Detailed N-glycan analysis combining Glycan profiles taken by Lectin Microarrays and AI

A group from Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA, etc. has reported a lectin and AI-based approach to predict N-glycan structures and determine their relative abundance in purified proteins based on lectin-binding patterns.

This method can be used when the number of glycanss to be evaluated is limited, but there are a lot of problems when applying it generally.

A similar software named “SA/DL easy” had been created by Mx using Deep Learning as a core technology 5 years ago. By using this software, you can quickly do the same thing.
The problem lies in the tedious work of creating training data, or preparing a large number of expressed glycan structures whose structures have been properly identified, and obtaining glycan profiles.

From the roles of galectins in epithelial-to-mesenchymal transition particulary in cancer

I have read a review article on the epithelial-to-mesenchymal transition (EMT) of galectins written by the groups of CEBICEM, Facultad de Medicina y Ciencia, Universidad San Sebastián, Santiago, Chile, and others. The following is the typical phrases extracted from this review.

In gastric cancer, increased levels of Gal-1 have been associated with lower overall and disease-free survival, as well as with an increased incidence of lymph node metastasis in patients. Gastric cancer cell lines produce Gal-1, which promotes EMT and increases proliferation, invasion and metastatic potential of these cells. In ovarian cancer, serum samples show that Gal-1 levels are increased and correlate with a higher histological grade and lymph node metastasis. In ovarian cancer cell lines, Gal-1 overexpression promotes EMT and increases cell migration and invasion through the activation of the MAPK-JNK/p38 signaling pathway, while silencing of Gal-1 has opposite effects. High levels of Gal-1 are detected in stromal cells from gastric cancer and pancreatic ductal adenocarcinoma tumors in correlation with an EMT phenotype of carcinoma cells. Gal-1-overexpression in pancreatic stellate cells (PSC) induces EMT in co-cultured pancreatic carcinoma cells, enhancing their proliferation and invasion through the NF-κB pathway. Downregulation of Gal-3 expression reduces tumor growth in xenograft colon cancer models whereas its overexpression enhances the metastatic potential of cancer cells. In breast, colon, and prostate cancer cell lines exogenously added Gal-3 promotes EMT by its interaction with Trop-2, a highly-glycosylated membrane protein involved in cancer progression. Gal-4 has been reported in human prostate cancer tissues with expression levels correlating with metastasis and poor patient survival. Gal-8 is a widely expressed galectin in human tissues and carcinomas and has been associated with an unfavorable prognosis in various types of cancer. Gal-8 contributes to cancer progression and metastasis by regulating the production of immunoregulatory cytokines, thereby facilitating the recruitment of cancer cells to metastatic sites.

In other words, different types of galectins are involved in cancer in various places, but I think the issue is the degree of the contribution of galectin involvement. Glycans and lectins basically play regulatory roles except for innate immunity and congenital disorder of glycosylation (CDG).

Therefore, when trying to cure disease from a view point of glycans and lectins, I think it is necessary to narrow down the disease to those in which these are involved with higher contributions.
What do you think? ?

α2,3-sialylation is essential for melanoma growth and progression

A group from Department of Pathology, NYU Grossman School of Medicine, New York, USA etc. has reported about cganges in glycosylation of melanoma.

It has shown using lectin microarrays that α1,2 fucose decreased in primary melanoma compared to nevi.
Interestingly, core fucose was high in nevi and lower in primary melanoma but then regained in metastatic melanoma.
It was also observed that 2,3 syalylation increased significantly in both primary and metastatic melanoma compared to nevi.

Changes in glycosylation in Pancreatic Ductal Adenocarcinoma mediated by KRAS mutations

A group from Department of Gastrointestinal and Hepato-Biliary-Pancreatic Surgery, Faculty of Medicine, University of Tsukuba, Japan, etc. has reported about changes in glycosylation in Pancreatic Ductal Adenocarcinoma mediated by KRAS gene mutations.

It was shown that Fucosilation and mannosylation were upregurated in pancreatin ductal adenocarcinoma with KRAS gene mutations.
The lectins enriched in KRAS mutants included fucose-binding lectins (AAL, rAAL, AOL, rAOL, rRSIIL, and UEAI) and mannose-binding lectins (rRSL, rBC2LCA, rPAIIL, and NPA).

Detecting Triple-Negative Breast Cancer with using Glycan Profiling of Extracellular Vesicles

A group from Beijing Engineering Research Center for BioNanotechnology, CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing, China, etc. has reported about glycan profiling of extracellular vesicles (EVs) for detecting triple-negative breast cancer (TNBC).

A panel of 3 lectins (ConA, WGA and RCA I) was used to detect the EV surface glycan profiles unique to TNBC.
As a result, they succeeded in getting an area under ROC curve (AUC) of 0.91 with using the weighted sum of 3 lectins (ConA, WGA and RCA I) for discriminatiing TNBC from other BCs and HDs.


They say that prostate cancer can be detected by using its exosomes, but

A group from Institute of Chemistry, Slovak Academy of Sciences, Bratislava, etc. has reported about a measurement using a sandwich scheme with CD63, exosomes and SNA lectin for detecting prostate cancer.

In this experment, exosomes produced by prostate cancer cells are examined as a new biomarker for detecting prostate cancer.

Comparing with exosomes produced by benign (control) cell line RWPE1 and carcinoma cell line 22Rv1, it was showen that
(1) the control exosomes mainly interacted with SNA and MAAII lectins; however, they exhibited a lower affinity than the carcinoma exosomes, and also
(2) PHA-L and PHA-E were only able to bind poorly to control-derived exosomes, while there were no interactions to carcinoma exosomes.
This result is quite reasonable because usually the signal intensity of PHA-L and PHA-E disapper with fully sialylated N-glycans suggesting that sialylation is stronger in carcinoma exsosomes than that of control exosomes.

However, blog author is skeptical about their conclusion that it is possible to perform measurements in a sandwich configuration, i.e., antibody/exosomes/lectin, because exsosmes are generally strongly sialylated and CD63 can not discriminate exsosomes produced by prostate cancer cells from other exosomes.

Sialic Acid is strong on Exosomes, but Why?

Glycans are said to be the face of cells, and the glycosylation on the cell surface changes depending on the tissue and desease state.
As a result, the glycosylation of exosomes released from cells drags the glycosylation of the cell surface, but for some reason, expression of sialic acid tends to be very strong.
For example, there is a paper written by Shimoda and Akiyoshi at. al., Kyoto University (see below).
Why is this?
There is a paper that says it may be aimed at masking the immune system (in Japanese), but is that true?
for example,
In contrast, the authors cited above suggest that it is involved in the uptake of exosomes via Siglecs on the cell surface.

(cited from the above listed paper)

Behind the “Cry for Help” response caused by plant pathogen infection

A group from State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China, etc. has reported about how to induce “cry for help” response to assemble disease suppressing and growth promoting rhizomicrobiome.

The well-studied model pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 and its nonpathogenic derivatives (D36E, D36EFLC and D36EHPM) were used in this experiment using Arabidopsis as a model plant.

Treatment with either DC3000 or the derivatives increased the relative contents of long chain organic acids (LCOAs) and amino acids in root exudates. The bacterial phyla Proteobacteria (32.1%–38.3%) and Actinobacteria (15.4%–20.7%) were the most abundant groups in the rhizosphere, and the genus Devosia (belonging to phylum Proteobacteria) was enriched in the D36E and D36EFLC treatments. Interestingly, the abundance of genus Devosia was negatively correlated with L-malic acid and myristic acid in root exudates but positively correlated with 4-hydroxypyridine.

Finally, it was shown that the metabolites of D36E and D36EFLC alone are sufficient to induce a “cry for help” response. So, this study demonstrates the ability of nonpathogenic strains and their MAMPs to act as elicitors to induce the formation of a disease-suppressive soil legacy, which can potentially support agricultural applications.

International Carbohydrates related Conferences scheduled in 2024 – 2025

  1. 7th canadian Glycomics Symposium & 10th warren Workshop (May 27-29, 2024, Edmonton, Canada)
  2. SialoGlyco 2024 (June 4-7, 2024, Lilli, France)
  3. 31st International Carbohydrate Symposium (July 14-19, 2024, Shanghai, China)
  4. 5th Australasian Glycoscience Symposium (Aug. 27-30 2024, Wellington, New Zealand)
  5. Microbial Glycobiology 2024 (Sept. 8-12, 2024, Southbridge, MA, USA)
  6. 16th Bratislava Symposium on Saccharides (Sept. 23-27, 2024, Smolenice Castle, Slovakia)
  7. HUPO 2024 (Oct. 20-24, 2024, Dresden, Germany)
  8. 2024 Glycobiology Annual Meeting (Nov. 10-13, 2024, Amelia Island, FL, USA)
  9. Glycobiology Gordon Research Conference (Mar. 23-28, 2025, Lucca, Italy)
  10. Glyco27 International Symposium on Glycoconjugates (May 26-30, 2025, Edmonton, Canada)

DC-SIGN recognizes the outer core oligosaccharide of LPS expressed on Gram-negative bacteria

Department of Chemical Science, University of Naples Federico II Via Cinthia 4, Naples, Italy, etc. has reported about molecular recognition of LPS by DC-SIGN.

Lipopolysaccharides (LPS) are peculiar glycolipids which represent the major components of the external leaflet of the gram-negative bacteria outer membrane. They consist of three structurally and genetically distinct domains: the lipid A, integrated in the outer membrane; the core oligosaccharide (OS), in turn composed of inner and outer core regions; and the distal O-specific polysaccharide (O-PS) chain, that extends outwards the bacterial surface

Structurally speaking, it is a dodecasaccharide composed of two residues of galactose and three glucose units in the outer core region and three L-glycero-D-manno-heptoses and two 3-deoxy-D-manno-oct-2-ulosonic acids (Kdo), in the inner core portion; the two glucosamine residues at reducing end belong to the lipid A moiety.

One of the main representatives of transmembrane C-type lectins is DC-SIGN also known as CD209. This lectin is found on macrophages, monocytes, and is mainly expressed by dendritic cells which act as potent phagocytic cells, and it is know that DC-SIGN belongs to the mannose receptor family. On the other hand, it has been shown that the DC-SIGN induced phagocytosis of E. coli occurs in the absence of O-antigen polysaccharides, and in the presence of a complete core OS.

In this study, it was found that DC-SIGN binds to the outer core pentasaccharide (composed of two residues of galactose and three glucose units), which acts as a crosslinker between two different tetrameric units of DC-SIGN.