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Highlights in Chemical Biology

Chemical biology news from across RSC Publishing.



Instant insight: Living computers


15 March 2007

Hao Song, Cheemeng Tan, and Lingchong You, at Duke University in Durham, US, explain how cells can solve problems

"Employing elaborate signalling networks, [cells] constantly process diverse environmental cues to make appropriate decisions - they compute. "
Turning cells into computers is an appealing challenge. Thanks to advances in biology and engineering, cell behaviour can now be modulated to meet specific design objectives in a rational and, to a certain extent, predictable manner. Being able to program cell behaviour opens doors to many potential applications, including cellular computers. If we consider computation as a generic term for information processing that transforms a set of inputs to a certain output, then cells are already computers. Employing elaborate signalling networks, they constantly process diverse environmental cues to make appropriate decisions - they compute. 


Can we exploit and reprogram these networks to accomplish specific computational tasks? One may argue that basic programmed cellular computation has been achieved with engineered gene circuits, including logic gates and switches. Nevertheless, these examples are so far limited to fairly simple logic functions.


How about more complex computational tasks? To address this question, we may draw inspiration by examining some of the characteristics of natural cellular information processing, especially in comparison with digital computers.


Firstly, whilst cells can adapt to their environment to enhance fitness, integrated electronic circuits cannot change once constructed. Meanwhile, cellular information processing is naturally parallel: different types of membrane receptor proteins mean that each cell can receive multiple signals at the same time, and a large number of cells (up to 1010 per millilitre) can process information simultaneously. 


Moreover, cells can move. By modifying the cell machinery, cell migration can be controlled for a specific purpose. This aspect will become more attractive if coupled with cells' ability to communicate with one another. Combining these features could allow scientists to program cells to form self-organised patterns and optimise their distribution over complex landscapes. 

Bacteria migrating toward a point where a function (concentration of a ligand) is a maximum

By reprogramming their genes, bacteria (red) could be used to solve computational problems. Here, the bacteria are shown migrating toward a point where a function (concentration of a ligand) is a maximum.


While some of these capabilities may also be realised with digital computers, heat accumulation in silicon chips becomes a significant constraint in accelerating their operational speed any further. This highlights some additional advantages of cellular computation: energy consumption is extremely small and heat generation is easily manageable.


By examining and exploiting cell signalling characteristics, it is possible to frame computational problems where cells might perform comparably well with or even better than digital computers. As a start, we proposed three commonly-encountered problems (integration, optimisation and Fourier transform) that could feasibly be solved by engineering cell gene circuits. These examples attempt to take advantage of the key information processing capabilities outlined above, in particular parallelism, communication, and motility.


Take the optimiser as an example. Inspired by a computational search algorithm, this circuit design attempts to use cell mobility controlled by both ligand sensing and cell-cell communication to effectively search a complex landscape with unevenly distributed ligand concentrations (see figure). 


"One can imagine using a cellular optimiser to search and destroy cancer cells or toxic agents in a polluted environment. "
Given the numerous challenges in engineering even basic gene circuits with reliable function (a lesson well-learned by synthetic biologists) it may take a while for such designs to be implemented and optimised. Even then, they may not compete with conventional computers in terms of speed. However, an appealing aspect of cellular circuits is that their outputs can be directly connected to practical functions. For instance, one can imagine using a cellular optimiser to search and destroy cancer cells or toxic agents in a polluted environment. 


Addressing the challenges and limitations of programming cells to compute will enhance our understanding of the mechanisms involved in natural cellular information processing and is critical if we are to build functional cellular computers.

Read Tan, Song, Niemi, and You's review 'A synthetic biology challenge: making cells compute' in April's issue of Molecular BioSystems.

Link to journal article

A synthetic biology challenge: making cells compute
Cheemeng Tan, Hao Song, Jarad Niemi and Lingchong You, Mol. BioSyst., 2007, 3, 343
DOI: 10.1039/b618473c