Universality of clonal dynamics poses fundamental limits to identify stem cell self-renewal strategies

Abstract
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Abstract

How adult stem cells maintain self-renewing tissues is in vivo commonly assessed by analysing clonal data from cell lineage tracing assays. To identify strategies of stem cell self-renewal requires that different models of stem cell fate choice predict sufficiently different clonal statistics. Here we show that models of cell fate choice can, in homeostatic tissues, be categorized by exactly two 'universality classes', whereby models of the same class predict, under asymptotic conditions, the same clonal statistics. Those classes relate to generalizations of the canonical asymmetric vs. symmetric stem cell self-renewal strategies and are distinguished by a conservation law. This poses both challenges and opportunities to identify stem cell self-renewal strategies: while under asymptotic conditions, self-renewal models of the same universality class cannot be distinguished by clonal data only, models of different classes can be distinguished by simple means.

Data availability

All numerical data used for figures is produced by programme code, which can be found on Github, under https://github.com/cp4u17/simCellState

The following data sets were generated

1. Cristina Parigini
(2020) simCellState
Github, cp4u17/simCellState.

https://github.com/cp4u17/simCellState

Article and author information

Author details

Cristina Parigini

Mathematical Sciences, University of Southampton, Southampton, United Kingdom

Competing interests
The authors declare that no competing interests exist.
Philip Greulich

Mathematical Sciences, University of Southampton, Southampton, United Kingdom

For correspondence
P.S.Greulich@soton.ac.uk

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-5247-6738

Funding

Medical Research Council (MR/R026610/1)

Philip Greulich

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.