Mathematical Modeling of Streptococcus pneumoniae Colonization, Invasive Infection and Treatment.
Mathematical Modeling of Streptococcus pneumoniae Colonization, Invasive Infection and Treatment.
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DOI：
10.3389/fphys.2017.00115
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发表时间：
2017
影响因子：
4
通讯作者：
Tanaka RJ
中科院分区：
文献类型：
--
作者：
Domínguez-Hüttinger E;Boon NJ;Clarke TB;Tanaka RJ
肺炎链球菌（Sp）是一种细菌，通常存在于上呼吸道上皮细胞上而不引起感染。然而，诸如与流感病毒共感染的因素可损害复杂的Sp-宿主相互作用，并随后发展成许多危及生命的感染性和炎性疾病，包括肺炎、脑膜炎甚至败血症。由于新的抗生素耐药性Sp菌株的出现，Sp感染的威胁增加，迫切需要更好的治疗策略，有效地防止由Sp感染引发的疾病进展，最大限度地减少抗生素的使用。宿主-病原体相互作用的复杂性使得对SP触发的发病机制的充分理解成为一个挑战，尽管其在确定有效治疗方法方面至关重要。为了实现复杂的和动态变化的主机SP相互作用的系统水平和定量的理解，在这里，我们开发了一个机械的数学模型，描述SP，免疫细胞和上皮组织之间的动态相互作用，其中主机-病原体相互作用开始。该模型作为一个数学框架，连贯地解释了各种体外和体外研究，模型参数拟合。我们的模型模拟再现了强大的稳态SP-宿主相互作用，以及三种性质不同的致病行为：免疫瘢痕形成，侵入性感染及其组合。模型的参数敏感性和分叉分析确定了负责从健康到这种病理行为的定性转变的过程。我们的模型还预测，侵袭性感染的发作发生在短暂的Sp挑战不到2天。这一预测为使用疫苗接种提供了论据，因为适应性免疫反应不能在如此短的时间内从头发展。我们进一步设计了最佳的治疗策略，最小强度和最短的抗生素持续时间，为我们的模型区分的三种致病行为中的每一种。拟议的数学框架将有助于设计更好的疾病管理策略和新的诊断标志物，可用于为最合适的患者特定治疗方案提供信息。
Streptococcus pneumoniae (Sp) is a commensal bacterium that normally resides on the upper airway epithelium without causing infection. However, factors such as co-infection with influenza virus can impair the complex Sp-host interactions and the subsequent development of many life-threatening infectious and inflammatory diseases, including pneumonia, meningitis or even sepsis. With the increased threat of Sp infection due to the emergence of new antibiotic resistant Sp strains, there is an urgent need for better treatment strategies that effectively prevent progression of disease triggered by Sp infection, minimizing the use of antibiotics. The complexity of the host-pathogen interactions has left the full understanding of underlying mechanisms of Sp-triggered pathogenesis as a challenge, despite its critical importance in the identification of effective treatments. To achieve a systems-level and quantitative understanding of the complex and dynamically-changing host-Sp interactions, here we developed a mechanistic mathematical model describing dynamic interplays between Sp, immune cells, and epithelial tissues, where the host-pathogen interactions initiate. The model serves as a mathematical framework that coherently explains various in vitro and in vitro studies, to which the model parameters were fitted. Our model simulations reproduced the robust homeostatic Sp-host interaction, as well as three qualitatively different pathogenic behaviors: immunological scarring, invasive infection and their combination. Parameter sensitivity and bifurcation analyses of the model identified the processes that are responsible for qualitative transitions from healthy to such pathological behaviors. Our model also predicted that the onset of invasive infection occurs within less than 2 days from transient Sp challenges. This prediction provides arguments in favor of the use of vaccinations, since adaptive immune responses cannot be developed de novo in such a short time. We further designed optimal treatment strategies, with minimal strengths and minimal durations of antibiotics, for each of the three pathogenic behaviors distinguished by our model. The proposed mathematical framework will help to design better disease management strategies and new diagnostic markers that can be used to inform the most appropriate patient-specific treatment options.