Seeman Student Travel Awards at DNA31
Joshua Petrack, UC Davis, USA
Our work is a simulation algorithm for a model that scientists might use to create DNA-based designs and predict how they will behave. By simulating this model more quickly while still maintaining accuracy, it will be possible to iterate these designs more quickly. Designing individual molecules to behave how you want is a finicky problem, so predictive models and tools are crucial. Our field is wonderful because it brings theorists like myself who can demonstrate exactly what promises a predictive tool like this can make together with the people who will actually use that tool. We actually do work directly together, sharing a common understanding of the kinds of problems we face in the field and leveraging all the strengths and knowledge from our different backgrounds to propel our mutual understanding forward.
Kate Collins, Imperial College London, United Kingdom
In industrial manufacturing plants, complex products are often assembled on moving conveyor belts, with static robots sequentially adding components. I aim to apply the concept of assembly lines on the nanoscale in order to produce complex molecules. Instead of factories, I work with networks of microscopic channels, known as microfluidic devices. Here, liquid flow in channels acts as conveyor belts, moving products to different ‘stations’. Each station consists of molecules bound to the channel surface, sequentially adding molecular components. At DNA31, my poster will describe a method to produce such stations inside microfluidic devices. I use UV-light to pattern chemical groups on channel surfaces, and then functionalize these groups with DNA strands, proteins, and nanoparticles. Using this method, we can position gene-encoding DNA but also use DNA nanotechnology to reversibly functionalize specific patterns. This constitutes a step towards flexible, programmable molecular assembly lines in microfluidic devices.
Kohei Nishiyama, University of Mainz, Germany
I have been fascinated by how complex spatiotemporal dynamics can emerge from the coordinated interactions of multiple chemical species. This interest led me to explore the reaction–diffusion behavior of DNA, which can be precisely programmed through rational sequence design. In our current research, we investigate how the sequence and the initial spatial distribution of DNA affect the emergence of collective chemical patterns through reaction–diffusion processes. Using high-resolution patterning techniques, we construct arrays of DNA-based reaction hubs that interact via designed DNA circuits to produce diverse and dynamic behaviors. Our work extends Ned Seeman’s vision of “controlling matter with chemical information” into the spatiotemporal domain. By converting static molecular inputs into dynamic spatial patterns, this system not only offers a model for understanding biological pattern formation but also represents a promising platform for future neuromorphic computing based on distributed molecular communication.
Myoungseok Kim, UC Berkeley, USA
As a mechanical and electrical engineer, I am fascinated by the beauty, strength, and precision of DNA nanotechnology, which enables design, construction, and programming of arbitrary molecular platforms at the nanoscale. My research focused on (1) developing design principles for robust multi-reconfiguration of foldable DNA origami (by optimizing the mechanical flexibility of strain energy and the chemical orthogonality of DNA hybridization) and (2) constructing molecular numeral systems of programmable multi-base and multi-digit using folding-based proximity control with optical readouts. This multiplexed control enabled the implementation of 7-bit encoding of 128 characters with secure information interchange and data storage for simple arithmetic operations. By providing a more scalable, deployable, and 3D transformable approach, I envision this research will advance the field of molecular programming and accomplish even more extended and complex signal processing, which could be highly received by Ned Seeman’s vision of controlling and programming DNA platforms with computing information.
Salvador Buse, California Institute of Technology, USA
My path into molecular programming was by way of developmental biology. I have always been completely fascinated by pattern formation and morphogenesis — it is astonishing that the few billion base pairs of DNA in a fertilised egg can grow into something as complex as a human being. I came to realise that at the level of ‘algorithms’ of development, a huge amount remains unknown. Molecular programming is uniquely well-placed to study this problem: unlike artificial life, we share physical reality with biology; unlike developmental or synthetic biology, we benefit from the sorts of simplicity and abstractions that make computer programming so powerful. Our DNA31 paper on indexed chemical reaction networks emerged from a desire to explore some of the connections between chemistry, neural networks, and morphogenesis, and to run related differentiable simulations. We developed software we hope others will find useful in pursuing an even wider set of questions.
Zoë Derauf, University of Washington, USA
My research on polymerase-mediated strand displacement systems reflects my broader vision for DNA computing as a platform for building programmable, adaptive molecular systems that function reliably in complex, real-world environments. I am drawn to this field for its unique blend of creativity, precision, and potential to transform diagnostics, therapeutics, and synthetic biology. Ned Seeman’s pioneering vision of DNA as a material for nanoscale engineering continues to inspire my work, which aims to transform DNA’s role as nature’s information system, into systems capable of sensing, decision-making, and actuation. By tackling key challenges such as signal leakage, I aim to contribute towards the development of architectures that are robust, scalable, and accessible, enabling molecular programs to operate with the reliability needed for practical applications. Ultimately, I hope to help advance the field toward deployable molecular tools that seamlessly interface with biological systems, expanding the reach of molecular programming into point-of-care medicine and other impactful domains.
