In Mirit Aladjem’s lab at the National Cancer Institute, the concepts associated with systems biology are beginning to take practical form. Aladjem, using a graphical language first developed by Kurt Kohn, a principal investigator in the NCI’s laboratory of molecular pharmacology, is spearheading an effort to reduce complex bioregulatory networks to a mathematically representable form. In addition to models of DNA replication, the cell cycle, and hypoxia, her group most recently collaborated with researchers at the University of Genoa to create an online, interactive representation of the Myc pathway, which is closely associated with cancer.
Aladjem, who originally received her PhD from Tel Aviv University in Israel, says her approach provides a universal tool that biologists can use to represent the workings of their pet systems in a mathematically rigorous format. Using Kohn’s library of 16-odd graphical symbols — [http://discover.nci.nih.gov/kohnk/symbols.html] representing events ranging from proteolytic cleavage within a specific spot on a protein to formation of a homodimer — Aladjem says she and her colleagues can “depict any [bioregulatory system], unambiguously.”
In contrast, Aladjem says, more traditional metabolic pathway maps tend to be linear, making it difficult to represent networks in which one enzyme acts as the substrate for another. In addition, traditional pathway maps typically don’t differentiate between modified and unmodified versions of an enzyme, an imprecision that Kohn and Aladjem have taken pains to avoid, Aladjem says.
The NCI’s completed molecular interaction maps (MIMs) also offer the added benefit of appearing online in a readily accessible format that provides researchers with the ability to link to additional information about a particular interaction or regulatory motif. With help from computer programmers in John Weinstein’s group at the NCI, the maps contain links to resources including PubMed, GeneCards, and Matchminer, among others. [http://discover.nci.nih.gov/mim/html/index.html] In addition, individual modules extracted from the MIMs can be converted directly to simulations with the help of SBML, the systems biology markup language.
With adequate funding, Aladjem says her effort could expand to translate every well-understood bioregulatory network into a MIM. At the moment, however, given time and resource constraints, she works with researchers on a case by case basis, allowing her to spend time investigating DNA replication, her area of expertise. “Researchers like me find it very useful to implement MIMs as a way to organize knowledge within their areas of expertise,” she says in an e-mail. “In my case, my major field of inquiry is DNA replication, so the MIMs I opted to generate organize knowledge about DNA replication and cell cycle control.”
Next up for Aladjem is the ATR pathway, an important component of the cellular response to environmental signals and a target for anti-cancer drugs. And in the future, she hopes to obtain dedicated funds and recruit additional experts to help create new MIMs. “Creating each MIM is like writing a review paper,” says Aladjem. “By putting knowledge into a diagram, you can gain new understandings that weren’t clear before.”
—John S. MacNeil