Protein Marker Imaging
Protein Marker Imaging - Related Videos
14:02
Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons
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Cited by 3 •
2020
This protocol shows how to employ super-resolution microscopy to study protein co-localization in primary neuronal cultures.
11:15
Imaging Protein-protein Interactions in vivo
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Cited by 5 •
2010
This protocol describes how to image protein-protein interactions using a FRET-based proximity assay.
07:13
Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
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Cited by 1 •
2023
The combination of multiple imaging modalities is often necessary to gain a comprehensive understanding of pathophysiology. This approach utilizes phantoms to generate a differential transformation between the coordinate systems of two modalities, which is then applied for co-registration. This method eliminates the need for fiducials in production scans.
02:52
Visualizing Bacterial Protein Distribution in Three Dimensions by Fluorescence Imaging
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2026
Source: Bratton, B. P., et al., Three-dimensional Imaging of Bacterial Cells for Accurate Cellular Representations and Precise Protein Localization. J. Vis. Exp. (2019)This video demonstrates the method for acquiring and analyzing three-dimensional fluorescence images of bacterial cells to study protein organization at the single-cell level.
08:59
4D Imaging of Protein Aggregation in Live Cells
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Cited by 4 •
2013
Cellular viability depends on timely and efficient management of protein misfolding. Here we describe a method for visualizing the different potential fates of a misfolded protein: refolding, degradation, or sequestration in inclusions. We demonstrate the use of a folding sensor, Ubc9ts, for monitoring proteostasis and aggregation quality control in live cells using 4D microscopy.
FAQs
Fluorescent proteins, labeled antibodies, and other affinity probes provide different ways to recognize selected protein targets. The probe establishes which molecular feature is measured, while microscopy captures the resulting emitted or transmitted signal. Choosing among these options allows investigators to examine protein location, abundance, or activity in cells, tissues, and engineered biological systems.
The biological target and the measurement design determine the type of information obtained. Spatial signal patterns can reveal where a protein is distributed, while changes in signal can indicate altered abundance or activity. Tracking these measurements over time adds a temporal dimension, helping researchers evaluate dynamic responses in engineered cells, tissues, or biomaterial-associated systems.
A protein signal can vary across individual cells, tissue regions, or engineered structures rather than changing uniformly. Spatial mapping identifies where molecular events occur, whereas repeated measurements reveal how those events change over time. Together, these dimensions help connect protein behavior with cell signaling, differentiation, viability, and interactions within engineered biological systems.
Protein marker imaging preserves information about where the selected target appears within cells, tissues, or engineered constructs. A measurement focused only on overall abundance would not provide the same spatial map. By combining affinity-based recognition with microscopy, the imaging approach can relate molecular signals to specific locations and follow their distribution or changes over time.
A typical workflow begins by selecting a protein target and an appropriate fluorescent protein, labeled antibody, or other affinity probe. The probe is then used to mark the target in the biological system, after which microscopy detects emitted or transmitted signals. Researchers analyze the resulting spatial or temporal patterns to evaluate the selected molecular feature.
Bioengineers use this approach when they need molecular evidence about how cells behave within engineered tissues, biomaterials, or tissue constructs. Imaging can support evaluation of cell signaling, differentiation, viability, and cell interactions with the surrounding engineered environment. These observations help assess whether a construct or cell-based model produces the intended biological responses.
Changes in protein distribution, abundance, or activity can provide measurable evidence of how cells respond to a therapeutic condition or engineered environment. Researchers can compare these molecular patterns across samples or time points to assess responses. The resulting data also help validate cell-based models by showing whether relevant biological behaviors occur within the system.