Capturing and controlling the movement of genes

Pictures of DNA often look very tidy – the strands of the double helix neatly wind around each other, making it seem like studying genetics should be relatively straightforward. In truth, these strands aren’t often so perfectly picturesque. They are constantly twisting, bending, and even being repaired by minuscule proteins. These are movements on the nanoscale, and capturing them for study is extremely challenging. Not only do they wriggle about, but the camera’s fidelity must be high enough to focus on the tiniest details.

Researchers from the University of Illinois Urbana-Champaign (U. of I.) have been working on resolving a grand challenge for molecular biology, and more specifically, genetic research: how to take a high-resolution image of DNA to facilitate study. Using a number of compute resources, including NCSA’s Delta, Aleksei Aksimentiev, a professor of physics at U. of I, and Dr. Kush Coshic, formerly a graduate research assistant in the Center for Biophysics and Quantitative Biology and the Beckman Institute for Advanced Science and Technology at U. of I., and currently a postdoctoral fellow at the Max Planck Institute of Biophysics, recently made significant contributions to solving this challenge. They did it by focusing on two specific problems: creating a “camera” that could capture the molecular movement of DNA, and by creating an environment in which they could predictably direct the movement of the DNA strands.

“The fundamental problem we try to address is the gap between our ability to engineer DNA structures and our ability to predict and control their motion on 2D surfaces, a challenge which requires a deeper, molecular-level understanding to lay the groundwork for future biosensors and structural biology tools,” said Aksimentiev.

The team relied on massive, microsecond-long Molecular Dynamics (MD) simulations to computationally model the atomic interactions and validate their experimental setup, a task that demanded the immense parallel compute power that Delta and DeltaAI provide.

Creating a nanoscale camera

When you imagine trying to take a photo of a DNA strand on a camera, you might think the best way to keep it still would be to place it on its side when trying to capture an image. However, researchers discovered that DNA can stand up straight on certain surfaces – a breakthrough for those attempting to capture high-quality images.

It’s essential to recognize that these breakthroughs result from highly collaborative efforts, often building upon the foundational work of scientists and researchers worldwide. In this case, Aksimentiev’s team was able to conduct their research due to the discovery made by researchers at Tinnefeld Lab at Ludwig Maximilian University (LMU) in Munich, Bavaria, Germany. That team created a “DNA camera” using a single, atomic-layer-thick sheet of graphene. They called this method GETvNA. Aksimentiev’s team built upon the work at LMU by exploring the atomic-level workings of this “DNA camera.”

“The GETvNA method builds on a discovery by our collaborators (Tinnefeld Lab, LMU, Germany) that double-stranded DNA adopts a vertical orientation on graphene, enabling detection of subtle conformational changes via energy transfer between a dye-labeled DNA and the graphene surface,” explained Coshic. “Like a car’s suspension system, this configuration allows the DNA to flex and fluctuate freely while remaining vertically positioned on the surface, capturing its structural dynamics with Angstrom-level spatial and subsecond temporal resolution.”

Aksimentiev’s team was able to achieve a resolution down to the Angstrom scale (less than a billionth of a meter) and capture events in real-time. This is essential for observing processes such as DNA damage repair or protein translocation as they occur.

Capturing those images is a significant achievement in itself, but the team’s research has an even greater impact: their discovery means that even labs lacking access to expensive resources can study DNA at this scale.

“A key strength of GETvNA is its accessibility. It enables high-resolution single-molecule studies using a standard fluorescence microscope, removing the need for costly facilities to host cryogenic electron microscopy or nuclear magnetic resonance equipment,” said Aksimentiev.

Guiding DNA

What if you could also control where DNA moved? If you were able to get DNA to move along a selected path, you could sort and manipulate individual strands of DNA easily, but you could also start to build a “molecular machine” of sorts. Aksimentiev’s team discovered that by using a 2D material, hexagonal boron nitride (hBN), they could direct single-stranded DNA (ssDNA) along selected paths. In a previous study published in Nature Nanotechnology, the team discovered that step defects can be used to guide biomolecules. A step defect is essentially a nanoscale stair-step or ledge on the surface of a material, such as graphene. These nano-sized, naturally occurring “stairs” can create channels through which biomolecules will move.

Initially, experiments performed with a team of collaborators, which included researchers Chirlmin Joo and Peter Steeneken, both from the Delft University of Technology (TU Delft), showed the DNA diffusing thousands of times slower than predicted. The team’s computational analysis solved this mystery, revealing that atomic defects on the hBN surface act as temporary trapping sites that intermittently slow the molecules, allowing for predictable control over their movement.

“Understanding the molecular interactions and how surface defects influence biomolecular motion on 2D surfaces, our ACS Nano work paves the way for designing 2D nanofluidic devices with precisely confined channels,” said Aksimentiev. “These can guide biomolecules directionally, via diffusion or external cues, for high-resolution sensing and without relying on complex nanofabrication protocols. GETvNA complements this by offering a novel, low-cost pipeline that achieves Angstrom-level localization precision for single-molecule measurements.”

The combination of these two breakthroughs allows for a wide range of impactful applications in biomolecular medicine.

“While our work is fundamental, focusing on understanding the rules to build new tools, it lays essential groundwork for the precise control and guiding of biomolecules for next-generation medical diagnostics,” said Aksimentiev. “The GETvNA method serves as a powerful and low-cost platform for studying how single DNA molecules interact with proteins, a fundamental process in both health and disease. Its accessibility unlocks a wide range of applications, from enabling deeper biological research to offering a practical way to quantify the specific molecular interactions that are crucial for designing and testing new drugs.”

This research would have been impossible without the resources available at centers like NCSA. For research of this resource-intensive nature, Aksimentiev’s team had to utilize numerous resources. To get those resources, his team turned to the U.S. National Science Foundation ACCESS program. Through ACCESS, Aksimentiev was able to qualify for a “Maximize” allocation, granting him access to hundreds of thousands of compute hours on resources nationwide.

NCSA resources, including Delta, were instrumental in enabling our microsecond-long simulations, currently the state-of-the-art, by reducing computation time from several months on personal machines to just a few days using high-performance computing.

–Aleksei Aksimentiev, University of Illinois

In addition to obtaining allocations on NCSA’s Delta and DeltaAI machines, the team utilized resources from the Pittsburgh Supercomputing Center (PSC), the Texas Advanced Computing Center (TACC), the San Diego Supercomputer Center (SDSC), and Purdue’s Rosen Center for Advanced Computing (RCAC).

“For many years, the ACCESS, and its predecessor (XSEDE), program has been enabling our lab to perform computational discovery at the interface of biology and nanotechnology,” said Aksimentiev. “Being able to use these state-of-the-art resources is pivotal to ensuring global leadership of U.S. science and the emergence of breakthrough technological innovations.”

Building on a Breakthrough

The team has published results of their work in two papers: Diffusion of DNA on Atomically Flat 2D Material Surfaces in ACS Nano, and Single-molecule dynamic structural biology with vertically arranged DNA on a fluorescence microscope in Nature Methods. However, a researcher’s work is never truly over. Aksimentiev and his team will continue to expand upon their results.

“We would like to better understand from a molecular standpoint the milliseconds-to-seconds dynamics of the vertical standing DNA on the graphene surface,” said Aksimentiev. “Atomistic simulations cannot be used to probe such timescales, and instead, we will use our microsecond-long atomistic trajectories to calibrate coarser resolution models such as our in-house mrDNA method that we previously used to unravel the physical process of viral genome packaging inside the virus’ protein capsid.”

This research was funded in part by the Human Frontier Science Program (grant RGP0047/2020) and the National Science Foundation (grant DMR-1827346). Research computing time was funded by the U.S. NSF ACCESS program (allocation no. MCA05S028).

ABOUT DELTA AND DELTAAI
NCSA’s Delta and DeltaAI are part of the national cyberinfrastructure ecosystem through the U.S. National Science FoundationACCESS program. Delta (OAC 2005572) is a powerful computing and data-analysis resource combining next-generation processor architectures and NVIDIA graphics processors with forward-looking user interfaces and file systems. The Delta project partners with the Science Gateways Community Institute to empower broad communities of researchers to easily access Delta and with the University of Illinois Division of Disability Resources & Educational Services and the School of Information Sciences to explore and reduce barriers to access. DeltaAI (OAC 2320345) maximizes the output of artificial intelligence and machine learning (AI/ML) research. Tripling NCSA’s AI-focused computing capacity and greatly expanding the capacity available within ACCESS, DeltaAI enables researchers to address the world’s most challenging problems by accelerating complex AI/ML and high-performance computing applications running terabytes of data. Additional funding for DeltaAI comes from the State of Illinois.