Gut Analysis Toolbox: Automating quantitative analysis of enteric neurons
- Author(s)
- Sorensen, L; Humenick, A; Poon, SSB; Han, MN; Mahdavian, NS; Rowe, MC; Hamnett, R; Gómez-de-Mariscal, E; Neckel, PH; Saito, A; Mutunduwe, K; Glennan, C; Haase, R; McQuade, RM; Foong, JPP; Brookes, SJH; Kaltschmidt, JA; Muñoz-Barrutia, A; King, SK; Veldhuis, NA; Carbone, SE; Poole, DP; Rajasekhar, P;
- Journal Title
- Journal of Cell Science
- Publication Type
- Sep 2 epub ahead of print
- Abstract
- The enteric nervous system (ENS) consists of an extensive network of neurons and glial cells embedded within the wall of the gastrointestinal (GI) tract. Alterations in neuronal distribution and function are strongly associated with GI dysfunction. Current methods for assessing neuronal distribution suffer from undersampling, partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. We present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using 2D images of GI wholemount preparations. It is developed in Fiji, has a user-friendly interface and offers rapid and accurate segmentation via custom deep learning (DL) based cell segmentation models developed using StarDist, and a ganglion segmentation model in deepImageJ. We use proximal neighbor-based spatial analysis to reveal differences in cellular distribution across gut regions using a public dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput allowing unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples rapidly.
- Publisher
- COB
- Keywords
- Enteric nervous system; Fiji; Gut analysis toolbox; Image analysis; Machine learning; Spatial analysis
- Research Division(s)
- Advanced Technology And Biology
- PubMed ID
- 39219476
- Publisher's Version
- https://doi.org/10.1242/jcs.261950
- Open Access at Publisher's Site
https://doi.org/10.1242/jcs.261950- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2024-10-09 01:19:13
Last Modified: 2024-10-09 01:19:21