Technological biology? Things and kinds in synthetic biology

Social scientific and humanistic research on synthetic biology has focused quite narrowly on questions of epistemology and ELSI. I suggest that to understand this discipline in its full scope, researchers must turn to the objects of the field—synthetic biological artifacts—and study them as the objects in the making of a science yet to be made. I consider one fundamentally important question: how should we understand the material products of synthetic biology? Practitioners in the field, employing a consistent technological optic in the study and construction of biological systems, routinely employ the mantra ‘biology is technology’. I explore this categorization. By employing an established definition of technological artifects drawn from the philosophy of technology, I explore the appropriateness of attributing to synthetic biological artifacts the four criteria of materiality, intentional design, functionality, and normativity. I then explore a variety of accounts of natural kinds. I demonstrate that synthetic biological artifacts fit each kind imperfectly, and display a concomitant ontological ‘messiness’. I argue that this classificatory ambivalence is a product of the field’s own nascence, and posit that further work on kinds might help synthetic biology evaluate its existing commitments and practices.     

Is biology science?

Yes of course it is, you reply, and so do I. But, are we in a minority in recognizing that the life sciences can be hard science?     

Molecular biology of β-lactam acylases

-Lactam acylases such as penicillin G acylases, penicillin V acylases and glutaryl 7-aminocephalosporanic acid acylases are used in the manufacture of 6-aminopenicillanic acid, 7-aminodesacetoxycephalosporanic acid and 7-aminocephalosporanic acid (7-ACA). Genetically-engineered strains producing 1050 U/g, 3200 U/g and 7000 to 10,000 U/I of penicillin G acylase, penicillin V acylase and glutaryl-7-ACA acylase, respectively, have been developed. The penicillin G acylase studied to date and the glutaryl-7-ACA acylase from Pseudomonas sp. share some common features: the active enzyme molecules are composed of two dissimilar subunits that are generated from respective precursor polypeptide; the proteolytic processing is a post-translational modification which is regulated by temperature; and the Ser residue at the N-terminus of the -sub-unit (Ser²⁹⁰; penicillin G acylase numbering) is implicated as the active site residue. Protein engineering, to generate penicillin G acylase molecules and their precursors with altered sequences, and the structure-function correlation of the engineered molecules are discussed.The authors are with Research and Development, Hindustan Antibiotics Ltd, Pimpri, Pune 411 018, India;     

Identification and biology of α-secretase

Our knowledge of the etiology of Alzheimer's disease (AD) has advanced tremendously since the discovery of amyloid beta (Aβ) aggregation in diseased brains. Accumulating evidence suggests that Aβ plays a causative role in AD. The β-secretase enzyme, beta-site APP cleaving enzyme-1 (BACE1), is also implicated in AD pathogenesis, given that BACE1 cleavage of amyloid precursor protein is the initiating step in the formation of Aβ. As a result, BACE1 inhibition has been branded as a potential AD therapy. In this study, we review the identification and basic characteristics of BACE1, as well as the progress in our understanding of BACE1 cell biology, substrates, and phenotypes of BACE1 knockout mice that are informative about the physiological functions of BACE1 beyond amyloid precursor protein cleavage. These data are crucial for predicting potential mechanism-based toxicity that would arise from inhibiting BACE1 for the treatment or prevention of AD.     

Deductive biology—Some cautious steps

For certain environments, the Darwinian model allows unique prediction of a function that any surviving system adapted to such an environment has to perform. This is the case for those environments that determine a “survival functional” of position in space-time of known shape. Purely temporal survival functionals can be distinguished from spatial and mixed ones. In each case, there exists an optimum path in combined physical and (reduced) metabolic space. Dependent on the admissible error, approximate solutions of different complexity are sufficient. All solutions possess an afferent, a central, and an efferent part. Within this general frame, specific, “probably simplest”, solutions are proposed for adaptive chemotaxis, insect locomotion, lower vertebrates locomotion, higher vertebrates locomotion, chronobiological systems, and immune systems, respectively—or rather, for the underlying functionals. Presented at the Society for Mathematical Biology Meeting, University of Pennsylvania, Philadelphia, August 19–21, 1976.     

Are we doing synthetic biology?

Synthetic Biology is a singular, revolutionary scenario with a vast range of practical applications but, is SB research really based on engineering principles? Is it contributing to the artificial synthesis of life or using approaches “sophisticated” enough to fall outside the scope of biotechnology or metabolic engineering? We have reviewed the state of the art on synthetic biology and we conclude that most research projects actually describe an extension of metabolic engineering. We draw this conclusion because the complexity of living organisms, their tight dependence on evolution and our limited knowledge of the interactions between the molecules they are made of, actually make life difficult to engineer. We therefore propose the term synthetic biology should be used more sparingly.     

Cancer immunotherapy: simply cell biology?

There is a clear need for improved cancer therapy and survival rates. Effective immunotherapy would be the treatment modality of choice from several viewpoints, and dendritic cell (DC)-based immunotherapy is emerging as the most promising approach to cancer immunotherapy. However, the plethora of approaches to DC-based cancer therapy now threatens to impede the development of an effective immunotherapy regime, as competing egos and commercial interests masquerade as scientific rigour. Here, I argue that the current controversies regarding the numerous approaches reflect the paucity of our immunological understanding, and present a simple cell biological analysis that defines the rationale for the development of effective cancer immunotherapy.     

How can ontologies help vector biology?

The reach of genomics has now extended to vector biology, with three mosquito genomes already sequenced and more arthropod vector genomes in the pipeline. The availability of these genomes has paved the way for high-throughput investigations on genome-wide gene expression and proteomics in vector biology. Such investigations would not have been possible without parallel progress in bioinformatics. It is now necessary to construct specific ontologies that will enable vector biologists to achieve computer-comprehensible annotation of genes and genomes, but also of various experimental, clinical and surveillance data. This will inevitably lead to the enhanced usage of such controlled vocabularies, and to an effort to develop novel ontologies, particularly in the context of disease control.     

Interdisciplinary integration in biology? An overview

Philosophical theories about reduction and integration in science are at variance with what is happenign in science. A realistic approach to science show that possibilities for reduction and integration are limited. The classical ideal of a unified science has since long been rejected in philosophy. But the current emphasis on interdisciplinary integration in philosophy and in science shows that it survives in a different guise. It is necessary to redress the balance, specifically in biology. Methodological analysis shows that many of the grand interdisciplinary theories involving biology actually represent pseudo-integration covered up by inappropriate, overgeneral concepts. Integrationism is not bad, but it must be kept within reasonable bounds. If the present analysis is appropriate, there will have to be fundamental changes in research strategy both in science and in the philosophy of science.