# Bioloc3D (B3D): Protocol for 3D automated analysis of colocalization in microscopy v2

Thibault Dhellemmes, Rémi Kinet, Fabrice Cordelières, Marc Landry

► To cite this version:

Thibault Dhellemmes, Rémi Kinet, Fabrice Cordelières, Marc Landry. Bioloc3D (B3D): Protocol for 3D automated analysis of colocalization in microscopy v2. 2025. hal-05196203

HAL Id: hal-05196203

https://hal.science/hal-05196203v1

Preprint submitted on 1 Aug 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Bioloc3D (B3D) : Protocol for 3D automated analysis of colocalization in microscopy V.2

DOI

dx.doi.org/10.17504/protocols.io.kxygx4p5zl8j/v2

Thibault Dhellemmes<fnref n="1" />, Rémi Kinet<fnref n="1" />, Fabrice Cordelières<fnref n="2" />, Marc Landry<fnref n="1" />

## Bioloc3D (B3D)

<figure><img src="image_2.png" /></figure>

Thibault Dhellemmes

Institut des Maladies Neurodégénératives (IMN)

<figure><img src="image_3.png" /></figure>

OPEN

<figure><img src="image_4.png" /></figure>

ACCESS

<figure><img src="image_5.png" /></figure>

DOI: dx.doi.org/10.17504/protocols.io.kxygx4p5zl8j/v2

External link: https://github.com/Bioloc3D

**Protocol Citation:** Thibault Dhellemmes, Rémi Kinet, Fabrice Cordelières, Marc Landry 2025. Bioloc3D (B3D) : Protocol for 3D automated analysis of colocalization in microscopy. protocols.io

https://dx.doi.org/10.17504/protocols.io.kxygx4p5zl8j/v2Version created by Thibault Dhellemmes

**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

**Created:** July 24, 2025

**Last Modified:** July 25, 2025

**Protocol Integer ID:** 223277

<footnote n="1">¹Université de Bordeaux - Institut des Maladies Neurodégénératives (IMN) / UMR 5293;</footnote>

<footnote n="2">²Bordeaux Imaging Center</footnote>
<figure><img src="image_6.png" /></figure>

**Keywords:** Software, Microscopy, Automatization, Colocalization, Fluorescent, Quantification, Automated analysis, Statistics, bioloc3d, tools capable of colocalization quantification, microscopy this protocol, microscopy, fluorescent labeling across entire stack, fluorescent labeling, colocalization quantification, analysis of colocalization, colocalization, b3d, automate statistical analysis, automated analysis

**Funders Acknowledgements:**

ANR
Grant ID: ANR-19-CE37-0019 Relax
FRM
Grant ID: FDT202404018302

Abstract

This protocol introduces Bioloc3D, a fully open-source tool designed to quantify fluorescent labeling across entire stacks and automate statistical analysis. It offers a solution to the lack of tools capable of colocalization quantification between multiple identified elements in 3D. Expected results includes graphical representations of the results through images and estimation plots.

Image Attribution

Thibault Dhellemmes

Materials

Raw image stacks with fluorescent signals to analyze in any format adapted to ImageJ.
Linux/Mac/Windows computer with ImageJ, Excel and Bioloc3D-Plt installed. ImageJ installation file is available
online at https://imagej.net.

Before start

To operate in the best condition, the minimal requirement for colocalization analysis is a stack of 2 channels with 2
images (i); in 8-bit color depth (ii); preferably in TIFF format (iii)
# B3D workflow and protocol

1. Schematic representation of the analysis workflow using B3D

* Diagram of the simplified procedure

* User-interface (UI) of B3D-Img toolset in ImageJ and B3D-PIt standalone application

## B3D workflow

<figure><img src="image_7.png" /></figure>

## B3D simplified protocol & UI

<figure><img src="image_8.png" /></figure>

Illustrations of B3D workflow and protocol

2. **! CAUTION** Figures mentioned under brackets (e.g. (Supplementary Fig. 1C)) refer to the method publication in which the experimental design of B3D toolset is detailed (cf. "Manuscript citation" section)

## Installation

3m

3. Download the B3D-Imaging (B3D-Img) ImageJ macro at https://github.com/Bioloc3D/B3D-Img
<figure><img src="image_9.png" /></figure>

4 Install B3D-Img in ImageJ macro library, by drag/drop the .ijm file in the toolsets folder of the application (Fiji/ImageJ → macros → toolsets)

5 Install latest version of 3D Objects Counter plugin available online on GitHub, by drag/drop the .jar file in the plugins folder of the application (Fiji/ImageJ → plugins)

<figure><img src="image_10.png" /></figure>

6 Launch ImageJ software

Software

ImageJ (Fiji)

NAME

Windows 10

OS

National Institutes of Health (USA)

DEVELOPER

https://imagej.net/software/fiji/downloads

SOURCE LINK

7 Through ImageJ install MorphoLibJ, 3D ImageJ Suite and Read and Write Excel additional plugins available in plugin list (Help → Update... → Manage Update Sites → tick plugins → Apply and Close)

<figure><img src="image_11.png" /></figure>

8 Close ImageJ software

<figure><img src="image_12.png" /></figure>

9 Download the B3D-Plt application depending of the user operating system at https://github.com/Bioloc3D/B3D-Plt

Software

Bioloc3D

NAME

Windows / MacOS

OS

Thibault Dhellemmes / Rémi Kinet

DEVELOPER

https://github.com/Bioloc3D

SOURCE LINK
<figure><img src="image_13.png" /></figure>

Image analysis : B3D-Imaging (B3D-Img)

10 Launch B3D toolset in ImageJ software

30s

10.1 Start ImageJ software

10.2 Click on the "More Tools" menu (>>>) and select B3D-Img

11 Defining the correct parameters

2m 30s

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

11.1 Click on B3D parameters icon (cf. Supplementary Fig. 1A)

11.2 Select the stack to test the parameters and the folder in which test data will be saved.
Parameters must be tested in an iterative matter, select one channel from the stack (cf.
Supplementary Fig. 1C, Step 1 of the diagram).

<figure><img src="image_16.png" /></figure>

11.3 Click "OK"

11.4 Define the threshold adapted to the signal of the selected channel (cf. Supplementary Fig. 1C, Step 2 of the diagram).

<figure><img src="image_17.png" /></figure>

11.5 Click "OK"

11.6 Use the threshold defined in sub-step 11.4 and define minimal and maximal size threshold to test (Supplementary Fig. 1C, Step 3 of the diagram). If needed, define minimal area for soma detection (cf. Supplementary Fig. 1C, Step 4 of the diagram)

<figure><img src="image_18.png" /></figure>

11.7 Click "OK": Test analysis is launched

<figure><img src="image_19.png" /></figure>

12 **Analysis of one stack and raw data export**

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

**! CAUTION** As discussed in the "advantages and limitations" section, time of analysis depends on several aspects, including computation power of the machine, size, potential number of objects to count per channel and signal-to-noise ratio of your images. To
<figure><img src="image_23.png" /></figure>

estimate the time of each step of the procedure, we used a stack presenting the
following characteristics: size= 1024 × 1024; z= 25; objects counted per channel= 1000.
In addition, sample is presenting a moderate signal-to-background (SBR) but a low
signal-to-noise ratio (SNR).

12.1 Click on B3D analysis icon (cf. Fig. 2A)

12.2 Select the folder containing stack(s) to analyze and numbered your batch of analysis (Fig2C, section 1 on the diagram). Normalization of the name of exported data files is compulsory for the automatic computation. If more than one file is present in this folder, "headless" option must be defined on "Yes"

**! CAUTION** Select folder must contains only tiff file(s) before starting the analysis in ImageJ.

<figure><img src="image_24.png" /></figure>

12.3 Click "OK"

12.4 Enter parameters defined in step 11, in the GUI (Fig. 2C, section 3 on the diagram) and select options for quantification based on expected information

<figure><img src="image_25.png" /></figure>

12.5 **Option A:** 30s
Simple quantification (3D-Simple) of primary channels, without quantification of additional features (control of colocalizations sites and soma)
(i) Select "Yes" for "Simple segmentation of C1 & C2:"
(ii) Select "No" for "Check colocalization with an additional channel"
(iii) Select "No" for "Complete counting with an additional channel"

12.6 **Option B :** 3m
Complete quantification (3D-OC) of primary channels, without quantification of additional features
(i) Select "No" for "Simple segmentation of C1 & C2:"
(ii) Select "No" for "Check colocalization with an additional channel"
(iii) Select "No" for "Complete counting with an additional channel"

12.7 **Option C :** 40s
Simple quantification (3D-Simple) of primary channels, including quantification of additional features
(i) Select "Yes" for "Simple segmentation of C1 & C2:"
(ii) Select "Yes" for "Check colocalization with an additional channel"
(iii) Enter parameters for colocalization control (threshold and size)
(iv) Select "Yes" for "Complete counting with an additional channel"
(v) Enter parameters for soma counting (minimum area and threshold)

12.8 **Option D:**
<figure><img src="image_26.png" /></figure>

Complete quantification (3D-OC) of primary channels, including quantification of additional features

3m 30s

(i) Select "No" for "Simple segmentation of C1 & C2:"

(ii) Select "Yes" for "Check colocalization with an additional channel"

(iii) Enter parameters for colocalization control (threshold and size)

(iv) Select "Yes" for "Complete counting with an additional channel"

(v) Enter parameters for soma counting (minimum area and threshold)

12.9 Click "OK"

12.10 (Optional) Click "Help" to be redirected to GitHub repository

13 **(Optional) Proofreading of 3D quantification on one stack**
**! CAUTION** If only one stack is present in the folder, illustrations of the results can be displayed by selecting "No" for headless mode (Fig2C, section 2 on the diagram).

5m

13.1 For a more precise proofreading apply option B or D (Sub-steps 12.6 or 12.8)

13.2 Overview the different output stacks with the excel of the data aside to check if it counts what you wanted

**Computation, plotting and statistical analysis : B3D-Plotting (B3D-Plt)**

14 Open the B3D-Plt application

15 Click on "Load file" and select the folder containing the Excels to analyze

<figure><img src="image_27.png" /></figure>

16 Click on "Save file" and select the folder in which graphs and analysis will be saved

<figure><img src="image_28.png" /></figure>

17 Click on the drop-down menu and select the number of conditions you have to analyze

<figure><img src="image_29.png" /></figure>

18 In the bars that appear, enter the name of the condition and the color you want to associate with it (seaborn or hexadecimal #FF0000 style, but can stay empty)
Seaborn color link : https://seaborn.pydata.org/tutorial/color palettes.html
<figure><img src="image_30.png" /></figure>

19 Click on "Launch analysis"
**! CAUTION** Timing indicated for this step has been tested on a file containing 60 excel files

15m

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>

20 The name of the document currently analyzed is printed to monitor progress

21 Analysis end is notified through a pop-up window

22 Find the figures and Excel in the folder selected in step 16