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

• 批准号: 8115157
• 负责人: Yousif Shamoo
• 金额: $ 25.1万
• 依托单位: RICE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8115157
• 关键词: Agriculture; Antibiotic Resistance; Antibiotics; Aquaculture; Area; Attention; Bacteria; Bacteroides; Biological Models; Breeding; Cefotaxime; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Child; Clinical; Communities; Community Hospitals; DNA Sequence; Data; Development; Disease Outbreaks; Drug Delivery Systems; Drug resistance; Elderly; Enterococcus faecalis; Environment; Enzymes; Escherichia coli; Event; Evolution; Family; Farming environment; Gene Targeting; General Practitioners; Genes; Genetic Epistasis; Grant; Health; Hospitals; Human; Lactams; Lead; Libraries; Link; Measurement; Mediating; Medical; Medicine; Methicillin; Mobile Genetic Elements; Modeling; Molecular; Molecular Evolution; Molecular Models; Mutation; Natural Selections; Nosocomial Infections; Organism; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Plasmids; Population; Population Dynamics; Population Pressures; Posture; Process; Property; Proteins; Reagent; Regimen; Research; Resistance; Resolution; Roentgen Rays; Role; Schools; Scientist; Societies; Specialist; Staphylococcus aureus; Structure; System; Testing; Tetracycline Resistance; Tetracyclines; Validation; Vancomycin resistant enterococcus; Work; assay development; base; clinically relevant; cost; direct application; drug development; drug resistant bacteria; experience; fitness; interdisciplinary approach; microbial; molecular modeling; molecular shape; mutant; novel; prevent; protein function; protein structure function; resistance mechanism; resistant strain; transmission process; vector

DESCRIPTION (provided by applicant): Each year the CDC estimates that there are approximately two million cases of nosocomial infection that result in over 80,000 patient deaths. Antibiotic resistance is an evolutionary consequence of successful drug therapies and highlights the role of natural selection in shaping the molecular mechanisms leading to resistance. To examine these mechanisms in molecular detail, we are subjecting large populations of bacteria, carrying one of three antibiotic resistance genes, to continuous experimental evolution. By varying the conditions of selection during adaptation, antibiotic resistance mediated by changes to the target genes will be used to: 1) identify the network of mutations that define the functional intermediates to adaptation within the population; 2) determine the physicochemical basis for changes in protein function that lead to increased fitness (i.e. resistance) and 3) provide data for the successful modeling of successful evolutionary trajectories using correlated sign epistasis models. The target genes for study are E. faecalis Tn916 tetM (ribosomal protection against tetracyclines), Bacteroides Tn4400 tetX (enzymatic inactivation of tetracyclines) and TnA TEM-1 (enzymatic inactivation of (-lactams). These studies will provide a wide range of data and results including: high resolution crystallographic structures of Bacteroides Tn4400 TetX and E. faecalis Tn916 TetM, libraries of characterized expanded spectrum TetX and TetM mutants for drug development, a scalable high throughput TetM activity assay, and development of robust turbidostat systems for continuous evolution. By taking an interdisciplinary approach combining biophysical and population strategies, we can link changes in proteins at the atomic level to their consequences for the organism in its environment and vice versa. Developing validated models for molecular adaptation is an important step towards making accurate predictions of antibiotic resistance. Once fully realized, evolutionary forecasting holds the promise of going beyond the identification of traditional drug targets to the development of new clinical strategies that consider the molecular mechanisms of adaptation to prevent drug resistance. PUBLIC HEALTH RELEVANCE: The rise of antibiotic resistance is a clear health threat that requires immediate and continuing attention. As strains of drug resistant bacteria continue to spread into hospitals and communities the cost to society are staggering. Data from 2004 show that despite the best efforts of the medical community, methicillin resisistant Staphylococcus aureus (MRSA) were found in over 60% and vancomycin resistant Enterococci (VRE) in nearly 30% of ICU patients compared to 37% and 14% respectively in 1995 and continue to rise. Children and the elderly are particularly vulnerable. Unfortunately, community associated (CA) outbreaks of MRSA are also increasing suggesting that drug resistant strains are making their way into the locker rooms of schools and other public areas. In addition to human-to-human transmission within clinical settings, the widespread use of antibiotics in agriculture and aquaculture has also led to the proliferation of resistant strains. Mobile genetic elements such as transposons, conjugative transposons and plasmids act as vectors between microbial populations and can spread resistance beyond the agricultural or clinical environment. Hospitals and farms can therefore act as breeding grounds and reservoirs for the transfer of drug resistance genes into the general community. Although there is no way to stop evolution, a more complete understanding of the principles underlying molecular adaptation to resistance can be a powerful asset to both scientists and clinicians. The proposed work is an important step in the transition of molecular evolution from a retroactive posture that analyzes past events to one in which evolution research is used pro-actively for the prediction of drug resistance, optimization of drug regimens, and perhaps development of novel reagents that restrict pathogenic adaptation with direct application to medicine.

描述（由申请人提供）：每年CDC估计大约有200万例医院感染病例导致80,000例患者死亡。抗生素耐药性是成功药物疗法的进化后果，并突出了自然选择在塑造导致抗性的分子机制中的作用。为了通过分子细节检查这些机制，我们正在对大量细菌种群进行连续的实验进化。通过改变适应过程中的选择条件，将使用对目标基因的变化介导的抗生素耐药性：1）确定定义功能中间体在人群中适应的突变网络； 2）确定蛋白质功能变化的物理化学基础，从而导致适应性提高（即电阻）和3）为成功建模使用相关的符号上位症模型提供了成功建模的数据。用于研究的靶基因是粪肠球菌TN916四甲虫（核糖体保护四环素），细菌型TN4400 TETX（酶促灭活四环素）和TNA TEM-1和TNA tem-1（酶促的酶灭活（ - lactactams）。这些研究将提供（ - l-llactams）。 TETX和E.粪便TN916 TETM，特征的扩展的谱谱TETX和TETM突变体用于药物发育，可伸缩的高吞吐量TETM活性测定，以及可靠的浊度系统的发展，以通过将生物物质和人群的策略与人群相结合，使其与持续的进化相结合，我们可以在策略中脱颖而出。反之亦然。开发经过验证的分子适应模型是对抗生素抗性进行准确预测的重要一步。公共卫生相关性：抗生素抗性的兴起是一种明显的健康威胁，需要立即并继续关注。随着抗药性细菌的菌株继续传播到医院和社区，社会成本令人震惊。 2004年的数据表明，尽管医学界做出了最大的努力，但在60％以上的ICU患者中发现了超过30％的ICU患者中的60％和抗性霉素肠球菌（VRE），在60％以上和耐华霉素抗霉素的葡萄球菌（MRSA）中，相比之下，与1995年的37％和14％相比，在近30％的ICU患者中发现了甲氧西林。儿童和老年人特别脆弱。不幸的是，MRSA的社区（CA）爆发也在增加，这表明耐药菌菌株正在进入学校和其他公共区域的更衣室。除了在临床环境中进行人类到人类的传播外，抗生素在农业和水产养殖中的广泛使用也导致了抗性菌株的扩散。移动遗传因素，例如转座子，共轭转座子和质粒作为微生物种群之间的向量，并且可以在农业或临床环境中传播耐药性。因此，医院和农场可以充当将耐药基因转移到普通社区的繁殖场和水库。尽管无法停止进化，但对抗药性的分子适应性原理的更全面了解可能是科学家和临床医生的强大资产。提出的工作是分子进化从追溯姿势转变为分析过去事件的重要步骤，该事件将进化研究主要用于预测耐药性的预测，药物治疗方案的优化以及可能限制了直接适用于医学的病原性适应的新型试剂的发展。