Neutral competition explains the clonal composition of neural organoids.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
22 Apr 2024
Historique:
received: 09 10 2023
accepted: 03 04 2024
medline: 23 4 2024
pubmed: 23 4 2024
entrez: 22 4 2024
Statut: aheadofprint

Résumé

Neural organoids model the development of the human brain and are an indispensable tool for studying neurodevelopment. Whole-organoid lineage tracing has revealed the number of progenies arising from each initial stem cell to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This high variability exceeds what can be explained by existing stochastic models of corticogenesis and indicates the existence of an additional source of stochasticity. To explain this variability, we introduce the SAN model which distinguishes Symmetrically diving, Asymmetrically dividing, and Non-proliferating cells. In the SAN model, the additional source of stochasticity is the survival time of a lineage's pool of symmetrically dividing cells. These survival times result from neutral competition within the sub-population of all symmetrically dividing cells. We demonstrate that our model explains the experimentally observed variability of lineage sizes and derive the quantitative relationship between survival time and lineage size. We also show that our model implies the existence of a regulatory mechanism which keeps the size of the symmetrically dividing cell population constant. Our results provide quantitative insight into the clonal composition of neural organoids and how it arises. This is relevant for many applications of neural organoids, and similar processes may occur in other developing tissues both in vitro and in vivo.

Identifiants

pubmed: 38648250
doi: 10.1371/journal.pcbi.1012054
pii: PCOMPBIOL-D-23-01614
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012054

Informations de copyright

Copyright: © 2024 Pflug 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.

Déclaration de conflit d'intérêts

I have read the journal’s policy and the authors of this manuscript have the following competing interests: J.A.K. is on the supervisory and scientific advisory board of a:head bio AG (https://aheadbio.com) and is an inventor on several patents relating to cerebral organoids.

Auteurs

Florian G Pflug (FG)

Biological Complexity Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Onna, Okinawa, Japan.
Center for Integrative Bioinformatics Vienna (CIBIV), Max Perutz Labs, University of Vienna and Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria.

Simon Haendeler (S)

Center for Integrative Bioinformatics Vienna (CIBIV), Max Perutz Labs, University of Vienna and Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria.
Vienna Biocenter (VBC) PhD Program, a Doctoral School of the University of Vienna and the Medical University of Vienna, Vienna, Austria.

Christopher Esk (C)

Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Vienna BioCenter (VBC), Vienna, Austria.
Institute of Molecular Biology, University of Innsbruck, Innsbruck, Austria.

Dominik Lindenhofer (D)

Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Vienna BioCenter (VBC), Vienna, Austria.
Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.

Jürgen A Knoblich (JA)

Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Vienna BioCenter (VBC), Vienna, Austria.
Department of Neurology, Medical University of Vienna, Vienna, Austria.

Arndt von Haeseler (A)

Center for Integrative Bioinformatics Vienna (CIBIV), Max Perutz Labs, University of Vienna and Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria.
Faculty of Computer Science Bioinformatics and Computational Biology, University of Vienna, Vienna, Austria.

Classifications MeSH