Systems Biology

Industrial Organization

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Science  04 Jun 2010:
Vol. 328, Issue 5983, pp. 1208
DOI: 10.1126/science.328.5983.1208-a

E. coli (left) and Linux (right) networks

CREDIT: KOON-KIU YAN AND NITIN BHARDWAJ

Yan et al. have compared the transcriptional control network in the bacterium Escherichia coli to the network depiction (known as the call graph) of the Linux kernel, which is the central component of a highly popular operating system. Both systems feature (i) master regulators (yellow in the graphic), which send directions to targets; (ii) middle managers (red), which both send and receive orders; and (iii) workhorses (green), which are controlled but do not control others. For the bacterium, there are lots of workhorses but relatively few regulators at the other levels. The Linux call graph is top-heavy or more populated at the master regulator and middle-manager levels. In other words, a workhorse in the transcriptional network usually has only a few supervisors, but in Linux, a workhorse answers to a large number of regulators. The authors also contrasted evolution in the two systems by looking at the functions that persist in 24 versions of the Linux source code relative to genes that persist in 200 phylogenetically distinct bacteria. For E. coli, the workhorses showed the greatest persistence, whereas for Linux, there was persistence at all three levels, but mostly in the master regulators and middle managers. The authors interpret these differences in terms of two design principles. The need for cost-effectiveness (or reusability) is central in programming, and robustness—that is, resistance to breakdown due to failure of a part—is the driving factor in biological systems. Evolution, they speculate, goes from top to bottom in software, but from bottom to top in biological systems.

Proc. Natl. Acad. Sci. U.S.A. 107, 9186 (2010).

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