BUILDING A BETTER MODEL:
Metabolic and regulatory networks may be expanded by coupling high-throughput phenotyping and gene expression data with the predictions of a computational model. (Reprinted with permission,
Most people like their predictions to pan out, but Markus Covert is glad when his fail. That's because he has developed a genome-scale mathematical model of the transcriptional interactions that regulate bacterial metabolism. The model's mistakes lead to new ideas about how the network is put together.
Covert, now a postdoctoral fellow in David Baltimore's lab at the California Institute of Technology, constructed the
To validate the model, Covert tapped into the ASAP database of the
The wrongly predicted outcomes identified five growth conditions in which unknown regulatory interactions must have produced the observed results. They also revealed that eight of the mutants require unknown enzymes or pathways to grow under various conditions.
To test the utility of his model for discovering transcriptional regulatory networks, Covert made six new strains of
Using two-way analysis of variance to identify the differentially expressed transcription factors, Covert updated his model. The second iteration,
The researchers plan eventually to replace the model's Boolean logic with quantitative data on the interactions of transcription factors with genes. They also want to write algorithms that automatically devise the most appropriate experiment after the model makes a mistake.
Meanwhile, the model is being put to good use. "We have already started incorporating these regulatory constraints into the OptKnock computational framework, developed in our lab, for identifying gene deletions that lead to targeted overproductions," says Costas Maranas, associate professor of chemical engineering at Pennsylvania State University.
Palsson also predicts commercial applications. For example, the model could be used to uncover and modify regulatory networks of bacteria used for bioremediation or bioprocessing. He adds, "A futuristic idea is to think of these models in the context of synthetic biology, for designing new organisms."
- Linda Sage