COUNTEN, an AI-Driven Tool for Rapid and Objective Structural Analyses of the Enteric Nervous System
The enteric nervous system (ENS) consists of an interconnected meshwork of neurons and glia residing within the wall of the gastrointestinal (GI) tract. While healthy GI function is associated with healthy ENS structure, defined by the normal distribution of neurons within ganglia of the ENS, a comp...
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| Published in: | eNeuro Vol. 8; no. 4; p. ENEURO.0092-21.2021 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Society for Neuroscience
01-07-2021
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | The enteric nervous system (ENS) consists of an interconnected meshwork of neurons and glia residing within the wall of the gastrointestinal (GI) tract. While healthy GI function is associated with healthy ENS structure, defined by the normal distribution of neurons within ganglia of the ENS, a comprehensive understanding of normal neuronal distribution and ganglionic organization in the ENS is lacking. Current methodologies for manual enumeration of neurons parse only limited tissue regions and are prone to error, subjective bias, and peer-to-peer discordance. There is accordingly a need for robust, and objective tools that can capture and quantify enteric neurons within multiple ganglia over large areas of tissue. Here, we report on the development of an AI-driven tool, COUNTEN (COUNTing Enteric Neurons), which is capable of accurately identifying and enumerating immunolabeled enteric neurons, and objectively clustering them into ganglia. We tested and found that COUNTEN matches trained humans in its accuracy while taking a fraction of the time to complete the analyses. Finally, we use COUNTEN’s accuracy and speed to identify and cluster thousands of ileal myenteric neurons into hundreds of ganglia to compute metrics that help define the normal structure of the ileal myenteric plexus. To facilitate reproducible, robust, and objective measures of ENS structure across mouse models, experiments, and institutions, COUNTEN is freely and openly available to all researchers. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Author contributions: J.A.K., A.V., and S.K. designed research; Y.K., A.B., S.D., N.W., S.B., M.S., and S.K. performed research; C.E. and J.G.-F. contributed unpublished reagents/analytic tools; Y.K., A.B., J.A.K., A.V., and S.K. analyzed data; J.A.K., A.V., and S.K. wrote the paper. C. Espenel’s present address: 10x Genomics Inc., Pleasanton, CA 94588. This work was supported by a Stanford ChEM-H Seed grant (S.D.); a Beckman Center Bioimage Analysis grant (C.E.); the Stanford ChEM-H Chemistry/Biology Interface Predoctoral Training Program and the National Institute of General Medical Sciences of the National Institutes of Health Award T32GM120007 (to J.G.-F.); the Wu Tsai Neurosciences Institute and a research grant from The Shurl and Kay Curci Foundation (J.A.K.); grants from the National Science Foundation (CRCNS 1822575 and CAREER Award 1845430; to A.V.); and funding from the Ludwig Foundation, the National Institute of Aging Grant 1R01AG066768, and the Hopkins Digestive Diseases Basic and Translational Research Core Center Pilot Grant P30DK089502 (to S.K.). Y.K., A.B., and S.D. are co-first authors. The authors declare no competing financial interests. J.A.K., A.V., and S.K. are co-senior authors. |
| ISSN: | 2373-2822 2373-2822 |
| DOI: | 10.1523/ENEURO.0092-21.2021 |