Plant Rhythms Model for Computing
Photo via flickr by Martin_Heigan
A newfound ability to model the complex feedback loops that control plant clocks could have important implications for computing.
One of the limitations of conventional thinking in computation is that computable functions proceed in a sequential manner, one independent step after another. In the biological world, things are more complex because steps in biological computations may not be independent—for example, the circadian rhythm in plants, the 24 hour cycle of biochemical processes that govern behavior. The cycle has various important features such as the ability to synchronize with an external periodic light source and to continue to oscillate even in the absence of variations in illumination.
Biochemists have long known that these cycles are the result of various biochemical feedback loops in which the transcription of genes is boosted and damped. Of course, plant clocks have been studied for hundreds of years and a huge amount is known about how they work, particularly about Arabidopsis thaliana, a small flowering plant that is the standard object of study for plant biologists. The trouble is that nobody has been able to accurately model the behavior of these rhythms from first principles. That’s because these processes do not involve independent sequential steps, so conventional computational methods are just not up to the job. Biochemists need some other way of thinking about their problem.
As luck would have it, just such a system has been waiting in the wings. Process algebra is a form of computation that can handle multiple simultaneous interdependent steps and this makes it perfect for modeling these tricky biochemical networks and the feedback loops that drive them. Ozgur Akman, Andrew Millar and colleagues at the University of Edinburgh used this approach to model the circadian rhythm of the green alga Ostreococcus tauri, which has the honor of possessing the simplest planet clock yet discovered.
They co-created a model of the various feedback loops in the Ostreococcus clock using a process algebra known as Bio-PEPA. This allowed them to explore how the clock responds to factors such as changes in illumination patterns and to genetic mutations, a factor that effects how the clock might change over evolutionary time scales.
While the outcome will help make predictions for plant biology, the real importance may be more subtle. An often overlooked property of process algebra is that it is not equivalent to a standard sequential Turing machine. Because process algebra encompasses concurrent processes and the communication between them, it is subtly different and potentially more powerful.