Biomod/2011/Caltech/DeoxyriboNucleicAwesome/Project

Tuesday, April 16, 2024 Home Members Project Protocols Progress Discussion References

Project Design Overall Project Design Main article: Domain Level Project Design DNA, which encodes most organisms in nature, is considered as an effective medium for representing and storing information. Noting that a computer can be modeled as a device that can carry out computation to produce desired output data for the given input data, we conclude that finding a way of processing data represented by DNA will lead to establishment of a new computational model, or a DNA computer. In this process, we tried to imitate and recreate nature’s precise and intricate engineering unmatched by the most sophisticated engineering of the mankind. In fact, many different approaches for DNA computing have been studied in the last decade. One example would be Georg Seelig’s implementation of logic gates using Watson-Crick base pairing and strand displacement between DNA segments that represent different data [1]. Another example is David Soloveichik’s work on chemical reaction networks, where it was shown that chemical reactions can be implemented by a cascade of DNA reactions and that such chemical reaction networks are actually Turing-universal [2,3]. Since all such computation (or data processing) takes place on the molecular scale, this research makes a promising approach to nanotechnology. However, despite the enormous computational power of such models, they are distinguished from what happens in biology because they are purely computational and rather unintuitive. Recently a group of researchers turned their attention to implementing more visible and intuitive mechanisms, such as robots, using DNA molecules. Biomolecular robotics is relatively recent research field. Many kinds of walkers are demonstrated to walk on 1-dimensional track [4], but just a few of them are demonstrated to walk on 2-dimensional track [5]. Even fewer perform specific functions such as transferring god nanoparticle species as cargos while traversing the pathway [6]. This project aims to incorporate both 2-dimensional walking and a specialized function into a DNA-based robot. More specifically, a molecular-scale DNA-based robot will reorganize cargos on 2dimensional fields. Our goal for the summer is to develop a system that autonomously sorts DNA tagged structures. Our base system involves randomly placed DNA tagged cargo on a rectangular DNA origami [7]. One edge of the origami is tagged with goal strands, and the rest of the origami is filled with track strands. The origami is then populated with random walkers that traverse the origami, picking up cargo and dropping them off at the goal. The motion of the walker and cargos will be examined by atomic force microscopy imaging. Bulk behavior of the system, kinetics of walking, and mechanisms of cargo picking up, and cargo dropping off will be analyzed by SPEX experiment. [1] Lulu Qian and Erik Winfree. A simple DNA gate motif for synthesizing large-scale circuits. In International Meeting on DNA Computing, 2008. [2] David Soloveichik, Georg Seelig and Erik Winfree. DNA as a Universal Substrate for Chemical Kinetics. DNA 14, LNCS 5347: 57-69, 2009 [3] David Soloveichik, Matthew Cook, Erik Winfree and Jehoshua Bruck. Computation with Finite Stochastic Chemical Reaction Networks. Natural Computing Feburary, 2008. [4] Ye Tian, Yu He, Yi Chen, Peng Yin, and Chengde mao. A DNAzyme That Walks Processively and Autonomously along a One-Dimensional Track. Angewandte Chemie International EditionVol. 44, 4355-4358, 2005 [5] Kyle Lund, Anthony J. Manzo, Nadine Dabby, Nicole Michelotti, Alexander Johnson-Buck, Jeanette Nangreave, Steven Taylor, Renjun Pei, Milan N. Stojanovic, Nils G. Walter, Erik Winfree, and Hao Yan. Molecular Robots Guided by Prescriptive Landscapes. Nature, 206-210, 2010 [6] Hongzhou Gu, Jie Chao, Shou-Jun Xiao, Nadrian C. Seeman. A proximity-based programmable DNA nanoscale assembly line. Nature 465, 202–205. 2010 [7] Paul W. K. Rothemund. Folding DNA to Create Nanoscale Shapes and Patterns. Nature, 297-302, 2006 Domain Level Design The random Walker consists of a body which is a 15nt long domain (b in figure 1), and two arms each which are 6nt short toeholds (a1 and a2 in figure 1) at at each end of the body. Tracks on which it walks contain the complement of one of the two toeholds: track 1 with a1* domain and track 2 with a2* domain. When a walker is on track 1, a2 domain is unpaired and searches for a complementary single strand. When track 2 is adjacent, it serves as a complementary sequence to which it can bind. After an arm of the walker (a2 domain) binds to an adjacent track 2, which serves as a "distal toehold", the hybridization extends by the rest of track 2. By this branch migration, the whole walker moves from track 1 to track 2. Similarly, a walker can move randomly from one kind of track to another kind. To accomplish a cargo-reorganizing-task, a walker is extended to have picking up arm which is complementary to cargos (domain x and l in figure 1). When walker randomly walks and encounters a cargo molecule, it picks up the cargo by strand displacement using toehold l. It continues random walking after picking up, and when a walker gets to the cargo goal, cargo is dropped off at the cargo goal using toehold u/u*, which both cargo and cargo goal share. Therefore, random walking process is purely stochastic, yet a deterministic end result can be achieved by specific recognition between the cargo molecules and their destinations. Another important stand is walker goal. Since walker goal contains both a1* and a2* which are complementary to the both of the toeholds of the walker, walker stays on the walker goal when it gets there. Walker goal will be used in verifying random walking on origami, and its use will be explained in later section. While the system is under construction, (e.g. track being planted), a walker or cargo goal should be deactivated to prevent undesired random walking or cargo sorting. Walker inhibitor and cargo goal inhibitor are thus designed. Later, walker trigger and cargo goal trigger will rip off the inhibitors by strand displacement using toehold wi and cgi. Detacher stands were designed to detach particular strands from samples with origami for the future gel experiments. Probes are the extended part of staples which are complementary to the bottom part of the strands which should be anchored on the origami surface. Different kinds of probes were designed for each strand. Origami will be annealed with certain staples extended with probes at predetermined positions, and some strands, such as tracks or cargo goals, will be planted on those specific positions using interaction between probe regions. Overall domain level design is illustrated in figure 1. Following abbreviation will be frequently used: walker [W], walker inhibitor [WI], track 1 [TR1], probe for track 1 [PTR1], track 2 [TR2], probe for track 2 [PTR2], cargo 1 [C1], cargo attacher [CA], probe for cargo attacher [PCA], cargo goal inhibitor [CGI], cargo goal 1 [CG1], probe for cargo goal [PCG], walker goal [WG], and probe for walker goal [PWG]. Sequence Design Main article: Sequence Design With our overall design in mind, we must design DNA sequences, down to the base level, which undergo the interactions that we desire, without forming secondary structures and binding in unintended ways. We approach this through a combination of pre-generated noninteracting sequences, and trial-and-error design using NUPACK simulation software. Theoretical Work Simulation of Expected Results Main article: Simulation Before undertaking our experiments, it's desirable to have an idea what our results our going to look like, particularly in the case of random walking, which we intend to investigate rather thoroughly. To do this, we use a stochastic simulation, written in MATLAB. Derivation of Random Walk Formula Main article: Random Walk Formula Besides the MATLAB simulation of random walking and cargo sorting, a random walk formula was developed to further investigate and verify the random walking mechanism on DNA origami. The probability of reaching the walker goal is expressed as a function of the number of steps taken. Experimental Design Verification of Mechanisms through Gel Experiments Main article: Gel Experiments Before constructing our origami and observing how it behaves, we run a large number of experiments observable through Gel Electrophoresis to verify that many of our mechanisms behave as we expect them to. Verification of Mechanisms through Fluorescent Spectroscopy Main article: SPEX Experiments Various DNA strands were tagged with fluorophores and quenchers in order to investigate different mechanisms more directly, both in solution and on origami. Verification of Mechanisms through Atomic Force Microscopy Main article: AFM Imaging Walkers tagged with biotins were planted onto DNA origami, attempts were made to observe random walking on the origami directly under AFM.