Genomics approaches to elucidating pathways to antibiotic resistance in Neisseria gonorrhoeae

阐明淋病奈瑟菌抗生素耐药性途径的基因组学方法

基本信息

批准号：
9367004
负责人：
Yonatan H Grad
金额：
$ 39.75万
依托单位：
HARVARD SCHOOL OF PUBLIC HEALTH
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9367004
关键词：
Address Alleles Antibiotic Resistance Antibiotic Therapy Antibiotic susceptibility Antibiotics Appearance Azithromycin Bacteria Bioinformatics Biological Models Biology Cefixime Ceftriaxone Cephalosporins Ciprofloxacin Clinical Complex Data Set Development Epidemiology Experimental Models Genes Genetic Genome Genomic approach Genomics Genotype Goals Gonorrhea Growth In Vitro Infection Intervention Knowledge Libraries Link Macrolides Maintenance Measures Methods Mutagenesis Mutation Nature Neisseria gonorrhoeae Pathway interactions Pattern Pharmaceutical Preparations Phenotype Population Population Surveillance Predisposition Prevalence Public Health Quinolones Resistance Sexually Transmitted Diseases Statistical Methods System United States Validation Variant Work bacterial resistance burden of illness clinically relevant comparative genomics computerized tools cost drug sensitivity fitness gene interaction improved in vivo mutant new therapeutic target novel novel strategies novel therapeutics pathogen population based prevent resistance allele resistance mechanism resistant strain screening support network therapeutic development tool

项目摘要

Project Summary/Abstract The rise of antibiotic resistant bacteria poses a grave threat to public health. To outcompete susceptible bacteria and increase in prevalence, resistant strains must be able to compensate for fitness costs incurred by resistance-conferring mutations and genes. However, not every strain of a bacterial species can compensate equally well, yielding a complex evolutionary landscape between susceptibility and resistance. Elucidating the nature and diversity of the mechanisms that support acquisition and maintenance of resistance will allow us to understand how resistant strains emerge and spread and thereby accelerate development of desperately needed new strategies to prevent and treat resistant infections. We use the clinically important pathogen Neisseria gonorrhoeae (the gonococcus) as a model system, given its high burden of disease (820,000 cases in the US and nearly 80 million cases globally each year), the imminent threat of untreatable infection, and the ease of experimental manipulation. Our goal is to define the genetic networks that support acquisition and maintenance of resistance to three of the clinically most important antibiotics for treatment of gonococcus: the extended spectrum cephalosporins, azithromycin, and the quinolones. To do so, we will leverage our unique dataset of >1100 epidemiologically and genetically diverse clinical gonococcal isolates for which we have full genome sequences and antibiotic susceptibility profiles. We will use population-based computational and experimental methods that incorporate the diversity of susceptible and resistant populations and thus represent a fundamental shift from single reference strain studies. These methods include unbiased statistical tools to identify genetic differences in sub-populations; high-throughput transposon mutagenesis screens to define the loci that impact resistance as a function of genetic background; and a system for genome manipulation to validate links between genotype and resistance phenotype. We expect that the results from these studies will define the interacting loci that contribute to resistance in natural populations. These results can be applied to improving public health surveillance efforts and development of therapeutics. Moreover, the system we establish here can be used to further probe the biology of gonococcus and provides a framework for the development of similar systems to dissect of the genetic networks of resistance in other bacterial pathogens.

项目概要/摘要抗生素耐药细菌的增加对公众健康构成严重威胁。战胜易受影响的人细菌和患病率的增加，耐药菌株必须能够补偿因细菌而产生的健康成本赋予抗性的突变和基因。然而，并非每种细菌菌株都能补偿同样好，在易感性和抵抗性之间产生了复杂的进化景观。阐明支持获得和维持抵抗力的机制的性质和多样性将使我们能够了解耐药菌株如何出现和传播，从而加速绝望的发展需要新的策略来预防和治疗耐药感染。我们使用临床上重要的病原体淋病奈瑟菌（淋球菌）作为模型系统，给定其疾病负担沉重（每年美国有 82 万例，全球有近 8000 万例），无法治疗的感染的迫在眉睫的威胁，以及实验操作的便利性。我们的目标是定义支持获得和维持对临床上最常见的三种耐药性的遗传网络治疗淋球菌的重要抗生素：广谱头孢菌素、阿奇霉素和喹诺酮类药物。为此，我们将利用我们独特的超过 1100 个流行病学和遗传学数据集我们拥有完整的基因组序列和抗生素敏感性的多种临床淋球菌分离株配置文件。我们将使用基于人口的计算和实验方法，融合多样性易感人群和耐药人群，因此代表了单一参考菌株的根本转变研究。这些方法包括用于识别亚群体遗传差异的公正统计工具；高通量转座子诱变筛选以确定影响抗性的基因座遗传背景；以及用于验证基因型和抗性之间联系的基因组操作系统表型。我们期望这些研究的结果将确定有助于耐药性的相互作用基因座自然种群。这些结果可用于改善公共卫生监测工作和治疗学的发展。此外，我们在这里建立的系统可用于进一步探讨生物学淋球菌，并为开发类似系统来剖析遗传提供了一个框架其他细菌病原体的耐药网络。