Rodriguez-Gonzalez Rogelio A, Balacheff Quentin, Debarbieux Laurent, Marchi Jacopo, Weitz Joshua S
Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, Atlanta, Georgia, USA.
School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA.
bioRxiv. 2024 Jan 31:2024.01.31.578251. doi: 10.1101/2024.01.31.578251.
Infections caused by multi-drug resistant (MDR) pathogenic bacteria are a global health threat. Phage therapy, which uses phage to kill bacterial pathogens, is increasingly used to treat patients infected by MDR bacteria. However, the therapeutic outcome of phage therapy may be limited by the emergence of phage resistance during treatment and/or by physical constraints that impede phage-bacteria interactions . In this work, we evaluate the role of lung spatial structure on the efficacy of phage therapy for infection. To do so, we developed a spatially structured metapopulation network model based on the geometry of the bronchial tree, and included the emergence of phage-resistant bacterial mutants and host innate immune responses. We model the ecological interactions between bacteria, phage, and the host innate immune system at the airway (node) level. The model predicts the synergistic elimination of a infection due to the combined effects of phage and neutrophils given sufficiently active immune states and suitable phage life history traits. Moreover, the metapopulation model simulations predict that local MDR pathogens are cleared faster at distal nodes of the bronchial tree. Notably, image analysis of lung tissue time series from wild-type and lymphocyte-depleted mice (n=13) revealed a concordant, statistically significant pattern: infection intensity cleared in the bottom before the top of the lungs. Overall, the combined use of simulations and image analysis of experiments further supports the use of phage therapy for treating acute lung infections caused by while highlighting potential limits to therapy given a spatially structured environment, such as impaired innate immune responses and low phage efficacy.
多重耐药（MDR）病原菌引起的感染是全球健康威胁。噬菌体疗法利用噬菌体杀死细菌病原体，越来越多地用于治疗耐多药细菌感染的患者。然而，噬菌体疗法的治疗效果可能受到治疗期间噬菌体耐药性的出现和/或阻碍噬菌体与细菌相互作用的物理限制的影响。在这项工作中，我们评估了肺空间结构对噬菌体治疗感染效果的作用。为此，我们基于支气管树的几何结构开发了一个空间结构化的集合种群网络模型，并纳入了噬菌体抗性细菌突变体的出现和宿主先天免疫反应。我们在气道（节点）水平上模拟细菌、噬菌体和宿主先天免疫系统之间的生态相互作用。该模型预测，在免疫状态足够活跃且噬菌体具有合适的生活史特征的情况下，由于噬菌体和中性粒细胞的联合作用，可协同消除感染。此外，集合种群模型模拟预测，局部耐多药病原体在支气管树的远端节点清除得更快。值得注意的是，对野生型和淋巴细胞耗竭小鼠（n = 13）的肺组织时间序列进行的图像分析揭示了一种一致的、具有统计学意义的模式：肺部底部的感染强度在顶部之前清除。总体而言，模拟和实验图像分析的结合进一步支持了噬菌体疗法用于治疗由引起的急性肺部感染，同时突出了在空间结构化环境中治疗的潜在局限性，如先天免疫反应受损和噬菌体疗效低下。
