated by nonporous silica reversed-phase (NPS-RP)-HPLC. Individual RP-HPLC fractions were printed on nitrocellulose coated slides which were then probed with lectins to determine glycan patterns in plasma samples from 9 normal, 5 adenoma, and 6 colorectal cancer patients. Statistical tools, including principal component analysis, hierarchical clustering, and Z-statistics analysis, were employed to identify distinctive glycosylation patterns. Patients diagnosed with colorectal cancer or adenomas were shown to have dramatically higher levels of sialylation and fucosylation as compared to normal controls. Plasma glycoproteins with aberrant glycosylation were identified by nano-LC-MS/MS, while a lectin blotting methodology was used to validate proteins with significantly altered glycosylation as a function of cancer progression. The potential markers identified in this study for diagnosis to distinguish colorectal cancer from adenoma and normal include elevated sialylation and fucosylation in complement C3, histidine-rich glycoprotein, and kininogen-1. These potential markers of colorectal cancer were subsequently validated by lectin blotting in an independent set of plasma samples obtained from 10 CRC patients, 10 patients with adenomas, and 10 normal subjects. These results demonstrate the utility of this strategy for the identification of N -linked glycan patterns as potential markers of CRC in human plasma, and may have the utility to distinguish different disease states.     

Tyramide signal amplification for antibody-overlay lectin microarray: a strategy to improve the sensitivity of targeted glycan profiling

Antibody-overlay lectin microarray (ALM) has been used for targeted glycan profiling to identify disease-related protein glycoforms. In this context, high sensitivity is desired because it allows for the identification of disease-related glycoforms that are often present at low concentrations. We describe a new tyramide signal amplification (TSA) for the antibody-overlay lectin microarray procedure for sensitive profiling of glycosylation patterns. We demonstrate that TSA increased the sensitivity of the microarray over 100 times for glycan profiling using the model protein prostate specific antigen (PSA). The glycan profile of PSA enriched from LNCAP cells, obtained at a subnanogram level with the aid of TSA, was consistent with the previous reports. We also established the glycan profile of prostate specific membrane antigen (PSMA) using the TSA and ALM. Thus, the TSA for antibody-overlay lectin microarray is a sensitive, rapid, comprehensive, and high-throughput method for targeted glycan profiling and can potentially be used for the identification of disease-related protein glycoforms.     

Exploring the glycan repertoire of genetically modified mice by isolation and profiling of the major glycan classes and nano-NMR analysis of glycan mixtures

The production of mice with genetic alterations in glycosyltransferases has highlighted the need to isolate and study complex mixtures of the major classes of oligosaccharides (glycans) from intact tissues. We have found that nano-NMR spectroscopy of whole mixtures of N- and O-glycans can complement HPLC profiling methods for elucidating structural details. Working toward obtaining such glycan mixtures from mouse tissues, we decided to develop an approach to isolate not only N- and O-glycans, but also to separate out glycosphingolipids, glycosaminoglycans and glycosylphosphatidylinositol anchors. We describe here a comprehensive Glycan Isolation Protocol that is based primarily upon the physicochemical characteristics of the molecules, and requires only commonly available reagents and equipment. Using radiolabeled internal tracers, we show that recovery of each major class of glycans is as good or better than with conventional approaches for isolating individual classes, and that cross-contamination is minimal. The recovered glycans are of sufficient purity to provide a "glycoprofile" of a cell type or tissue. We applied this approach to compare the N- and O-glycans from wild type mouse tissues with those from mice genetically deficient in glycosyltransferases. N- and O-glycan mixtures from organs of mice deficient in ST6Gal-I (CMP-Sia:Galbeta1-4GlcNAc alpha2-6 sialyltransferase) were studied by the nano-NMR spectroscopy approach, showing no detectable alpha2-6-linked sialic acids. Thus, ST6Gal-I is likely responsible for generating most or all of these residues in normal mice. Similar studies indicate that this linkage is very rare in ganglioside glycans, even in wild-type tissues. In mice deficient in GalNAcT-8 (UDP-GalNAc:polypeptide O-Ser/Thr GalNAc transferase 8), HPLC profiling indicates that O-glycans persist in the thymus in large amounts, without a major change in overall profile, suggesting that other enzymes can synthesize the GalNAc-O-Ser/Thr linkage in this tissue. These results demonstrate the applicability of nano-NMR spectroscopy to complex glycan mixtures, as well as the versatility of the Glycan Isolation Protocol, which makes possible the concurrent examination of multiple glycan classes from intact vertebrate tissues.     

Informatics platform for global proteomic profiling and biomarker discovery using liquid chromatography-tandem mass spectrometry

We have developed an integrated suite of algorithms, statistical methods, and computer applications to support large-scale LC-MS-based gel-free shotgun profiling of complex protein mixtures using basic experimental procedures. The programs automatically detect and quantify large numbers of peptide peaks in feature-rich ion mass chromatograms, compensate for spurious fluctuations in peptide signal intensities and retention times, and reliably match related peaks across many different datasets. Application of this toolkit markedly facilitates pattern recognition and biomarker discovery in global comparative proteomic studies, simplifying mechanistic investigation of physiological responses and the detection of proteomic signatures of disease.     

A combined strategy for glycan profiling: a model study with pyridylaminated oligosaccharides

Structural glycomics plays a fundamental role in glycoscience and glycotechnology. In this paper, a novel strategy for the structural characterization of glycans is described, in which MS2 analysis involving a LIFT-TOF/TOF procedure is combined with frontal affinity chromatography (FAC). As model compounds, 20 neutral pyridylaminated (PA) oligosaccharides were chosen, which included four groups of structural isomers differing in sequence, linkage, position, or branching features. By depicting significant diagnostic ions on MS2, most of the analyzed oligosaccharides were successfully differentiated, while two pairs of linkage isomers, i.e., LNT/LNnT, and LNH/LNnH were not. For subsequent analysis by FAC, 14 lectins showing significant affinity to either LNT (type 1) or LNnT (type 2) were screened, and a galectin from the marine sponge Geodia cydonium (GC1) and a plant seed lectin from Ricinus communis (RCA-I) were used for determination of type 1 and 2 chains, respectively. With these specific probes, both of the isomeric pairs were unambiguously differentiated. Furthermore, a pair of triantennary, asparagine-linked oligosaccharide isomers could also be successfully differentiated. Thus, the combination of MS2 and FAC is a practical alternative for the structural characterization of complex glycans.     

Noncovalent functionalization of carbon nanotubes with lectin for label-free dynamic monitoring of cell-surface glycan expression

A kind of concanavalin A functionalized multiwalled carbon nanotube (ConA-MWCNT) was constructed by noncovalent assembly of ConA on carboxylated MWCNT with poly(diallyldimethylammonium) as a linker. The novel nanomaterial was characterized with scanning electron microscopy and atomic force microscopy. It incorporated both the specific recognition ability of lectin for cell-surface mannosyl groups and the unique electronic and mechanical properties of MWCNT. An electrochemical label-free method for cytosensing was proposed by constructing a ConA-MWCNT interface on a glassy carbon electrode, which showed a linear response to K562 cells ranging from 1 × 10⁴ to 1 × 10⁷ cells mL⁻¹. The ConA-MWCNT interface could be further used for monitoring of dynamic variation of glycan expression on K562 cells in response to drugs. A facile and high-throughput optical method for the analysis of dynamic glycan expression on living cells was also developed by constructing an array of ConA-MWCNT spots on a glass slide. This method showed acceptable rapidity and low cost. The noncovalent functionalization of MWCNTs with lectins could be potentially applied in cell biological studies based on cell-surface glycan expression.     

Protein biochips for differential profiling

Progress has been made in utilizing ProteinChip technology to profile and compare protein expression in normal and diseased states, particularly in the areas of cancer, infectious disease and toxicology. The past year has also seen the development of several novel chip types designed to analyze proteins in a fashion analogous to the array-based format of DNA microarrays. Some of these platforms may be used for differential profiling.     

Specific glycan elements determine differential binding of individual egg glycoproteins of the human parasite Schistosoma mansoni by host C-type lectin receptors

During infection with the blood fluke Schistosoma mansoni, glycan motifs present on glycoproteins of the parasite’s eggs mediate immunomodulatory effects on the host. The recognition of these glycan motifs is primarily mediated by C-type lectin receptors on dendritic cells and other cells of the immune system. However, it is not yet known which individual glycoproteins interact with the different C-type lectin receptors, and which structural components are involved. Here we investigated the structural basis of the binding of two abundant egg antigens, kappa-5 and IPSE/α1, by the C-type lectin receptor dendritic cell-specific ICAM3-grabbing non-integrin, macrophage galactose-type lectin and mannose receptor. In the natural soluble form, the secretory egg glycoprotein IPSE/α1 interacts with dendritic cells mainly via mannose receptors. Surprisingly, in plate-based assays mannose receptors preferentially bound to mannose conjugates, while in cell-based assays, IPSE/α1 is bound via the fucosylated Galβ1-4(Fucα1-3)GlcNAc (LeX) motif on diantennary N-glycans. Kappa-5, in contrast, is bound by dendritic cells via all three C-type lectin receptors studied and for a minor part also via other, non-C-type lectin receptors. Kappa-5 interacts with macrophage galactose-type lectins via the GalNAcβ1-4GlcNAc antenna present on its triantennary N-glycans, as well as the GalNAcβ1-4(Fucα1-3)GlcNAc antennae present on a minor N-glycan subset. Dendritic cell-specific ICAM3-grabbing non-integrin binding of kappa-5 was mediated via the GalNAcβ1-4(Fucα1-3)GlcNAc antennae, whereas binding of mannose receptors may involve either GalNAcβ1-4(Fucα1-3)GlcNAc antennae or the fucosylated and xylosylated chitobiose core. This study provides a molecular and structural basis for future studies of the interaction between C-type lectin receptors and other soluble egg antigen glycoproteins and their effects on the host immune response.     

Proteomic profiling of pancreatic cancer for biomarker discovery

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.     

An in vivo platform for tumor biomarker assessment

Tumor biomarkers provide a quantitative tool for following tumor progression and response to therapy. However, investigations of clinically useful tumor biomarkers are time-consuming, costly, and limited by patient and tumor heterogeneity. In addition, assessment of biomarkers as indicators of therapy response is confounded by the concomitant use of multiple therapeutic interventions. Herein we report our use of a clinically relevant orthotopic animal model of malignant pleural mesothelioma for investigating tumor biomarkers. Utilizing multi-modality imaging with correlative histopathology, we demonstrate the utility and accuracy of the mouse model in investigating tumor biomarkers--serum soluble mesothelin-related peptide (SMRP) and osteopontin (OPN). This model revealed percentage change in SMRP level to be an accurate biomarker of tumor progression and therapeutic response--a finding consistent with recent clinical studies. This in vivo platform demonstrates the advantages of a validated mouse model for the timely and cost-effective acceleration of human biomarker translational research.     

The glycolyzer: Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked, and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.     

Reliability of mRNA profiling: verification for samples with different complexities.

Normalization of mRNA profiling data remains an open issue, which turns critical when comparing divergent samples or mRNA populations with different complexities. To address this question, we generated samples with different RNA amounts and complexities by subcellular fractionation of cytoplasmic RNA into the mutually exclusive ribosome-free and polysome-bound RNA pools. For each of the 563 mRNAs analyzed, the hybridization signal corresponding to the cytoplasmic sample equals the sum of signals from the ribosome-free plus the polysome-bound targets (cytoplasmic mRNA = ribosome-free mRNA + polysome-bound mRNA). This intuitive equation was fulfilled only after data normalization following "spiking" of the samples with an exogenous RNA. This is the first demonstration that spiking allows one to correct not only for differences in reaction efficiencies but also to reflect the variations in amount and complexity between the initial mRNA populations.     

A profiling platform for the identification of selective metalloprotease inhibitors

Although proteases represent an estimated 5% to 10% of potential drug targets, inhibitors for metalloproteases (MPs) account for only a small proportion of all approved drugs, failures of which have typically been associated with lack of selectivity. In this study, the authors describe a novel and universal binding assay based on an actinonin derivative and show its binding activities for several MPs and its lack of activity toward all the non-MPs tested. This newly developed assay would allow for the rapid screening for inhibitors of a given MP and for the selectivity profiling of the resulting hits. The assay has successfully enabled for the first time simultaneous profiling of 8 well-known inhibitors against a panel of selected MPs. Previously published activities for these inhibitors were confirmed, and the authors have also discovered new molecular targets for some of them. The authors conclude that their profiling platform provides a generic assay solution for the identification of novel metalloprotease inhibitors as well as their selectivity profiling using a simple and homogeneous assay.     

An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform

The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina HumanMethylation450 BeadChip is widely used to quantify DNA methylation; nevertheless, the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate data sets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished data sets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. We evaluated the performance of different analysis pipelines and demonstrated that: (1) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; (2) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); (3) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive data set suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450K arrays.     

Targeted quantitation of CVD-linked plasma proteins for biomarker verification and validation

Despite significant advances in treatment, cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in developed and developing countries. Judicious monitoring of common risk factors has been unable to control this global epidemic, necessitating novel biomarkers for improved screening and earlier disease detection and management. Although numerous plasma proteins have been associated with CVD, only a few of these potential biomarkers have been validated for clinical use. Here we review the quantitative proteomic methods used to verify and validate new biomarker candidates in human plasma. These methods center on a bottom-up approach involving multiple or selected reaction monitoring, for targeted detection, with stable isotope-labeled standards, for peptide normalization. Also included are a discussion of future strategies for improved CVD protein biomarker verification and validation, recommendations for method translation to the clinic, and future projections for protein biomarker research.