Bio‐informational futures

Abstract

Synthetic biology and artificial intelligence naturally converge in the biofoundry. Navigating the ethical and societal issues of the biofoundry's potential remains a major challenge.

Seeding the idea of encapsulating a representative synthetic metagenome in a single yeast cell

“…Synthetic Biology has revolutionised research in life sciences. By combining DNA reading (sequencing), writing (synthesis) and editing technologies with the integrative functionalities of artificial intelligence and biodigital engineering 2 , 3 , it seems reasonable to envisage a future ‘bio-informational’ scenario where researchers, could design ecosystem-wide dynamic models and network-based analytical approaches to disentangle microbial interactions, and to assess, measure and control complex biological systems. The early signs of such a scenario are already visible and real in that, close on the heels of the creation of the first bacterial cell controlled by a chemically synthesised genome 6 , the synthesis of the first eukaryotic genome is nearing completion in the context of the Synthetic Yeast Genome (Sc 2.0 or Yeast 2.0) consortium 7 , 8 .…”

Drawing on the Past to Shape the Future of Synthetic Yeast Research

“…This shift in capacity saw the design-build-test-learn process adopted by the emerging field of synthetic biology. Engineering processes were adopted in order to rationalise biological device design [89]. The chemical synthesis of artemisinin in S. cerevisiae [90] was the first major achievement in biodesign.…”

Sensing the future of bio-informational engineering

“…This is in part due to the analytical capacities of artificial intelligence and the role such algorithms can play in extricating information from high levels of signal noise. Artificial intelligence data handling will very likely be an essential enabler of bio-informational engineering due to its algorithmic capacity for automating decisions and generating meaningful signals based on big data pattern analysis 90 . This is a keystone capability for engineering bio-informational control loops that involve noisy signal actuation, monitoring and translation across organic and inorganic information substrates.…”

“…This is likely to incorporate traditional technological solutions in the age of big data—i.e. artificial intelligence data handling and insight generation 90 —but it also suggests the outlook for novel bio-informational solutions is one of increased public and private funding. In order to maintain legitimacy and support for population-level bio-surveillance tools across the long-term, governments will need to undertake nuanced and sophisticated communication programs.…”