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In vitro competition between two transmissible cancers and potential implications for their host, the Tasmanian devil

Version 4 2024-11-29, 05:08
Version 3 2024-06-20, 00:16
Version 2 2024-06-03, 03:31
Version 1 2024-03-19, 22:17
journal contribution
posted on 2024-11-29, 05:08 authored by Anne-Lise GerardAnne-Lise Gerard, Rachel S Owen, Antoine DujonAntoine Dujon, Benjamin Roche, Rodrigo Hamede, Frédéric Thomas, Beata UjvariBeata Ujvari, Hannah V Siddle
AbstractSince the emergence of a transmissible cancer, devil facial tumour disease (DFT1), in the 1980s, wild Tasmanian devil populations have been in decline. In 2016, a second, independently evolved transmissible cancer (DFT2) was discovered raising concerns for survival of the host species. Here, we applied experimental and modelling frameworks to examine competition dynamics between the two transmissible cancers in vitro. Using representative cell lines for DFT1 and DFT2, we have found that in monoculture, DFT2 grows twice as fast as DFT1 but reaches lower maximum cell densities. Using co‐cultures, we demonstrate that DFT2 outcompetes DFT1: the number of DFT1 cells decreasing over time, never reaching exponential growth. This phenomenon could not be replicated when cells were grown separated by a semi‐permeable membrane, consistent with exertion of mechanical stress on DFT1 cells by DFT2. A logistic model and a Lotka–Volterra competition model were used to interrogate monoculture and co‐culture growth curves, respectively, suggesting DFT2 is a better competitor than DFT1, but also showing that competition outcomes might depend on the initial number of cells, at least in the laboratory. We provide theories how the in vitro results could be translated to observations in the wild and propose that these results may indicate that although DFT2 is currently in a smaller geographic area than DFT1, it could have the potential to outcompete DFT1. Furthermore, we provide a framework for improving the parameterization of epidemiological models applied to these cancer lineages, which will inform future disease management.

History

Journal

Evolutionary Applications

Volume

17

Article number

e13670

Pagination

1-12

Location

London, Eng.

ISSN

1752-4571

eISSN

1752-4571

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Issue

3

Publisher

Wiley Open Access