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.

项目摘要/摘要抗生素耐药细菌的兴起对公共卫生构成了严重威胁。胜任易感性细菌和患病率的增加，耐药菌株必须能够补偿由抗性的突变和基因。但是，并非细菌物种的每个菌株都可以补偿同样好的，在敏感性和电阻之间产生复杂的进化景观。阐明支持获取和维持抵抗的机制的性质和多样性将使我们能够了解抗性菌株如何出现和传播，从而加速拼命的发展需要新的策略来预防和治疗抗性感染。我们将临床上重要的病原体淋病奈瑟氏菌（淋球菌）作为模型系统，给定它的疾病负担很高（美国有820,000例，每年近8000万例），迫在眉睫的感染的威胁以及实验性操纵的易度性。我们的目标是定义支持获得和维持对三个临床上最大三个的耐药性的遗传网络淋球菌治疗的重要抗生素：扩展的光谱头孢菌素，阿奇霉素和喹诺酮。为此，我们将在流行和遗传学上利用> 1100的独特数据集我们具有完整基因组序列和抗生素易感性的多种临床淋球菌分离株概况。我们将使用基于人群的计算和实验方法，以结合多样性易感和抵抗种群的人群，因此代表了从单个参考应变的基本转移研究。这些方法包括公正的统计工具，以识别亚群中的遗传差异。高通量转座子诱变筛选，以定义影响抗性的基因座遗传背景；以及一个基因组操纵系统，以验证基因型与电阻之间的联系表型。我们预计这些研究的结果将定义有助于阻力的相互作用基因座天然人群。这些结果可以应用于改善公共卫生监视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的构造，并为开发类似系统的开发提供了遗传的框架其他细菌病原体中的抗性网络。