A combined modeling framework to break the lethal alliance between influenza and bacterial coinfections

打破流感和细菌合并感染之间致命联盟的组合建模框架

• 批准号: 408736049
• 负责人: Professorin Dr. Dunja Bruder
• 金额: --
• 依托单位: Frankfurt Institute for Advanced Studies (FIAS)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/408736049?language=en
• 关键词: combined; modeling; framework; break; lethal

Influenza A virus (IAV) infection enhances host susceptibility to bacterial pathogens such as Streptococcus pneumoniae, resulting in severe respiratory diseases, high rates of hospitalization and death. Although several aspects of the lethal synergism between IAV / S. pneumoniae coinfections have been explored, a holistic understanding of the synergistic action of viral and bacterial pathogens that is key to the design of effective therapeutic interventions, remains elusive to date. To fill existing knowledge gaps the collaborative research project proposed here will utilize an interdisciplinary approach intertwining mathematical modeling, engineering approaches, and tailored in vivo mouse infection experiments. The major objectives of this project are i) to develop within-host mathematical models to quantify the host regulatory mechanisms being active during IAV infections and to predict and possibly prevent the complications of a severe secondary bacterial infection ii) to create and implement innovative nonlinear observers as an in silico tool to provide better prognosis of infections iii) to clarify the role of interferon-γ released following virus encounter by natural killer cells and CD8+ T cells in impaired alveolar macrophage functions as a potential underlying mechanism for enhanced susceptibility to bacterial coinfection following influenza. The proposed iterative process in which models and engineering tools will be progressively refined based on individually fitted infection experiments, will enable the formulation of more valid hypotheses. Ultimately, we are aiming towards a complete understanding of the processes underlying the synergism between IAV and S. pneumoniae which will be the crucial basis for the development of strategies for treatment and prophylaxis in the future.

甲型流感病毒（IAV）感染增强宿主对细菌病原体如肺炎链球菌的易感性，导致严重的呼吸道疾病、高住院率和死亡率。虽然IAV / S.尽管已经探索了肺炎合并感染的可能性，但迄今为止，对病毒和细菌病原体的协同作用的整体理解仍然是难以捉摸的，这是设计有效治疗干预的关键。为了填补现有的知识空白，这里提出的合作研究项目将利用一种跨学科的方法，交织数学建模，工程方法和量身定制的体内小鼠感染实验。该项目的主要目标是：i）开发宿主内数学模型，以量化IAV感染期间活跃的宿主调节机制，并预测和可能预防严重继发性细菌感染的并发症; ii）创建和实施创新的非线性观测器，作为计算机工具，以提供更好的感染预后; iii）澄清干扰素的作用，在受损的肺泡巨噬细胞中，自然杀伤细胞和CD 8 + T细胞与病毒相遇后释放的γ是流感后细菌合并感染易感性增强的潜在潜在机制。所提出的迭代过程中，模型和工程工具将逐步完善的基础上，个别拟合感染实验，将使制定更有效的假设。最终，我们的目标是全面了解IAV和S之间协同作用的过程。这将是未来治疗和预防策略发展的重要基础。