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)

Despite the multidisciplinary dimension of the kinds of research conducted under the umbrella of synthetic biology, the US-based founders of this new research area adopted a disciplinary profile to shape its institutional identity. In so doing they took inspiration from two already established fields with very different disciplinary patterns. The analogy with synthetic chemistry suggested by the term ‘synthetic biology’ is not the only model. Information technology is clearly another source of inspiration. The purpose of the paper, with its focus (...) on the US context, is to emphasize the diversity of views and agendas coexisting under the disciplinary label synthetic biology, as the two models analysed are only presented as two extreme postures in the community. The paper discusses the question: in which directions the two models shape this emerging field? Do they chart two divergent futures for synthetic biology? (shrink)

Despite the multidisciplinary dimension of the kinds of research conducted under the umbrella of synthetic biology, the US-based founders of this new research area adopted a disciplinary profile to shape its institutional identity. In so doing they took inspiration from two already established fields with very different disciplinary patterns. The analogy with synthetic chemistry suggested by the term ‘synthetic biology’ is not the only model. Information technology is clearly another source of inspiration. The purpose of the paper, with its focus (...) on the US context, is to emphasize the diversity of views and agendas coexisting under the disciplinary label synthetic biology, as the two models analysed are only presented as two extreme postures in the community. The paper discusses the question: in which directions the two models shape this emerging field? Do they chart two divergent futures for synthetic biology? (shrink)

The question is discussed how noise gained a functional meaning in the context of biology. According to the common view, noise is considered a disturbance or perturbation. I analyze how this understanding changed and what kind of developments during the last 10 years contributed to the emergence of a new understanding of noise. Results gained during a field study in a synthetic biology laboratory show that the emergence of this new research discipline—its highly interdisciplinary character, its new technologies and novel (...) modeling strategies—provided essential impulses, which led to the observed change in the concept of noise. The laboratory study is combined with a historical analysis, which explores the general question as to how concepts travel between disciplines and, specifically, how noise was transferred from engineering and physics into biology. In the past, scientists, such as Lotka and Goodwin, tried to introduce a statistical mechanics into biology and discussed the problem of “unfitting” concepts. The change in the meaning of the concept can be interpreted as a way of making it fit to the novel context in which it is applied. (shrink)

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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)

Although the emerging field of synthetic biology looks back on barely a decade of development, the stakes are high. It is a multidisciplinary research field that aims at integrating the life sciences with engineering and the physical/chemical sciences. The common goal is to design and construct novel biological components, functions and systems in order to implement, in a controlled way, biological devices and production systems not necessarily found in nature. Among the many potential applications are novel drugs and pesticides, cancer (...) treatments, biofuels, and new materials. According to the most optimistic visions, synthetic biology may thus lead to a biotechnological revolution by transforming microorganisms into ‘factories’ of sorts, which could eventually displace conventional industrial methods. (shrink)

Synthetic biology and systems biology are often highlighted as antagonistic strategies for dealing with the overwhelming complexity of biology (engineering versus understanding; tinkering in the lab versus modelling in the computer). However, a closer view of contemporary engineering methods (inextricably interwoven with mathematical modelling and simulation) and of the situation in biology (inextricably confronted with the intrinsic complexity of biomolecular environments) demonstrates that tinkering in the lab is increasingly supported by rational design methods. In other words: Synthetic biology and systems (...) biology are merged by the use of computational techniques. These computational techniques are needed because the intrinsic complexity of biomolecular environments (stochasticity, non-linearities, system-level organization, evolution, independence, etc.) require advanced concepts of bio bricks and devices. A philosophical investigation of the history and nature of bio parts and devices reveals that these objects are imitating generic objects of engineering (switches, gates, oscillators, sensors, etc.), but the well-known design principles of generic objects are not sufficient for complex environments like cells. Therefore, the rational design methods have to be used to create more advanced generic objects, which are not only generic in their use, but also adaptive in their behavior. Case studies will show how simulation-based rational design methods are used to identify adequate parameters for synthesized designs (stability analyses), to improve lab experiments by ‘looking through noise’ (estimation of hidden variables and parameters), and to replace laborious and time-consuming post hoc tweaking in the lab by in-silico guidance (in-silico variation of bio brick properties). The overall aim of these developments, as will be argued in the discussion, is to achieve adaptive-generic instrumentality for bio parts and devices and thus increasingly merging systems and synthetic biology. (shrink)