DNA inside cells is not the neat double helix of textbook diagrams—it is coiled, twisted, and knotted under stress, and these contortions alter how the molecule interacts with the machinery that reads, repairs, and edits it. Current structural tools struggle to capture this complexity because they require averaging over many molecules or work in non-physiological conditions. The researcher has developed a high-resolution atomic force microscopy (AFM) method that images single DNA molecules in liquid at body temperature, revealing variations in helical structure along a single strand. But AFM is slow and operator-dependent, limiting its use. This project will automate AFM analysis using machine learning, making the technique accessible to non-specialists and reproducible. If successful, the approach will map how DNA topology affects interactions with three medically important systems: topoisomerases (targets of antibiotics and cancer drugs), CRISPR-Cas9, and G-quadruplexes (alternative DNA structures being explored as anti-cancer targets). The work is fundamental science—it aims to understand how physical stress on DNA shapes its function—but it could directly inform rational drug design by revealing structural features that existing methods miss.
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Rosalind Franklin's pioneering work to establish the atomic structure of DNA has underpinned much of our understanding of the 'molecule of life', however in the cell, DNA is tangled and twisted, adopts complex topologies and is frequently maintained under superhelical stress. The effect of coiling, twisting and knotting on complex genomic DNA affects its function and how it interacts with molecular machinery. However the complexity and flexibility of this molecule means that much about the structure and interactions of tangled and twisted DNA remains poorly defined. It is critical that we improve this understanding as complex DNA structures, which make up the majority of the genome, have a huge impact on our health: in aging, cancer and fighting infectious disease. The defining feature of AFM, unique among other structural tools operating at sub-nanometre resolution, is its capacity for imaging single molecules in liquid at physiological temperatures, where biomolecules are active (and free to explore their native conformational space), albeit tethered to a surface. AFM uses a sharp probe to 'feel' the surface of molecules adsorbed on a flat substrate, with nanometre precision in liquid. My high-resolution atomic force microscopy (AFM) methods are unique in their ability to provide quantitative information on DNA structure, function and kinetics without labelling or averaging, demonstrated by my work showing variation in the double-helical structure of DNA along a single molecule. Despite its unique capabilities for observing individual molecules at high resolution in fluid, the widespread adoption of AFM has been limited by the complexity of the technique, and the limited analysis of the powerful data produced. Traditionally, the majority of AFM analysis has been carried out by hand, relying on a highly trained and experienced researcher. When coupled with data acquisition that is highly dependent on the expertise of the operator, this has meant that AFM has not been adopted as the tool that can solve problems currently inaccessible to other tools of structural biology, which operate at this length scale. I will pioneer the use of high-resolution AFM and automated analysis to overcome these limitations and uncover the effect of DNA structure and conformation on DNA-protein interactions. To achieve this I will work in collaboration with industry to combine state-of-the-art atomic force microscopy developments, with new automated analysis tools that facilitate tracing and quantification of the topology, structure and conformation of DNA substrates, using multiple machine learning approaches. I will work with the AFM community to ensure that these tools are available to researchers at all levels, improving the reproducibility of their analysis, and lowering the activation energy for this method of imaging, currently a considerable barrier to entry. Using these tools I will determine how the structural heterogeneity of DNA impacts its interactions with key antibiotic and anti-cancer targets: topoisomerases; the gene editing tool CRISPR-Cas9; and G-quadruplexes, alternative DNA structures with potential as new anti-cancer targets. This programme is focussed on systems with translational potential, to enable me to impact pharmaceutical development. This ambitious programme is underpinned by my expertise in high-resolution AFM and supported by a diverse interdisciplinary team including an AFM manufacturer, and experts in complementary single-molecule biophysics techniques, machine learning, molecular dynamics simulations and biochemistry. Together we will uncover the hidden effect of topological stress in the genome on interactions across its entire conformational landscape. This knowledge can be harnessed to combat disease by aiding in the rational design of novel therapeutics.
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