Programming DNA topology: from folding DNA minicircles to revealing the spatial organization of bacterial genomes

虽然快速的DNA测序导致了可用遗传信息数量的显著增加，但我们对DNA如何运作的全面理解仍然很遥远。最近的实验表明，DNA环和折叠是基因在打开和关闭状态之间切换的基本机制，基因表达的不同模式受到基因组空间组织的强烈影响。这导致了遗传信息也可能通过DNA拓扑编码的想法，并强调了研究DNA及其相互作用分子的物理特性的重要性。对DNA拓扑结构的理解将为我们提供进一步控制遗传信息和设计最优基因组以用于合成生物学的能力。在这项研究中，我的目标是获得在广泛的长度尺度上编程和预测DNA拓扑结构的能力：从大约千bp （kbp）尺度的DNA微环到包含几个兆bp （Mbps）的细菌基因组。为了解决这个问题，我建议开发一种基于物理的计算方法，其范围将从建立原子和粗粒度模拟的协议和模型到开发用于快速预测DNA拓扑结构的统计力学算法。这些理论方法将是互补的，并将由一组适当的实验来支持，这些实验使用一系列单分子技术，包括原子力显微镜（AFM）。首先，我计划通过设计和模拟人工折叠的DNA小环来量化DNA编码其自身拓扑结构的能力以及它与DNA识别蛋白的相互依赖性。然后，我将把获得的结构信息转移到开发一种有效的预测算法，该算法将转化为“全基因组DNA环定位器”。由于超螺旋DNA环的顶端部分是由单个螺旋旋转（大约）决定的，因此提取碱基对水平上的波动将足以处理基因组尺度上的序列。一个概念验证系统的选择将被用来阐明DNA拓扑的控制规则和测试新的计算方法。随后，获得的技术可以很容易地应用到许多有趣的案例中。对具有特定构象的DNA微环进行编程的能力将对基因治疗产生影响，因为这些微小的DNA分子被认为是将遗传物质引入细胞而没有负面副作用的高效试剂。与此同时，“全基因组DNA环定位器”将用于预测细菌基因组的结构，因此，将有助于设计具有组成表达合成代谢途径的遗传稳定微生物。因此，如果拟议的研究取得成功，其影响可能是广泛的，因为它将导致医疗保健和合成生物学领域的进步。通过开发新的有效诊断和药物，并通过提高其应对重要社会经济挑战的能力，包括可再生能源、清洁水和安全食品的供应，从长远来看，这将有利于社会。

While rapid DNA sequencing has led to significant increases in the amount of genetic information available, we are still far from a comprehensive understanding of how DNA operates. Recent experiments have shown that DNA looping and folding are essential mechanisms in the switching of genes between their on and off states and that different patterns of gene expression are strongly influenced by genomic spatial organisation. This has led to the idea that genetic information may also be encoded through DNA topology and highlights the importance of studying the physical properties of DNA and its interacting molecules. An understanding of DNA topology will provide us with the capacity to further control genetic information and to design genomes optimal for utilisation in synthetic biology. In this fellowship, I aim to obtain the ability to program and predict DNA topology on a broad range of length scales: from DNA minicircles around the kilo-bp (kbp) scale to bacterial genomes containing several mega-bps (Mbps).To tackle this issue, I propose to develop a physics-based computational methodology that will range from establishing protocols and models for atomistic and coarse-grained simulations to the development of a statistical-mechanics algorithm for the fast prediction of the topology of DNA. These theoretical methods will be complementary and will be supported by an appropriate set of experiments performed using a range of single molecule techniques, including atomic force microscopy (AFM) . Firstly, I plan to quantify the capacity of DNA to encode its own topology and its interdependence with DNA-recognising proteins by means of the design and modelling of artificially folded DNA minicircles. I will then transfer the acquired structural information towards developing an efficient prediction algorithm that will be converted into a "genome-wide DNA loop locator". As the apical part of a supercoiled DNA loop is determined by a single helical turn (approximately), an extraction of the fluctuations at the base-pair level will be sufficient to deal with sequences at the genomic scale. A selection of proof-of-concept systems will be used to elucidate the governing rules of DNA topology and to test the novel computational methodology. The gained technology could then be easily applied to a multitude of interesting cases soon after. The capability to program DNA minicircles with a specific conformation will have consequences on gene therapy because these tiny DNA molecules are being recognised as highly efficient agents for the introduction of genetic material into cells without negative side effects. In parallel, the "genome-wide DNA loop locator" will be used to predict the architecture of bacterial genomes and, as a consequence, will help in the design of genetically stable microorganisms with constitutively-expressed synthetic metabolic routes. Thus, if the proposed research is successful, its impact could be broad as it would lead to advances in the fields of healthcare and synthetic biology. It would benefit society in the longer term, through the development of new effective diagnoses and medicines and through increasing its capacity to tackle important socioeconomic challenges, including the supply of renewable energy, clean water and safe food.