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，已有100多种抗菌剂被鉴定并用于治疗细菌感染。这导致发达国家的结核病等一些传染病几近根除。科学发现的这一进展伴随着一个警告，因为微生物已经获得了抵抗这些抗菌剂的毒性作用的能力。构成抗微生物威胁的大多数细菌都是兼性的、机会性的病原体，在环境中大量发现，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，以及抗菌素耐药基因，使它们对药物产生抗药性。近年来，最大的耐药性威胁是革兰氏阴性菌，它们越来越多地突破最后的药物。随着基因组测序的出现，我们了解了很多关于致病基因和使细菌产生耐药性的基因。然而，我们目前还没有必要的计算工具来确定“移动元素”在细菌谱系之间移动的路线，甚至没有量化这些交换的程度。这反过来又极大地限制了我们阻止这种抵抗分子转移的能力。我们已经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菌威胁--大肠杆菌、肺炎克雷伯菌和鲍曼不动杆菌--建立一个具有前所未有质量的完整基因组数据库。这将是有史以来第一个这样高质量的微生物基因组数据库，并将构成开发未来诊断和预后工具的宝贵资源。在第二步中，我们将开发新的计算工具来重建这三个物种在中国中获得和传播抗性的谱系。这些工具将足够灵活，可以应用于任何微生物的遗传序列数据，并将允许我们重建这三个物种的抗药性出现和蔓延。最后，我们将在实验室进行功能验证，以证实生物信息学和计算分析的发现。这项工作还将建立不同血统的基因构成与他们对三种最重要的最后手段药物碳青霉烯、替格环素和粘菌素的抗药性之间的复杂联系。本研究的意义在于多管齐下地描述和表征中国最具威胁性的革兰氏阴性菌的耐药性。这一努力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。这样的信息应该反过来导致关于如何优化抗菌素管理以造福于患者和阻止耐药性在未来传播的基本信息。

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.