Sialic Acid Overexpression
Sialic Acid Overexpression - Related Videos
12:06
Metabolic Glycoengineering of Sialic Acid Using N-acyl-modified Mannosamines
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Cited by 7 •
2017
Sialic acid is a typical monosaccharide-unit found in glycoconjugates. It is involved in a plethora of molecular and cellular interactions. Here we present a method to modify cell surface sialic acid expression using metabolic glycoengineering with N-acetylmannosamine derivatives.
08:04
Determination of Sialic Acids in Liver and Milk Samples of Wild-type and CMAH Knock-out Mice.
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Cited by 7 •
2017
We describe a HPLC-based method for the determination of N-acetylneuraminic acid and N-glycolylenuraminic acid in mouse liver and milk.
03:31
Reversed-Phase High-Performance Liquid Chromatography: A Robust Method for Quantitation of Fluorescently Labeled and Derivatized Sialic Acids Isolated from Mouse Liver
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2025
In this video, we demonstrate the detection of sialic acids, N-acetylneuraminic acid and N-glycolylneuraminic acid, using high-performance liquid chromatography, HPLC, following derivatization with a suitable fluorescent labeling reagent to aid in fluorescence detection.
05:16
Detecting Histone Modifications in Yeast Cells with Neurodegenerative Protein Overexpression
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2025
Source: Bennett, S. A., et al., Characterizing Histone Post-translational Modification Alterations in Yeast Neurodegenerative Proteinopathy Models. J. Vis. Exp. (2019).This video demonstrates the procedure of assessing histone modifications in yeast cells overexpressing neurodegenerative proteins. The steps include cell lysis, centrifugation, electrophoresis, membrane transfer, and antibody-based detection of modified histones.
08:12
Assessing Somatic Hypermutation in Ramos B Cells after Overexpression or Knockdown of Specific Genes
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Cited by 5 •
2011
We describe how to perform retroviral or lentiviral infections of overexpression or shRNA-containing constructs in the human Ramos B-cell line and how to measure somatic hypermutation in these cells.
FAQs
Additional sialic acid can mask underlying carbohydrate structures, changing which molecular features remain accessible to receptors and binding partners. This masking can modify receptor interactions rather than simply increasing a single signal. In immunology and infection studies, the consequence is altered cellular recognition, which may affect how immune cells or pathogens engage the surface.
High surface display can engage sialic acid-binding proteins, including immune inhibitory receptors. Those interactions can influence leukocyte activation and inflammatory responses, creating conditions in which immune detection or effector activity is modified. The key issue is not only the amount of sialic acid, but also which inhibitory recognition pathways encounter it and how that contact changes signaling.
In tumors, damaged tissues, or pathogen-associated interactions, elevated sialylation can change the molecular visibility of a cell surface. Masking may limit access to underlying structures, while engagement of inhibitory receptors can alter leukocyte responses. Together, these mechanisms provide a framework for studying how abnormal host cells or infectious agents avoid effective immune detection.
The same surface feature can have different biological consequences depending on the interacting cell or organism. In tumors, it may help explain reduced immune recognition; during infection, it can influence pathogen attachment to host cells and immune evasion. Comparing these settings separates shared recognition mechanisms from context-specific receptor interactions and inflammatory outcomes.
Measurement should be interpreted in relation to both sialic acid production and its cell-surface display, because these are related but not identical aspects of the phenotype. Researchers can then ask whether altered levels correlate with receptor engagement, leukocyte activation, inflammatory responses, or host-cell attachment. This links a molecular measurement to a biologically meaningful outcome.
Manipulating sialylation provides a way to test whether the observed phenotype contributes causally to altered recognition or signaling. Researchers can examine resulting changes in immune inhibitory receptor engagement, leukocyte activation, inflammation, or pathogen attachment to host cells. Such comparisons help distinguish a functional mechanism from a correlation and may identify effects suitable for therapeutic investigation.
Changes in sialylation can serve as a biological readout of altered recognition and signaling. In infection and immunology studies, measuring or manipulating the phenotype may reveal targets for therapeutics, inform vaccine-related investigations, or support diagnostic biomarker development. Its value comes from connecting cell-surface carbohydrate patterns with immune evasion, host-cell attachment, and inflammatory behavior.