Evolutionary paths toward intrinsic antibiotic resistance

内在抗生素耐药性的进化路径

• 批准号: 9123635
• 负责人: Alexandra Nogueira Ketcham
• 金额: $ 4.36万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9123635
• 关键词: Aminoglycoside Antibiotics; Anabolism; Antibiotic Resistance; Antibiotic susceptibility; Antibiotics; Area; Attention; Bacteria; Bacterial Infections; Biological Assay; Cataloging; Catalogs; Cause of Death; Cereals; Clinical; Complex; Cost Analysis; Coupled; Data; Development; Diagnostic; Drug Targeting; Escherichia coli; Evolution; Folic Acid; Foundations; Future; Gene Expression Profile; Genes; Genetic; Genetic Determinism; Genetic Epistasis; Genome; Health; High-Throughput Nucleotide Sequencing; Incidence; Individual; Infection; Knock-out; Laboratories; Learning; Libraries; Maps; Measures; Methods; Microbe; Minimum Inhibitory Concentration measurement; Morbidity - disease rate; Mutation; Pathway interactions; Pharmaceutical Preparations; Physiological; Process; Regulatory Pathway; Research; Research Personnel; Resistance; Resistance Process; Resistance development; Signal Pathway; Societies; Sorting - Cell Movement; Treatment Protocols; Work; antimicrobial; bacterial resistance; beta-Lactams; biological adaptation to stress; combat; cost; dosage; drug discovery; fitness; genetic linkage analysis; global health; information gathering; inhibitor/antagonist; microorganism; mortality; next generation; novel; novel diagnostics; novel therapeutic intervention; novel therapeutics; research study; resistance mechanism; resistant strain; response; transcriptome; treatment strategy; trend; whole genome

DESCRIPTION (provided by applicant): Widespread use or misuse of antibiotics has spurred evolutionarily adaptations that enable bacteria to survive many of our most powerful drugs. While existing antimicrobials are losing their effect, there has been in recent years a steep decline in the development of new drugs. If this trend continues, the drugs we have to combat resistant microorganisms will soon be depleted. The growing incidence of illness and death caused by antibiotic resistant infections, coupled with the cost that society has to pay for them, reflect our urgent need for new antibiotics that either block or circumvent resistance mechanisms, or attack new targets. We need a better understanding of the different ways in which resistance develops so that we can develop new methods to identify and counteract it. The research proposed here will provide a broader picture of the evolution of resistance and dissect the genetic mechanisms of its development. We plan to conduct laboratory evolution experiments in which we adapt E. coli to antibiotics from three commonly used classes and discern the mechanisms by which they develop resistance using high-�throughput sequencing and whole genome linkage analysis. Once contributing loci are identified and validated, we will use global epistasis assays and transcriptome analysis to place them in the broader network context of specific signaling and regulatory pathways. We will classify these mutations in order to help simplify and untangle the magnitude and complexity of antibiotic-�bacterial dynamics. Previous research suggests that clinical levels of antibiotic resistance may develop through the sequential accumulation of mutations of small individual effect. Understanding the order in which different mutations occur will give us information that may be useful for developing better diagnostics and in delaying the development of resistance. Throughout this research, special attention will be paid to the trajectory of resistance in the face of increasing drug dosage and also to associated fitness costs to the microorganism under other conditions. The ability of microbes to resist antibiotics often negatively impacts their fitness in the absence of treatment; however, mutations that confer resistance are often quickly followed by additional mutations elsewhere in the genome that compensate for these costs. Understanding the order in which different mutations occur will give us information about how strains become increasingly resistant. Also, since the fitness costs determine the strength of selection against resistant bacteria, analysis of these costs may inform novel treatment regimens. The aim of this research is to uncover new targets to combat resistance, new pathways that synergize with a particular antibiotic and, more broadly, to strengthen and enrich the underlying principles that will lay the foundation for the next generation of novel therapies, drug discovery, and diagnostics in the field.

描述（由申请人提供）：抗生素的广泛使用或滥用刺激了进化适应，使细菌能够在我们许多最强大的药物中生存。虽然现有的抗菌剂正在失去作用，但近年来新药的开发急剧下降。如果这种趋势继续下去，我们用来对抗耐药微生物的药物很快就会耗尽。抗生素耐药性感染引起的疾病和死亡发生率不断上升，加上社会必须为此付出的代价， 这反映了我们对新抗生素的迫切需求，这些抗生素要么阻断或绕过耐药机制，要么攻击新的靶标。我们需要更好地了解耐药性发展的不同方式，以便我们能够开发新的方法来识别和抵消它，这里提出的研究将提供更广泛的耐药性演变的图景，并剖析其发展的遗传机制。我们计划进行实验室进化实验，在实验中我们将E.大肠杆菌对三种常用抗生素的耐药性，并利用高通量测序和全基因组连锁分析来辨别它们产生耐药性的机制。一旦确定并验证了贡献基因座，我们将使用全局上位性分析和转录组分析将其置于特定信号传导和调控途径的更广泛的网络环境中。我们将对这些突变进行分类，以帮助简化和解开抗生素-细菌动力学的规模和复杂性。先前的研究表明，抗生素耐药性的临床水平可能通过个体效应小的突变的连续积累而发展。 了解不同突变发生的顺序将为我们提供可能有助于开发更好的诊断方法和延迟耐药性发展的信息。在整个研究过程中，将特别关注药物剂量增加时的耐药性轨迹，以及其他条件下微生物的相关适应性成本。在没有治疗的情况下，微生物抵抗抗生素的能力通常会对它们的适应性产生负面影响;然而，赋予耐药性的突变通常很快就会在基因组的其他地方发生额外的突变，以补偿这些成本。 了解不同突变发生的顺序将为我们提供有关菌株如何变得越来越耐药的信息。此外，由于适应性成本决定了对耐药细菌的选择强度，因此对这些成本的分析可能会为新的治疗方案提供信息。这项研究的目的是发现对抗耐药性的新靶点，与特定抗生素协同作用的新途径，更广泛地说，加强和丰富基本原理，为下一代新疗法，药物发现和诊断奠定基础。