Researchers simulate a living cell in 3D using the power of NVIDIA GPUs

Every living cell has a microcosm made up of thousands of components responsible for producing energy, building proteins, transcribing genes, and much more. Understanding how all components interact and change in response to internal and external signals helps to better understand the fundamentals of life. That’s why the simulation performed by a team from the University of Illinois at Urbana-Champaign using GPUs, specifically those from NVIDIA, is so important. The group of scientists has successfully recreated a 3D simulation that replicates the physical and chemical characteristics of a “minimal” living cell, developing a fully dynamic model that mimics the your behavior. The study was published in Cell magazine. The minimal cell contains a reduced set of genes essential for survival, function and replication. These cells are simpler than natural cells, making them easier to recreate digitally. “Even a tiny cell requires 2 billion atoms,” said Zaida Luthey-Schulten, professor of chemistry and co-director of the University’s Center for Living Cell Physics. “You can’t make a 3D model like this on a realistic human timescale without GPUs” The model is based on the use of NVIDIA GPUs to simulate 7000 processes of genetic information over a 20-minute period of the cell cycle, making it what scientists believe is the longest and most complex cellular simulation to date. Once further tested and refined, whole cell models will be able to help scientists predict how changes in real-world cell conditions or genomes will affect their function. To build the living cell model, the Illinois researchers simulated one of the simplest living cells, a parasitic bacterium called mycoplasma. They based the model on a scaled-down version of a mycoplasma cell synthesized by scientists at the J. Craig Venter Institute in La Jolla, California, which had just under 500 genes to keep it viable. For comparison, a single E. coli cell has about 5,000 genes. A human cell has more than 20,000 genes. Luthy-Schulten’s team then used the known properties of the inner workings of mycoplasma, including amino acids, nucleotides, lipids and small-molecule metabolites, to build the model with DNA, RNA, proteins and membranes. “We had enough reactions to be able to reproduce everything we knew,” he said.

Using Lattice Microbes software, which is capable of leveraging the Tensor cores of NVIDIA GPUs, the researchers performed a 20-minute 3D simulation of the cell’s life cycle before it began to substantially expand or replicate its DNA. The model showed that the cell devoted most of its energy to transporting molecules across the cell membrane, which fits the profile of a parasitic cell that gets most of what it needs to survive from other organisms.

“If you did these calculations in series,” said Zane Thornburg, lead author of the study, “it would take years.” But because they are all independent processes, we can bring parallelization to the code when using GPUs.

The simulations also allowed Thornburg to calculate the natural lifespan of messenger RNAs, the genetic blueprints for building proteins. They also revealed a relationship between the rate at which membrane lipids and proteins were synthesized and changes in membrane surface area and cell volume.

“We simulated all the chemical reactions inside a tiny cell, from its birth to the moment it split into two cells two hours later,” said Thornburg. “From this, we get a model that tells us how the cell behaves and how we can make it more complex to change its behavior,” said Professor Luthey-Schulten.

Thornburg is working on another GPU-accelerated project to simulate cell growth and division in 3D. “The team recently adopted NVIDIA DGX systems and RTX A5000 GPUs to accelerate their work,” notes NVIDIA, “noting that using A5000 GPUs improved simulation time by 40% compared to a workstation with an NVIDIA GPU. previous generation”