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：
8697252
负责人：
Yousif Shamoo
金额：
$ 35.99万
依托单位：
RICE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-08-01 至 2014-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8697252
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 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 RNA 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 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 resistance mechanism success tigecycline

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 in vitro 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 specfic 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。尽管抗生素取得了巨大成功，但细菌感染仍然是导致死亡的主要原因之一。抗生素的持续和广泛使用越来越多地选择了能够快速适应新抗生素的多重耐药细菌。产生抗生素并缩短其临床疗效。我们开发了一种可扩展的整体方法，称为“定量进化动力学”（QED），用于研究万古霉素耐药肠球菌（VRE）临床分离株对达托霉素和替加环素的耐药性以及鲍曼不动杆菌对替加环素的耐药性。 QED 可应用于许多生物体和抗生素，以提供：1) 概念和机制见解，2) 药物设计的新目标，3) 揭示细胞适应性变化的潜在生物物理基础，导致选择过程中产生更大的耐药性。为了进行 QED，我们结合使用浊度稳定器（将细菌群体维持在最快生长速度的发酵罐）中的体外实验进化、基因组测序、DNA 条形码来测量等位基因频率 (FREQ-SEQ)、RNA-SEQ 和理化表征，包括 X 射线晶体学，为耐药靶点和机制的识别和表征提供综合方法。 QED 使用实验进化来识别适应中间体，以重建负责抵抗的自适应网络。我们利用进化生物学的原理对人群中此类变化的可能重要性进行排名，并优先考虑最重要的目标，以进行更耗时的物理研究。 QED 显示出与抗生素耐药性体内临床观察的良好对应性。我们不仅深入了解临床相关的耐药策略，还深入了解耐药的具体生化机制、导致这些生化变化的具体候选基因，以及在这些变化和适应性（例如耐药）之间建立定量联系的基础病原体对特定药物的影响。 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态。