Introduction Emerging infectious diseases pose one of the greatest threats to human health and biodiversity. Phylodynamics is an effective tool for inferring epidemiological parameters to guide intervention strategies, particularly for human viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, phylodynamic analysis has historically been limited to the study of rapidly evolving viruses and, in rare cases, bacteria. Nonetheless, application of phylodynamics to nonviral pathogens has immense potential, such as for predicting disease spread and informing the management of wildlife diseases.

We conducted a phylodynamics analysis of devil facial tumor disease (DFTD), a transmissible cancer that has spread across nearly the entire geographic range of Tasmanian devils and threatens the species with extinction. DFTD is transmitted as an allograft through biting during common social interactions, susceptibility is nearly universal, and case fatality rates approach 100%. The goals of our study were to (i) characterize the geographic spread of DFTD, (ii) identify whether there are different circulating tumor lineages, and (iii) quantify rates of transmission among lineages.

Rationale In principle, phylodynamics should be readily extended to the study of slowly evolving pathogens with large genomes through careful interrogation of genes to identify those that are measurably evolving. By testing individual genes for a clocklike signal, these genes may then be used for phylodynamic analysis. We demonstrate this proof of concept in DFTD.

Results We screened >11,000 genes across the DFTD genome, identifying 28 that exhibited a strong, clocklike signal, and performed the first phylodynamic analysis of a genome larger than a bacterium. We demonstrate here, contrary to field observations, that DFTD spread omnidirectionally throughout the epizootic, leaving little signal of geographic structuring of tumor lineages across Tasmania. Despite predictions of devil extinction, we found that the effective reproduction number (R_E), a summary of the rate at which disease spreads, has declined precipitously after the initial epidemic spread of DFTD. Specifically, R_E peaked at a high of ∼3.5 shortly after the discovery of DFTD in 1996 and is now ∼1 in both extant tumor lineages. This is consistent with a shift from emergence to endemism. Except for a single gene, we found little evidence for convergent molecular evolution among tumor lineages.

Conclusion We have demonstrated that phylodynamics can be applied to virtually any pathogen. In doing so, we show that through careful interrogation of the pathogen genome, a measurably evolving set of genes can be identified to characterize epidemiological dynamics of nonviral pathogens with large genomes. By applying this approach to DFTD, we have shown that the disease appears to be transitioning from emergence to endemism. Consistent with recent models, our inference that R_E ∼1 predicts that coexistence between devils and DFTD is a more likely outcome than devil extinction. Therefore, our findings present cautious optimism for the continued survival of the iconic Tasmanian devil but emphasize the need for evolutionarily informed conservation management to ensure their persistence.