Mouse Liver Glycomics
Mouse Liver Glycomics - Related Videos
08:52
Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
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Cited by 1 •
2025
This protocol details the key steps to enable rigorous and reproducible measurement of both glycogen and N-linked glycans using mass spectrometry imaging.
11:38
A Quantitative Glycomics and Proteomics Combined Purification Strategy
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Cited by 18 •
2016
A high-throughput protocol was developed for combined proteomics and glycomics purification and LC-MS/MS quantification in plasma. Deamidation analysis of N-linked glycosylation motifs was specific to deglycosylated sites. Accurate quantitation of N-glycans was achieved by coupling filter aided N-glycan separation to the individuality normalization when labeling with glycan hydrazide tags strategy.
11:36
Glycan Node Analysis: A Bottom-up Approach to Glycomics
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Cited by 16 •
2016
This article presents an enhanced form of a novel bottom-up glycomics technique designed to analyze the pooled compositional profile of glycans in unfractionated biofluids through the chemical breakdown of glycans into their constituent linkage-specific monosaccharides for detection by GC-MS. Potential applications include early detection of cancer and other glycan-affective disorders.
03:42
Isolation of Marginating Hepatic Leukocytes from a Mouse Liver
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2025
In this video, we demonstrate the isolation of marginating hepatic leukocytes from mouse liver by forced perfusion.
11:44
Generation of a Humanized Mouse Liver Using Human Hepatic Stem Cells
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Cited by 3 •
2016
Here, we present a novel humanized mouse liver model generated in Alb-toxin receptor mediated cell knockout (TRECK)/SCID mice following the transplantation of immature and expandable human hepatic stem cells.
FAQs
Changes in glycan structures can reflect altered regulation of hepatic metabolism, signaling, or disease-related processes. Because glycans occur on glycan-modified molecules and proteins, their profiles provide biochemical information beyond a simple measurement of total carbohydrate. Examining which structures change, and under which biological condition, can connect altered glycosylation with liver function and help clarify disease mechanisms.
N-linked and O-linked glycans represent different forms of protein glycosylation, so researchers may release them through distinct enzymatic steps before analysis. Treating these classes separately helps determine whether a biological condition changes one glycan category, the other, or both. That distinction improves interpretation of altered protein glycosylation in mouse liver biochemical studies.
Comparing glycan profiles from healthy, diseased, developmental, or genetically modified mice can reveal condition-associated changes in protein glycosylation. Comparisons may also show how genetic or environmental factors reshape biochemical pathways in the liver. The resulting differences help connect a glycan pattern with altered hepatic function rather than treating glycosylation as a static feature.
A typical workflow begins by extracting glycoconjugates from liver tissue. Researchers then enzymatically release N-linked or O-linked glycans, separate the released molecules by chromatography, and analyze them with mass spectrometry. The sequence converts complex tissue material into measurable glycan profiles that can be compared across experimental groups for composition and abundance changes.
Chromatography separates glycans before detection, helping organize the mixture into analyzable components. Mass spectrometry then supports identification or quantification of their compositions. Used together, these methods provide both analytical separation and molecular measurement, allowing investigators to compare glycan profiles and recognize changes associated with liver disease, development, genetic modification, or environmental factors.
This approach is useful when researchers need to investigate molecular changes linked to liver disease, hepatic function, or altered biochemical pathways. It can support biomarker discovery by identifying glycan profiles that differ between biological conditions. It also helps evaluate how genetic or environmental factors affect protein glycosylation and provides molecular context for interpreting liver-related phenotypes.