POPULATION BIOLOGY AND GENETICS OF ANTIMICROBIAL ACTION

描述：本提案的总体目标是开始分析 为评估抗生素耐药性的进化动力学 逆转人类对抗生素耐药性增加的策略 病原体。这项建议有三个部分是合乎逻辑的 相互关联，但在模型和实验系统中是分开的。这个 首先是体外抗药性的种群动态，其次是 活体内的动力学，第三个涉及对猪流感的流行病学进行建模 抵抗。 第一部分将调查细菌模型的真实性。 增长(第18页的公式2)，其中m(A)是描述如何 浓度为A的抗菌剂会影响生长。一种可能 M(A)的函数是(n+1)f(A)，其中f(A)是细胞被杀死的分数 每个细胞周期。抗生素浓度对生长的影响 将使用批次培养进行调查。该模型适用于恒化器 培养(公式5，第20页)。恒化器培养的设计是这样的 有大量的耐药细胞，只有一小部分 敏感细胞。当加入抗生素时，敏感的数量 细胞会衰退，但恒化器的环境，也就是 由大多数人决定的，不会改变。据推测 函数f(A)将从批培养中确定，然后这将 被用来预测化学药物的生长速度。抗生素耐药性 研究的是染色体抗药性是由突变引起的，而不是 通过一个质粒进行转移。这种阻力的代价是在与 如果需要，将确定敏感度并将其包括在模型中。 第二部分研究了免疫应答和抗菌作用 对小鼠体内细菌生长的作用。免疫反应分为两个阶段 部分--非特异性免疫反应和抗原特异性免疫反应。这些遗嘱 通过使用SCID小鼠进行区分，SCID小鼠只有非特异性和 同基因对照小鼠，两者都有。细菌的生长速度 将在小鼠的脾中监测种群(单核细胞增多性乳杆菌)。 这一增长率将被确定为两种不同类型的小鼠 抗生素的剂量。这里的抗生素浓度是不同的 变量，而不是第一部分。在第一部分中，集中了 细菌所经历的浓度；在这一部分 浓度是注射到小鼠体内的浓度。在模型中 在本节中，假设抗生素对生长速度的影响为 生长速度和抗生素浓度之间存在交互作用， M(r，A)。 第三部分涉及如图7所示的模型的开发。 将使用结果和数据来研究该模型的性质 从其他两个部分。尤其是，安妮塔将查看来自 肺炎链球菌在似乎有大约40%耐药的阈值的地方可以 被解释清楚。

DESCRIPTION: The general goal of this proposal is to start the analysis of the evolutionary dynamics of antibiotic resistance in order to evaluate strategies for reversing the increase in antibiotic resistance among human pathogens. There are three parts to this proposal that are logically connected, but are separate in both models and experimental systems. The first is the population dynamics of resistance in vitro, the second, the dynamics in vivo, and the third involves modeling the epidemiology of resistance. The first part will investigate the reality of the model for bacterial growth (equation 2 on page 18) where m(A) is the function that describes how an antimicrobial agent at concentration A effects growth. One possible function of m(A) is (n+1)f(A) where f(A) is the fraction of cells killed each cell cycle. The effect of the concentration of antibiotic on growth will be investigated using batch culture. The model is adapted to chemostat culture (equation 5, page 20). The chemostat culture is designed such that there is a large population of resistant cells, with only a small fraction of sensitive cells. When the antibiotic is added, the number of sensitive cells will decline, but the environment of the chemostat, which is determined by the majority population, will not change. It is assumed that the function f(A) will be determined from batch culture and this will then be used to predict the growth rate in chemostats. The antibiotic resistance studied is chromosomal--resistance arising from mutation rather than transfer via a plasmid. The cost of this resistance when competing with the sensitive will be determined and included in the model if required. The second part studies the effect of the immune response and antimicrobial action on bacterial growth in mice. The immune response is divided into two parts--the non-specific and antigen-specific immune responses. These will be distinguished by using SCID mice, which have only the non-specific and isogenic control mice which have both. The growth rate of the bacterial population (L. monocytogenes) will be monitored in the spleen of the mouse. This growth rate will be determined for the two types of mice with various dosing of antibiotics. Here the concentration of antibiotics is a different variable than in the first part. In the first part, the concentration is the concentration experienced by the bacteria; in this part the concentration is the concentration injected into the mouse. In the model for this section, the effect of antibiotics on growth rate is assumed to have an interaction between growth rate and antibiotic concentration, m(r,A). The third part involves development of a model as given in figure 7. This properties of this model will be investigated using the results and data from the other two sections. In particular, Anita will see if the data from S. pneumoniae where there seems to be a threshold of about 40% resistant can be explained.