Supervisors info:
Θεόδωρος Αραμπατζής, Καθηγητής, Τμήμα Ιστορίας και Φιλοσοφίας της Επιστήμης, Εθνικό και Καποδιστριακό Πανεπιστήμιο Αθηνών
Summary:
This thesis aims to examine how fully synthetic organisms are materially crafted in
the “Design-Build-Test-Learn” bioengineering workflow, which has emerged in
recent years at the intersection of synthetic biology, metabolic engineering, and
computer science. To carry out this project, I analyse published scientific articles
documenting actual deployment cases of Design-Build-Test-Learn pipelines, focusing
on the process of creating entirely artificial biological matter as well as on the design
specifications guiding this. The analysis produced two main results. Firstly, biological
matter comes to life through the communication of two distinct environments
(ontologies), the laboratory of ‘wet’ biology and the electronic computer, with a
multiplicity of technoscientific objects, inscriptions, and translations mediating the
process. Secondly, the design choices involved inscribe a hybrid digital logic to the
outcome of the workflow, the artificial single-cell organism. This thesis could be
useful for science and technology studies (STS) scholars since it contributes: a) A
micro-level material analysis in bioengineering discussions, arguing that the current
literature regarding the role of metaphors and ethical responsibility fails to account
how discursive practices and ethical considerations interact with the design script of
bioengineered entities; b) To the ontological approaches in the field, by demonstrating
the versatility of such a framework, especially in highlighting the political stakes
involved in bioengineering practices. This thesis could be also useful for bioengineers
because it invites them to reconsider the current narrative of problem-solving in
synthetic biology, reflecting on the input–output framing of societal problems and the
corresponding engineering solutions developed in a research-for-industry context.
Keywords:
Bioengineering, Synthetic life, Design-Build-Test-Learn, Ontologies in Biology
