Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

COUNTEN – an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System

Yuta Kobayashi, Alicia Bukowski, Subhamoy Das, Cedric Espenel, Julieta Gomez-Frittelli, Narayani Wagle, Shriya Bakshi, Monalee Saha, Julia A. Kaltschmidt, Archana Venkataraman, Subhash Kulkarni
doi: https://doi.org/10.1101/2020.11.24.396408
Yuta Kobayashi
1Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alicia Bukowski
2Center for Neurogastroenterology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Subhamoy Das
3Department of Neurosurgery, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Cedric Espenel
4Cell Sciences Imaging Facility, Stanford University School of Medicine, Stanford, CA, USA
810x Genomics Inc., Pleasanton, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Julieta Gomez-Frittelli
5Department of Chemical Engineering, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Narayani Wagle
1Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shriya Bakshi
2Center for Neurogastroenterology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Monalee Saha
2Center for Neurogastroenterology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Julia A. Kaltschmidt
3Department of Neurosurgery, Stanford University, Stanford, CA, USA
6Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Archana Venkataraman
7Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Subhash Kulkarni
2Center for Neurogastroenterology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: skulkar9@jh.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

Healthy gastrointestinal functions require a healthy Enteric Nervous System (ENS). ENS health is often defined by the presence of normal ENS structure. However, we currently lack a comprehensive understanding of normal ENS structure as current methodologies of manual enumeration of neurons within tissue and ganglia can only parse limited tissue regions; and are prone to error, subjective bias, and peer-to-peer discordance. Thus, there is a need to craft objective methods and robust tools to capture and quantify enteric neurons over a large area of tissue and within multiple ganglia. Here, we report on the development of an AI-driven tool COUNTEN which parses HuC/D-immunolabeled adult murine myenteric ileal plexus tissues to enumerate and classify enteric neurons into ganglia in a rapid, robust, and objective manner. COUNTEN matches trained humans in identifying, enumerating and clustering myenteric neurons into ganglia but takes a fraction of the time, thus allowing for accurate and rapid analyses of a large tissue region. Using COUNTEN, we parsed thousands of myenteric neurons and clustered them in hundreds of myenteric ganglia to compute metrics that help define the normal structure of the adult murine ileal myenteric plexus. We have made COUNTEN freely and openly available to all researchers, to facilitate reproducible, robust, and objective measures of ENS structure across mouse models, experiments, and institutions.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵* Co-first authors

  • ↵§ Co-senior authors

  • https://github.com/KLab-JHU/COUNTEN

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted November 25, 2020.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
COUNTEN – an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
COUNTEN – an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System
Yuta Kobayashi, Alicia Bukowski, Subhamoy Das, Cedric Espenel, Julieta Gomez-Frittelli, Narayani Wagle, Shriya Bakshi, Monalee Saha, Julia A. Kaltschmidt, Archana Venkataraman, Subhash Kulkarni
bioRxiv 2020.11.24.396408; doi: https://doi.org/10.1101/2020.11.24.396408
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
COUNTEN – an AI-driven tool for rapid, and objective structural analyses of the Enteric Nervous System
Yuta Kobayashi, Alicia Bukowski, Subhamoy Das, Cedric Espenel, Julieta Gomez-Frittelli, Narayani Wagle, Shriya Bakshi, Monalee Saha, Julia A. Kaltschmidt, Archana Venkataraman, Subhash Kulkarni
bioRxiv 2020.11.24.396408; doi: https://doi.org/10.1101/2020.11.24.396408

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4838)
  • Biochemistry (10729)
  • Bioengineering (8005)
  • Bioinformatics (27166)
  • Biophysics (13930)
  • Cancer Biology (11079)
  • Cell Biology (15977)
  • Clinical Trials (138)
  • Developmental Biology (8757)
  • Ecology (13228)
  • Epidemiology (2067)
  • Evolutionary Biology (17306)
  • Genetics (11663)
  • Genomics (15877)
  • Immunology (10986)
  • Microbiology (25979)
  • Molecular Biology (10600)
  • Neuroscience (56311)
  • Paleontology (416)
  • Pathology (1727)
  • Pharmacology and Toxicology (2998)
  • Physiology (4528)
  • Plant Biology (9583)
  • Scientific Communication and Education (1610)
  • Synthetic Biology (2668)
  • Systems Biology (6954)
  • Zoology (1507)