Biologists frequently draw on ideas and terminology from engineering. Evolutionary systems biology—with its circuits, switches, and signal processing—is no exception. In parallel with the frequent links drawn between biology and engineering, there is ongoing criticism against this cross-fertilization, using the argument that over-simplistic metaphors from engineering are likely to mislead us as engineering is fundamentally different from biology. In this article, we clarify and reconfigure the link between biology and engineering, presenting it in a more favorable light. We do so (...) by, first, arguing that critics operate with a narrow and incorrect notion of how engineering actually works, and of what the reliance on ideas from engineering entails. Second, we diagnose and diffuse one significant source of concern about appeals to engineering, namely that they are inherently and problematically metaphorical. We suggest that there is plenty of fertile ground left for a continued, healthy relationship between engineering and biology. (shrink)

The comparison between natural evolution and the action of a tinkerer has become highly popular since its reintroduction by François Jacob at the end of the 1970s. It has been used as a weapon against the existence of an “intelligent design” as well as a way for synthetic biologists to promote their ambitious projects. I will describe the complex history of this metaphor, and examine its pertinence. Whereas Darwin considered it as a way to describe how evolution proceeded, Jacob linked (...) it with a description of the imperfections of organisms, while Stephen Jay Gould and Richard Lewontin criticized what they called the “Panglossian” vision of most evolutionary biologists. The distinction between the work of engineers and that of tinkerers is not obvious. There are limits to the process of evolution, but their alleged description so far reflects the limits of knowledge on the part of evolutionary biologists more than the existence of true barriers to the evolutionary process. And, in their work, synthetic biologists crucially need the optimizing action of natural selection. To give a definition of synthetic biology is no easy task; the false distinction drawn between the work of synthetic biologists and the action of evolution is of no help. (shrink)

Synthetic biology is often described as a project that applies rational design methods to the organic world. Although humans have influenced organic lineages in many ways, it is nonetheless reasonable to place synthetic biology towards one end of a continuum between purely ‘blind’ processes of organic modification at one extreme, and wholly rational, design-led processes at the other. An example from evolutionary electronics illustrates some of the constraints imposed by the rational design methodology itself. These constraints reinforce the limitations of (...) the synthetic biology ideal, limitations that are often freely acknowledged by synthetic biology’s own practitioners. The synthetic biology methodology reflects a series of constraints imposed on finite human designers who wish, as far as is practicable, to communicate with each other and to intervene in nature in reasonably targeted and well-understood ways. This is better understood as indicative of an underlying awareness of human limitations, rather than as expressive of an objectionable impulse to mastery over nature. (shrink)

Evolution is often characterized as a tinkerer that creates efficient but messy solutions to problems. We analyze the nature of the problems that arise when we try to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem – solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational problems, we show that the reason for why evolutionary (...) designs are often hard to understand is that they exhibit non-modular functionality, and that breaches of modularity wreak havoc on our strategies of causal and constitutive explanation. (shrink)

The picture of synthetic biology as a kind of engineering science has largely created the public understanding of this novel field, covering both its promises and risks. In this paper, we will argue that the actual situation is more nuanced and complex. Synthetic biology is a highly interdisciplinary field of research located at the interface of physics, chemistry, biology, and computational science. All of these fields provide concepts, metaphors, mathematical tools, and models, which are typically utilized by synthetic biologists by (...) drawing analogies between the different fields of inquiry. We will study analogical reasoning in synthetic biology through the emergence of the functional meaning of noise, which marks an important shift in how engineering concepts are employed in this field. The notion of noise serves also to highlight the differences between the two branches of synthetic biology: the basic science-oriented branch and the engineering-oriented branch, which differ from each other in the way they draw analogies to various other fields of study. Moreover, we show that fixing the mapping between a source domain and the target domain seems not to be the goal of analogical reasoning in actual scientific practice. (shrink)

Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is (...) typically combined with experiments on model organisms as well as mathematical modeling and simulation. What is especially interesting about this combinational modeling practice is that, apart from greater integration between these different epistemic activities, it has also led to the questioning of some central assumptions and notions on which synthetic biology is based. As a result synthetic biology is in the process of becoming more “biology inspired.”. (shrink)

Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is (...) typically combined with experiments on model organisms as well as mathematical modeling and simulation. What is especially interesting about this combinational modeling practice is that, apart from greater integration between these different epistemic activities, it has also led to the questioning of some central assumptions and notions on which synthetic biology is based. As a result synthetic biology is in the process of becoming more “biology inspired.”. (shrink)

The parts-based engineering approach in synthetic biology aims to create pre-characterised biological parts that can be used for the rational design of novel functional systems. Given the context-sensitivity of biological entities, a key question synthetic biologists have to address is what properties these parts should have so that they give a predictable output even when they are used in different contexts. In the first part of this paper I will analyse some of the answers that synthetic biologists have given to (...) this question and claim that the focus of these answers on parts and their properties does not allow us to tackle the problem of context-sensitivity. In the second part of the paper, I will argue that we might have to abandon the notions of parts and their properties in order to understand how independence in biology could be achieved. Using Robert Cummins’ account of functional analysis, I will then develop the notion of a capacity and its condition space and show how these notions can help to tackle the problem of context-sensitivity in biology. (shrink)

The term “synthetic biology” is a popular label of an emerging biotechnological field with strong claims to robustness, modularity, and controlled construction, finally enabling the creation of new organisms. Although the research community is heterogeneous, it advocates a common denominator that seems to define this field: the principles of rational engineering. However, it still remains unclear to what extent rational engineering—rather than “tinkering” or the usage of random based or non-rational processes—actually constitutes the basis for the techniques of synthetic biology. (...) In this article, we present the results of a quantitative bibliometric analysis of the realized extent of rational engineering in synthetic biology. In our analysis, we examine three issues: (1) We evaluate whether work at three levels of synthetic biology (parts, devices, and systems) is consistent with the principles of rational engineering. (2) We estimate the extent of rational engineering in synthetic biology laboratory practice by an evaluation of publications in synthetic biology. (3) We examine the methodological specialization in rational engineering of authors in synthetic biology. Our analysis demonstrates that rational engineering is prevalent in about half of the articles related to synthetic biology. Interestingly, in recent years the relative number of respective publications has decreased. Despite its prominent role among the claims of synthetic biology, rational engineering has not yet entirely replaced biotechnological methods based on “tinkering” and non-rational principles. (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...