A Cell-Free Toolbox to Anticipate, Learn and Counter Antimicrobial Resistance

抗菌素耐药(AMR)是一种跨多种传染病的全球性健康危机。这个问题如果得不到解决，将破坏医疗保健系统几十年来一直依赖的目前的抗生素治疗。专家预测，到2050年，AMR在全球范围内导致的死亡人数将超过癌症和糖尿病。目前，这一威胁是隐蔽的，并影响到免疫受损的人和老年人，特别是在发展中国家。然而，随着这个问题的加速，即使是日常的伤口或割伤，最终也可能导致健康的人需要严重的治疗和住院治疗。因此，虽然更广泛地说，我们需要一个长期战略来管理广谱抗生素的使用，作为第一道防线，但也需要考虑非标准抗菌药、噬菌体疗法和宿主导向疗法的作用，作为对抗耐药性的对策。我们的项目涉及开发一种安全的无细胞工具来研究一种特定类型的传染病致病细菌-肺炎克雷伯菌，并探索一种新的合成生物学方法来替代抗菌剂。肺炎克雷伯菌很重要，因为它是医院获得性菌血症的主要原因，在一些国家导致高达50%的死亡率。我们的项目将使用最新的技术进步，包括下一代DNA测序、自动化和无细胞合成生物学。总体而言，我们的项目有三个总体目标，作为提案的主题：“预测、学习和应对”。预期-我们需要预测肺炎克雷伯菌将如何对抗生素产生抗药性。这一点很重要，因为肺炎克雷伯菌和许多其他传染病很快就能在目前所有的抗生素治疗中存活下来。学习-我们需要研究个体抗生素耐药机制如何赋予肺炎克雷伯菌优势。反-我们需要通过寻找新的非标准抗生素来阻止抗药性肺炎克雷伯菌感染，特别是那些可以关键地逃避或逃脱当前耐药机制的抗生素。在此，我们提供了一种无细胞合成生物学工具，使我们能够在遏制级别1研究重大传染病，同时该系统是自动化兼容的，以帮助加速发现新的抗生素。此外，我们的方法是通用的，因此可以扩展到几乎任何传染病，即ESKAPE病原体或结核病。总体而言，我们的项目在概念上非常新颖、及时和令人兴奋，并在合成生物学和传染病这两个不同的领域之间创造了新的协同效应。我们的项目将创造一种新的、快速和安全的方法来研究肺炎克雷伯菌如何对抗生素产生抗药性，并提供一个寻找新抗生素的平台。

Antimicrobial resistance (AMR) is a global health crisis branched over multiple infectious diseases. This problem, if unaddressed, will breach current antibiotic treatments which healthcare systems have relied upon for decades. Experts predict AMR will cause more deaths worldwide than cancer and diabetes by 2050. Currently, this threat is insidious, and affects the immunocompromised and the elderly, particularly in developing countries. However, as this problem speeds up, even everyday wounds or cuts could eventually lead to healthy individuals requiring serious treatment and hospitalisation. Therefore, while more broadly we require a long-term strategy to manage broad-spectrum antibiotic usage as the first line of defence, there is also a need to consider the role of non-standard antimicrobials, phage therapy, and host-directed therapeutics as a countermeasure to fight resistance. Our project concerns the development of a safe cell-free tool to study a specific type of infectious disease-causing bacteria, Klebsiella pneumoniae, and explores a new synthetic biology method to alternative antimicrobials. K. pneumoniae is important since it is a leading cause of hospital-acquired bacteraemia and causes up to a ~50% mortality rate in some countries. Our project will use the latest technological advances that include next-generation DNA sequencing, automation, and cell-free synthetic biology. Overall, our project has three general goals that act as our theme for the proposal: "anticipate, learn, and counter".1. Anticipate - We need to predict how K. pneumoniae will become resistant to antibiotics. This is important because K. pneumoniae and many other infectious diseases will soon be able to survive all current antibiotic treatments.2. Learn - We need to study how individual antibiotic resistance mechanisms confer an advantage to K. pneumoniae.3. Counter - We need to stop antibiotic-resistant K. pneumoniae infections by finding new kinds of non-standard antibiotics, especially ones that can crucially evade or escape current resistance mechanisms.Herein, we provide a cell-free synthetic biology tool that enables us to study a major infectious disease at Containment Level 1, while the system is automation compatible to help speed up the discovery of new antibiotics. Also, our approach is generalisable, and therefore can expand to almost any infectious disease, i.e., ESKAPE pathogens or tuberculosis. Overall, our project is remarkably novel, timely and exciting in its conception and creates a new synergy between the two distinct areas of synthetic biology and infectious diseases. Our project will create a new, fast, and safe way to study how K. pneumoniae becomes resistant to antibiotics, as well as providing a platform to search for novel antibiotics.