Data from: Phagocytosed photoreceptor outer segment particles within the retinal pigment epithelium show diurnal rhythmicity and variation between cone subtypes in larval zebrafish

During phagocytosis of retinal rod and cone outer segments (OSs) by the
retinal pigment epithelium (RPE), RPE bites off and internalizes the
oldest parts of the OS tips to prevent the accumulation of harmful
compounds in the photoreceptors. Increases in the number of phagocytosed
OS particles in the RPE appear rhythmically once or twice a day, depending
on the animal species. However, the variation of this rhythmicity between
the distinct photoreceptor types is not well understood. To compare the OS
phagosome numbers and their daily rhythms between the different cone
subtypes, we used zebrafish larvae as an animal model. We collected
zebrafish larvae at seven different time points during a 24 h circadian
cycle and prepared histological sections of their eyes. We immunolabelled
the different cone opsins together with the RPE-specific proteins in the
histological sections. The sections were then imaged with a laser scanning
confocal microscope, after which the internalized OS particles were
quantified from the images. To make the quantification of the OS particles
more efficient, we developed a semi-automated analysis tool for
ImageJ-Fiji. The analysis tool allows the user to select the RPE area from
which it then segments and counts the detected OS particles. After
quantification, the results revealed the presence of OS particles of all
cone subtypes in the RPE throughout the day in larval zebrafish. However,
the phagosome numbers from UV and blue cone OSs increased significantly at
two time points, whereas the number of green cone OS particles was more
constant. The numbers of red cone OS particles were continuously lower
compared to other cone types and showed only one increase in the latest
time point during the dark phase of the day. We also investigated whether
the rhythmicity is affected by external light by keeping the larvae in
constant darkness for at least 24 h before sample preparation. We found
that the complete darkness condition decreased the phagosome numbers of
all cone subtypes, and additionally, the daytime peaks in the UV and blue
cones disappeared. This indicates that the rhythmicity is strongly
affected by the external light in the larval zebrafish. Our findings
provide new understanding on the cone OS phagocytosis and its rhythmicity.

# Data from: Phagocytosed photoreceptor outer segment particles within the
retinal pigment epithelium show diurnal rhythmicity and variation between
cone subtypes in larval zebrafish Dataset DOI:
[10.5061/dryad.76hdr7t64](10.5061/dryad.76hdr7t64) ## Description of the
data and file structure This is accompanying data for the research article
“Phagocytosed photoreceptor outer segment particles within the retinal
pigment epithelium show diurnal rhythmicity and variation between cone
subtypes in larval zebrafish” compressed into Dataset_.zip folder. We have
included raw and processed versions of the images presented in the
published article and its supplementary files. Additionally, we provide
the full script of our developed semi-automatized analysis tool for
imageJ-Fiji macro used for data analysis, as well as numerical data on the
OS phagosome quantification used to generate the graphs in the main
article and in the supplementary files. ### Files and variables The
dataset inside compressed archive named as Dataset_.zip is organized into
three folders as follows: 1. Imaging data, 2. Quantitative analysis tool,
3. Quantitative data. ### 1.Imaging data The data in this folder is
further organized into the subfolders “Raw images” and “Processed images”
which are organized even further into folders named after the figures of
the main article and the supplementary material (Figure 1, Figure 2,
Supplementary Figure S1, etc.). Raw images are in the form of .ND2 files
and processed images as .tiff files. Imaging data folder also contains a
.docx file with more detailed information on the naming of the image
files, used microscope and laser lines, as well as image processing.
Abbreviations in the file names: UV=UV cones, Blue= Blue cones,
Green=Green cones, Red=Red cones, ZPR2= antibody that labels RPE tissue,
RPE65=antibody that labels RPE tissue, ZPR3=antibody that labels green
cones, UV opsin= antibody that labels UV cones, Blue opsin= antibody that
labels blue cones, Red opsin= antibody that labels red cones, ZT=zeitgeber
time ### 2.Quantitative analysis tool This folder contains files that
provide the full script of the analysis tool for quantitative analysis of
outer segment (OS) phagosomes in the RPE tissue as .ijm file and .docx
file. The tool is for ImageJ-Fiji (ImageJ 1.54), and it utilizes standard
ImageJ-Fiji libraries for general image processing and MorphoLibJ
(MorphoLibJ_-1.6.2) for all morphological operations. The full script of
the analysis tool .docx file also contains information on the description
and key features of the analysis tool. The entire workflow is performed as
an interactive script that allows the user to configure the used channels,
adjust parameters and select RPE area from which the OS phagosomes are
then quantified by the tool. The analysis tool uses confocal z-stack
images of fluorescently labelled cryosections containing RPE and
photoreceptor channels as input. The output of the analysis (segmented RPE
area and detected OS phagosomes) are saved as ROI files and .xlsx files.
Before further analysis, the stacks are processed into maximum intensity
projections and Gaussian blur filter with radius 1 is applied. The
workflow of the analysis tool is divided into two steps: Manual RPE area
selection by the user and OS phagosome segmentation. OS phagosome
segmentation is based on the extraction of local bright objects using the
h-dome transform to detect all local maxima. h-dome transform method
suppresses low-contrast regions and enhances significant intensity peaks
bigger than defined h-value. The Maxima Finder is then applied to detect
the intensity peaks with an additional criterion called prominence that is
the minimum height difference between a local maximum and its surrounding
region for the maximum to be considered significant. In addition, the
folder contains .xlsx file with different numerical parameters used for
the analysis tool development and testing needed for the evaluation of the
performance of the analysis tool's peak detection algorithm. A
randomly chosen set of Z-stacks with each cone subtype (UV, blue and
green) labelled together with the RPE tissue was used. Empirical testing
was conducted to determine appropriate values for the parameters
"h-value" and "prominence" to find the balance between
sensitivity (detecting enough intensity peaks) and specificity (avoiding
false positives or irrelevant peaks) and the values are included in
separate worksheets for each cone subtype (named as Parameter
testing_UVcones, Parameter testing_Bluecones, Parameter testing_Green
cones). The test analysis for each image was performed with the analysis
tool using all combinations of five h-dome values (5, 15, 25, 50, 100) and
five prominence thresholds (5, 10, 20, 40, 80). The local maxima detected
by the analysis tool were then matched to the manually annotated local
maxima (Ground truth) and the detected peaks were defined as True positive
(TP), False positive (FP) and False negative (FN) (see the definitions in
the table below). By using the counts of TP, FP and FN, the values for
Precision, Sensitivity, F1-score and False positive rate (FPR) (see the
definitions and equations in the table below) were calculated for each
parameter combination of h-values and prominence thresholds to evaluate
the algorithm’s performance and its overall detection reliability in the
current analysis. The "Plotted values" worksheet in the .xlsx
file contains the average values and standard deviations (SD) of UV, blue
and green cones for each parameter (F1-score, FPR, Precision and Recall)
with each prominence and h-value combinations. The parameter combinations
of all five h-dome values and prominence thresholds between 5-20 produced
relatively similar values for precision, sensitivity, F1-score and FPR,
the performance and peak detection reliability with these parameters were
highly equal. Therefore, in our analysis tool, the h-value was set to 15,
whereas the prominence threshold was set specifically, always under the
value of 20, for each analysed image during the OS phagosome
quantification to reach the most reliable detection of OS phagosomes.
Missing values in this .xlsx file are marked as NaN. | **Parameter** |
**Definition** | **Equation** | | :------------------------ |
:---------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Precision | The proportion of detected peaks that were correct |  | | Ground truth | The manually annotated local intensity maxima |   | | Sensitivity (Recall) | The proportion of ground truth peaks that were successfully detected |  | | F1-score (F1) | The harmonic mean of precision and sensitivity, providing a single measure of performance |  | | False Positive Rate (FPR) | The proportion of negative ground truth peaks incorrectly classified as positive |  | | True positive (TP) | A detected peak that was within three pixels of a ground truth peak |   | | False positive (FP) | A detected peak that could not be matched to any ground truth peak |   | | False Negative (FN) | A ground truth peak that was not matched to any detected peak |   | ### 3.Quantitative data The folder of Quantitative data contains two .xlsx files: for the raw and processed quantitative data shown in the main article and for the data shown in the supplementary files. Quantitative data_OS phagosomes_main article.xlsx file contains numerical data on the quantified OS phagosomes counted by the semi-automatized analysis tool. The data is organized into multiple Excel worksheets, where the cone subtype (UV, Blue, Green) and the light condition (LD= normal light cycle; DD=constant darkness) are indicated. Each worksheet contains the number of outer segment (OS) phagosomes counted by the analysis tool from the RPE tissue of the whole eye cryosection and RPE length, which was manually measured from the RPE-OS interface individually in each cryosection. In addition, the number of OS phagosomes/1 µm RPE, as well as OS phagosomes/10 µm RPE were calculated and shown in the columns. These data are shown at each studied time point as zeitgeber times (ZT1, ZT3, ZT5, ZT10, ZT16, ZT18, ZT23). The h-value was fixed to get value 15, whereas the prominence values were set specifically by the user for each sample in the analysis tool during quantification of the OS phagosomes and are shown in the worksheets. The file also contains worksheets for LD and DD conditions with the averages of OS phagosomes/10 µm of RPE at each time point for UV, blue and green cones shown in the same table one below another in order UV, blue and green cones (named as Averages_UV, Blue, Green_LD and Averages_UV, Blue, Green_DD). Additionally, averaged values were normalized to the largest value of the averages throughout the time points for each cone subtype individually and shown in separate worksheets for LD and DD conditions (named as Normalized_UV,Blue,Green_LD and Normalized_UV,Blue,Green_DD). The order of photoreceptor types is UV, blue and green. Quantitative data_OS_phagosomes_supplementary material.xlsx file contains raw and processed numerical data on the quantified OS phagosomes counted by the analysis tool (rod precursors, LD) and raw and processed numerical data of the manually quantified OS phagosomes (red cones, LD and red cones, DD). Worksheets and columns are named similarly to the ones in Quantitative data_OS phagosomes_main article .xlsx file and the red cone and rod precursor data are shown in the same format. Abbreviations in the excel work sheets: OS phagosome= outer segment phagosome, ZT=Zeitgeber time, LD= normal light cycle, DD=constant darkness, µm= micrometer ## Code/software ### **Semi-automatized analysis tool for quantitative analysis of outer segment (OS) phagosomes in the RPE tissue** We developed the analysis tool for ImageJ-Fiji (ImageJ 1.54). It uses standard ImageJ-Fiji libraries for general image processing and MorphoLibJ (MorphoLibJ_-1.6.2) for all morphological operations. The analysis tool utilizes confocal z-stack images of fluorescently labeled whole eye cryosections containing RPE and photoreceptor channels as input. Before further analysis, the stacks are processed into maximum intensity projections and denoised with Gaussian filter with radius 1. The workflow is performed as an interactive script that allows the user to select the channels from the z-stack image, adjust certain parameters, and select the RPE area from which the OS phagosomes are then counted by the analysis tool. First, the tool enables the user to define which channels to use for analysis, after which the workflow of the analysis tool is divided into two steps: Manual RPE area selection by the user and OS phagosome segmentation. The tool then allows the user to define RPE area after which the selected area is binarized through auto-thresholding using Li's method. A morphological opening with a disc-shaped structuring element of radius 6 pixels is then applied automatically by the tool to remove holes and smooth the selection. The final selection is saved as an ImageJ region of interest (ROI) to be used as the area to search for OS phagosomes in the following steps. OS phagosome segmentation is based on the extraction of local bright objects using the h-dome transform method to find all local maxima. h-dome transform dampens low-contrast regions and boosts significant intensity peaks bigger than defined h-value. The Maxima Finder is applied to find the intensity peaks with an additional criterion called prominence. Prominence is the minimum height difference between a local intensity maximum and its surrounding area for the maximum to be considered significant. In the analysis tool, the prominence value of the analysis tool can be adjusted by the user to get any value between 1 and 20. The tool then quantifies the total number of detected intensity peaks representing the OS phagosomes within the segmented RPE area. The results are saved as ROI images and optionally as an Excel file.