The devil is in the details: Genomics of transmissible cancers in Tasmanian devils

Cancer poses one of the greatest human health threats of our time. Fortunately, aside from a few rare cases of cancer transmission in immune-suppressed organ transplant recipients or a small number of transmission events from mother to fetus, cancers are not spread from human to human. However, transmissible cancers have been detected in vertebrate and invertebrate animals, sometimes with devastating effects. Four examples of transmissible cancers are now known: 1) canine transmissible venereal tumor (CTVT) in dogs, 2) a tumor in a laboratory population of Syrian hamsters that is no longer cultured, 3) infectious neoplasias in at least four species of bivalve mollusks, and 4) two independently derived transmissible cancers (devil facial tumor disease [DFTD]) in Tasmanian devils (Fig 1A and 1B). The etiologic agents of CTVT, the bivalve cancers, and DFTDare the transplants (allografts) of the neoplastic cells themselves, but the etiologic agent is unknown for the hamster tumor.The effects of these transmissible cancers on their respective host populations vary. CTVT is spread in dogs through sexual contact and is at least 11,000 years old, placing the timing of its origin close to that of the domestication of dogs. Although genomic analyses of the tumor suggest evasion of multiple components of the dog immune system, dogs most commonly survive and often show evidence of spontaneous tumor regression within a year of initial diagnosis. For the infectious bivalve neoplasias, which have existed for at least 40 years, population effects vary from enzootic infections with no noticeable effects on population sizes to evidence of a catastrophic population decline. In Tasmanian devils (Fig 1A), the first infectious tumor discovered (DFT1; Fig 1B) has spread across approximately 95% of the geographic range of Tasmanian devils since 1996 (Fig 1C). DFTD is almost always fatal (Fig 1B), with >90% declines in infected localities and an overall species-wide decline exceeding 80%. Transmission dynamics appear consistent with frequency dependence, with DFTD spread by biting during social interactions, resulting in predictions of extinction from standard epidemiological models. Despite these predictions, long-infected devil populations persist at reduced densities, suggesting that individual-level variability in fecundity and tumor growth rate in infected individuals are key for understanding epidemiological dynamics. Additionally, the origin of the second, independent lineage of DFTD (i.e., DFT2) within 20 years of the discovery of DFT1 suggests that transmissible cancers may be a recurring part of the Tasmanian devils' evolutionary history, without causing extinction

Evaluating the Influence of Epidemiological Parameters and Host Ecology on the Spread of Phocine Distemper Virus through Populations of Harbour Seals

Catriona Harris was supported by a grant from the UK Natural Environment Research Council. The funders had no role in study design, data collections and analysis, decision to publish, or preparation of the manuscript.Background: Outbreaks of phocine distemper virus (PDV) in Europe during 1988 and 2002 were responsible for the death of around 23,000 and 30,000 harbour seals, respectively. These epidemics, particularly the one in 2002, provided an unusual opportunity to estimate epidemic parameters for a wildlife disease. There were marked regional differences in the values of some parameters both within and between epidemics. Methodology and Principal Findings: We used an individual-based model of seal movement that allowed us to incorporate realistic representations of space, time and animal behaviour into a traditional epidemiological modelling framework. We explored the potential influence of a range of ecological (foraging trip duration, time of epidemic onset, population size) and epidemiological (length of infectious period, contact rate between infectious and susceptible individuals, case mortality) parameters on four readily-measurable epidemic characteristics (number of dead individuals, duration of epidemic, peak mortality date and prevalence) and on the probability that an epidemic would occur in a particular region. We analysed the outputs as if they were the results of a series of virtual experiments, using Generalised Linear Modelling. All six variables had a significant effect on the probability that an epidemic would be recognised as an unusual mortality event by human observers. Conclusions: Regional and temporal variation in contact rate was the most likely cause of the observed differences between the two epidemics. This variation could be a consequence of differences in the way individuals divide their time between land and sea at different times of the year.Publisher PDFPeer reviewe

Structural Perturbations to Population Skeletons: Transient Dynamics, Coexistence of Attractors and the Rarity of Chaos

Simple models of insect populations with non-overlapping generations have been instrumental in understanding the mechanisms behind population cycles, including wild (chaotic) fluctuations. The presence of deterministic chaos in natural populations, however, has never been unequivocally accepted. Recently, it has been proposed that the application of chaos control theory can be useful in unravelling the complexity observed in real population data. This approach is based on structural perturbations to simple population models (population skeletons). The mechanism behind such perturbations to control chaotic dynamics thus far is model dependent and constant (in size and direction) through time. In addition, the outcome of such structurally perturbed models is [almost] always equilibrium type, which fails to commensurate with the patterns observed in population data.We present a proportional feedback mechanism that is independent of model formulation and capable of perturbing population skeletons in an evolutionary way, as opposed to requiring constant feedbacks. We observe the same repertoire of patterns, from equilibrium states to non-chaotic aperiodic oscillations to chaotic behaviour, across different population models, in agreement with observations in real population data. Model outputs also indicate the existence of multiple attractors in some parameter regimes and this coexistence is found to depend on initial population densities or the duration of transient dynamics. Our results suggest that such a feedback mechanism may enable a better understanding of the regulatory processes in natural populations

Tasmanian devil facial tumour disease: lessons for conservation biology

Tasmanian devil facial tumour disease is an infectious cancer that threatens the largest surviving marsupial carnivore with extinction. After emerging in 1996, it has spread across most of the range of the species, leading to a population decline of more than 60%. This bizarre disease, in which the cancer cells themselves are the infective agent, illustrates some important general principles about disease and conservation biology, including the threat posed by loss of genetic diversity and the potential of pathogens with frequency-dependent transmission to cause extinction

Six degrees of Apodemus separation

The yellow-necked mouse (Apodemus flavicollis) has been the subject of many studies examining parasite–host systems. Perkins et al. (2009) used ecological monitoring (radio-tracking and capture–mark–recapture) and graph theory to construct a contact network of the population to explain potential disease transmission dynamics. Social network analysis has been widely used to help understand the transmission of human diseases. Its application to wildlife disease is very much in its infancy, largely because of the difficulty of recording contacts between wild animals. Sarah Perkins et al. have constructed contact networks for yellow-necked mice (Apodemus flavicollis) in the Italian Alps, comparing networks derived from radio-tracking and mark–recapture data. They found that the method producing the most informative data depended on population density. However, all networks had aggregated contact distributions, which is important for understanding disease transmission

Disease and connectivity

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