SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent
SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent
复制标题
DOI：
10.1371/journal.pcbi.1005130
复制
发表时间：
2016-09-01
影响因子：
4.3
通讯作者：
Wilson, Daniel J.
中科院分区：
文献类型：
--
作者：
De Maio, Nicola;Wu, Chieh-Hsi;Wilson, Daniel J.
利用病原体基因组重建传播是抗击传染病的有力工具。然而，他们的解释依赖于一些简化的假设，经常忽略重要的复杂性的真实的数据，特别是在主机内的演变和非抽样患者。在这里，我们提出了一种新的方法来传输推理称为SCOTTI（结构化合并传输树推理）。该方法基于一个统计框架，该框架将每个主机建模为不同的种群，并将主机之间的传输建模为迁移事件。我们的计算效率实现这个模型，使主机到主机传输的推断，同时容纳内主机的演变和非采样主机。SCOTTI是作为系统发育软件BEAST 2的开源软件包分发的。我们表明，SCOTTI通常可以推断传输事件，即使在存在相当大的主机内的变化，可以占与可能存在的非采样主机的不确定性，并可以有效地使用来自同一主机的多个样本的数据，虽然有一些减少的准确性时，收集的样本非常接近感染时间。我们通过调查英国口蹄疫病毒（FMDV）兽医疫情和尼泊尔新生儿肺炎克雷伯菌疫情的遗传和流行病学数据，说明了我们方法的特点。传播史推断与SCOTTI将是重要的，在制定有效的措施，以防止和停止传输。
Exploiting pathogen genomes to reconstruct transmission represents a powerful tool in the fight against infectious disease. However, their interpretation rests on a number of simplifying assumptions that regularly ignore important complexities of real data, in particular within-host evolution and non-sampled patients. Here we propose a new approach to transmission inference called SCOTTI (Structured COalescent Transmission Tree Inference). This method is based on a statistical framework that models each host as a distinct population, and transmissions between hosts as migration events. Our computationally efficient implementation of this model enables the inference of host-to-host transmission while accommodating within-host evolution and non-sampled hosts. SCOTTI is distributed as an open source package for the phylogenetic software BEAST2. We show that SCOTTI can generally infer transmission events even in the presence of considerable within-host variation, can account for the uncertainty associated with the possible presence of non-sampled hosts, and can efficiently use data from multiple samples of the same host, although there is some reduction in accuracy when samples are collected very close to the infection time. We illustrate the features of our approach by investigating transmission from genetic and epidemiological data in a Foot and Mouth Disease Virus (FMDV) veterinary outbreak in England and a Klebsiella pneumoniae outbreak in a Nepali neonatal unit. Transmission histories inferred with SCOTTI will be important in devising effective measures to prevent and halt transmission.