FInCH: FIJI plugin for automated and scalable whole-image analysis of protein expression and cell morphology

Abstract

Study of morphogenesis and its regulation requires analytical tools that enable simultaneous assessment of processes operating at cellular level, such as synthesis of transcription factors (TF), with their effects at the tissue scale. Most current studies conduct histological, cellular and immunochemical (IHC) analyses in separate steps, introducing inevitable biases in finding and alignment of areas of interest at vastly distinct scales of organization, as well as image distortion associated with image repositioning or file modifications. These problems are particularly severe for longitudinal analyses of growing structures that change size and shape. Here we introduce a python-based application for automated and complete whole-slide measurement of expression of multiple TFs and associated cellular morphology. The plugin collects data at customizable scale from the cell-level to the entire structure, records each data point with positional information, accounts for ontogenetic transformation of structures and variation in slide positioning with scalable grid, and includes a customizable file manager that outputs collected data in association with full details of image classification (e.g., ontogenetic stage, population, IHC assay). We demonstrate the utility and accuracy of this application by automated measurement of morphology and associated expression of eight TFs for more than six million cells recorded with full positional information in beak tissues across 12 developmental stages and 25 study populations of a wild passerine bird. Our script is freely available as an open-source Fiji plugin and can be applied to IHC slides from any imaging platforms and transcriptional factors.

Keywords: Cell shape; Evolutionary diversification; Histology; Immunohistochemistry; Morphogenesis; Ontogeny; Scalable whole-image analysis of immunohistochemistry expression and cell segmentation: FInCH (File Iterating and Color deconvolving Histogram) plugin; Transcription factors.

Graphical abstract

Fig. 1

FInCH program workflow. The program processes the images in the “AOI image folder” (selected by the user). A “Processed folder” is created inside the “AOI image folder” and stores the deconvoluted images as well as the thresholded images (a folder “Saved”). The program also creates “IHC data and grid .csv files” in the “Processed folder”. “ROI.zip files” folder is created inside the “Grids” subfolder in the “Processed folder”. All cell morphology .csv files for each grid cell corresponding to the same image, are stored inside a folder with the image's name inside the “Cell Data” folder. Finally, the thresholded image that was used by the program to perform cell morphology analysis is saved along with the cell morphology.csv files inside the ID subfolder in the Cell Data folder.

Fig. 2

Structure of files included in FInCH plugin. Boxes in blue describe the folders that hold python scripts, boxes in yellow show associated scripts for FInCH Fiji functionality. FInCH_.py should be placed in the Fiji plugins folder (Fiji.app/plugins/). All the other files (__init__.py, Interface.py, DataManager.py, GridGen.py, Utils.py, FInCHPlugins.py, FInCHminilogo.png) should be placed in the jars/Lib folder (Fiji.app /jars/Lib/FInCH/).

Fig. 3

FInCH initial setup menu. If no additional changes are needed, select “Use Default Settings” (A). To make changes or additions select “Setup FInCH” (C). To terminate the plugin, select “Cancel” (B).

Fig. 4

Setup parameters in FInCH. (A) Enter “Filename identifiers”, e.g., TFs for analyses. (B) Enter “Color Deconvolution Spectra” with the set of TFs analysed along with their IHC spectra as default. (C) Enter “Threshold Cutoff Value” (default value = 207). (D) Enter additional functionality, (e.g., “Upper/Lower Image Functionality”) or leave unchecked. This function creates a grid on a lower beak image with cell dimensions that match the grid cell of its associated upper beak image. Select “Finish Setup” to save new settings.

Fig. 5

FInCH menu with the default settings. (A) Enter rows and columns to generate a grid (default 10×10). (B) “Process a single image” is unchecked by default (program assumes an entire folder will be processed). (C) “Grid data already exists for image(s)” is unchecked by default. If the user would like to open previously processed images with the previously created grid, this option should be selected, and the rest of the options should be left unchecked. The program also assumes that the user wants to do expression analysis (“Collect Pixel Data” (E) options checked by default). d-F Settings create a .zip file for each image, with the coordinates of the grid cells that will be necessary for future cell analysis. For cell morphology analysis, “Grid data already exists for image(s)” (C) and “Cell analysis” (D) options should be selected. (F) To modify FInCH settings, select “Complete initial setup (change settings)”.

Fig. 6

Image Navigator window once FInCH is finished processing images. (A) The names of the processed images are in the navigator window. Clicking on the filename will bring the corresponding image to the front of the screen. (B) “Toggle the grid overlay” or (C) “Toggle Threshold” will overlay the grid/threshold created by FinCH on the selected image. (D) “Close all windows” closes all windows opened by FinCH during the analyses.

Fig. 7

Representative stages of the TF expression analysis process in FInCH. (a) original image is (b) colour deconvoluted by FInCH based on specified TF – only the TF expression is thresholded. (c) The thresholded image is analysed by Fiji using the ROI Manager menu to compute the number of white pixels (which correspond to the TF expression) and black pixels (no TF expression) for (d) each grid cell. All stages of image processing can be manually confirmed by the user (Fig. 6).

Fig. 8

FInCH plugin menu for cell morphology analysis. All options should be unchecked except for option “C”, “Grid data already exists for image(s)” and option “D”, “Cell analysis”. Option “B”, “process a single image” can be both checked or unchecked, depending on if the user desires to process a single image or an entire folder respectively. A set of .csv files with the cell data will be created for each image.

Fig. 9

Representative thresholded image created by FinCH during cell morphology analysis.

Fig. 10

FInCH menu with settings for reapplying grid over processed images. All options should be unchecked except for option “C”, “Grid data already exists for image(s)”. Option “B”, “Process a single image” can be both checked or unchecked, depending on if the user desires to process a single image or an entire folder respectively.

Fig. 11

Examples of data files. (a) data.csv (b) grid.csv and (c) grid_ID.csv.