Joint estimation of epidemiological and genetic processes for Mycobacterium bovis transmission dynamics in cattle and badgers

对于能够在多个宿主物种中持续存在的病原体，控制和根除传染病可能是困难的。牛结核病（bTB）就是这种情况，这种疾病主要影响牛，但也存在于一些野生动物物种中;在英国和爱尔兰，其中最重要的是欧亚獾（Meles meles）。虽然爱尔兰的牛一直存在bTB问题，但到20世纪70年代，bTB几乎已从英国根除，但自那时以来，bTB一直是牛中戏剧性地重新出现的疾病。BTB是一种对人类和动物健康都有影响的人畜共患病，尽管在英国和爱尔兰这两种疾病的慢性病例很少。控制bTB也给个体农民、农业和政府带来了严重的压力，预计未来十年仅英格兰和威尔士的成本就超过10亿英镑。虽然长期以来一直怀疑獾参与其中，但迄今为止的研究工作尚未确定獾在多大程度上负责消除牛的bTB，并且这个话题是巨大的社会和政治争议的主题。过去几十年流行病学最重要的发展之一是越来越多地使用“基因指纹”来识别疾病传播模式。直到最近，这在很大程度上是使用基因组中的少数选定区域完成的。虽然这种“基因指纹”非常有用，并表明同一地区的牛和獾通常感染相同的bTB菌株，但指纹远非唯一：许多牛和许多獾共享同一类型，因此无法确定谁感染了谁。在这个项目中，我们将利用新的技术，使其可行和负担得起的测序整个M。牛的基因组进行大量的样本。由于这种细菌在复制其基因组时偶尔会出错，因此新的突变不断出现，使用传统的指纹识别方法看不到，但新技术创造了一个更加独特和歧视性的遗传指纹。使用几十年来从英国和北方爱尔兰的牛和獾中收集的样本，我们将对数百个分离株的基因组进行测序，以从基因上追踪病原体的传播，并测试它是否主要存在于牛、獾或两者中。本提案中利用的独特机会是牛和獾感染的非常密集的采样以及个体牛的整个生活史的可用性，包括迁移到其他农场以及是否在其生命的某个时间点感染了bTB。这创造了一个特殊的资源，使我们能够将我们对牛之间和牛群之间接触的非常详细的了解与遗传指纹信息进行比较。基于这些信息，我们将使用与统计推断方法直接相关的数学模型来模拟感染如何在英国和爱尔兰的牛群中传播，以及在此过程中如何发生遗传变化。这将在关于多种可能的感染来源和机制的各种不同假设下进行。通过将我们的模拟结果与实际观察结果（例如受感染牛的数量和它们携带的bTB类型等）进行比较，我们将获得对疾病传播的驱动因素以及可能阻止其当前控制的因素的前所未有的洞察力。

The control and eradication of infectious diseases can be difficult for pathogens that are able to persist in multiple host species. This is the case for bovine tuberculosis (bTB), a disease primarily affecting cattle but also found in a number of wildlife species; in Britain and Ireland, the most important of these is the Eurasian badger (Meles meles). While Ireland has had a persistent bTB problem in cattle, by the 1970's bTB had been almost eradicated from Great Britain but since then the has been a dramatically re-emerging disease in cattle. BTB is a zoonosis with implications for both human and animal health, though chronic cases of either in Britain and Ireland are few. Control of bTB also places a severe strain on individual farmers, the farming industry and government, with a projected cost in England and Wales alone of over £1bn over the next decade. While it has long been suspected that badgers are involved, research efforts to date have not determined the extent to which badgers are responsible for eradicating bTB from cattle, and this topic is the subject of great social and political controversy. One of the most important developments in epidemiology of the last few decades has been the increased use of 'genetic fingerprinting' to identify patterns of disease spread. Until recently, this has largely been done using only a small number of selected regions in the genome. While this kind of "genetic fingerprinting" has been very useful and shows that cattle and badgers in the same region are usually infected by the same bTB strain, the fingerprints are far from unique: many cattle and many badgers share the same type, making it impossible to determine who infected whom. In this project, we will take advantage of novel technology making it feasible and affordable to sequence the entire M. bovis genome for large numbers of samples. Because the bacterium occasionally makes mistakes while replicating its genome, new mutations constantly arise not seen using traditional fingerprinting methods but with the new technology creating a much more unique and discriminatory genetic fingerprint of transmission. Using samples collected over decades from cattle and badgers in Great Britain and Northern Ireland, we will sequence the genomes of hundreds of isolates to genetically track the spread of the pathogen and to test whether it is predominantly maintained in cattle, in badgers, or both. The unique opportunity exploited in this proposal is the availability of extraordinarily dense sampling of cattle and badgers infection together with entire life histories of individual cattle, including movement to other farms and whether it became infected with bTB at some point of its life. This creates an exceptional resource, allowing us to compare our very detailed understanding of contacts between cattle and between herds with the genetic fingerprint information. Based on this information, we will use mathematical models linked directly to statistical inference methods to simulate how the infection may have spread through cattle populations in Britain and Ireland and how it may have genetically changed in the process. This will be done under various different assumptions about the multiple possible sources and mechanisms of infection. By comparing our simulated results to the actual observations (e.g. the number of infected cattle and the type of bTB they carry, etc), we will gain unprecedented insight into the drivers for the spread of the disease and what may prevent its current control.