Defining Evolutionary Trajectories: Molecular adaptation to antibiotic resistance

定义进化轨迹：抗生素耐药性的分子适应

基本信息

批准号：
8693548
负责人：
Yousif Shamoo
金额：
$ 23.6万
依托单位：
RICE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-07-15 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8693548
关键词：
Acinetobacter baumannii Alleles Antibiotic Resistance Antibiotics Award Bacterial Infections Bar Codes Biochemical Biology Biophysics Candidate Disease Gene Cessation of life Clinical Clinical Research Complement DNA Sequence Daptomycin Development Dinucleoside Phosphates Drug Design Drug resistance Effectiveness Enterococcus Enterococcus faecalis Enzyme Kinetics Evolution Experimental Models Future Gene Frequency Generations Genes Genome Genomics Goals Growth Human In Vitro Individual Infection Kinetics Laboratories Ligand Binding Link Measures Membrane Metabolic Pathway Modeling Molecular Multi-Drug Resistance Mutation Organism Output Pathway interactions Patients Pharmaceutical Preparations Phenotype Population Property Proteins Public Health Relative (related person)Resistance Signal Pathway Signaling Protein Stress System Systems Biology Tetracyclines Time United States Validation Vancomycin resistant enterococcus Variant X-Ray Crystallography base biophysical properties cardiolipin synthase clinical efficacy clinically relevant comparative genomics drug resistant bacteria fitness glutathione synthase holistic approach in vivo insight member mortality novel novel strategies pathogen phosphoric diester hydrolase public health relevance resistance mechanism success tigecycline transcriptome sequencing

项目摘要

DESCRIPTION (provided by applicant): Antibiotic resistance among bacterial pathogens remains one of the great challenges confronting public health in the world today. Despite the remarkable success of antibiotics, bacterial infections remain one of the leading causes for mortality. Increasingly, sustained and broad use of antibiotics has selected for multi-drug resistant bacteria that adapt rapidly to newer generation antibiotics and shorten their clinical efficacy. We have developed a scalable and holistic approach that we call 'Quantitative Evolutionary Dynamics' (QED) to study daptomycin and tigecycline resistance in clinical isolates of vancomycin-resistant enterococci (VRE) and to tigecycline resistance in Acinetobacter baumannii. QED can be applied across many organisms and antibiotics to provide: 1) conceptual and mechanistic insights, 2) new targets for drug design, and 3) reveal the underlying biophysical basis for changes in cellular fitness leading to greater resistance during selection. To conduct QED, we use a combination of experimental evolution in turbidostats (fermentors that maintain bacterial populations at their fastest growth rate), genomic sequencing, DNA bar-coding to measure allelic frequencies (FREQ-SEQ), RNA-Seq and physicochemical characterization, including X-ray crystallography, to provide an integrative approach to the identification and characterization of drug resistance targets and mechanisms. QED uses experimental evolution to identify the intermediates of adaptation to reconstruct the adaptive networks responsible for resistance. We use principles from evolutionary biology to rank the likely importance of such changes within the population and prioritize the most important targets for the more time consuming physical studies. QED shows excellent correspondence to in vivo clinical observations of antibiotic resistance. We produce insights not just into the clinically relevant strategies for resistance, but also the specific biochemical mechanisms of resistance, the specific candidate genes responsible for those biochemical changes, and the basis for developing a quantitative link between those changes and the fitness (e.g. resistance) of the pathogen towards a specific drug. QED is a powerful and novel approach that can complement in vivo and clinical studies as well as reveal the evolutionary dynamics of antibiotic resistance.

描述（由申请人提供）：细菌病原体之间的抗生素耐药性仍然是当今世界公共卫生面临的巨大挑战之一。尽管抗生素取得了显着的成功，但细菌感染仍然是死亡率的主要原因之一。越来越多的抗生素使用抗生素的持续和广泛使用已选择用于迅速适应新产生抗生素并缩短其临床功效的多药抗菌细菌。我们已经开发了一种可扩展的整体方法，我们称之为“定量进化动力学”（QED），以研究抗性霉素抗性肠球菌（VRE）临床分离株（VRE）的daptomycin和tigecycline抗性，并在抗激素的baumanniii中对tigecycline抗性。 QED可以在许多生物体和抗生素中应用：1）概念和机械洞察，2）药物设计的新目标； 3）揭示了细胞适应性变化的潜在生物物理基础，从而在选择过程中导致更大的耐药性。要进行QED，我们将实验进化的组合（以最快的生长速率保持细菌群体维持细菌种群的发酵罐），基因组测序，DNA键编码来测量等位基因频率（FREQ-SEQ），RNA-SEQ和物理化学表征，包括X射线晶体术和识别型的鉴定方法，并具有识别型和特征的方法。 QED使用实验进化来识别适应性的中间体，以重建负责电阻的自适应网络。我们使用进化生物学的原则来对这种变化在人群中的重要性进行排名，并优先考虑更耗时的物理研究目标。 QED显示出与抗生素耐药性体内临床观察结果的极好对应关系。我们不仅会洞悉抗药性的临床相关策略，还可以产生抗药性的特定生物化学机制，负责对这些生化变化的特定候选基因，以及在这些变化与适应性（例如，对特定药物的病原体抗性）之间建立定量联系的基础。 QED是一种强大而新颖的方法，可以补充体内和临床研究，并揭示抗生素耐药性的进化动力学。