Cornell Researchers Construct DNA Material with Artificial Metabolism

DNA is a genetic material that is responsible for the function of all living things. However, this genetic material is also a polymer.

Now, inspired by the exceptional nature of this molecule, engineers at Cornell University have developed simple machines made from biomaterials; these biomaterials have properties of living things.

Using the so-called DNA-based Assembly and Synthesis of Hierarchical (DASH) materials, the Cornell team engineered a DNA material that has capabilities of self-assembly, organization, and metabolism, which are three major traits of life.

We are introducing a brand-new, lifelike material concept powered by its very own artificial metabolism. We are not making something that’s alive, but we are creating materials that are much more lifelike than have ever been seen before.

Dan Luo, Professor, Department of Biological and Environmental Engineering, College of Agriculture and Life Sciences, Cornell University

The paper titled, “Dynamic DNA Material with Emergent Locomotion Behavior Powered by Artificial Metabolism,” has been reported in Science Robotics on April 10th, 2019.

For any living thing to sustain itself, there should be a system to control change. For example, new cells should be produced, and old cells and waste should be eliminated. The major elements of self-sustainability are biosynthesis and biodegradation which need metabolism to sustain both form and functions.

It is via this system that DNA molecules are produced and organized into patterns in a hierarchical manner, leading to something that can maintain an autonomous, dynamic process of growth and decay.

The Cornell engineers used DASH to produce a unique biomaterial that can independently arise from its nanoscale building blocks and organize itself—initially into polymers and then into mesoscale shapes. Beginning from a sequence of 55-nucleotide base seed, the DNA molecules were multiplied a countless number of times, producing chains of repeating DNA that measure only a few millimeters in size. Subsequently, the reaction solution was administered into a microfluidic device that not only offered a liquid flow of energy but also provided the required building blocks for biosynthesis.

When the flow of energy washed across the material, the DNA was able to produce its own new strands, with the tail end of the material degrading and the front end growing in optimized balance. In this fashion, the DNA made its own movement, inching forward, against the flow, just like how slime molds would move.

The locomotive potential of the DNA enabled the Cornell engineers to pit groups of the material against each other in competitive races. The randomness existing in the environment would allow one body to ultimately gain an advantage over the other, and will enable it to cross the finish line first.

The designs are still primitive, but they showed a new route to create dynamic machines from biomolecules. We are at a first step of building lifelike robots by artificial metabolism. Even from a simple design, we were able to create sophisticated behaviors like racing. Artificial metabolism could open a new frontier in robotics.

Shogo Hamada, Study Lead and Co-Corresponding Author and Lecturer, Department of Biological and Environmental Engineering, Cornell University

Hamada is also a research associate in the Luo lab.

At present, the team is looking for ways to make the material to detect stimuli and independently seek it out in the case of food or light, or avoid it if it is dangerous. The major breakthrough is the programmed metabolism integrated within the DNA materials. The set of instructions for autonomous regeneration and metabolism are included in the DNA. After that, the molecule is on its own.

Everything from its ability to move and compete, all those processes are self-contained. There’s no external interference. Life began billions of years from perhaps just a few kinds of molecules. This might be the same.

Dan Luo, Professor, Department of Biological and Environmental Engineering, College of Agriculture and Life Sciences, Cornell University

The material developed by the Cornell researchers can withstand two cycles of synthesis and degradation before it decomposes. According to the team, longevity can possibly be extended, paving the way for increased “generations” of the novel material as it replicates on its own. “Ultimately, the system may lead to lifelike self-reproducing machines,” stated Hamada.

More excitingly, the use of DNA gives the whole system a self-evolutionary possibility,” Luo added. “That is huge.”

On a theoretical level, it can possibly be developed so that following generations can emerge within a few seconds. According to Luo, reproduction at this extreme pace would exploit the natural mutational properties of DNA and expedite the evolutionary process.

In the coming days, the innovative system can perhaps be utilized as a biosensor for identifying the presence of any RNA and DNA molecules. Furthermore, this concept may be used for producing a dynamic template for creating proteins without living cells.

The study was partly funded by the National Science Foundation and supported by the Cornell NanoScale Science and Technology Facility and Kavli Institute at Cornell for Nanoscale Science. Study collaborators include Jenny Sabin, the Arthur L. and Isabel B. Wiesenberger Professor in Architecture, and scientists from the Chinese Academy of Sciences and Shanghai Jiaotong University.

A patent is pending with the Center for Technology Licensing.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.