Mechanisms of Adaption: Genotype to Molecular Phenotype to Growth Rate

描述(由申请人提供)： 40年来，进化遗传学一直是纯粹的统计学方法，但最近，操纵性方法(如反向遗传学)已与生物化学和结构生物学结合起来，以剖析适应性变化的机制基础。我研究的广泛和长期目标是利用这些操纵性的变化，并采取机械的方法来研究适应。对于我的博士后研究，我正在开发一个适合我长期研究计划的模型系统。模型系统是一个单一的大肠杆菌菌株和16个等位基因的β-内酰胺酶，这些基因赋予了对氨苄西林的耐药性。具体目标1.开发和测试一个新的模型，描述整个有机体的生长速度如何随着温度和抗生素浓度的变化而变化。表征不同温度和抗生素浓度的生长率的等位基因内和等位基因间的差异。对于每个等位基因，测量在广泛的温度和抗生素浓度范围内的生长速度。根据Arrhenius方程假设生长速度依赖于温度，将生长速度数据与细菌生长速度模型相结合，计算出每个等位基因的激活能。具体目标2.在15至60摄氏度的多个温度下，测量16个β-内酰胺酶等位基因的最大反应速度(Vmax)。用圆二色谱测量这些相同等位基因的热稳定性。使用动力学数据计算每个等位基因的激活能。测试每个等位基因的活化能的体外测量结果与目标1中的活化能估计值一致的假设。测试酶活性和稳定性之间通常存在权衡的假设，以及这些权衡可以解释整个有机体的生长速度的假设。相关性：这些实验的模式系统，即β-内酰胺酶，使人对β-内酰胺类抗生素产生耐药性。β-内酰胺类抗生素占所有抗生素的65%，每年的营业额为150亿美元。通过测量这些β-内酰胺酶等位基因在不同温度和抗生素浓度下的生长速度，我将能够评估这些β-内酰胺酶等位基因在自然界中的持久性。

DESCRIPTION (provided by applicant): For 40 years evolutionary genetics has been purely statistical but recently manipulative methods (e.g. reverse genetics) have been joined with biochemistry and structural biology to dissect the mechanistic basis of adaptive changes. The broad, long-term objective of my research is to take advantages of these manipulative changes and take a mechanistic approach to study adaptation. For my postdoctoral research, I am developing a model system suited to my long term research program. The model system is a single strain of E.coli and 16 alleles of beta-lactamase that confer resistance to ampicillin. Specific Aim 1. Develop and test a novel model describing how whole-organism growth rate varies across temperature and antibiotic concentration. Characterize intra and inter allelic variation in growth rate across temperatures and antibiotic concentrations. For each allele, measure growth rate across a wide range of temperatures and antibiotic concentrations. Assuming growth rate depends on temperature according to the Arrhenius equation, combine the growth rate data with the model of bacterial growth rate to calculate each alleles activation energy. Specific Aim 2. At multiple temperatures between 15 and 60 degrees Celcious, measure the maximum reaction velocity (vmax) for each of the 16 beta-lactamase alleles. Measure the thermostability of these same alleles with circular dichroism. Use the kinetic data to calculate the activation energy for each allele. Test the hypothesis that the in vitro measures of activation energy for each allele agree with the estimates of activation energy made in Aim 1. Test the hypothesis that trade-offs commonly occur between enzyme activity and stability and that these trade-offs explain whole-organism growth rates. Relevance: The mode system for these experiments, the beta-lactmase enzyme, confers resistance to beta- lactam antibiotics. Beta-lactam antibiotics represent 65% of all antibiotics and account for 15 billion dollars a year in business. By measuring the growth rate of these beta-lactamase alleles at different temperatuers and antibiotic concentrations, I will be in a position to assess the persistence of these beta-lactamase alleles in nature.