Creating the First Full-fledged Model of the Human Cell
Posted January 18, 2008, 4:07 PM EST
Photo by Tom Cogill
The human cell is a complicated and idiosyncratic masterpiece, honed by evolution to conduct the full range of functions needed to keep us alive. It generates its own power, manufactures a vast number of proteins, and communicates constantly with its environment, in a constant stream of activity that is far too intricate to be grasped by the human mind.
Biomedical engineering graduate student Erwin Gianchandani is developing new techniques for modeling these complex activities on the computer, with the hope of one day creating a digital cell. “A digital cell—incorporating millions of interrelated regulatory, metabolic, and signaling events—would prove of immense value to researchers investigating the fundamental mechanisms of disease,” he says.
Running the digital cell on a computer, scientists could knock out individual reactions, modify the composition of a specific protein, or change the conditions in the cell’s immediate environment. Such computer-based experimentation would provide critical baseline information that could accelerate the development of new diagnostic markers and therapies. “With a model you can generate a wealth of hypotheses much more quickly and less expensively than if you were working in a laboratory,” Gianchandani explains. “The model can tell wet lab researchers where to go next.”
Tools already exist for modeling the metabolic network, which governs the production of energy, and the cell-signaling network, the system that brings external stimuli into the cell and prompts the cell to respond. Gianchandani recently developed a framework for modeling the regulatory network, or the set of rules that govern which genes are expressed in response to these external stimuli. He is testing his approach on the genomes of the bacterium Escherichia coli and eukaryote Saccharomyces cerevisiae (baker’s yeast). This involves synthesizing vast amounts of data, from the scientific literature as well as from automated high-throughput studies of gene expression conducted by researchers around the world. Gianchandani is also developing other techniques for analyzing large-scale cell-signaling networks.
“One of the reasons I like systems biology is that it is an emerging field,” Gianchandani says. “There is a lot of opportunity for young researchers like myself to break new ground.”
Gianchandani’s progress so far shows that he is making the most of this opportunity. He has published one book chapter and four articles in peer-reviewed journals, including one that was featured on the cover of PloS Computational Biology, a premier journal in his field. He was also singled out for an Award for Excellence in Scholarship in the Sciences and Engineering from the University.
Ironically, Gianchandani, who received his B.S. in computer science from U.Va. in 2005, almost went to the University of Pennsylvania for graduate study. As he was preparing to accept an offer from Penn, he received a call from Thomas Skalak, chair of U.Va.’s Department of Biomedical Engineering. Skalak told Gianchandani about work being done in systems biology by Jason Papin, a new faculty member, and urged him to reconsider. Intrigued, Gianchandani opted to return to U.Va.
“It has worked out wonderfully,” Gianchandani declares. “I was fortunate to be Jason’s first graduate student and get his undivided attention for nine months. I love the research and I love being part of one of the foremost centers for systems biology in the nation.”