Gut Analysis Toolbox – automating quantitative analysis of enteric neurons

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 two-dimensional images of GI wholemount preparations. GAT 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, as well as a ganglia segmentation model in deepImageJ. We apply 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 rapid unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples.

Authors

Institutions

Publication Details

Journal
Journal of Cell Science
Published
2024-09-02
DOI
https://doi.org/10.1242/jcs.261950
Citations
5
Primary Topic
Congenital gastrointestinal and neural anomalies
Type
article
Field-Weighted Citation Impact
2.86

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gut Analysis Toolbox – automating quantitative analysis of enteric neurons

Myat Noe Han, Ayame Saito, Jaime P. P. Foong, Simona Carbone et al.
5 citations
Journal of Cell Science
Congenital gastrointestinal and neural anomalies
2.86
article

Gut Analysis Toolbox – automating quantitative analysis of enteric neurons

Myat Noe Han, Ayame Saito, Jaime P. P. Foong, Simona Carbone, Daniel P. Poole, Arrate Muñoz‐Barrutia, Nicholas A. Veldhuis, Peter H. Neckel, Matthew C. Rowe, Estibaliz Gómez‐de‐Mariscal, Sabrina Poon, Robert Haase, Adam Humenick, Simon J. Brookes, Pradeep Rajasekhar, Ryan Hamnett, Rachel M. McQuade, Sebastian K. King, Julia A. Kaltschmidt, Keith Mutunduwe, Narges Mahdavian, Christie Glennan, Luke Sorensen
article en
5 citations

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 two-dimensional images of GI wholemount preparations. GAT 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, as well as a ganglia segmentation model in deepImageJ. We apply 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 rapid unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples.

Journal of Cell ScienceVol. 137(20)
Royal Children's Hospital (AU), The University of Melbourne (AU), Flinders University (AU), Neurosciences Institute (US), Walter and Eliza Hall Institute of Medical Research (AU), Discovery Institute (US), Flinders Medical Centre (AU), Hospital General Universitario Gregorio Marañón (ES), Western Health (AU), Australian Institute for Musculoskeletal Science (AU), Adelaide Institute for Sleep Health (AU), Stanford Medicine (US), Murdoch Children's Research Institute (AU), Instituto Gulbenkian de Ciência (PT), Universidad Carlos III de Madrid (ES), Monash University (AU), University of Tübingen (DE), RMIT University (AU), Leipzig University (DE), Stanford University (US)
Australian Government, European Commission, Monash University, University of Melbourne, Scheme for Promotion of Academic and Research Collaboration, National Institutes of Health, HORIZON EUROPE Framework Programme, Medical Research Council, Australian Research Council, National Health and Medical Research Council, HORIZON EUROPE European Research Council
Partnerships for the goals
Openalex Percentile: Top 9%
Congenital gastrointestinal and neural anomalies
2.86
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.