Researchers at the Stanford Covert System Biology Lab recently developed the world’s first whole-cell model of all the biological processes in a cell, which can be used to educate medical decisions, such as allowing for more detailed prognoses delivered to patients.
The team developed a model of Mycoplasma genitalium, a small bacterium. They will work on a similar whole-cell model for E. coli over the next year, which they expect to attract the attention of the biofuel community. E. coli has been used and modified by companies looking to popularize biofuel over fossil fuel to consumers.
The whole-cell model of M. genitalium, named WholeCellKB-MG, was published in the journal Cell last November.
The MG model represents a departure from work that hones in on one biological process at a time, such as only looking how the cell grows.
“Most people focus on just one piece at a time, and that might mean that they’re missing part of the picture by only focusing on one little thing at a time,” said Jonathan Karr M.S. ’13, Ph.D. ’13, a researcher in the biophysics department at Stanford working on the project. “We build on all of that work that everyone’s doing. We take all of those models that people are publishing and assemble it into one cohesive picture.”
Whole-cell models, developed by these system biologists, also give bioengineers a better opportunity to understand how their designed system will operate in different conditions.
“Our major focus is on building these comprehensive models of cells and using that to discover new biology to guide rational bioengineering to do things like produce drugs, biofuels and commodity chemicals,” Karr said.
The novelty and applicability of the MG model prompted researchers to begin looking more boldly at how it can be improved, which is vital if the team is to be successful in personalizing patient treatment through this out-of-the-box approach, Karr said.
“Maybe further into the future, [we can] use these kinds of models to guide medical decisions if we got to the point where we could accurately model [not only] bacteria but also other mammalian cells and human cells,” Karr added.
According to Karr, one of the challenges with this type of modeling is that not all parts of cells are equally well described.
Topics that have been more extensively researched allow for more detailed quantitative models. For this model, the researchers use data measured in other organisms to make up for missing information, as M. genitalium “is not very experimentally tractable and not very well-studied,” Karr said.
“Any model of a poorly studied organism, especially large models which require lots of training data, have to be built using data from multiple organisms,” he said.
Thus far, no academics have published work using the team’s WholeCellKB model. Karr hopes this will change after they release their model of E. coli.