Developing a pipeline for rapid optimisation of transcriptional expression regulation

工程生物系统中的一个关键挑战是开发可重复使用的、精确的和可调的基因表达控制元件。目前，开发这些系统需要基于试错法的昂贵且耗时的实验。这对于需要具有多个共调节组分的复杂系统或使用从非模型微生物获得的组分的系统的应用尤其成问题。该项目将开发工具来系统地识别转录控制元件，揭示其设计规则，以使这些控制元件在替代宿主和遗传背景中重新使用。原核生物中的转录调控主要通过转录因子（TF）与启动子的结合来实现。每个TF具有特定的结合偏好，这决定了其功能（激活剂或阻遏物）及其在启动子内的结合位点的位置。因此，了解TF的生物物理结合偏好，能够计算预测任何给定启动子的调控逻辑和转录活性1，2。然而，目前，已知的生物物理结合偏好只有少数的TF，这意味着我们不能很容易地利用生物工程中的异源TF。在这个跨学科项目中，学生将利用一系列分子/合成生物学，微生物学和生物物理学方法来：（i）开发实验和数据分析管道，可以确定任何给定TF的结合偏好;（ii）解开激活剂的设计规则;（iii）使用管道来研究TF如何适应异源宿主的进化规则。因此，学生将获得与未来在分子生物学和微生物学，生物技术，生物制药，工业生物技术和相关行业的职业高度相关的技能。实现这些目标将使研究人员能够快速表征功能（即结合偏好），将该TF并入任何期望的调控网络中，并通过计算预测将含有所需调控逻辑并导致所需转录表达水平的启动子序列。

A key challenge in engineering biological systems is the development of re-usable, precise and tunable gene expression control elements. Currently, developing these systems requires expensive and time-consuming experiments based on trial-and-error. This is particularly problematic for applications requiring complex systems with multiple co-regulated components or systems that use components obtained from non-model microorganisms. This project will develop tools to systematically characterise transcriptional control elements, uncovering their design rules to enable re-use of these control elements in alternative hosts and genetic contexts. Transcriptional regulation in prokaryotes is achieved primarily through the binding of transcription factors (TFs) to a promoter. Each TF has a specific binding preference, which determines its function (activator or repressor) and the location of its binding site(s) within a promoter. Knowing the biophysical binding preferences of TFs, hence, enables computational prediction of the regulatory logic and the transcriptional activity of any given promoter1,2. Currently, however, the biophysical binding preferences are known for only a handful of TFs, meaning that we cannot easily exploit heterologous TFs in bioengineering. In this interdisciplinary project, the student will utilize a range of molecular/synthetic biology, microbiology, and biophysical approaches to: (i) develop an experimental and data analysis pipeline that can determine the binding preferences of any given TF; (ii) unravel design rules of activators; (iii) use the pipeline to study the evolutionary rules governing how TFs adapt to heterologous hosts. As such the student will acquire skills that are highly relevant for future careers in the molecular biology and microbiology, biotechnology, biopharmaceutical, industrial biotechnology and related industries.Achieving these objectives will enable researchers to rapidly characterize the function (i.e. binding preference) of any desired TF, incorporate that TF into any desired regulatory network, and computationally predict promoter sequences that would contain a desired regulatory logic and result in desired transcriptional expression levels.