Trends in Glycoscience and Glycotechnology
Online ISSN : 1883-2113
Print ISSN : 0915-7352
ISSN-L : 0915-7352
Volume 24, Issue 137
Displaying 1-6 of 6 articles from this issue
MINIREVIEW
  • Akira Togayachi, Hisashi Narimatsu
    Article type: MINIREVIEW
    2012 Volume 24 Issue 137 Pages 95-111
    Published: 2012
    Released on J-STAGE: June 15, 2012
    JOURNAL FREE ACCESS
    We have cloned many genes of β1,3-glycosyltransferases, which transfer sugars via a β1,3-linkage, and have characterized their biological functions. Among β1,3-glycosyltransferases, β1,3-N-acetylglucosaminyltransferases (β3GnTs) synthesize a unique carbohydrate structure known as “polylactosamine (poly-N-acetyllactosamine)”. Polylactosamine is carried on N- and O-glycans, and on glycolipids. Polylactosamine structures are considered to be integral components serving as a fundamental structure and backbone for carbohydrate structures. However, most of their biological functions are still unknown. To investigate the in vivo function of polylactosamine on glycoconjugates, we generated and analyzed two mouse lines of β1,3-N-acetylglucosaminyltransferase (B3gnt)-deficient (B3gnt2-/- or B3gnt5-/-) mice lacking the polylactosamine structure. First, to investigate the in vivo function of polylactosamine on glycoproteins, we analyzed gene knockout mice lacking B3gnt2, which synthesizes polylactosamine on glycoproteins. In B3gnt2-/- mice, glycan analysis demonstrated that the amount of long polylactosamine chains on N-glycan was greatly reduced in the tissues of B3gnt2-/- mice. We also examined immunological responses in B3gnt2-/- mice. B3gnt2-/- lymphocytes showed hyperactivation via TCR/CD28 or BCR stimulation. Next, to investigate the in vivo function of polylactosamine on glycosphingolipids (glycolipid), we analyzed B3gnt5-/- mice lacking lacto/neolacto-series glycolipids. B3gnt5-/- B cells showed an abnormality of glycolipid-enriched microdomains (GEMs; also known as glycolipid rafts) and showed hyperactivation via BCR-related molecules in GEMs, as compared with wild-type (WT) B cells. Polylactosamine deficiency seems to be involved in the immunological disorders observed in these mice. Taken together, these studies suggest that the polylactosamine chain is a putative immune regulatory factor that presumably suppresses excessive responses during immune reactions and has an important biological role in the immune system.
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  • Akira Minami, Takashi Suzuki
    Article type: MINIREVIEW
    2012 Volume 24 Issue 137 Pages 112-121
    Published: 2012
    Released on J-STAGE: June 15, 2012
    JOURNAL FREE ACCESS
    Sialic acid is an acidic monosaccaride and plays crucial roles in various membrane functions in mammalian central nervous systems. Sialidase removes sialic acid from sialoglycoconjugates and also plays crucial roles in many neural functions, including differentiation and maturation of neurons and learning and memory. Recently, we visualized extracellular sialidase activity on the membrane surface in the rat brain by using a highly sensitive fluorescent histochemical method. Myelin-abundant regions showed intense fluorescence in the rat brain. Although the hippocampus showed weak fluorescence in the brain, mossy fiber terminals in the hippocampus showed relatively intense fluorescence. In this review, we describe the distribution of sialidase activity in the brain and discuss the role of sialidase in myelin and the hippocampus.
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  • Jun Sese
    Article type: MINIREVIEW
    2012 Volume 24 Issue 137 Pages 122-128
    Published: 2012
    Released on J-STAGE: June 15, 2012
    JOURNAL FREE ACCESS
    Although most glycan research has focused on a few interactions between glycans and samples, recent technology has made it possible to observe many glycan-sample interactions at once. Consortium for Functional Glycomics (CFG) has collected data and compiled a database that contains glycan-sample interactions for more than three thousand samples. The large CFG database gives us “birds-eye view” of glycan interactions and the data from this database can be used to generate new hypothesis about interactions between glycans and samples or provide new rules about protein binding sites on glycans. This paper introduces computational techniques for analyzing large datasets and demonstrates that these techniques can be used to find interactions without prior knowledge about those interactions. The results in this paper indicate that collaboration between computational analysis and experimental evidence can be used to open the new door into glycan research.
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