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

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.

The proposed research will produce two main deliverables with impact beyond academia. Firstly, a new computational capability will be acquired for predicting the design of DNA minicircles targeted to specific medically relevant cases. Secondly, a new computational approach to predict DNA topology will be obtained which will provide knowledge of the optimum rearrangements in genomic engineering. The impact of these two deliverables will target the healthcare and synthetic biology sectors, respectively.

DNA minicircles are being recognised as a highly efficient way for introducing exogenous genetic material into cells without negative side effects. As a consequence, this promising gene therapy technology is being tested in a broad range of cases including treatment of human lymphoma, early diagnosis of cancer, and cellular reprogramming for regenerative medicine. Thus, the capacity to design case-specific DNA minicircles will be of high interest to a broad range of companies within the pharmaceutical sector and, in the long term, will benefit public health.

The pharmaceutical industry has faced a persistent increase in the average costs of developing a drug in the last few decades. Hence, the appearance of novel gene-targeting treatments has created high expectations. Particularly, the approval in November 2012 of the first gene therapy (uniQure's Glybera) in Europe and the United States was an important milestone, boosting interest in this technology. For example, according to an article in Forbes magazine, the investment in gene therapy research by US companies alone totalled over US$600m between January 2013 and April 2014 [1]. In parallel, in silico methods have been crucial in the decrease of the costs associated with pharmaceutical research as their predictive power has become a shortcut for experimental design. With an ageing society increasingly dependant on new medicines, the development of future therapies has become a major public concern as is reflected in the EPSRC Healthcare Technologies theme. In light of these reasons, the computational methods proposed in this fellowship will have an impact in the pharmaceutical industry and will benefit society by dealing with the challenge of developing effective diagnoses and medicines.

Progress in bacterial genomic engineering is absolutely crucial for the design of producers effective enough for industrial commercialisation. So far, attempts to introduce metabolic pathways in bacteria have relied on the use of plasmid-based systems, separated from the main chromosome, that suffer from genetic instability and compromise the overall productivity. Thus, a new approach for improving genomic transformations directed to enhance the biosynthetic capacity will benefit a broad range of companies within the field of synthetic biology. According to the "Synthetic biology roadmap for the UK'', advances in the use of microorganisms as "biofactories" will be crucial in tackling major societal challenges such as reducing the dependence on non-renewable energy supplies through biofuel production, bio-remediation of water or progress in innovative manufacturing. Moreover, taking advantage of the opportunities raised by synthetic biology will lead to economic growth and the creation of highly-paid jobs. Specifically, according to estimations from the BCC Research 2014 report, the global synthetic biology market is expected to grow at 34.4% annually, from $2.7 billion in 2013 to $11.8 billion in 2018.

[1] Matthew Harper, "Gene Therapy's Big Comeback", 2014, Forbes.