An integrated approach to understand the emergence and spread of extensively resistant Gram-negative bacteria in China

自1928年发现青霉素以来，已经鉴定出100多种抗菌剂并用于治疗细菌感染。这导致发达国家几乎消灭了结核病等一些传染病。这一科学发现的进步伴随着一个警告，因为微生物已经获得了抵抗这些抗菌剂毒性作用的能力。构成抗菌剂威胁的大多数细菌是兼性的机会致病菌，它们在环境中大量存在，并且很容易与各种其他微生物交换基因。这些因素包括毒力因子，使它们能够感染动物并逃避宿主的免疫系统，以及使它们对药物产生抗性的抗菌素抗性基因。近年来，最大的新兴抗生素耐药性威胁是革兰氏阴性菌，它们越来越多地破坏最后的药物。随着基因组测序的出现，我们已经了解了很多关于使细菌致病的基因以及使它们对药物产生耐药性的基因。然而，我们目前还没有必要的计算工具来确定“移动的元素”在细菌谱系之间移动的路线，甚至还没有量化这些交换的程度。这反过来又大大限制了我们阻止抵抗分子转移的能力，我们组建了一个多学科小组来处理三个综合问题。首先，我们将为三种主要的抗生素威胁，大肠杆菌，肺炎克雷伯菌和鲍曼不动杆菌，生成一个广泛的完整基因组数据库，其质量前所未有。这将是有史以来第一个高质量的微生物基因组数据库，并将成为未来诊断和预后工具开发的宝贵资源。在第二步中，我们将开发新的计算工具来重建中国这三个物种谱系中抗性的获得和传播。这些工具将足够灵活，可以应用于任何微生物的基因序列数据，并将使我们能够重建这三个物种的抗性的出现和蔓延。最后，我们将在实验室中进行功能验证，以证实生物信息学和计算分析的结果。这项工作还将允许建立不同谱系的遗传组成与其对三种最重要的最后药物碳青霉烯，替加环素和粘菌素的耐药性水平之间的复杂联系。本研究的意义在于多管齐下的方法来描述和监测在中国最具威胁性的革兰阴性菌的抗菌药物耐药性。这项工作将最终确定促进多重耐药病原体增殖和传播的关键遗传和环境因素。这些信息反过来又会产生关于如何优化抗菌药物管理的基本信息，以使患者受益并阻止未来耐药性的传播。

Since the discovery of penicillin in 1928 more than 100 antimicrobial agents have been identified and used to treat bacterial infections. This led to the near-eradication of some infectious diseases such as tuberculosis in the developed world. This advance in scientific discovery comes with a caveat, as microbes have acquired the ability to resist the toxic effects of these antimicrobial agents.The majority of bacteria that constitute antimicrobial threats are facultative, opportunistic pathogens which are found in great numbers in the environment and readily exchange genes with a variety of other microbes. Such elements include virulence factors, which allow them to infect animals and elude the host's immune system, and antimicrobial resistance genes that render them resistant to drugs. Over recent years, the biggest emerging antimicrobial resistance threat is represented by Gram-negative bacteria, which are increasingly breaching the last-resort drugs.With the advent of genome sequencing, we have learned a lot about the genes which make bacteria pathogenic and the ones that allow them to become resistant to drugs. However, we currently do not have the required computational tools to identify the routes through which "mobile elements" move between lineages of bacteria, or even quantify the extent of these exchanges. This in turn greatly limits our ability to block such transfer of resistance elements.We have assembled a multidisciplinary team to address three integrated issues. First, we will generate an extensive database of complete genomes of unprecedented quality for three major antimicrobial threats, Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii. This will represent the first such high-quality microbial genomic database ever and will constitute a precious resource for the development of future diagnostic and prognostic tools. In a second step we will develop new computational tools to reconstruct the acquisition and spread of resistance in lineages of these three species in China. These tools will be flexible enough to be applied to genetic sequence data of any microbe and will allow us to reconstruct emergence and sread of resistance in these three species.Finally, we will perform functional validation in the lab to corroborate the findings from the bioinformatics and computational analyses. This work will also allow establishing the complex link between the genetic makeup of different lineages and their level of resistance to the three most important last-resort drugs carbapenem, tigecycline and colistin. The significance of this study lies in the multipronged approach to describe and characterise antimicrobial resistance in the most threatening Gram-negative bacteria in China. This effort will culminate in the identification of the key genetic and environmental factors that facilitate the proliferation and transmission of multi drug resistant pathogens. Such information should in turn lead to essential information on how to optimise antimicrobial stewardship both to the benefit of the patients and to stem the spread of resistance in the future.