In-silico and in-vitro morphometric analysis of intestinal organoids

Sandra Montes Olivas, Danny N Legge, Abbie Lund, Alexander G. Fletcher, Ann C Williams, Lucia Marucci*, Martin E Homer*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)

Abstract

Organoids offer a powerful model to study cellular self-organisation, the growth of specific tissue morphologies in-vitro, and to assess potential medical therapies. However, the intrinsic mechanisms of these systems are not entirely understood yet, which can result in variability of organoids due to differences in culture conditions and basement membrane extracts used. Improving the standardisation of organoid cultures is essential for their implementation in clinical protocols. Developing tools to assess and predict the behaviour of these systems may produce a more robust and standardised biological model to perform accurate clinical studies. Here, we developed an algorithm to automate crypt-like structure counting on intestinal organoids in both in-vitro and in-silico images. In addition, we modified an existing two-dimensional agent-based
mathematical model of intestinal organoids to better describe the system physiology, and evaluated its ability to replicate budding structures compared to new experimental data we generated. The crypt-counting algorithm proved useful in approximating the average budding structures found in our in-vitro intestinal organoid culture images on days 3 and 7 after seeding. Our changes to the in-silico model maintain the potential to produce simulations that replicate the number of budding structures found on days 5 and 7 of in-vitro data. The present study aims to aid in quantifying key morphological structures and provide a method to compare both in-vitro and in-silico experiments. Our results could be extended later to 3D in-silico models.
Original languageEnglish
Article numbere1011386
JournalPLoS Computational Biology
Volume19
Issue number8
DOIs
Publication statusPublished - 14 Aug 2023

Bibliographical note

Funding Information:
This work was funded through the UK’s Biotechnology and Biological Sciences Research Council (BB/R016925/1 to A.G.F., and BrisSynBio BB/L01386X/1 to L.M), the UK’s Engineering and Physical Sciences Research Council (EP/W024144/ 1 to A.G.F., and EP/S01876X/1 to L.M.), and the Mexico Consejo Nacional de Ciencia y Tecnología (CONACYT) PhD scholarship provided to S.M-O. The EP/S01876X/1 fund covered parts of the salary for L.M. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors gratefully acknowledge the expertise provided by Dr Dominic Alibhai and Mr Adam Chambers from the Wolfson Bioimaging Facility, University of Bristol in the development of the initial custom code for image analysis. The authors also thank Dr Thomas Gorochowski and Dr Christopher Parker for their insightful comments and discussions throughout this work.

Publisher Copyright:
© 2023 Montes-Olivas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Structured keywords

  • BrisSynBio
  • Bristol BioDesign Institute
  • BrisEngBio
  • Engineering Mathematics Research Group

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