Label-free Analysis
Label-free Analysis - Related Videos
09:19
Simultaneous Label-Free Autofluorescence Multi-Harmonic Microscopy
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Cited by 3 •
2025
This protocol presents a step-by-step guide for the Simultaneous Label-free Autofluorescence Multi-harmonic (SLAM) microscopic technique, including details on how to generate the laser light source, prepare a tissue sample, conduct imaging, and analyze the data. SLAM advances nonlinear microscopy by measuring four complementary label-free contrasts to investigate the tissue microenvironment.
12:19
ReAsH/FlAsH Labeling and Image Analysis of Tetracysteine Sensor Proteins in Cells
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Cited by 10 •
2011
The biarsenical dyes FlAsH and ReAsH bind specifically to tetracysteine motifs in proteins and can selectively label proteins in live cells. Recently this labeling strategy has been used to develop sensors for different protein conformations or oligomeric states. We describe the labeling approach and methods to quantitatively analyze binding.
08:28
Metabolic Labeling
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2023
Metabolic labeling is used to probe the biochemical transformations and modifications that occur in a cell. This is accomplished by using chemical analogs that mimic the structure of natural biomolecules. Cells utilize analogs in their endogenous biochemical processes, producing compounds that are labeled. The label allows for the incorporation of detection and affinity tags, which can then be used to elucidate metabolic pathways using other biochemical analytical techniques, such as SDS-PAGE...
11:01
Automated Imaging and Analysis for the Quantification of Fluorescently Labeled Macropinosomes
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Cited by 8 •
2021
Automated assays using multi-well microplates are advantageous approaches for identifying pathway regulators by allowing the assessment of a multitude of conditions in a single experiment. Here, we have adapted the well-established macropinosome imaging and quantification protocol to a 96-well microplate format and provide a comprehensive outline for automation using a multi-mode plate reader.
11:44
Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures
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Cited by 5 •
2013
Here we describe a robust method for the fractionation of plant plasma membranes into detergent resistant and detergent soluble membranes based on a mixture of unlabeled and in vivo fully 15N labeled Arabidopsis thaliana cell cultures. The procedure is applied for comparative proteomic studies to understand signaling processes.
FAQs
Label-free analysis derives measurements from intrinsic properties that change with biological state. Light scattering and absorption can reflect cellular or tissue structure, while refractive-index changes, electrical responses, and mechanical properties provide additional physical readouts. Because these signals respond to structure, metabolism, or molecular composition, researchers can follow changes in living systems without introducing an external reporter.
Choice depends on the biological feature being monitored. Signals linked to structure or morphology may help follow changes in cell form, whereas measurements affected by metabolism or molecular composition can reveal other disease-related changes. Electrical or mechanical responses add distinct physical information. Matching the readout to the research question helps interpret tumor-cell behavior more directly.
It avoids attaching fluorescent, radioactive, or other external labels to the specimen. That reduces sample preparation and the possibility of labeling artifacts while preserving native biological states. Measurements therefore center on changes in intrinsic physical or chemical signals, including structure, metabolism, molecular composition, refractive index, electrical behavior, or mechanical properties, rather than on a label-derived signal.
Noninvasive measurements can support repeated observation of the same living system over time. In cancer studies, this enables longitudinal tracking of proliferation, migration, morphology, and treatment response instead of limiting observation to a single endpoint. Preserving the native state also helps researchers examine disease-related changes and therapy-associated effects with less disruption from sample preparation.
Researchers select a relevant intrinsic readout, such as light scattering, absorption, refractive-index change, electrical response, or mechanical property. They then monitor that signal in cells, tissues, or molecules and relate changes to outcomes such as proliferation, migration, morphology, or treatment response. Repeated measurements can provide a time-resolved view while minimizing sample preparation.
It is useful when investigators need to observe living tumor cells while preserving their native condition. Applications include real-time assessment of proliferation and migration, characterization of morphological changes, and monitoring responses to treatment. The approach can also support longitudinal studies in living systems, where repeated, less disruptive measurements are especially valuable.
They can capture changes in morphology and behavior, including how tumor cells proliferate, migrate, or respond to treatment. Depending on the intrinsic signal, the analysis may also indicate shifts associated with cell structure, metabolism, molecular composition, or physical properties. This broader set of readouts helps connect observed cancer-cell behavior with disease-related changes.