Evolution is cleverer than you are: Is Synthetic biology a flawed concept?
Is synthetic biology sending ‘scientists on a wild goose chase’? Are synthetic biologists guilty of lazy thinking, or perhaps just naivety? These are some of the questions that have been posed in the literature recently, so where do the doubts come from, and are the criticisms fair?
Synthetic biology is the attempt to apply rational design principles to biotechnology, bringing together disciplines including computer science, engineering, chemistry and molecular biology. A widely cited description of the field is the use of standardized biological components to construct complex devices with predictable outputs. The idea is that once a device is assembled, a mathematical model representing its behaviour can be iteratively tested and refined, providing a basis for rational improvement according to the classic ‘engineering cycle’.
Synthetic biologists often invoke analogies from computer science when describing their work, in using the machine analogy they draw on concepts closely aligned to ‘Mechanical biology’ which has its origins in the work of the seventeenth century philosopher René Descartes. Mechanical philosophy proposes a clockwork model of the universe, where all phenomena can be explained by simple deterministic laws, and are therefore predictable if sufficient information is available.
The challenges facing synthetic biology are well documented, ranging from the difficulty of moving parts from one organism to another, noise from stochastic fluctuations, to cross-talk between synthetic circuits and host molecular processes. The argument arises when choosing the best approach to overcome these issues, and whether the machine analogy are hindering progress.
Critics argue these problems result from the misguided application of rational design principles to biotechnology, built on the faulty assumption that organisms are machines. This leads Boudry and Pigliucci state that ‘the more bioengineers will adhere to a straightforward ‘‘engineering’’ perspective on living organisms, the more obstacles they will throw in the way of their own progress’.
Instead, they argue that biologists should abandon rational design and embrace a combination of borrowing genes from existing organisms and directed evolution. The authors draw parallels with the field of artificial intelligence (AI), where rationally designed ‘hard’ AI has been superseded by ‘soft’ AI, in which ‘black-box’ algorithms are instead created by statistical inferences and have achieved greater success, most famously with the chess playing algorithm Deep Blue.
However, is this reasonable? Directed evolution is dependent on the ability to select for a desired trait which may not always be possible. It is hard to imagine how the major success in synthetic biology to date - the synthesis of the anti-malaria drug artemisinin in yeast – could be achieved by directed evolution alone.
In a recent article Sune Holm defends synthetic biologists, finding they are well aware of the disanalogies between organisms and machines, before going on to suggest an alternate paradigm for reflecting on the machine analogy in biology. He argues that in contrast to being naïve and damaging, the value of Synthetic Biology as a concept lies precisely in its understanding that organisms are not machines, and that this realisation drives the desire to make biological devices that are more machine-like to produce better biotechnology.
Critics are right to call for caution, and perhaps a more thorough examination of whether it is actually possible to ‘get rid of biological complexity’ is required. But if synthetic biologists manage to produce truly machine-like devices, with reliable, predictable behaviour, the machine analogy will have been useful indeed.
Written by:
Dr. Steven J. Burgess
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Steven is a post-doc in plant molecular biology at the University of Cambridge. During his PhD, Steven did research into algal biofuels and currently works on improving crop yields as part of a group dedicated to the production of C4 rice.
Edited by: Devang Mehta
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