Cell Lineage Proteomics
Cell Lineage Proteomics - Related Videos
09:18
Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo
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Cited by 2 •
2022
Here we describe a mass spectrometry-based proteomic characterization of cell lineages with known tissue fates in the vertebrate Xenopus laevis embryo.
09:29
Skeletal Muscle Gender Dimorphism from Proteomics
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Cited by 4 •
2011
A straight-forward set of methods to isolate and determine the identity of the most abundant proteins expressed in skeletal muscle. About 800 spots are discerned on a two-dimensional gel from 10 mg muscle; this allows for the determination of gender-specific protein expression. These methods will give equivalent results in most tissues.
09:20
Proteomic Sample Preparation from Formalin Fixed and Paraffin Embedded Tissue
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Cited by 50 •
2013
Archival formalin fixed and paraffin embedded (FFPE) clinical samples are valuable material for investigation of diseases. Here we demonstrate a sample preparation workflow allowing in-depth proteomic analysis of microdissected FFPE tissue.
10:11
Glycopeptide Capture for Cell Surface Proteomics
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Cited by 8 •
2014
Cell surface proteins are biologically important and widely glycosylated. We introduce here a glycopeptide-capture approach to solubilize, enrich, and deglycosylate these proteins for facile LC-MS based proteomic analyses.
07:35
Lineage Labeling of Zebrafish Cells with Laser Uncagable Fluorescein Dextran
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Cited by 8 •
2011
This protocol delineates a way to label and trace the fate of small groups of cells zebrafish embryos using UV-uncaging of caged fluorescein, followed by whole mount immunolabeling to amplify the signal from the uncaged fluorescein.
FAQs
A heritable tag introduced into a progenitor is retained by its descendants, providing an identity signal for cells that share a developmental origin. Researchers can then associate that clonal identity with protein measurements obtained from mass spectrometry. This linkage makes it possible to compare protein composition among related descendants and determine how their molecular states diverge during differentiation.
Cells from the same lineage can display different protein compositions, indicating that shared ancestry does not guarantee an identical molecular state. Cell lineage proteomics exposes this heterogeneity by associating protein patterns with clonal identity. The resulting comparisons can help distinguish lineage-associated differences from broader population averages and clarify how molecular function changes as descendants adopt distinct states.
Mass spectrometry supplies the protein-level measurements needed to characterize each lineage-associated cell population. In the chemistry context, these measurements connect molecular composition with developmental history rather than examining lineage identity alone. Comparing the resulting proteomic profiles can reveal changes in signaling pathways, metabolic programs, and other protein-based features linked to cell fate.
Lineage tags report where cells came from, whereas proteomic measurements describe the molecular state they currently occupy. Considering both signals together lets researchers ask whether descendants with a common history retain similar protein programs or diverge functionally. This distinction is useful for interpreting differentiation, because developmental origin and present signaling or metabolic activity may not correspond perfectly.
A typical workflow begins by introducing heritable lineage tags or barcodes into progenitor cells. Researchers then follow the tagged descendants as they develop and measure their proteins with mass spectrometry. Finally, they match clonal identities to proteomic profiles and compare the resulting groups. This sequence connects developmental tracking with chemical analysis of protein composition.
Researchers can apply the strategy when they need to relate cell fate decisions to molecular function in developing or diseased systems. It supports analysis of proteomic differences among related cell populations and can examine how signaling pathways, metabolic programs, or therapeutic treatments influence those differences. These comparisons may clarify why cells with shared ancestry acquire distinct functional states.