The tumour is in the detail: Local phylogenetic, population and epidemiological dynamics of a transmissible cancer in Tasmanian devils

Authors: Rodrigo Hamede, Nicholas M. Fountain-Jones, Fernando Arce, Menna Jones, Andrew Storfer, Paul A. Hohenlohe, Hamish McCallum, Benjamin Roche, Beata Ujvari, Frédéric Thomas

Source: Evolutionary Applications (Jun 2023)

Abstract

Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies.

Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size.

However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection.

Our results support the view that evolutionary processes and epidemiological trade-offs can drive host-pathogen coexistence, even when disease-induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long-term epidemic dynamics and evaluating disease control strategies.

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