Point of contact
In the past few decades, synthetic biology has laid considerable focus on the re-programming of cells as computing machines. They have been engineered to sense a range of inputs (metabolites, light, oxygen, pH) and process them to produce desired outputs according to defined processing codes (primarily digital, but occasionally analog). Some potential applications of the cellular machines include production of metabolic compounds of interest, bio-remediation of toxic environments, sensing of disease bio-markers, and therapeutic intervention by targeted effector delivery. Yet, the ability of single cells to reliably process multiple inputs is acutely constrained by their limited resources.
Adding too many processes into one cell leads to resource-stress and eventually the code is lost due to mutation, a baseline error mechanism present in all living systems. This has, in part, encouraged the notion of distributing the computational tasks across multiple cells, to reduce resource-stress and improve robustness. The value of the idea is corroborated by the success of the division of labor seen in multi-cellular organisms that have naturally evolved from their unicellular ancestors. While task-distribution in cell populations solves some problems, it immediately leads to other challenges that must be tackled for the successful implementation of any complex distributed program. Some of these challenges include: the orthogonality/specificity of communication signals, the rate and bandwidth of communication channels, cellular growth and its effect on signal amplification or dissipation, and effect of cross-talk between different signals.
Researchers involved or interested
- Matthias Függer, LMF, email@example.com
- Thomas Nowak, LISN, firstname.lastname@example.org
- Patrick Amar, LISN, email@example.com
- Joffroy Beauquier, LISN, firstname.lastname@example.org
- Janna Burman, LISN, email@example.com
- Laurent Fribourg, LMF, firstname.lastname@example.org
A few references
- Sergi Regot, Javier Macia, Nuria Conde, Kentaro Furukawa, Jimmy Kjellen, Tom Peeters, Stefan Hohmann,Eulàlia de Nadal, Francesc Posas, Ricard Sole. Distributed biological computation with multicellular engineered networks. Nature, 469(7329):207–211, 2010
- Michael J. Liao, M. Omar Din, Lev Tsimring, Jeff Hasty. Rock-paper-scissors: Engineered population dynamics increase genetic stability. Science 365(6457):1045-1049. 2019.
- Da-Jung Cho, Matthias Függer, Corbin Hopper, Manish Kushwaha, Thomas Nowak, Quentin Soubeyran. Distributed computation with continual population growth. Proceedings of the 34th International Symposium on Distributed Computing (DISC). 2020.
Related Digicosme project
- HicDiesMeus: Highly Constrained Discrete Agents for Modeling Natural Systems
- DIGIT: Distributed Pulse Generation in Bacterial Colonies