LM-GlycomeAtlas v.2.0 is a web tool visualizing the data from Lectin Microarray analyses using a commercialized lectin microarray ( 45 lectins ) by the Kuno Laboratory at AIST with collaborators.

As the first database for LMA-based glycomic profiling data, a future updated version of the LM-GlycomeAtlas has the potential to be used as a standard repository system of LMA data provided by other researchers. Related to this, we also plan to update this atlas to extensively deposit “human” tissue glycome mapping data obtained from clinicopathological specimens. Please contact us if you are interested in this project.
*E-mail: atsu-kuno[at]aist.go.jp ([at]=@)

This work was supported by a project for utilizing glycans in the development of innovative drug discovery technologies in the project focused on developing key technology for discovering and manufacturing drugs for next-generation treatment and diagnosis from the Japan Agency for Medical Research and Development (AMED).

Collaborators (alphabetical order)

References

Lectin microarray technology

  1. Kuno A, Uchiyama N, Koseki-Kuno S, Ebe Y, Takashima S, Yamada M, Hirabayashi J. Evanescent-Field Fluorescence-Assisted Lectin Microarray: A New Strategy for Glycan Profiling. Nat. Methods 2(11):851-856, 2005. https://doi.org/10.1038/nmeth803.
  2. Hirabayashi H, Yamada M, Kuno A, Tateno H. Lectin microarrays: concept, principle and applications. Chem. Soc. Rev. 42(10):4443-4458, 2013. https://doi.org/10.1039/c3cs35419a
  3. T Hiono, C Nagai-Okatani, A Kuno. Application of Glycan-Related Microarrays. Comprehensive Glycoscience (Second Edition) 4:134-148, 2021. https://doi.org/10.1016/B978-0-12-819475-1.00059-6

Tisssue glycome mapping technology

  1. Matsuda A, Kuno A, Ishida H, Kawamoto T, Shoda J, Hirabayashi J. Development of an all-in-one technology for glycan profiling targeting formalin-embedded tissue sections. Biochem Biophys Res Commun 370(2):259-63, 2008. https://doi.org/10.1016/j.bbrc.2008.03.090
  2. Zou X, Yoshida M, Nagai-Okatani C, Iwaki J, Matsuda A, Tan B, Hagiwara K, Sato T, Itakura Y, Noro E, Kaji H, Toyoda M, Zhang Y, Narimatsu H, Kuno A. A standardized method for lectin microarray-based tissue glycome mapping. Sci Rep 7:43560, 2017. https://doi.org/10.1038/srep43560
  3. Narimatsu H, Kaji H, Vakhrushev S Y, Clausen H, Zhang H, Noro E, Togayachi A, Nagai-Okatani C, Kuno A, Zou X, Cheng L, Tao SC, Sun Y. Current Technologies for Complex Glycoproteomics and Their Applications to Biology/Disease-Driven Glycoproteomics. J. Proteome Res. 2018, 17 (12), 4097–4112. https://doi.org/10.1021/acs.jproteome.8b00515
  4. Nagai-Okatani C, Aoki-Kinoshita KF, Kakuda S, Nagai M, Hagiwara K, Kiyohara K, Fujita N, Suzuki Y, Sato T, Angata K and Kuno A. LM-GlycomeAtlas Ver. 1.0: A Novel Visualization Tool for Lectin Microarray-Based Glycomic Profiles of Mouse Tissue Sections. Molecules 24(3):486, 2019. https://doi.org/10.3390/molecules24162962
  5. Nagai-Okatani C, Zou X, Fujita N, Sogabe I, Arakawa K, Nagai M, Angata K, Zhang Y, Aoki-Kinoshita KF, Kuno A. LM-GlycomeAtlas Ver. 2.0: An Integrated Visualization for Lectin Microarray-based Mouse Tissue Glycome Mapping Data with Lectin Histochemistry. J Proteome Res 20(4):2069-2075, 2021. https://doi.org/10.1021/acs.jproteome.0c00907
  6. Nagai-Okatani C, Zou X, Matsuda A, Itakura Y, Toyoda M, Zhang Y, Kuno A. Tissue Glycome Mapping: Lectin Microarray-Based Differential Glycomic Analysis of Formalin-Fixed Paraffin-Embedded Tissue Sections. Methods Mol Biol 2460:161-180, 2022. https://doi.org/10.1007/978-1-0716-2148-6_10

Tissue glycomic profiling dataset (References in the chart)

  1. Nagai-Okatani C, Aoki-Kinoshita KF, Kakuda S, Nagai M, Hagiwara K, Kiyohara K, Fujita N, Suzuki Y, Sato T, Angata K and Kuno A. LM-GlycomeAtlas Ver. 1.0: A Novel Visualization Tool for Lectin Microarray-Based Glycomic Profiles of Mouse Tissue Sections. Molecules 24(3):486, 2019.  https://doi.org/10.3390/molecules24162962
  2. Zou X, Yoshida M, Nagai-Okatani C, Iwaki J, Matsuda A, Tan B, Hagiwara K, Sato T, Itakura Y, Noro E, Kaji H, Toyoda M, Zhang Y, Narimatsu H, Kuno A. A standardized method for lectin microarray-based tissue glycome mapping. Sci Rep. 7:43560, 2017.
  3. Nagai-Okatani C, Nishigori M, Sato T, Minamino N, Kaji H, Kuno A. Wisteria Floribunda Agglutinin Staining for the Quantitative Assessment of Cardiac Fibrogenic Activity in a Mouse Model of Dilated Cardiomyopathy. Lab Invest. 99(11):1749-1765, 2019. https://doi.org/10.1038/s41374-019-0279-9
  4. Itakura Y, Hasegawa Y, Kikkawa Y, Murakami Y, Sugiura K, Nagai-Okatani C, Sasaki N, Umemura M, Takahashi Y, Kimura T, Kuno A, Ishiwata T, Toyoda M. Spatiotemporal Changes of Tissue Glycans Depending on Localization in Cardiac Aging. Regen Ther 22:68-78, 2023. https://doi.org/10.1016/j.reth.2022.12.009

Other applications for glycobiomarker discovery

  1. Matsuda A, Kuno A, Kawamoto T, Matsuzaki H, Irimura T, Ikehara Y, Zen Y, Nakanuma Y, Yamamoto M, Ohkohchi N, Shoda J, Hirabayashi J, Narimatsu H. Wisteria Floribunda Agglutinin-Positive Mucin 1 Is a Sensitive Biliary Marker for Human Cholangiocarcinoma. Hepatology 52(1):174-182, 2010. https://doi.org/10.1002/hep.23654
  2. Hirao Y, Matsuzaki H, Iwaki J, Kuno A, Kaji H, Ohkura T, Togayachi A, Abe M, Nomura M, Noguchi M, Ikehara Y, Narimatsu H. Glycoproteomics Approach for Identifying Glycobiomarker Candidate Molecules for Tissue Type Classification of Non-Small Cell Lung Carcinoma. J. Proteome Res 13(11):4705-4716, 2014. https://doi.org/10.1021/pr5006668
  3. Yamashita K, Kuno A, Matsuda A, Ikehata Y, Katada N, Hirabayashi J, Narimatsu H, Watanabe M. Lectin Microarray Technology Identifies Specific Lectins Related to Lymph Node Metastasis of Advanced Gastric Cancer. Gastric Cancer 19(2):531-542, 2016.  https://doi.org/10.1007/s10120-015-0491-2
  4. Wagatsuma T, Nagai-Okatani C, Matsuda A, Masugi Y, Imaoka M, Yamazaki K, Sakamoto M, Kuno A. Discovery of Pancreatic Ductal Adenocarcinoma-Related Aberrant Glycosylations: A Multilateral Approach of Lectin Microarray-Based Tissue Glycomic Profiling with Public Transcriptomic Datasets. Front. Oncol. 10:338, 2020. https://doi.org/10.3389/fonc.2020.00338

Last update: April 24, 2023