May 2000

Biological Computing

Continued from page 1

By Simson L. Garfinkel

The New Biology

Biocomputing research is one of those new disciplines that cuts across well-established fields-in this case computer science and biology-but doesn't fit comfortably into either culture. "Biologists are trained for discoveries," says Collins. "I don't push any of my students towards discovery of a new component in a biological system." Rockefeller University postdoctoral fellow Michael Elowitz explains this difference in engineering terms: "Typically in biology, one tries to reverse-engineer circuits that have already been designed and built by evolution." What Collins, Elowitz and others want to do instead is forward-engineer biological circuits, or build novel ones from scratch.

But while biocomputing researchers' goals are quite different from those of cellular and molecular biologists, many of the tools they rely on are the same. And working at a bench in a biologically oriented "wet lab" doesn't come easy for computer scientists and engineers-many of whom are used to machines that faithfully execute the commands that they type. But in the wet lab, as the saying goes, "the organism will do whatever it damn well pleases."

After nearly 30 years as a computer science researcher, MIT's Knight began to set up his biological lab three years ago, and nothing worked properly. Textbook reactions were failing. So after five months of frustratingly slow progress, he hired a biologist from the University of California, Berkeley, to come in and figure out what was wrong. She flew cross-country bearing flasks of reagents, biological samples-even her own water. Indeed, it turned out that the water in Knight's lab was the culprit: It wasn't pure enough for gene splicing. A few days after that diagnosis, the lab was up and running.

Boston University's Gardner, a physicist turned computer scientist, got around some of the challenges of setting up a lab by borrowing space from B.U. biologist Charles Cantor, who has been a leading figure in the Human Genome Project. But before Gardner turned to the flasks, vials and culture dishes, he spent the better part of a year working with Collins to build a mathematical model for their genetic one-bit switch, or "flip-flop." Gardner then set about the arduous task of realizing that model in the lab.

The flip-flop, explains Collins, is built from two genes that are mutually antagonistic: When one is active, or "expressed," it turns the second off, and vice versa. "The idea is that you can flip between these two states with some external influence," says Collins. "It might be a blast of a chemical or a change in temperature." Since one of the two genes produces a protein that fluoresces under laser light, the researchers can use a laser-based detector to see when a cell toggles between states.

In January, in the journal Nature, Gardner, Collins and Cantor described five such flip-flops that Gardner had built and inserted into E. coli. Gardner says that the flip-flop is the first of a series of so-called "genetic applets" he hopes to create. The term "applet" is borrowed from contemporary computer science: It refers to a small program, usually written in the Java programming language, which is put on a Web page and performs a specific function. Just as applets can theoretically be combined into a full-fledged program, Gardner believes he can build an array of combinable genetic parts and use them to program cells to perform new functions. In the insulin-delivery example, a genetic applet that sensed the amount of glucose in a diabetic's bloodstream could be connected to a second applet that controlled the synthesis of insulin. A third applet might enable the system to respond to external events, allowing, for example, a physician to trigger insulin production manually.