A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory.
A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory.
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DOI：
10.3389/fmicb.2018.01165
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发表时间：
2018
影响因子：
5.2
通讯作者：
Molina-París C
中科院分区：
文献类型：
--
作者：
Carruthers J;López-García M;Gillard JJ;Laws TR;Lythe G;Molina-París C
我们提出了图拉氏方济氏菌吞噬细胞内、宿主内和种群水平感染动力学的多尺度模型，扩展了Wood等人提出的机理模型。我们的多尺度模型结合了宿主吞噬细胞和胞外细菌之间相互作用的关键方面，考虑了吞噬细胞破裂时释放的细菌数量在吞噬细胞间的可变性，并允许计算感染个体的应答概率和平均应答时间作为初始感染剂量的函数。贝叶斯方法被应用于使用感染数据对吞噬细胞内和宿主内模型进行参数化。最后，我们展示了如何通过确定性的分区通风模型，在个体水平上使用剂量响应概率来估计图拉氏方济氏菌在室内环境(如微生物实验室)中在种群水平上的空气传播。
We present a multi-scale model of the within-phagocyte, within-host and population-level infection dynamics of Francisella tularensis, which extends the mechanistic one proposed by Wood et al.. Our multi-scale model incorporates key aspects of the interaction between host phagocytes and extracellular bacteria, accounts for inter-phagocyte variability in the number of bacteria released upon phagocyte rupture, and allows one to compute the probability of response, and mean time until response, of an infected individual as a function of the initial infection dose. A Bayesian approach is applied to parameterize both the within-phagocyte and within-host models using infection data. Finally, we show how dose response probabilities at the individual level can be used to estimate the airborne propagation of Francisella tularensis in indoor settings (such as a microbiology laboratory) at the population level, by means of a deterministic zonal ventilation model.