Statistical modelling of in vivo immune response dynamics in zebrafish to multiple stimuli

斑马鱼对多种刺激的体内免疫反应动态的统计模型

• 批准号: BB/K017284/1
• 负责人: Michael Stumpf
• 金额: $ 39.37万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FK017284%2F1
• 关键词: Statistical; modelling; vivo; immune; response

Zebrafish embryos are optically transparent and allow us to visualize biological processes in real time. Here we will study how the innate immune response deals with different threats to the fish's health. In particular we will study the response to wounding and to cancer in the fish. In both cases cells of the immune response system are drawn to the wound site or the location of the tumor/cancer cell and determining the precise way in which this is achieved is one of the fundamental aims of our research. We will use a combination of microscopy and mathematical modelling in order to understand how the immune system senses and responds to such stimuli. We will reconstruct mechanistic models that capture how cells react and reach decisions from the observed data. To this end we will also develop new statistical and computational tools. These will allow us to analyze the complex data generated over the course of this project. We are very interested in how cells make decisions and how we can guide such behaviour. To this end we will also selectively interfere with and probe molecular interaction networks that affect directly how the immune cells respond to stimuli and move towards their target.Mathematical models will, crucially, also allow us to assess how the immune response is regulated if it receives more than one stimulus. This is a completely unsolved problem but one of great fundamental and biomedical importance: for example surgery is still one of the important therapeutic approaches against many cancers and our initial analyses have shown that wounding (surgery) and cancer affect cells of the innate immune response differently. More generally, this research will develop a platform that can be applied also in other contexts, where we want to analyze biological processes inside living organisms. Such investigations will benefit greatly from the statistical, computational and image analysis tools and protocols that are developed as part of this research.

斑马鱼胚胎是光学透明的，使我们能够在真实的时间可视化生物过程。在这里，我们将研究先天免疫反应如何应对鱼类健康的不同威胁。特别是我们将研究鱼对创伤和癌症的反应。在这两种情况下，免疫应答系统的细胞被吸引到伤口部位或肿瘤/癌细胞的位置，确定实现这一点的精确方式是我们研究的基本目标之一。我们将使用显微镜和数学建模的组合，以了解免疫系统如何感知和响应这些刺激。我们将重建机械模型，捕捉细胞如何反应，并根据观察到的数据做出决定。为此，我们还将开发新的统计和计算工具。这些将使我们能够分析在该项目过程中生成的复杂数据。我们对细胞如何做出决定以及我们如何引导这种行为非常感兴趣。为此，我们还将选择性地干扰和探测直接影响免疫细胞如何对刺激做出反应并向其目标移动的分子相互作用网络。至关重要的是，数学模型还将使我们能够评估免疫反应在接受多个刺激时是如何调节的。这是一个完全未解决的问题，但具有重要的基础和生物医学意义：例如，手术仍然是对抗许多癌症的重要治疗方法之一，我们的初步分析表明，创伤（手术）和癌症对先天免疫反应细胞的影响不同。更一般地说，这项研究将开发一个平台，也可以应用于其他情况下，我们希望分析生物体内的生物过程。这种调查将大大受益于统计，计算和图像分析工具和协议，开发作为本研究的一部分。

项目成果

Accurate Reconstruction of Cell and Particle Tracks from 3D Live Imaging Data.

• DOI: 10.1016/j.cels.2016.06.002
• 发表时间: 2016-07
• 期刊: Cell systems
• 影响因子: 9.3
• 作者: Liepe J;Sim A;Weavers H;Ward L;Martin P;Stumpf MP
• 通讯作者: Stumpf MP

Model of Host-Pathogen Interaction Dynamics Links In Vivo Optical Imaging and Immune Responses.

• DOI: 10.1128/iai.00606-16
• 发表时间: 2017-01
• 期刊: Infection and immunity
• 影响因子: 3.1
• 作者: Ale A;Crepin VF;Collins JW;Constantinou N;Habibzay M;Babtie AC;Frankel G;Stumpf MPH
• 通讯作者: Stumpf MPH

Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection.

单细胞表型分析揭示了感染后造血干细胞的异质性。

• DOI: 10.1002/stem.2692
• 发表时间: 2017
• 期刊: Stem cells (Dayton, Ohio)
• 作者: MacLean AL

Goldstein-Kac telegraph processes with random speeds: Path probabilities, likelihoods, and reported Lévy flights.

Goldstein-Kac 电报以随机速度进行处理：路径概率、可能性和报告的 Lévy 航班。

• DOI: 10.1103/physreve.91.042115
• 发表时间: 2015
• 期刊: Physical review. E, Statistical, nonlinear, and soft matter physics
• 作者: Sim A