Single Cell Protein Detection
Single Cell Protein Detection - Related Videos
09:45
Detection of Copy Number Alterations Using Single Cell Sequencing
0 Views •
Cited by 9 •
2017
Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.
05:00
Localized Surface Plasmon Resonance Imaging to Detect Protein Secretions from a Single Cell
0 Views •
2025
This video demonstrates localized surface plasmon resonance imaging to detect protein secretions from a single cell. Using a microfluidic setup and a peptide-bound plasmonic nanostructure chip, changes in reflected light intensity at the resonance angle reveal interactions with secreted proteins from a single cell.
12:25
Counting Proteins in Single Cells with Addressable Droplet Microarrays
0 Views •
Cited by 2 •
2018
Here we present addressable droplet microarrays (ADMs), a droplet array based method able to determine absolute protein abundance in single cells. We demonstrate the capability of ADMs to characterize the heterogeneity in expression of the tumor suppressor protein p53 in a human cancer cell line.
06:15
Biotinylated Cell-Penetrating Peptide Probe to Detect Protein-Protein Interactions
0 Views •
2025
This video demonstrates a technique that uses biotinylated cell-penetrating peptides to detect intracellular protein-protein interactions. The cell-penetrating peptides facilitate the conjugated peptide to enter a cell and specifically bind to its interacting proteins. The biotin, after binding to avidin, allows purification of the interacting proteins’ complex from a cell lysate.
09:00
Detection of Protein Ubiquitination
0 Views •
Cited by 96 •
2009
Ubiquitination is a key posttranslational modification carried out by a set of three enzymes. Mutations of genes involved in this modification are associated with many different human diseases. Here, we describe protocols to detect protein ubiquitination in cultured cells in vivo and test tubes in vitro.
FAQs
Affinity probes recognize selected proteins through specific binding interactions, allowing the detected signal to represent a particular cellular target. Researchers can attach fluorescent labels, DNA barcodes, or elemental tags to these probes. The resulting signals provide information about protein abundance, location, or activity, depending on the detection format and the biological question being investigated.
Bulk analysis combines signals from many cells, which can conceal differences among tumor cells and surrounding cell populations. Examining cells individually preserves that variation and exposes distinct protein patterns or signaling states. In cancer research, this makes it possible to study tumor heterogeneity rather than treating the tumor as a uniform biological system.
Protein abundance indicates how much of a target is present, whereas location can show where it occurs within a cell or cellular population, and activity can indicate whether a signaling process is engaged. Considering these properties together gives a more informative view of cellular state and helps distinguish molecularly different cells within a tumor.
These tags provide different ways to convert probe binding into a measurable signal. Fluorescent labels support imaging or flow cytometry, while DNA barcodes and elemental tags support other forms of encoded detection, including mass cytometry for elemental signals. The selected tag and readout determine how protein patterns can be measured across individual cells.
A typical experiment begins by selecting protein targets relevant to the biological question and applying matching antibodies or other affinity probes to individual cells. The bound probes are then measured through imaging, flow cytometry, or mass cytometry. Researchers interpret the resulting signals to compare protein abundance, location, or activity among cellular populations.
Protein measurements provide patterns that help characterize the identities and states of cells within a tumor sample. By examining selected proteins at single-cell resolution, researchers can separate malignant populations from immune or stromal populations and assess how those groups differ. This cellular classification supports more precise analysis of tumor composition and signaling behavior.
The method can reveal which cellular populations or signaling states are associated with treatment response, persistence, or resistance. Comparing protein patterns among individual cells may identify candidate biomarkers that would be obscured in an averaged measurement. These findings support models of tumor progression and help researchers examine why responses vary within the same tumor.