Liquid-liquid phase separation (LLPS) is a thermodynamic process by which a mixture of solutions de-mixes into separate, coexisting phases. In cells, macromolecules such as proteins and nucleic acids can undergo LLPS to form membraneless structures known as biomolecular condensates. These condensates are usually liquid-like droplets highly concentrated in the species they are composed of. Condensates are crucial to many cellular processes and functions, such as protein assembly, gene regulation, subcellular organization, storage, and stress response. On a larger scale, condensates are also implicated in various neurodegenerative diseases, such as Huntington's and Alzheimer's disease.
\r\n\r\nDNA condensates are easy to engineer due to the programmable nature of the molecule. DNA nanostars are multi-armed junctions with double-stranded arms and typically single-stranded, palindromic overhangs or 'sticky ends' that allow for transient interactions between the molecules. They can phase-separate to form liquid-like droplets at the microscopic scale. Centrifugation of a high concentration solution of nanostars coalesces condensates into a macroscopic liquid that is visible to the naked eye.
\r\n\r\nIn biology, one of the key functions of condensates is to act as compartments and localize various molecules, such as enzymes and nucleic acids. Our goal is to engineer macroscopic DNA liquids to similarly act as compartments that can separate multiple biomolecular targets. We propose that these macroscopic DNA liquids are a potentially novel method for multiplexed separation that is fast, simple to use, and biocompatible with various high-value targets, such as protein therapeutics.
\r\n\r\nWe designed multiple immiscible DNA liquids of different densities to act as macroscopic compartments. We present a set of design principles for engineering nanostars to create liquid layers in a microcentrifuge tube. We show via UV absorbance measurements how various nanostar features, such as arm length, sticky end strength, and valency, affect liquid phase density, which determines the order of layering between liquids. We further show that the interface quality between pairwise liquids is determined by a combination of density differences between liquids and the orthogonality of nanostar sticky ends, and we devise a metric to calculate this orthogonality. Using these design principles, we are currently able to create up to five orthogonal liquid layers in a tube.
\r\n\r\nWith these DNA liquid layers, we envision separation to be a two step process. The first step is to localize specific target biomolecules into these layers. We demonstrate localization of oligos in a multilayer DNA liquid system by modifying nanostars with tag regions complementary to the target strand. We also demonstrate localization of fluorescent streptavidin to a single DNA liquid layer by modifying nanostars with a streptavidin-binding aptamer. The second step is to release targets from the liquid layers so that they can be collected for downstream use. After localization of the aforementioned targets, we added strands complementary to either the tag region or the aptamer. This causes targets to be displaced from their binding moiety and released into the supernatant.
", "doi": "10.7907/3639-5v91", "publication_date": "2026", "thesis_type": "phd", "thesis_year": "2026" }, { "id": "thesis:17148", "collection": "thesis", "collection_id": "17148", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:04092025-234838672", "primary_object_url": { "basename": "DavidsonSamuel2025_Thesis (Version 2025-04-08).pdf", "content": "final", "filesize": 24258588, "license": "cc_by_nc_sa", "mime_type": "application/pdf", "url": "/17148/1/DavidsonSamuel2025_Thesis (Version 2025-04-08).pdf", "version": "v6.0.0" }, "type": "thesis", "title": "Localized Catalytic DNA Circuits for Integrated Information Processing in Molecular Machines", "author": [ { "family_name": "Davidson", "given_name": "Samuel Ryan", "orcid": "0000-0002-8081-3591", "clpid": "Davidson-Samuel-Ryan" } ], "thesis_advisor": [ { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "thesis_committee": [ { "family_name": "Pierce", "given_name": "Niles A.", "orcid": "0000-0003-2367-4406", "clpid": "Pierce-N-A" }, { "family_name": "Winfree", "given_name": "Erik", "orcid": "0000-0002-5899-7523", "clpid": "Winfree-E" }, { "family_name": "Wang", "given_name": "Kaihang", "orcid": "0000-0001-7657-8755", "clpid": "Wang-Kaihang" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "This thesis supports the long-term goal of engineering molecular devices with computational complexity akin to cells. Like cells, artificial molecular devices can benefit from integrating multiple computational modalities.
\r\n \r\nTo that end, this thesis advances molecular computing systems in three modalities: dynamic molecular assembly, well-mixed circuits, and spatially-organized cascades. Specifically, it introduces methods to enhance control over DNA structural assembly, well-mixed DNA circuits, and DNA circuits localized to a DNA origami surface.
\r\n \r\nAs DNA structural assembly grows increasingly complex, so too grows the potential for off-target structures. This issue can be addressed through developmental self-assembly, where components join a growing structure in a programmed sequence under controlled kinetics. The scope of developmental self-assembly is here expanded by a method enabling specific pathway selection among multiple encoded options.
\r\n \r\nWell-mixed DNA circuits require catalytic motifs for signal restoration and amplification. A catalytic motif is presented where two input strands cooperate to control catalysis. This motif could enhance AND gates and thresholding, and could enable adaptive memories and learning behaviors in DNA-based neural networks.
\r\n\r\nLocalized DNA circuits lack cascadable catalytic mechanisms for signal restoration and amplification. Two designs for a localized catalytic mechanism are presented. Each omits any intermediate diffusible species to support nanodevices compatible with uncontrolled environments, as in biomedical contexts. This constraint leads to design lessons; principally, we respond to leak in the first design through geometric constraints in the second design.
", "doi": "10.7907/831v-vq95", "publication_date": "2025", "thesis_type": "phd", "thesis_year": "2025" }, { "id": "thesis:16363", "collection": "thesis", "collection_id": "16363", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:04292024-172707491", "primary_object_url": { "basename": "Thesis_Cherry_Kevin_Redacted.pdf", "content": "final", "filesize": 20088636, "license": "other", "mime_type": "application/pdf", "url": "/16363/6/Thesis_Cherry_Kevin_Redacted.pdf", "version": "v5.0.0" }, "type": "thesis", "title": "Molecular Pattern Recognition and Supervised Learning in DNA-Based Neural Networks", "author": [ { "family_name": "Cherry", "given_name": "Kevin Matthew", "orcid": "0000-0002-2343-0754", "clpid": "Cherry-Kevin-Matthew" } ], "thesis_advisor": [ { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "thesis_committee": [ { "family_name": "Winfree", "given_name": "Erik", "orcid": "0000-0002-5899-7523", "clpid": "Winfree-E" }, { "family_name": "Yue", "given_name": "Yisong", "orcid": "0000-0001-9127-1989", "clpid": "Yue-Yisong" }, { "family_name": "Rothemund", "given_name": "Paul W. K.", "orcid": "0000-0002-1653-3202", "clpid": "Rothemund-P-W-K" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "Adaptation in nature begins at the subcellular, molecular level with the delicate interplay of biomolecule cascades orchestrating the myriad function of cells. The intermingling activity of these cells becomes expressions of complex behavior of multi-cellular system. Nature provides a dazzling array of examples showcasing the variations of intelligent functions. However, in the realm of synthetic construction, what systems have humans managed to engineer, and what are the boundaries of our technological power? In comparison to nature's repertoire, mankind's accomplishments appear rather modest. The intricate behaviors observed in intelligent organisms emerge from the collective interactions and feedback loops among their constituent elements, resulting in the emergence of novel properties and phenomena. To develop large-scale engineered systems exhibiting ever more brain-like, intelligent behaviors, we must first devise new molecular architectures and algorithms designed for adaptation and learning at the molecular scale. My research presented here is a humble step toward those goals. I will present the design of novel molecular systems made from DNA that exhibit complex neural computation and learning behaviors.
\r\n\r\nChapter 2 covers my contribution to scaling up the computing power of DNA circuits. From bacteria following simple chemical gradients to the brain distinguishing complex odor information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks. Winner-take-all computation has been suggested as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits and Hopfield networks used previously, winner-take-all circuits are computationally more powerful, allow simpler molecular implementation, and are not constrained by coupling the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here, we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement reactions. We use a previously developed seesaw DNA gate motif, extended to include a simple and robust component that facilitates the cooperative hybridization involved in selecting a \u2018winner.' We show that with this extended seesaw motif, DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10x10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits \u20181\u2019 to \u20189.' The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns \u2018remembered\u2019 during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory.
\r\n\r\nChapter 3 investigates the development of a computational neural network model inspired by biological learning mechanisms, particularly focusing on the new mechanisms for learning in a WTA neural network. The study incorporates novel molecular motifs used in inhibited activators and inhibited weights, designed specifically for training from environmental input patterns. These motifs emulate biological systems by facilitating memory storage and retrieval within DNA-based neural networks, similar to synaptic connections and signal processing observed in living organisms. We assess the function of the individual molecular motifs and characterize their specificity in up to 18-species cross-talk experiments. Furthermore, we characterize the network's performance across a wide array of training and test patterns, mirroring the adaptive responses and diverse conditions encountered by biological systems. Additionally, we analyze the computational efficiency and speed of the learning system, comparing it with both the previous non-learning DNA-based WTA model and a direct weight activation model. By exploring the principles of molecular learning, particularly within winner-take-all neural networks, this study aims to advance computational systems by emulating adaptability and resilience observed in biological organisms using robust, new molecular motifs.
", "doi": "10.7907/529f-kf62", "publication_date": "2024", "thesis_type": "phd", "thesis_year": "2024" }, { "id": "thesis:15093", "collection": "thesis", "collection_id": "15093", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:01272023-184413283", "primary_object_url": { "basename": "Thesis.pdf", "content": "final", "filesize": 16608292, "license": "other", "mime_type": "application/pdf", "url": "/15093/1/Thesis.pdf", "version": "v4.0.0" }, "type": "thesis", "title": "Towards Integrated Molecular Machines: Structural, Mechanical, and Computational Motifs", "author": [ { "family_name": "Sarraf", "given_name": "Namita", "orcid": "0000-0001-8692-7429", "clpid": "Sarraf-Namita" } ], "thesis_advisor": [ { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "thesis_committee": [ { "family_name": "Shapiro", "given_name": "Mikhail G.", "orcid": "0000-0002-0291-4215", "clpid": "Shapiro-M-G" }, { "family_name": "Murray", "given_name": "Richard M.", "orcid": "0000-0002-5785-7481", "clpid": "Murray-R-M" }, { "family_name": "Rothemund", "given_name": "Paul W. K.", "orcid": "0000-0002-1653-3202", "clpid": "Rothemund-P-W-K" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "The programmability of DNA has made it well-suited for building molecular machines, performing nanoscale self-assembly, and computing via biochemical circuits. In the last few decades, great strides have been made in characterizing the interactions between DNA molecules such that they can be predicted and engineered.
\r\n\r\nThe development of frameworks for those interactions has enabled the construction of more complex molecular systems that can execute specified programs. Such programs have included mechanical tasks, like walking and sorting cargo; assembly and reconfiguration of 2D and 3D shapes; and computation, like Boolean logic and pattern recognition.
\r\n\r\nHowever, the continuing development of more complex molecular programs relies upon expanding the modules available for molecular systems to use to execute them. Expanded functionality of mechanical, structural, and computation modules are required in order to build compound systems that can interact with the physical world, reconfigure, and analyze signals in a variety of interesting ways. In this dissertation, we will discuss our contributions to this effort, which include exploring a motif for molecular robotic behavior, characterizing tile-tile interactions, and developing new capabilities for bimolecular circuits.
\r\n\r\nWithin the framework of a maze-solving molecular robot, we aim to implement walking behavior on DNA origami that introduces a surface modification via a four-way strand displacement reaction. Surprisingly, our experiments suggest that the walking behavior is at least two orders of magnitude slower than expected. To understand why, we quantitatively explore to what extent the speed and completion level of the robot can be modulated by design considerations such as toehold lengths, track redundancy, and strand purity. Another factor affecting the reaction rate is the number of tethering points, and we demonstrate an order of magnitude speed up in the four-way strand displacement reaction when we remove one tethering point. The characterization of a surface-modifying four-way strand displacement reaction is a useful tool for the continued development of molecular robots with more complex functionality.
\r\n\r\nFree-floating DNA origami tiles, called invaders here, can swap out DNA origami tiles within larger assemblies via a technique called tile displacement, which has previously been demonstrated using single tile and dimer invaders with 4- and 9-tile arrays. We introduce initial structures and invading assemblies with more complex shapes. We explore the robustness of this reaction by testing a variety of edge configurations and comparing their reaction rates. We demonstrate tunable growth of one of the invaders, which can grow into polymers of arbitrary length or close into 3D structures. By a tile displacement reaction, we reconfigure the 3D structures into 2D. The invaders with complex shapes are able to reconfigure the original tile assembly at rates comparable to simpler tile displacement reactions, and two reconfiguration events can take place sequentially or simultaneously.
\r\n\r\nFinally, we build two new modules for use with biochemical circuits. The first, a loser-take-all circuit, yields binary outputs indicating which analog signal is the smallest among all inputs. We implement a signal reversal function that converts the smallest input to the largest output, which can then be composed with a previously developed winner-take-all function to achieve loser-take-all. By making concentration adjustments, we can mitigate biases in the circuit that are a result of sequence-dependent different in reaction rates. We experimentally demonstrate a three-input loser-take-all circuit with nine input combinations. With further development, this circuit could be used to implement the activation function in neural networks that perform pattern classification according to which memory an input pattern is least similar to.
\r\n\r\nThe second circuit processes information using temporary memory. We design and implement a circuit that outputs distinct logic decisions based on relative timing information of a pair inputs and their logic values. We show that we can mitigate crosstalk in the circuit by utilizing mismatches and adjusting toehold lengths. The circuit is able to display clear ON-OFF separation at time intervals as short as one minute between the two inputs arriving.
", "doi": "10.7907/cdwp-c709", "publication_date": "2023", "thesis_type": "phd", "thesis_year": "2023" }, { "id": "thesis:13687", "collection": "thesis", "collection_id": "13687", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:04292020-052418975", "type": "thesis", "title": "Formal Design and Analysis for DNA Implementations of Chemical Reaction Networks", "author": [ { "family_name": "Johnson", "given_name": "Robert Francis", "orcid": "0000-0002-5340-8347", "clpid": "Johnson-Robert-Francis" } ], "thesis_advisor": [ { "family_name": "Winfree", "given_name": "Erik", "orcid": "0000-0002-5899-7523", "clpid": "Winfree-E" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "thesis_committee": [ { "family_name": "Murray", "given_name": "Richard M.", "orcid": "0000-0002-5785-7481", "clpid": "Murray-R-M" }, { "family_name": "Pierce", "given_name": "Niles A.", "orcid": "0000-0003-2367-4406", "clpid": "Pierce-N-A" }, { "family_name": "Bruck", "given_name": "Jehoshua", "orcid": "0000-0001-8474-0812", "clpid": "Bruck-J" }, { "family_name": "Winfree", "given_name": "Erik", "orcid": "0000-0002-5899-7523", "clpid": "Winfree-E" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "In molecular programming, the Chemical Reaction Network model is often used to describe systems of interacting molecules. This model can describe either real systems, allowing us to analyze and determine their computational function; or describe hypothetical systems, with known computational function but perhaps no known physical example. One significant breakthrough in the field is that any Chemical Reaction Network can be approximated by a system using DNA Strand Displacement mechanisms. This allows the Chemical Reaction Network model to be treated like a programming language, where programs can be written in the abstract and then compiled into physical molecules. Given a programming language and a proof-of-concept compiler, one would want to take the compiler from the proof-of-concept stage into a more reliable, more systematic, and better understood process. This thesis is made up of my contributions to that effort.
\r\n\r\nFirst, given a programming language and a compiler, it would be useful to formally verify that the compiler is correct. My collaborators, Qing Dong and Erik Winfree, and I defined a Chemical Reaction Network-specific form of bisimulation equivalence, which can compare two such networks and verify that one is (or is not) a correct implementation of the other. For example, the compiler-produced DNA circuit can be verified as an implementation of its abstract program, although this is not the only possible use. After defining this concept of equivalence, we show that it can be checked by algorithm; although various parts of the problem are NP-complete or PSPACE-complete, we give algorithms that meet these lower bounds. We also prove a number of interesting properties of Chemical Reaction Network bisimulation equivalence, including transitivity and modularity properties which are particularly useful for stepwise checking of large systems. We further extend this bisimulation method to linear Polymer Reaction Networks, a strictly more powerful abstraction which has been occasionally used in molecular programming. Again we prove complexity hardness results, which in this case are as expected uncomputable in the general case; however, many practical systems can still be verified, and we give one such example. Finally, we use bisimulation to identify a class of single-locus networks that are practical to implement. Thus we show a method of verification which can simplify use of the above-mentioned compiler by proving general statements of correctness about its results.
\r\n\r\nSecond, given a programming language and a concept of compiling it, it would be useful to optimize the result of the compilation. One particular area of optimization is the number of DNA strands per prepared complex; some experiments suggest that systems with no more than 2 strands per complex are more robust. Lulu Qian and I developed some proposed DNA Strand Displacement schemes for general Chemical Reaction Network implementations with no more than 2 strands per complex, and a number of other desirable properties. Meanwhile, having been shown to be useful for many reasons, the mechanisms of DNA Strand Displacement have recently been formalized, abstracted, and analyzed. I show that this formalization, combined with the bisimulation methods above, can prove various statements about the limits of DNA Strand Displacement systems. For example, a set of desirable conditions including the 2-strand limit cannot be achieved by any general Chemical Reaction Network implementation scheme. I also observe that two of the new schemes we discovered, each meeting all but one condition of the impossible set, were found in the process of coming up with this proof. I thus argue that through formalization of DNA Strand Displacement we can have a more systematic method of finding and designing molecular programs, and of knowing when the programs we want do not exist.
", "doi": "10.7907/a74v-kv80", "publication_date": "2020", "thesis_type": "phd", "thesis_year": "2020" }, { "id": "thesis:10980", "collection": "thesis", "collection_id": "10980", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:05312018-112853523", "primary_object_url": { "basename": "Philip Petersen Thesis Final 2.pdf", "content": "final", "filesize": 12657109, "license": "other", "mime_type": "application/pdf", "url": "/10980/1/Philip Petersen Thesis Final 2.pdf", "version": "v6.0.0" }, "type": "thesis", "title": "Engineering Molecular Self-assembly and Reconfiguration in DNA Nanostructures", "author": [ { "family_name": "Petersen", "given_name": "Philip Fai", "orcid": "0000-0002-9912-389X", "clpid": "Petersen-Philip-Fai" } ], "thesis_advisor": [ { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "thesis_committee": [ { "family_name": "Winfree", "given_name": "Erik", "orcid": "0000-0002-5899-7523", "clpid": "Winfree-E" }, { "family_name": "Rothemund", "given_name": "Paul W. K.", "orcid": "0000-0002-1653-3202", "clpid": "Rothemund-P-W-K" }, { "family_name": "Mayo", "given_name": "Stephen L.", "orcid": "0000-0002-9785-5018", "clpid": "Mayo-S-L" }, { "family_name": "Qian", "given_name": "Lulu", "orcid": "0000-0003-4115-2409", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "Smart electronics have developed ubiquitously to assist people in everything from navigation to health monitoring. The rise of complex electronics relied on rational design of platforms to build ever larger and more complex circuit networks and for frameworks to test those electronics. Biochemical circuits have also seen dramatic advancement in the last two decades within the field of DNA nanotechnology. As with electronics, DNA nanotechnology applied rational design to DNA molecules to build ever more complex biochemical networks that, beyond current electronics, also retain a significant measure of biological compatibility and plasticity akin to many networks of biological origin. Well situated for promising applications in diagnostics and therapeutics, advancing DNA nanotechnology devices will also rely upon larger platforms and testing frameworks.
\r\n\r\nIn roughly the last decade, researchers have been building upon the invention of DNA origami, a technique allowing the robust construction of biomolecular nano-structures capable of precise nanometer positioning of proteins, nanoparticles, and other molecules. DNA circuits have computed on the nanostructures; DNA robots have moved nanoparticles, made choices, and have even sorted cargo on the surface of a nanostructure. The complexity of circuits and devices continues to rise.
\r\n\r\nIn this thesis, we will discuss our contributions to the field of DNA nanotechnology by developing design rules and systematic approaches to controlling nanostructure complex assembly. These rules and approaches allow for the construction of molecular structures with a tunable diversity, large systems approaching the size of bacteria yet retaining nanometer precision, and biological plasticity inspired dynamic systems for arbitrary reconfiguration.
\r\n\r\nUsing a DNA origami tile tailored for array formation with a high continuous surface area, we create a framework inspired from molecular stochasticity for programming DNA array formation and gaining control over diversity of global properties through simple local rules. Three general forms of planar networks, random loops, mazes, and trees, were manipulated on the micron scale upon the self-assembled DNA arrays. We demonstrate control of several properties of the networks, such as branching rules, growth directions, the proximity between adjacent networks, and size distributions. The large diversity, in principle, allows for a wide, but tunable, testing environment for molecular circuits. By further applying these principles to subunits of finite assemblies, variable components may be mixed with fixed components potentially opening additional applications in high throughput device or drug screening.
\r\n\r\nNext we turned to expanding the platform size biochemical circuits may be built upon. While DNA origami allows nanometer precise placement, the size remains roughly below 0.05 um2. Toward making large arbitrarily complex structures with only a set of simple tiles, multi-stage self-assembly has been explored in theory and for small DNA tiles. None were successful experimentally with DNA origami. We developed a strategy for DNA origami: a simple rule set applied recursively in each stage of a hierarchical self-assembly process, and to significantly reduce costs, a constant set of unique DNA strands regardless of size. We also developed a software tool to automatically compile a designed surface pattern into experimental protocols. We experimentally demonstrated DNA origami arrays approaching the size of small bacteria, 0.5 um2, with several arbitrary patterns, each consisting of 8,704 specifically chosen pixel locations with nanometer precision, including a bacteria sized portrait of a bacteria. The large platform opens the door to more advanced molecular circuits for applications such as diagnostics.
\r\n\r\nFinally we demonstrated control over the dynamics of DNA origami reconfiguration in tile arrays. In an approach we call DNA tile displacement, we showed that a DNA origami array may have tiles arbitrarily replaced by another tile, including tiles of another shape or surface pattern. We also demonstrated control over the kinetics of tile displacement and performed several general purpose reconfigurations of DNA nanostructures. Examples include sequential reconfiguration, competitive reconfiguration, cooperative reconfiguration, and finally the scalability of multi-step reconfiguration as demonstrated through a fully playable nano-scale biomolecular tic-tac-toe game. The major ramifications are a plasticity more common to biology than to electronics\u2014molecular platforms with arbitrary patterning that can reconfigure an arbitrary part of the nanostructure in an arbitrary order based on environmental signals. In principle, such reconfiguration can allow advanced circuits with the capacity to adapt to environmental needs or heal damaged components.
\r\n", "doi": "10.7907/7FXP-8402", "publication_date": "2018", "thesis_type": "phd", "thesis_year": "2018" }, { "id": "thesis:10323", "collection": "thesis", "collection_id": "10323", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:06082017-194534497", "primary_object_url": { "basename": "Anu_Thubagere_BBE.pdf", "content": "final", "filesize": 18346331, "license": "other", "mime_type": "application/pdf", "url": "/10323/1/Anu_Thubagere_BBE.pdf", "version": "v4.0.0" }, "type": "thesis", "title": "Programming Complex Behavior in DNA-based Molecular Circuits and Robots", "author": [ { "family_name": "Thubagere Jagadeesh", "given_name": "Anupama", "clpid": "Thubagere-Jagadeesh-Anu" } ], "thesis_advisor": [ { "family_name": "Qian", "given_name": "Lulu", "clpid": "Qian-Lulu" }, { "family_name": "Murray", "given_name": "Richard M.", "clpid": "Murray-R-M" } ], "thesis_committee": [ { "family_name": "Murray", "given_name": "Richard M.", "clpid": "Murray-R-M" }, { "family_name": "Rothemund", "given_name": "Paul W. K.", "clpid": "Rothemund-P-W-K" }, { "family_name": "Shapiro", "given_name": "Mikhail G.", "clpid": "Shapiro-M-G" }, { "family_name": "Qian", "given_name": "Lulu", "clpid": "Qian-Lulu" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "Integrated electronic circuits, like those found in cellphones and computers, are ubiquitous in our information-driven society. The success of electronics has, in part, been due its modular architecture that enables individual components to be independently improved while the overall device functionality remains unchanged. Over the last two decades the emerging field of dynamic DNA nanotechnology has been trying to apply the underlying philosophy of electronics to biochemical circuits. DNA nanotechnology employs rationally designed DNA molecules as building blocks of biochemical circuits that can, in principle, enable powerful applications like diagnostics and therapeutics.
\r\n\r\nResearchers in the field of DNA nanotechnology have developed simple elements to construct biomolecular systems with desired functions. They have also developed molecular compilers for defining design principles. The cost of DNA synthesis has decreased by over three orders of magnitude in the past decade. This has lead to a non-trivial number of small scale circuits, like DNA-based logic gates and chemical oscillators, being implemented. However, the scalability of this approach has yet to be clearly demonstrated. n this thesis, we will discuss our main contributions to facilitating the advancement of DNA nanotechnology by developing systematic approaches for constructing modular DNA building blocks. These modules can be used to construct biochemical circuits and molecular robotic systems. The performance of the modules can be individually tuned and integrated into large-scale systems.
\r\n\r\nUsing automated circuit-design software and cheap unpurified DNA, we demonstrated the design and construction of a complex synthetic biochemical circuit consisting of 78 distinct DNA species. The circuit is capable of computing the transition rules of a cell updating its state based on its neighboring cells, defined in a classic computational model called cellular automata. Using a bottom-up approach, we first characterized the component necessary for basic Boolean logic computation. We then systematically integrated more circuit elements and eventually constructed the full circuit. By developing a systematic procedure for building DNA-based circuits using unpurified components, we significantly simplified the experimental procedure. By using unpurified DNA components, we reduced the cost and technical barrier for circuit construction, thus making the design and synthesis of complex DNA circuits accessible to even novice researchers.
\r\n\r\nNext we demonstrated a cargo sorting DNA nano-robot, using a simple algorithm and modular building blocks. The DNA robot has a leg and two foot domains for exploring a two-dimensional DNA origami surface, and an arm and hand domain for picking up randomly located cargos and dropping them off at their designated locations. It is completely autonomous and is programmed to perform a random walk without requiring an external energy source. Further, we demonstrated sorting multiple copies of two distinct cargo species on the same origami. Additionally, by compartmentalizing each sorting task on a single origami, we showed that two distinct sorting tasks can be implemented on different origami simultaneously in the same test tube. The recognition of a cargo is embedded in its destination, therefore it is possible to scale up the system simply by having multiple types of cargos. The same robot design can be used for performing multiple instances of distinct tasks in parallel. The different modules can be integrated to perform diverse functions, including applications in time-release targeted therapeutics.
", "doi": "10.7907/Z9WD3XMS", "publication_date": "2017-06-16", "thesis_type": "phd", "thesis_year": "2017" } ]