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预测性虚拟真菌感染模型在人全血中的真菌免疫逃逸研究。

Predictive Virtual Infection Modeling of Fungal Immune Evasion in Human Whole Blood.

机构信息

Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute (HKI), Jena, Germany.

Faculty of Biological Sciences, Friedrich Schiller University Jena, Jena, Germany.

出版信息

Front Immunol. 2018 Mar 21;9:560. doi: 10.3389/fimmu.2018.00560. eCollection 2018.

Abstract

Bloodstream infections by the human-pathogenic fungi and increasingly occur in hospitalized patients and are associated with high mortality rates. The early immune response against these fungi in human blood comprises a concerted action of humoral and cellular components of the innate immune system. Upon entering the blood, the majority of fungal cells will be eliminated by innate immune cells, i.e., neutrophils and monocytes. However, recent studies identified a population of fungal cells that can evade the immune response and thereby may disseminate and cause organ dissemination, which is frequently observed during candidemia. In this study, we investigate the so far unresolved mechanism of fungal immune evasion in human whole blood by testing hypotheses with the help of mathematical modeling. We use a previously established state-based virtual infection model for whole-blood infection with to quantify the immune response and identified the fungal immune-evasion mechanism. While this process was assumed to be spontaneous in the previous model, we now hypothesize that the immune-evasion process is mediated by host factors and incorporate such a mechanism in the model. In particular, we propose, based on previous studies that the fungal immune-evasion mechanism could possibly arise through modification of the fungal surface by as of yet unknown proteins that are assumed to be secreted by activated neutrophils. To validate or reject any of the immune-evasion mechanisms, we compared the simulation of both immune-evasion models for different infection scenarios, i.e., infection of whole blood with either or under non-neutropenic and neutropenic conditions. We found that under non-neutropenic conditions, both immune-evasion models fit the experimental data from whole-blood infection with and . However, differences between the immune-evasion models could be observed for the infection outcome under neutropenic conditions with respect to the distribution of fungal cells across the immune cells. Based on these predictions, we suggested specific experimental studies that might allow for the validation or rejection of the proposed immune-evasion mechanism.

摘要

血液感染人类致病性真菌越来越多地发生在住院患者中,并与高死亡率相关。人体血液中针对这些真菌的早期免疫反应包括先天免疫系统的体液和细胞成分的协同作用。进入血液后,大多数真菌细胞将被先天免疫细胞(即中性粒细胞和单核细胞)消除。然而,最近的研究发现了一种能够逃避免疫反应的真菌细胞群体,从而可能传播并导致器官传播,这在念珠菌血症中经常观察到。在这项研究中,我们通过数学建模来测试假设,从而研究目前尚未解决的人类全血中真菌免疫逃避的机制。我们使用先前建立的基于状态的全血感染模型来量化免疫反应,并确定真菌免疫逃避机制。虽然在之前的模型中,这个过程被假设为自发的,但我们现在假设免疫逃避过程是由宿主因素介导的,并将这种机制纳入模型中。特别是,我们基于先前的研究提出,真菌免疫逃避机制可能是通过真菌表面的修饰而产生的,这些修饰可能是由激活的中性粒细胞分泌的未知蛋白引起的。为了验证或拒绝任何一种免疫逃避机制,我们比较了两种免疫逃避模型在不同感染情况下的模拟,即全血感染 和 ,分别在非中性粒细胞减少和中性粒细胞减少的情况下。我们发现,在非中性粒细胞减少的情况下,两种免疫逃避模型都适用于全血感染 的实验数据。然而,在中性粒细胞减少的情况下,对于感染结果,两种免疫逃避模型之间存在差异,这涉及到真菌细胞在免疫细胞中的分布。基于这些预测,我们提出了具体的实验研究,这可能允许验证或拒绝所提出的免疫逃避机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f656/5871695/b1fb8066d407/fimmu-09-00560-g001.jpg

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