Feedback and Noise in a Multiple Antibiotic Resistance Circuit

描述：抗生素耐药性在临床环境中是一个日益严重的问题，对多种药物具有耐药性的细菌菌株正以惊人的频率出现。虽然遗传变化传统上被研究为耐药的来源，但细菌也可以通过短暂的、嘈杂的耐药机制表达来逃避抗生素。迄今为止，对短暂耐药的研究主要集中在全耐或无耐药机制上，如细菌持久性，细胞在耐药状态和药敏状态之间切换。在对能够在种群中产生连续的抗性水平的机制的理解方面存在根本性的差距。这是一个重要的问题，因为细菌可以利用这种策略作为跳板，达到更高的、永久的耐药性水平。为了解决这个问题，我们将研究一种重要的调节蛋白，即多重抗生素耐药激活因子（MarA），它控制着临床相关病原体中许多抗生素耐药基因的表达。我们的初步数据表明，MarA的表达在单个细胞中是嘈杂的，在一个群体中产生连续的表达水平。这些发现引发了这样一个问题：这种噪音是否会导致耐药性的多样性，从而使细菌种群能够抵御突然出现的抗生素。我们的中心假设是，控制MarA的调控电路结构放大了噪声，导致耐药基因表达的变异性，并允许一部分细胞在抗生素治疗中存活下来。我们将使用一种结合定量延时显微镜和随机数学模型的方法来检验这一假设，以确定MarA中噪声的机制和功能。该项目主要围绕三个目标：(1)通过比较调控网络和替代工程网络，确定MarA表型变异性的遗传基础。(2)量化MarA中的噪声如何传播到其调节的各种下游抗生素抗性基因。(3)确定随时间变化的抗生素治疗下，MarA变异如何影响生存。这项综合研究具有重要意义，因为它有望提出对抗短暂性抗生素耐药性的治疗策略，并将揭示短暂性耐药性发展和持续时间的重要动态信息。此外，它还研究了一种引入抗生素耐药基因表达多样性的新机制，这可能与产生短暂抗生素耐药的其他机制普遍相关。

DESCRIPTION: Antibiotic resistance is an increasing problem in clinical settings and strains of bacteria that are resistant to multiple drugs are appearing with alarming frequency. While genetic changes have traditionally been studied as the source of drug resistance, bacteria can also evade antibiotics through transient, noisy expression of resistance mechanisms. Studies on transient resistance to date have focused on all-or-none tolerance mechanisms such as bacterial persistence where cells switch between a drug-tolerant and a drug-sensitive state. There is a fundamental gap in understanding of mechanisms that can generate a continuum of resistance levels within a population. This is a significant problem because bacteria can use such a strategy as a stepping stone to achieve higher, permanent levels of drug resistance. To address this, we will study an important regulatory protein, the multiple antibiotic resistance activator (MarA), which controls expression of many antibiotic resistance genes in clinically relevant pathogens. Our preliminary data show that expression of MarA is noisy in single cells, generating a continuum of expression levels within a population. These findings provoke the question of whether this noise leads to diversity in drug resistance, allowing populations of bacteria to hedge against the sudden appearance of an antibiotic. Our central hypothesis is that the regulatory circuit architecture controlling MarA amplifies noise, leading to variability in expression of resistance genes, and allowing a subset of cells to survive antibiotic treatment. We will test this hypothesis using an approach that integrates quantitative time-lapse microscopy and stochastic mathematical modeling to determine the mechanism and function of noise in MarA. The project is focused around three Aims: (1) Identify the genetic basis for phenotypic variability in MarA by comparing the regulatory network to alternative engineered networks. (2) Quantify how noise in MarA propagates to the diverse downstream antibiotic resistance genes it regulates. (3) Determine how variability in MarA impacts survival under time-varying antibiotic treatment. This integrative research is significant because it is expected to suggest treatment strategies for combating transient antibiotic resistance and will reveal important dynamic information about the period over which transient resistance develops and persists. Furthermore, it examines a novel mechanism for introducing diversity in antibiotic resistance gene expression, which is likely to be generally relevant to other mechanisms that generate transient antibiotic resistance.