Synthetic biologists explain cell behaviors while desinging new ones
Without synchronized clocks—whether embedded in our body’s cells or programmed into our desktop computers—any kind of coordinated activity is impossible. So after synthetic biologists succeeded last year in programming individual bacteria to keep time and blink rhythmically, they wanted to find a way to coax each bacterium away from the beat of its own idiosyncratic drummer. Now they've figured out how to genetically engineer a population of E. coli that can not only blink in unison, but also automatically synchronize itself.
“Often synchronization is achieved by enslaving multiple clocks, or oscillators, to one ‘central command unit,’” says Lev Tsimring, PhD, associate director of the University of California, San Diego’s BioCircuits Institute, who headed the research team with Jeff Hasty, PhD, associate professor of biology and bioengineering at UCSD. But that’s putting a lot of eggs in one basket: If something goes wrong with the master clock, the whole system can collapse.
The team’s solution was to make use of quorum sensing, in which cells communicate with each other by relaying small molecules between them. In their design, a genetic oscillator first drives engineered bacteria to turn fluorescent proteins on and off. Then the cells use quorum-sensing components to share information about the timing of their oscillations and adjust their cycles accordingly.
The work, which was published in Nature in January 2010. used computational modeling of the oscillators to quantitatively explain the experimental observations. For example, the researchers tweaked the computational model parameters to artificially prevent a certain molecule—which was thought to be involved in both the cells’ time-keeping and communication—from penetrating the cell walls. Their results showed that without the molecule, the individual cells were indeed cut off from each other and their environment, and their clocks remained unsynchronized. And because there's no way to confine this molecule within cell walls experimentally, “observing” this behavior was possible only through computational modeling, says Tal Danino, graduate student in the UCSD Department of Bioengineering and lead author of the study.
Computation is indeed a valuable tool for understanding gene networks, Hasty says. “We learned about time delay in gene regulatory networks, how signals propagate through colonies, and how interactions come together to synchronize behavior between cells.” And with essentially only two genes at the heart of the synchronization mechanism, the system is a great demonstration of how small systems can generate very complex behavior. “It showed that you don’t need a lot of genes in a network to get very interesting and rich dynamics, where all kinds of spectacular things can happen,” he says.
“The complexity of the system is astonishing,” says Martin Fussenegger, PhD, professor of biosystems science and engineering at the Swiss Federal Institute of Technology Zurich in Basel, Switzerland, who wrote an accompanying perspective on the study. Not only is the timing mechanism radically different from that of the central pacemaker in the brain, which uses one-way synchronization to control cellular clocks in remote tissue, but the cells manage to stay synchronized even while in constant motion and dividing every 20 minutes.
The bacteria can also be programmed to change their synchronized blinking rate in response to environmental triggers. This ability could lead to applications such as super-sensitive bacterial sensors that would flash more quickly in the presence of environmental contaminants, says James Anderson, PhD, program director for the Center for Bioinformatics and Computational Biology at the National Institute of General Medical Sciences within the National Institutes of Health.
But the immediate use of the work is more basic, Anderson points out. These researchers created computational models of the synchronization to drive both in silico and in vitro experiments of the synthetic biology, which in turn help refine the computational models even further. “What the synthetic biologists are doing now is helping us understand how the natural traits actually work at the same time that they’re creating synthetic ones.”