Quantifying Drosophila melanogaster Eye Phenotypes: A Computational Approach Integrating ilastik and Flynotyper

Summary

The Drosophila eye system is a useful tool for studying various biological processes, particularly human neurodegenerative diseases. However, manual quantification of rough eye phenotypes can be biased and unreliable. Here we describe a method by which ilastik and Flynotyper are used to quantify eye phenotype in an unbiased way.

Abstract

The Drosophila melanogaster compound eye is a well-structured and comprehensive array of around 800 ommatidia, exhibiting a symmetrical and hexagonal pattern. This regularity and ease of observation make the Drosophila eye system a powerful tool to model various human neurodegenerative diseases. However, ways of quantifying abnormal phenotypes, such as manual ranking of eye severity scores, have limitations, especially when ranking weak alterations in eye morphology. To overcome these limitations, computational approaches have been developed such as Flynotyper. The use of a ring light allows for better qualitative images accessing the intactness of individual ommatidia. However, these images cannot be analyzed by Flynotyper directly due to shadows on ommatidia introduced by the ring light. Here, we describe an unbiased way to quantify rough eye phenotypes observed in Drosophila disease models by combining two software, ilastik and Flynotyper. By preprocessing the images with ilastik, successful quantification of the rough eye phenotype can be achieved with Flynotyper.

Introduction

The Drosophila melanogaster genome contains ~75% of human disease-related gene orthologs. Additionally, during Drosophila eye development, approximately two-thirds of the genes in the genome are expressed, making the Drosophila eye an outstanding genetic system to investigate various molecular and cellular functions, development, and disease models^1,2. Thus, the Drosophila eye system is a useful experimental tool to study various biological processes.

The Drosophila compound eye is a well-structured and comprehensive array of ~800 ommatidia that exhibit a symmetrical and hexagonal pattern³. The regularity of this hexagonal pattern can be used to estimate the effect of introducing mutations and gene expression changes in eye morphology⁴. Previous studies that require evaluation of eye morphology have heavily relied on manual ranking of the severity of eye phenotypes detected by the naked eye. To rank the eye phenotypes, external eye morphology images are taken by a stereomicroscope^5,6. The eye phenotype of each group is assessed by splitting the external eye into four areas and calculating the proportion of degeneration in each area^5,6. Then, the values are used to calculate averages that are compared with the values obtained from control flies⁷. The scoring is based on the extent of fusion, loss of ommatidia, and bristle organization^7,8. Fly eye photos taken with a stereomicroscope are acquired by one researcher, and the eye phenotype analysis is performed by another researcher with triple validation sets^7,8.

When it comes to ranking weak alterations in eye morphology with the naked eye, there are limitations⁴. To overcome these limitations, computational approaches such as FLEYE and Flynotyper have been developed^1,9. Flynotyper is a novel computational method for quantitatively estimating morphological changes in the Drosophila eye system¹. It automatically detects the Drosophila eye and individual ommatidium, calculating Phenotypic Scores (P-Scores) based on the irregularity of theeye¹. A higher P-Score indicates the fly eye is more degenerated. This software was successfully used in quantifying the abnormality of Drosophila eyes¹⁰. Although Flynotyper ensures an automated process, it still cannot be successfully applied to some eye images taken by various light microscopy methods.

Qualitatively, we prefer a ring light source compared to a single-point light source, as it offers a more accurate representation of each ommatidium. However, when the ring light is used, it generates a ring-shaped shadow at the top of each ommatidium due to the hemispherical shape of the ommatidium. This ring-shaped shadow inhibits accurate ommatidial detection by Flynotyper, leading to incorrect calculation of P-Scores.

To overcome these issues, we implemented ilastik, a machine learning-based tool for various analyses, to classify ommatidia in fly eye images¹¹. We then fed the ilastik-generated images into Flynotyper to calculate P-Scores. This allows us to quantify the Drosophila eye morphological defects unbiasedly¹.

Protocol

1. Preparing for quantification

1. Download and install ilastik¹¹, ImageJ, and the ImageJ plugin Flynotyper¹. See Table of Materials for website links to installation. Download the appropriate packages according to the computer operating system (Mac, Windows, Linux, etc). Follow the installation instructions exactly as stated.
   NOTE: Following the directions exactly as stated in the provided links is imperative. The computer used needs a 64-bit operating system; otherwise, there are no other required specifications. See the Table of Materials for the computer specifications of the system used for this protocol.
2. Use a standard image to train the machine learning model. Take an image of a healthy fly eye using a light microscope with a ring light (such as w1118 x GMR-GAL4), using the center of the eye as the focal point. Analyze males and females separately; therefore, acquire a standard image for males and for females.
   NOTE: Settings will vary widely depending on the microscope and camera. See the second paragraph in the discussion for more general information on fly preparation and image acquisition.
3. Take images of the experimental fly eyes using the same settings used for the standard image acquisition.
   NOTE:Good orientation is paramount for accurate quantification. See Figure 4 as an example for proper orientation.

2. Using ilastik to detect ommatidia from fly eye images

1. Before starting analysis, make sure all experimental groups, regardless of experimental condition, are in the same file folder to make the following processes easier. Make sure files are named appropriately to identify experimental groups and distinguish between males and females.
   NOTE: We recommend printing out the protocol and using the computer to zoom in on figures, as this protocol is most easily followed visually.
2. Open the software.
   NOTE: It is advised not to have other applications open while running the software; otherwise, the computer might run very slowly, particularly in older or less robust systems.
3. Click on Create New Project | Other Workflows, choose Cell Density Counting, and select a location to save the project file (Figure 1A).
4. Click on 1. Input Data | Add New | Add Separate Image(s). Choose the standard image (Figure 1B).
5. Click on 2. Feature Selection and select features to use. Select the features shown in Figure 1C; choose more sigma values to increase sensitivity (i.e., 10, 15, 20, etc).
   NOTE: If too many boxes are checked, the program might run for a long time.
6. Click on 3. Counting and set the Foreground sigma value to 5.00. Mark 50 or more individual ommatidium using the Foreground tool on the standard image.
   NOTE: Fifty markings are typically adequate for analysis; however, the more ommatidia marked, the more accurate the results will be (Figure 1D).
7. Click on 3. Counting and use the Background tool to mark the outside of the ommatidia (Figure 1E). Draw green lines in a lattice shape around the ommatidia.
   NOTE: Similar to more markings on the ommatidia, the more green lines drawn, the more accurate the results will be.
8. Click on 4. Density Export | Choose Export Image Settings to set image settings (Figure 1F). Click on Output File Info | select Format and tif for further analysis in Flynotyper.
9. Click on 5. Batch Processing | Select Raw Data Files and select all experimental fly photos to be analyzed (Figure 1G). The list of imported images to be analyzed is seen under Select Raw Data Files (Figure 1H). Click Process all Files at the bottom of the 5. Batch Processing section.
   NOTE: As a reminder, male and female analyses should be done separately. Depending on the computer used, this step can take 10 min or longer, especially if there are many imported images.
10. After the software has finished, check the same file folder containing the experimental fly eye images; there will be black images named "YourSampleName_Probabilities" (Figure 1I).

3. Using ImageJ to prepare photos for Flynotyper

1. Open the ilastik-generated .tif file (the black boxes) in ImageJ.
   NOTE: Each ilastik generated .tif file needs to be handled separately.
2. Use the Rectangle Select tool to make a rectangle around just the eye. After the rectangle has been drawn, crop the area by either choosing Ctrl + X or Ctrl + C (Figure 2A). Wait for a black box in the shape of the rectangle outline to appear.
   NOTE: The computer operating system will determine whether to use 'Ctrl + X' or 'Ctrl + C'. Usually, 'Ctrl + X' is for Windows and 'Ctrl + C' is used for Mac.
3. Open the now cut fly eye using ImageJ; click on File | New | Internal Clipboard (Figure 2B).
4. Save the cut fly eye as a JPEG by clicking on File | Save As | Jpeg. The cut images are now in the same file folder as the original experimental images.
   NOTE: To make the next step easier, it is recommended to create a new file folder called 'cut' and put all of the cut images into that folder.

4. Using Flynotyper to calculate phenotypic scores

1. Open Flynotyper as an ImageJ plugin by clicking on Plugins | Flynotyper.
2. Select Add Genotypes and open the folder containing the cut fly eye images (cut file folder). The folder name will appear under Genotypes (Figure 2C).
3. Check the Light microscope and Vertically boxes but adjust accordingly if needed. Check Stability and Distance to the Center boxes under Rank Ommatidia by: (Figure 2C).
4. For Number of ranked ommatidia considered, input 200.
   NOTE: In general, 200 is a good number but adjust accordingly to preferences.
5. Click Run and wait for the results of the analysis to appear (Figure 2D).
   NOTE: This step may take 5 min or longer (or shorter) depending on the processing power of the computer used.
6. Copy and paste the Sample File and P-Score into statistical software for further analysis.

Results

In a previous study, we used this protocol to determine genetic modifiers of mutant VCP protein linked to amyotrophic lateral sclerosis with frontotemporal dementia (ALS-FTD)¹². Additionally, this method was also used in another paper to assess the toxicity of CHCHD10^S59L-mediated ALS-FTD, even when using an older stereomicroscope¹³. To further validate these results, we used ilastik and Flynotyper in the same ALS-FTD disease mutation as Baek et al.

Discussion

The ommatidia of Drosophila comprise a useful system for studying various biological functions and genetic diseases. The regularity of ommatidia is a good measurement to examine the effect of genetic mutations⁴. Even though several methods for calculating ommatidial regularity exist, such as manual ranking, these methods can be heavily biased. To overcome this biased approach, semi-automatic tools have been developed^1,11.

Materials

Name	Company	Catalog Number	Comments
Computer specifications			Ryzen 5, 16 GB RAM, Nvidia RTX 3070 Super, Windows 10
Flynotyper	Iyer, J. et al. (2016)	Download software here: https://flynotyper.sourceforge.net/imageJ.html	Open source software. Do not use Flynotyper 2.0. At the time of publication, 2.0 was fairly new and this protocol is optimized for the original version of Flynotyper.
ilastik	Berg, S. et al. (2019)	Download software here: https://www.ilastik.org/download.html	Open source software. Download Version 1.4.0.post1 under Regular Builds corresponding to your computer operating system.
ImageJ		Download software here: https://imagej.net/ij/download.html	Open source software. Versions 1.53 and 1.54 were used. 1.54 is the updated version and is the default download.
Leica Application Suite (LAS X)	Leica Microsystems	LASX Office 1.4.6 28433	System and software used for z-stack acquisition.
Leica Z16 APO microscope with a DMC2900 camera	Leica Microsystems	10 447 173, 12 730 466	Referred to as Z-stack microscope and camera in the text. This product is now archived.