Synthetic biology is an umbrella term that covers a range of aims, approaches, and techniques. They are all brought together by common practices of analogizing, synthesizing, mechanicizing, and kludging. With a focus on kludging as the connection point between biology, engineering, and evolution, I show how synthetic biology’s successes depend on custom-built kludges and a creative, “make-it-work” attitude to the construction of biological systems. Such practices do not fit neatly, however, into synthetic biology’s celebration of rational design. Nor do they (...) straightforwardly embody Richard Feynman’s “last blackboard” statement that without creating something it cannot be understood. Reflecting further on the relationship between synthetic construction and knowledge making gives philosophy of science new avenues of insight into scientific practice. (shrink)

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into (...) two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (shrink)

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the (...) relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation. (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 ways in which the various activities of synthetic biology connect to those of conventional biology display both a multiplicity and variety that reflect the multiplicity and variety of meanings for which the term synthetic biology has been invoked, today as in the past. Central to this variety, as well as to the connection itself, is the complex relationship between knowing and making that has prevailed in the life sciences. That relationship is the focus of this article. More specifically, my (...) aim is to explore the different assumptions about how knowing is related to making that have prevailed, implicitly or explicitly in the various activities—now or in the past—subsumed under the name synthetic biology. (shrink)

We address three fundamental questions: What does it mean for an entity to be living? What is the role of inter-organismic collaboration in evolution? What is a biological individual? Our central argument is that life arises when lineage-forming entities collaborate in metabolism. By conceiving of metabolism as a collaborative process performed by functional wholes, which are associations of a variety of lineage-forming entities, we avoid the standard tension between reproduction and metabolism in discussions of life – a tension particularly evident (...) in discussions of whether viruses are alive. Our perspective assumes no sharp distinction between life and non-life, and does not equate life exclusively with cellular or organismal status. We reach this conclusion through an analysis of the capabilities of a spectrum of biological entities, in which we include the pivotal case of viruses as well as prions, plasmids, organelles, intracellular and extracellular symbionts, unicellular and multicellular life-forms. The usual criterion for classifying many of the entities of our continuum as non-living is autonomy. This emphasis on autonomy is problematic, however, because even paradigmatic biological individuals, such as large animals, are dependent on symbiotic associations with many other organisms. These composite individuals constitute the metabolic wholes on which selection acts. Finally, our account treats cooperation and competition not as polar opposites but as points on a continuum of collaboration. We suggest that competitive relations are a transitional state, with multi-lineage metabolic wholes eventually outcompeting selfish competitors, and that this process sometimes leads to the emergence of new types or levels of wholes. Our view of life as a continuum of variably structured collaborative systems leaves open the possibility that a variety of forms of organized matter – from chemical systems to ecosystems – might be usefully understood as living entities. (shrink)

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by (...) drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable—a research programme that is perhaps taken to its most extreme form in systems biology’s sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to ‘dirty, unruly living systems’. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. (shrink)

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine (...) the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.Keywords: Experimental organism; Genetics; Model organism; Modeling; Philosophy of biology; Representation. (shrink)

The present paper contributes to a growing body of philosophical, sociological, and historical analyses of recent nanoscale science and technology. Through a close examination of the origins of contemporary nanotech efforts, their ambitions, and strategic uses, it also aims to provide the basis for a critical theory of emerging technologies more generally, in particular in relation to their alleged convergence in terms of goals and outcomes. The emergence, allure, and implications of nanotechnology, it is argued, can only be fully appreciated (...) if one looks beyond its immediate technical and scientific payoffs to its infrastructural and ideological aspects. While nanotechnology aims to reshape the world 'atom by atom', its most tangible result so far has been the profound effect it has had on the organization of science-at-large, not least as the result of a thorough reshaping of the 'soft' funding infrastructure that places signifi cant constraints on the pursuit of long-term scientific research programmes. The paper concludes by noting a persistent, and perhaps deepening, gap between the utopian visions of some of nanotechnology's most vocal proponents and the realities of contemporary nanotechnological practice, which continue to be marked by global inequities. (shrink)

Synthetic biology emerged around 2000 as a new biological discipline. It shares with systems biology the same modular vision of organisms, but is more concerned with applications than with a better understanding of the functioning of organisms. A herald of this new discipline is Craig Venter who aims to create an artificial microorganism with the minimal genome compatible with life and to implement into it different 'functional modules' to generate new micro-organisms adapted to specific tasks. Synthetic biology is based on (...) the possibilities raised by genetic engineering, but it aims to engineer organisms, and not simply to modify them, mimicking the practice of computer engineers. Three points will be discussed: In what regard does synthetic biology represent a new epistemology of the life sciences? What are the relations between synthetic biology and evolutionary biology? What is the raison d'être of synthetic biology as a discipline independent of nanotechnologies? (shrink)