Researchers have successfully simulated nearly all chemical reactions occurring in a living bacterial cell. This groundbreaking virtual model illustrates the processes of DNA copying and cell division, offering insights into the molecular interactions that contribute to life.
Zane Thornburg, a computational biophysicist at the University of Illinois in Urbana-Champaign, co-led the study published on 9 March in Cell. He explained that understanding the interplay of proteins, nucleic acids, fats, and other molecules within a cell’s wall is crucial to comprehending the essence of life itself.
To create the simulation, Thornburg selected a simplistic bacterial organism, JCVI-Syn3a, which boasts a “minimal” genome consisting of just 493 genes. This organism was developed by trimming away over 400 non-essential genes from the parasite Mycoplasma mycoides.
The detailed three-dimensional simulation incorporated various cellular components such as DNA, proteins, and ribosomes, capturing their dynamic behaviour over time. Key molecular interactions, like those involving a DNA-copying enzyme, were based on real-world measurements. However, some aspects were approximated due to limited knowledge; for example, certain JCVI-Syn3a genes were represented as inert spheres.
Initially, the team faced challenges, such as the genome deteriorating faster than it could replicate. After adjustments, they allowed the model to run during the US Thanksgiving holiday, only to return to find that a complete cell cycle had progressed. Thornburg remarked on the significant advancement this represented.
The simulation accurately reflected real-life cellular processes, including the transformation in shape during division. The virtual cell took 105 minutes to divide, mirroring the reproductive timeline of actual cells, though the simulation required six days on a supercomputer, highlighting the complexity involved.
Bernhard Palsson, a bioengineer at the University of California, San Diego, praised this achievement, noting the significance of coherently representing diverse cellular activities during the cell cycle. Future directions for this research may explore further optimization and refinement of the simulation’s components.
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