Modeling early events in Francisella tularensis pathogenesis.

Modeling early events in Francisella tularensis pathogenesis.
复制标题

在弗朗西斯氏菌发病机理中建模早期事件。

DOI:
10.3389/fcimb.2014.00169
复制
发表时间:
2014
影响因子:
5.7
通讯作者:
Molina-París C
Molina-París C
中科院分区:
医学2区
文献类型:
--
作者:
Gillard JJ;Laws TR;Lythe G;Molina-París C

文献摘要

参考文献

被引文献

相似文献

计算模型可以为感染机制提供有价值的见解,并可用作支持医学治疗发展的调查工具。我们开发了一个随机的,在主机内,在BALB/c小鼠的感染过程中的计算模型,吸入暴露于土拉弗朗西斯菌SCHU S4。该模型是机械的,并由少量的实验验证的参数。给定初始剂量,该模型生成的细菌负荷曲线对应于实验产生的曲线,在感染的前48小时内倍增时间约为5小时。感染后的第一个24小时的吞噬体和细胞质中的细菌的平均数的解析近似推导和用于验证的随机模型。在我们对巨噬细胞感染动力学的描述中,每个破裂的巨噬细胞释放的细菌数量是几何分布的随机变量。当与倍增时间结合时,这提供了感染的巨噬细胞破裂并释放其细胞内细菌所需时间的分布。这些分布的均值和方差由具有精确生物学解释的模型参数确定,为免疫和细菌动力学的决定因素提供了新的机制见解。通过该模型获得的对巨噬细胞抑制和激活动力学的见解可用于探索刺激巨噬细胞激活的干预措施的潜在益处。
Computational models can provide valuable insights into the mechanisms of infection and be used as investigative tools to support development of medical treatments. We develop a stochastic, within-host, computational model of the infection process in the BALB/c mouse, following inhalational exposure to Francisella tularensis SCHU S4. The model is mechanistic and governed by a small number of experimentally verifiable parameters. Given an initial dose, the model generates bacterial load profiles corresponding to those produced experimentally, with a doubling time of approximately 5 h during the first 48 h of infection. Analytical approximations for the mean number of bacteria in phagosomes and cytosols for the first 24 h post-infection are derived and used to verify the stochastic model. In our description of the dynamics of macrophage infection, the number of bacteria released per rupturing macrophage is a geometrically-distributed random variable. When combined with doubling time, this provides a distribution for the time taken for infected macrophages to rupture and release their intracellular bacteria. The mean and variance of these distributions are determined by model parameters with a precise biological interpretation, providing new mechanistic insights into the determinants of immune and bacterial kinetics. Insights into the dynamics of macrophage suppression and activation gained by the model can be used to explore the potential benefits of interventions that stimulate macrophage activation.
DOI: 10.1016/j.jtbi.2011.03.022
发表时间: 2011-07-07
影响因子: 2
作者:
Marino, Simeone;El-Kebir, Mohammed;Kirschner, Denise
通讯作者: Kirschner, Denise
DOI: 10.1073/pnas.0904846106
发表时间: 2009-07-07
影响因子: 11.1
作者:
Day, Judy;Friedman, Avner;Schlesinger, Larry S.
通讯作者: Schlesinger, Larry S.
DOI: 10.1128/iai.71.10.5940-5950.2003
发表时间: 2003-10-01
影响因子: 3.1
作者:
Golovliov, I;Baranov, V;Sjöstedt, A
通讯作者: Sjöstedt, A
DOI: 10.1089/bsp.2013.0067
发表时间: 2014-02-01
期刊: BIOSECURITY AND BIOTERRORISM-BIODEFENSE STRATEGY PRACTICE AND SCIENCE
影响因子: --
作者:
Gutting, Bradford
通讯作者: Gutting, Bradford
DOI: 10.1371/journal.ppat.1003114
发表时间: 2013-01
期刊: PLoS pathogens
影响因子: 6.7
作者:
Dai S;Rajaram MV;Curry HM;Leander R;Schlesinger LS
通讯作者: Schlesinger LS