Development of synthetic, methylation based, epigenetic gene circuits

在我们最近的出版物中，我们描述了大肠杆菌中的合成表观遗传电路，它可以感知瞬时触发信号，并在几代细胞中以DNA甲基化模式的形式存储这些信息。这种人工表观遗传系统的潜在应用是多方面的，包括开发细菌，这些细菌可以用作活传感器来监测冷却链，检测生产地点或原子能发电厂附近的环境污染，或者通过人体并收集有关疾病标志和新陈代谢状态的信息。生物技术的应用包括用于诱导工业蛋白表达或在生物遏制系统中的存储开关。该项目旨在进一步开发这些新系统的基本属性，并更好地了解它们的信号特征。我们将改进现有的热检测，并采用新的输入信号，允许检测抗生素、代谢物、毒素、细菌细胞密度和放射性。为了改善信号处理，我们计划开发比现有系统更多的以反向方式工作的系统，这将允许开发随细菌细胞周期振荡的系统，以识别代谢活跃的细菌，并将它们与死亡或休眠的细胞区分开来。这里开发的基于DNA甲基化的存储系统的一个特别优点是它们对多路复用的适应性，允许收集许多不同的输入信号，并将信息存储在一个细胞中的不同DNA甲基化代码中。为了实现这一目标，我们计划整合更多兼容的DNA甲基转移酶和新的甲基化位点。不同的输入设备将被组合以生成显示用于初始数据处理的AND或OR行为的逻辑门。我们的目标是使用定量动态模型作为一个主要工具，以获得对表观遗传回路的调控原理、信息处理和存储的机械理解。这些模型及其分析也将对整个设计和实施周期提供高度支持。总之，我们的工作将为将含有合成表观遗传电路的设计菌应用于生物信号检测铺平道路，作为活的生物传感器，将DNA甲基化模式中的信息存储为细菌存储设备，并作为细菌微处理器执行初始数据处理。

In our recent publication, we described synthetic epigenetic circuits in E. coli that can sense transient trigger signals and store this information in form of DNA methylation patterns over several cell generations. Potential applications of such synthetic epigenetic systems are manifold and include the development of bacteria that could be used as live sensors to monitor cooling chains, detect environmental pollution next to production sites or atomic power plants, or passage through the human body and collect input about disease markers and metabolic states. Biotechnological applications include memory switches for induction of industrial protein expression or in biocontainment systems. This project aims to further develop fundamental properties of these novel systems and better understand their signaling characteristics. We will improve the existing heat detection and adopt new input signals allowing the detection of antibiotics, metabolites, toxins, bacterial cell density and radioactivity. To improve signal processing, we plan to develop additional systems working in an inverted manner than the existing ones, which will allow to develop systems that oscillate with the bacterial cell cycle to identify metabolically active bacteria and distinguish them from dead or dormant cells. One particular strength of the DNA methylation based memory systems developed here is their amenability to multiplexing allowing to collect many different input signals and deposit the information in different DNA methylation codes in one cell. Heading towards this goal, we plan to integrate additional compatible DNA methyltransferases and novel methylation sites. The different input devices will be combined to generate logic gates exhibiting AND or OR behavior for initial data processing. We aim to use quantitative dynamic modeling as a major tool to obtain a mechanistic understanding of the regulation principles, information processing and storage by epigenetic circuits. These models and their analysis will also be highly supportive for the entire design and implementation cycle. In summary, our work will pave the way towards the application of designer bacteria containing synthetic, epigenetic circuits in the detection of biological signals as live biosensors, storing the information in DNA methylation patters as bacterial storage devices and performing initial data processing as bacterial microprocessors.