14 DAY TRIAL // According to researchers at the Carnegie Mellon University, in the US, gene regulatory networks in cell nuclei are strikingly similar to cloud computer networks, such as Yahoo! and Google, in their ability to function even if one or more of their nodes are down. This characteristic is essential to cloud computing, as the failure of a single processor could otherwise have potentially devastating repercussions on the entire network. Similarly, the failure of some master genes inside the nuclei does not mean that the cells themselves die, as other genes take over some of the load, and share “responsibilities.”
The new find was of paramount importance for biology, the international science team, led by the CMU experts, announced online in yesterday's (June 16th) issue of the journal Molecular Systems Biology. The study is not essential only because it helps explain the longevity of the cell, but also because it offers some new insight into cellular readings that have, at some point or another in time, puzzled researchers around the world. It helps explain how cells continue to function as a whole, despite the fact that they lose some of their components.
“Similarities in the sequences of certain master genes allow them to back up each other to a degree we hadn't appreciated,” CMU Assistant Professor of Computer Science and Machine Learning Ziv Bar-Joseph, who is also a computational biologist at the Carnegie Mellon University-based Ray and Stephanie Lane Center for Computational Biology, explains.
Basically put, when a new organism is created, the most important agents in its development are transcription factors, proteins that have the ability to turn all genes on or off. These proteins are themselves made by master genes, which represent about five to ten percent of the genes in the organism. What the new research did was prove that, if one of the master genes somehow got compromised, others encoding similar information (called paralogs) would step in and encode the same set of proteins as their disabled predecessors.
“It's extremely rare in nature that a cell would lose both a master gene and its backup, so for the most part cells are very robust machines. We now have reason to think of cells as robust computational devices, employing redundancy in the same way that enables large computing systems, such as Amazon, to keep operating despite the fact that servers routinely fail,” CMU Computer Science Department graduate student Anthony Gitter, the lead author of the new study, concludes.