Hiromichi Sawaki

A strategy for discovery of cancer glyco-biomarkers in serum using newly developed technologies for glycoproteomics

Detection of cancer at early stages that can be treated through surgery is a difficult task. One methodology for cancer biomarker discovery exploits the fact that glycoproteins produced by cancer cells have altered glycan structures, although the proteins themselves are common, ubiquitous, abundant, and familiar. However, as cancer tissue at the early stage probably constitutes less than 1% of the normal tissue in the relevant organ, only 1% of the relevant glycoproteins in the serum should have altered glycan structures. Here, we describe our strategy to approach the detection of these low‐level glycoproteins: (a) a quantitative real‐time PCR array for glycogenes to predict the glycan structures of secreted glycoproteins; (b) analysis by lectin microarray to select lectins that distinguish cancer‐related glycan structures on secreted glycoproteins; and (c) an isotope‐coded glycosylation site‐specific tagging high‐throughput method to identify carrier proteins with the specific lectin epitope. Using this strategy, we have identified many glycoproteins containing glycan structures that are altered in cancer cells. These candidate glycoproteins were immunoprecipitated from serum using commercially available antibodies, and their glycan alteration was examined by a lectin microarray. Finally, they were analyzed by multistage tandem MS.

Strategy for glycoproteomics: identification of glyco-alteration using multiple glycan profiling tools.

Glycan alterations of proteins, a common feature of cancer cells, are associated with carcinogenesis, invasion and metastasis. Glycomics, the study of glycans and glycan-binding proteins in various biological systems, is an emerging field in the postgenome and postproteomics era. However, systematic and robust strategies for glycomics are still not fully established because the structural analysis of glycans, which comprise different patterns of branching, various possible linkage positions as well as monomer anomericity, is technically difficult. Here, we introduce a new strategy for glyco-alteration analysis of glycoproteins by using multiple glycan profiling tools. To understand glycan alterations of proteins by correlating the glycosyltransferase expression profile with the actual glycan structure, we systematically used three glycan profiling tools: (1) multiplex quantitative PCR (qPCR) array format for profiling the expression pattern of glycogenes, (2) lectin microarray as a multiplex glycan-lectin interaction analysis system for profiling either a pool of cell glycoproteins or a target glycoprotein, and (3) tandem mass spectrometry for identifying the glycan structure connected to a target glycoprotein. Using our system, we successfully identified glycan alterations on alpha-fetoprotein (AFP), including a novel LacdiNAc structure in addition to previously reported alterations such as alpha1,6 fucosylation.

Large-scale Identification of N-Glycosylated Proteins of Mouse Tissues and Construction of a Glycoprotein Database, GlycoProtDB

Protein glycosylation is a common post-translational modification that plays important roles in terms of protein function. However, analyzing the relationship between glycosylation and protein function remains technically challenging. This problem arises from the fact that the attached glycans possess diverse and heterogeneous structures. We believe that the first step to elucidate glycan function is to systematically determine the status of protein glycosylation under physiological conditions. Such studies involve analyzing differences in glycan structure on cell type (tissue), sex, and age, as well as changes associated with perturbations as a result of gene knockout of glycan biosynthesis-related enzyme, disease and drug treatment. Therefore, we analyzed a series of glycoproteomes in several mouse tissues to identify glycosylated proteins and their glycosylation sites. Comprehensive analysis was performed by lectin- or HILIC-capture of glycopeptide subsets followed by enzymatic deglycosylation in stable isotope-labeled water (H₂¹⁸O, IGOT) and finally LC-MS analyses. In total, 5060 peptides derived from 2556 glycoproteins were identified. We then constructed a glycoprotein database, GlycoProtDB, using our experimental-based information to facilitate future studies in glycobiology.

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed.

Introducing glycomics data into the Semantic Web

BackgroundGlycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as “switches” that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases.ResultsIn order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as “proofs-of-concept” to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement.ConclusionsWe were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains.

Phylogenetic position of an arbuscular mycorrhizal fungus, Acaulospora gerdemannii, and its synanamorph Glomus leptotichum, based upon 18S rRNA gene sequence

We examined the phylogenetic position of an arbuscular mycorrhizal fungus which produces two types of spore,Acaulospora gerdemannii andGlomus leptotichum, based upon the DNA sequence of the 18S rRNA gene. DNA was extracted separately from bothGlomus-like orAcaulospora-like spores and partial 5′-terminus segments of 18S rRNA gene were amplified by the PCR method. Several clones derived from each spore type were sequenced and compared. The sequences from both spore types agreed well, confirming that these morphologically different spores were formed by the same fungus. Nucleotide substitutions were found among several clones, suggesting polymorphism of the rRNA gene in glomalean fungi. Further phylogenetic analysis based upon the whole sequence of the 18S rRNA gene showed thatA. gerdemannii may be within the order Glomales but is far from the fungi that have been analyzed and probably should be in a new family.

GlycoRDF: an ontology to standardize glycomics data in RDF

MOTIVATION Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. RESULTS An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. AVAILABILITY AND IMPLEMENTATION The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/).

WURCS: The Web3 Unique Representation of Carbohydrate Structures

In recent years, the Semantic Web has become the focus of life science database development as a means to link life science data in an effective and efficient manner. In order for carbohydrate data to be applied to this new technology, there are two requirements for carbohydrate data representations: (1) a linear notation which can be used as a URI (Uniform Resource Identifier) if needed and (2) a unique notation such that any published glycan structure can be represented distinctively. This latter requirement includes the possible representation of nonstandard monosaccharide units as a part of the glycan structure, as well as compositions, repeating units, and ambiguous structures where linkages/linkage positions are unidentified. Therefore, we have developed the Web3 Unique Representation of Carbohydrate Structures (WURCS) as a new linear notation for representing carbohydrates for the Semantic Web.

Membrane sialidase NEU3 is highly expressed in human melanoma cells promoting cell growth with minimal changes in the composition of gangliosides

NEU3 is a membrane sialidase specific for gangliosides. Its increased expression and implication in some cancers have been reported. Here, we analyzed NEU3 expression in malignant melanoma cell lines and its roles in the cancer phenotypes. Quantitative RT‐PCR revealed that high levels of the NEU3 gene were expressed at almost equivalent levels with those in colon cancers. To examine the effects of overexpression of NEU3, NEU3 cDNA‐transfectant cells were established using a melanoma cell line SK‐MEL‐28 and its mutant N1 lacking GD3. SK‐MEL‐28 sublines overexpressing both the NEU3 gene and NEU3 enzyme activity showed no changes in both cell growth and ganglioside expression, while N1 cells showed a mild increase in cell proliferation with increased phosphorylation of the EGF receptor and neo‐synthesis of Gb3 after NEU3 transfection. In contrast, NEU3 silencing resulted in a definite reduction in cell growth in a melanoma line MeWo, while ganglioside patterns underwent minimal changes. Phosphorylation levels of ERK1/2 with serum stimulation decreased in the NEU3‐silenced cells. All these results suggest that NEU3 is highly expressed to enhance malignant phenotypes including apoptosis inhibition in malignant melanomas. (Cancer Sci 2011; 102: 2139–2149)

CA-S27: a novel Lewis a associated carbohydrate epitope is diagnostic and prognostic for cholangiocarcinoma.

Early and specific diagnosis is critical for treatment of cholangiocarcinoma (CCA). In this study, a carbohydrate antigen‐S27 (CA‐S27) monoclonal antibody (mAb) was established using pooled CCA tissue‐extract as immunogen. The epitope recognized by CA‐S27‐mAb was a new Lewis‐a (Lea) associated modification of MUC5AC mucin. A Soybean agglutinin/CA‐S27‐mAb sandwich ELISA to determine CA‐S27 in serum was successfully developed. High level of CA‐S27 was detected in serum of CCA patients and could differentiate CCA patients from those of gastro‐intestinal cancers, hepatomas, benign hepatobiliary diseases and healthy subjects with high sensitivity (87.5%) and high negative predictive value (90.4%). The level of serum CA‐S27 was dramatically reduced after tumor removal, indicating tumor origin of CA‐S27. Patients with high serum CA‐S27 had significantly shorter survivals than those with low serum CA‐S27 regardless of serum MUC5AC levels. Fucosyltransferase‐III (FUT3) was shown to be a regulator of CA‐S27 expression. Suppression of CA‐S27 expression with siRNA‐FUT3 or neutralization with CA‐S27 mAb significantly reduced growth, adhesion, invasion and migration potentials of CCA cells in vitro. In summary, we demonstrate that serum CA‐S27, a novel carbohydrate antigen, has potential as diagnostic and prognostic markers for CCA patients. CA‐S27 involves in promoting cell growth, adhesion, migration and invasion of CCA cells.