A systems biology approach to understanding and combating Clostridium difficile infection.

艰难梭菌每年在英国通过医疗保健相关感染导致数千人死亡。对医疗保健系统的影响是巨大的，并将由于高毒力和耐药性菌株的日益流行而恶化。迫切需要开发新的治疗方法来解决C。因此存在艰难感染。C.艰难梭菌感染由复杂的基因网络控制，该基因网络检测成功感染的最佳条件，从而调节毒素的产生和相关机制的启动。这种非线性网络的复杂性，无法通过单一学科来理解。该奖学金将为将要进行的关键实验工作提供必要的微生物学培训，并与这些网络的计算模型相结合，彻底增强我们对C的理解。将实现艰难感染。至关重要的是，这些模型将捕获传统和新型疗法（后者直接针对毒素产生），从而能够根据这些疗法的相对有效性产生假设，并根据所需剂量进行估计。因此，这种跨学科的方法有可能改善英国和全世界的健康和寿命，减少C。通过加速新疗法的进步，

The bacterium Clostridium difficile causes thousands of deaths every year in the United Kingdom through healthcare-associated infections. The impact upon the healthcare system is enormous and set to worsen due to the increasing prevalence of hypervirulent and antibiotic-resistant strains. An urgent need to develop novel therapies to tackle C. difficile infection thus exists. C. difficile infection is controlled by a complex network of genes that detects optimal conditions for a successful infection, regulating the production of toxins and the initiation of related mechanisms accordingly. The complexity of such nonlinear networks defies their understanding by a single discipline alone. This fellowship will provide the necessary microbiology training for crucial experimental work to be undertaken and, in tandem with computational models of these networks, a radical enhancement in our understanding of C. difficile infection will be achieved. Crucially, the models will capture conventional and novel therapies (the latter targeting toxin production directly), enabling hypotheses to be generated upon the relative effectiveness of these therapies and estimates made upon required dosages. Thus this interdisciplinary approach has the potential to improve health and longevity in the United Kingdom and worldwide, reducing the impact of C. difficile infection by accelerating the advancements of novel therapies.