Investigators at Stanford University have created the world’s first complete computer model of an organism. Reported in the journal Cell, the team used data from more than 900 scientific manuscripts to incorporate every molecular interaction taking place in the life cycle of Mycoplasma genitalium, the world’s smallest free-living bacterium.
Why is this such a profound development? To date, most experiments investigating the inner workings of the cell have relied on gene-knockout studies, which shed light on the inner workings of a single gene. However, according to Marcus Covert, assistant professor of bioengineering at Stanford, “Many of the issues we’re interested in aren’t single-gene problems…They’re the complex result of hundreds or thousands of genes interacting.”
This development offers the opportunity to investigate complex phenotypes by integrating several cell processes — not simply the function of individual proteins — into a single model. Furthermore, similar models for more relevant microorganisms or cells may lead to increasingly rational design of pharmaceuticals such as antibiotics or chemotherapeutics.
From the Stanford University announcement:
The purely computational cell opens up procedures that would be difficult to perform in an actual organism, as well as opportunities to reexamine experimental data.
In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.
The program also allowed the researchers to address aspects of cell behavior that emerge from vast numbers of interacting factors.
The researchers had noticed, for instance, that the length of individual stages in the cell cycle varied from cell to cell, while the length of the overall cycle was much more consistent. Consulting the model, the researchers hypothesized that the overall cell cycle’s lack of variation was the result of a built-in negative feedback mechanism.
Cells that took longer to begin DNA replication had time to amass a large pool of free nucleotides. The actual replication step, which uses these nucleotides to form new DNA strands, then passed relatively quickly. Cells that went through the initial step quicker, on the other hand, had no nucleotide surplus. Replication ended up slowing to the rate of nucleotide production.
These kinds of findings remain hypotheses until they’re confirmed by real-world experiments, but they promise to accelerate the process of scientific inquiry.
“If you use a model to guide your experiments, you’re going to discover things faster. We’ve shown that time and time again,” said Covert.
Abstract in Cell: A Whole-Cell Computational Model Predicts Phenotype from Genotype