Jun 16, 2026
Manual Quantification of Microscopy-Based Bead Assays
- Elisabeth Holzer1
- 1Laboratory of Sascha Martens, Max Perutz Labs, University of Vienna, Austria
Protocol Citation: Elisabeth Holzer 2026. Manual Quantification of Microscopy-Based Bead Assays. protocols.io https://dx.doi.org/10.17504/protocols.io.x54v95d7zl3e/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
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Created: August 06, 2025
Last Modified: June 16, 2026
Protocol Integer ID: 224294
Keywords: ASAPCRN, based bead assay, bead assay, bead assays this protocol, manual quantification of microscopy, microscopy, description of manual quantification, manual quantification
Funders Acknowledgements:
Aligning Science Across Parkinson’s (ASAP)
Grant ID: ASAP-000350
DOC Fellowship (Austrian Academy of Sciences)
Abstract
This protocol details the description of Manual Quantification of Microscopy-Based Bead Assays.
Manual Quantification of Microscopy
Perform manual quantification for microscopy-based bead assays in which weak fluorescence signals could not be reliably quantified using AI-based image analysis.
Open images using Fiji (ImageJ).
Select regions without beads to measure background intensity. The size of the region of interest (ROI) keep consistent across all measurements within one experiment.
Measure the total intensity of the full image.
Subtract background intensity from the total image intensity. All measurements from one replicate were then normalized to the maximum value (set to 100%). Plot the resulting values and subject to statistical evaluation using GraphPad PRISM software.
For experiments involving two fluorescence channels (e.g., green signal for bait protein and red for prey protein):
Measure the background and total signal separately for each channel.
For each channel, subtract background from the total intensity of the image.
Use the bait channel (present in all conditions) to normalize the signal of the prey:
(normalized prey signal) ÷ (normalized bait signal).
Use the maximum value across all replicates to normalize to 100%. Plot the resulting values and subject to statistical evaluation using GraphPad PRISM software.