Connecting in-vivo optical imaging with dynamic modelling of host-pathogen interaction during bacterial infection

几乎每个人一生中都至少经历过一次细菌感染。虽然抗生素治疗在大多数情况下可以治愈感染，但细菌会不断发展，并可能对抗生素产生耐药性。这样，新的细菌菌株不断出现，包括在发病率和死亡率方面具有相当大代价的菌株。近年来侵袭性大肠杆菌的多次暴发表明，这些类型的细菌并未完全得到控制。对于这些细菌，我们需要开发适当的治疗方法，这只有在我们了解细菌如何建立感染的情况下才能做到。为了弄清楚细菌感染是如何随着时间的推移在体内进化的，我们应该在活体动物（如老鼠）体内研究这一过程，这可以代表人类疾病的进程。最近，新的成像系统已经开发出来，可以在没有任何侵入性干预的情况下跟踪老鼠体内的细菌。这是通过使用细菌来实现的，细菌发出的光波长大于可见范围，可以穿过几厘米的组织；足以让肠道细菌的光到达动物的表面。也可以在小鼠体内使用荧光探针来观察对小鼠免疫反应很重要的其他细胞。通过这项技术，我们可以看到细菌和免疫细胞在体内的位置，有多少，通过在多个时间点成像，我们也可以跟踪它们的运动。我们在体内定位细胞的精度在毫米量级。为了能够根据小规模感染机制来解释大规模体内图像，我们需要将我们所能观察到的与我们基于其他调查所了解的感染联系起来。这些其他调查包括对不同器官进行详细的死后调查，以显示细菌的确切位置；例如，细菌是否附着在肠壁上，或者它们是否已经移动到肠壁之外。在这个项目中，我们将开发技术和工具，使我们能够将体内图像分析与细胞和分子尺度上可用的生物学知识结合起来。该项目包括用确定性和随机方法对细菌感染的进展进行理论建模，以及在小鼠体内进行生物发光细菌的实验体内成像。建模工作将在理论系统生物学小组内进行，而实验工作将在分子发病机制小组内进行，两者都在帝国理工学院。通过将理论建模与疾病模型的实验研究相结合，我们将能够将理论反馈到实验设计中，并将实验结果反馈到模型的定义中；两者同样重要，以便为感染过程建立良好的机制模型。因此，我们将获得的细菌感染进展模型可以跨空间和时间尺度提供新的见解，并可能有助于确定新的治疗靶点。

Bacterial infections are experienced by almost everyone at least once during their lifetime. Although antibiotic treatments will cure the infection in most cases, bacteria are constantly developing and can become resistant to antibiotics. This way, new strains of bacteria continue to emerge, including strains that have considerable costs in terms of morbidity and mortality. Multiple outbreaks of aggressive forms of E.coli in recent years have demonstrated that these types of bacteria are not completely under control. For these bacteria we need to develop appropriate treatments, which can only be done if we understand how bacteria establish infections.To find out how a bacterial infection evolves in the body over time, we should investigate this process inside living animals, such as mice, that can represent the course of human disease. Recently, new imaging systems have been developed that can track bacteria inside a mouse without any invasive intervention. This is achieved by using bacteria that emit light at a wavelength larger than the visible range, which can travel through several centimetres of tissue; enough for the light of bacteria in the gut to reach the surface of the animal. It is also possible to use a fluorescent probe inside the mouse to visualize other cells that are important for the immune response of the mouse. With this technique we can see where the bacteria and immune cells are in the body, how many there are, and by imaging at multiple time points, we can also follow their movement. The precision with which we can locate cells in the body is of the order of millimetres.In order to be able to interpret the large-scale in-vivo images in terms of the small-scale infection mechanisms, we need to link what we can observe with what we know about the infection based on other investigations. These other investigations include detailed post-mortem investigations of separate organs that show exactly where the bacteria are located; for example, whether bacteria are attached to the wall of the gut, or whether they have moved beyond it.In this project, we will develop techniques and tools that allow us to combine in-vivo image analysis with the available biological knowledge at the cellular and molecular scale. The project includes theoretical modelling of the progress of bacterial infection with deterministic and stochastic methods, as well as experimental in-vivo imaging of bioluminescent bacteria inside a mouse. The modelling work will be performed within the Theoretical Systems Biology group, while the experimental work will be performed within the Molecular Pathogenesis group, both at Imperial College London. By interweaving theoretical modelling with experimental investigation of the disease model, we will be able to feedback theory into experimental design, and experimental results into the definition of the model; both are equally important in order to arrive at good mechanistic models for the infection processes. The model we will thus obtain of the progress of bacterial infection can deliver new insights across spatial and temporal scales and potentially help identify new targets for treatment.