Our project is to develop a system that autonomously sorts DNA tagged structures as shown below. Our system involves randomly placed DNA tagged cargo on rectangular DNA origami, which is a 2D nano-scale surface . 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 fluorescence spectroscopy experiments.
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 . 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. Recently a group of researchers turned their attention to implementing the visible and intuitive mechanisms, such as robots, using DNA molecules. The state of the art in molecular robotics includes demonstrating DNA robots that can traverse a predetermined path in two dimensions , and ones that can traverse a path and at the same time collect up to three gold nanoparticle cargos .
Project Overview: Ultimate goal
Caltech’s 2011 BIOMOD team is pursuing a topic in DNA robotics, seeking to demonstrate a mechanism for the sorting of cargo particles, each tagged with an identifying DNA strand, scattered across a 100x70nm rectangular DNA origami playing field. Our mechanism is based on the cooperation of a number of independent DNA “walkers” that gradually wander around the playing field in a random walk, and specially positioned, cargo-specific goals. When a walker encounters a cargo, it picks it up by binding to its identifying DNA strand, and carries it around as it continues its exploration. The goals associated with a particular cargo retrieve that cargo from courier walkers by binding to the identifying strand in a way that frees the walker to collect more cargo, and prevents the cargo from being picked up again. Over time, this system will sort initially randomly strewn cargos to destinations predetermined by goal placement---a mechanism of simple directed transport potentially useful in many complex systems constructed on origami, such as complex molecular assembly lines. Our walker design is significant and novel on its own, due to its simplicity and ability to perform a 2-dimensional random walk, and should prove valuable on its own to future DNA robotics projects. More importantly, this project’s overarching principle of a useful result emerging from very simple and independently less useful elements working together is without a doubt vital to the eventual development of larger scale DNA robotic systems.
Elegance of Solution
We have a simple and elegant implementation to accomplish the goal of our project. Here are some of the key aspects of our approach that make it simple, yet stand out:
The random walking mechanism only uses two toeholds, and our entire sorting mechanism only requires two additional toeholds.
scales; as the number of cargos increases, neither the size of the walker nor the number of types of walkers needs to increase. This shows how a simple walker can accomplish a large number of tasks by essentially programming the tasks rather than the walker itself. One walker fits all!
Although we only need one type of walker, we can use many identical copies of the same walker simultaneously working on the same task to greatly speed up the process ((see simulation results).
increase in the number of base pairs when the cargo binds to the walker, and further the increase in the number of base pairs when the cargo binds to its goal, so the system is entirely autonomous (after we trigger our walkers). This means we neither need to have the walker eat up its environment nor supply fuel to the environment to keep the walker functioning over time, which were both common approaches in making various types of walkers in the past.
Why is this useful to us? We see this technology being used effectively in a number of practical applications. When coupled with other mechanisms, the ability to sort has the possibility to lead to systems that automatically collect and remove byproducts from a reaction, purify a system and condense products into specified locations, or aid in controlled and detailed nanoscale assembly machines. Additionally, our specific implementation of a solution to this problem is universal enough that it can be applied to not only DNA, but anything that can be tagged with a DNA identifier.
Furthermore, as mentioned above, our random walking mechanism can be extracted from our walker and used in many applications that don't involve sorting at all, but rather involve some other type of continuous exploration and information recognition on a 2D surface. Imagine walkers propagating signals over a complicated network, walkers picking up staple strands to modify the shape of origami, or walkers searching in parallel for a solution to some computational optimization problem, by exploring a surface of potential solutions to the problem. While some of these applications might be very abstract and not practically implementable, they give an idea of the great diversity of projects our random walker can be applied in.
Finally, by pushing the state of the art to robots that can do many more tasks that have previously been demonstrated in addition to walkers that can simultaneously work in parallel to complete a task, while maintaining a great degree of simplicity†, we demonstrate the full potential of DNA robotics. Our project is a milestone that suggests the field can take many new directions in the next few years. While it is obvious that DNA robotics is interesting, as high-profile journals such as Nature have published the most recent research in the field , , our project gives a compelling example of what makes the field interesting; this is something that previous research has not done but is essential to progressing the field.