Emergence, transmission and evolution of Tasmanian devil facial tumor disease

由于新发传染病对人类、野生动物和农业健康的影响，它们被认为是21世纪环境科学的一个重大挑战。传染病现在被列为物种灭绝的第六大原因，EID导致了标志性的塔斯马尼亚魔鬼的濒危。在塔斯马尼亚，一种叫做塔斯马尼亚魔鬼面部肿瘤病的传染性癌症正在摧毁魔鬼的数量。虽然只有少数传染性癌症被记录在案，但这种癌症与人类癌症有共同的特性。本研究将调查传播如何与接触者异质性以及宿主和/和/或群体内肿瘤的基因组变异相关。基因研究可能揭示魔鬼面部肿瘤寿命的潜在原因，可能为人类癌症复发提供信息。此外，对魔鬼的广泛背景研究，包括死亡前后的数千个样本，为研究整个物种中感染因子及其宿主的基因组相互作用提供了难得的机会。范围内。这些基因组研究将揭示魔鬼对肿瘤相对易感性的遗传基础，从而允许管理者为圈养繁殖计划选择最佳个体。此外，对过去肿瘤扩散的速率和方向的了解使得预测未来感染的精确位置具有独特的能力。反过来，魔鬼接触网络模型和预计受感染人群的基因组研究将有助于检验关于新人群中流行病进程的预测。这些知识可能有助于制定应对未来人类流行病的对策。

Emerging infectious diseases (EIDs) are considered a grand challenge in the environmental sciences for the 21st century because of their effects on human, wildlife and agricultural health. Infectious diseases are now listed as the sixth leading cause of species extinctions, and an EID has caused the endangerment of the iconic Tasmanian devil. Across Tasmania, devil populations are being decimated by an infectious cancer called Tasmanian devil facial tumor disease. Although only a few infectious cancers are documented, this cancer shares properties with human cancers. This study will investigate how transmission is related to heterogeneity in contacts and genomic variation in host and/and or tumor within populations. Genetic studies may reveal underlying causes of devil facial tumor longevity, perhaps providing information on cancer recurrence in humans. Further, extensive background research on devils, including thousands of samples before and after die-offs, affords the rare opportunity to study genomic interactions of an infectious agent and its host across an entire species? range. These genomic studies will shed light on the genetic basis of relative susceptibility of devils to the tumor, thereby allowing managers to choose the best individuals for captive breeding programs. In addition, knowledge of rates and direction of past tumor spread enables the unique ability to predict the precise location of future infections. In turn, devil contact network modeling and genomic studies of populations expected to become infected will facilitate the testing of predictions regarding the course of epidemics in new populations. This knowledge may help in developing responses to future human epidemics.