Foundational technologies

New tools and approaches are required in order to build information-processing systems in cells. If these tools are flexible enough, they can be applied to diverse set of specific cases, just like basic electronic building blocks can be integrated in an endless repertoire of devices and circuits. Any information processing system requires sensors to read out the requisite information; the bona fide computational module where the information is processed in a programmed fashion; and an actuation module that implements the results of a computation.

The same classification is valid in the biological context. Therefore we work on developing new sensors, computing modules, and actuators, as well as on combining them in a robust and reliable fashion into integrated systems. We are currently focused mainly on sensing gene-regulatory inputs such as microRNA and Transcription Factors. Our computing modules can be approximated as Boolean circuits, also known as digital, or logic, circuits. However this is a high-level approximation and in reality the circuits also operate in the continuous regime (analog computing).

Further reading

Logic with RNA interference

external pageRinaudo et al. A universal RNAi-based logic evaluator that operates in mammalian cells. Nature Biotechnology 25, 795 - 801 (2007)call_made

external pageXie et al. Logic integration of mRNA signals by an RNAi-based molecular computer. Nucl. Acids Res. 38, 2692-2701 (2010)call_made

external pageSchreiber, J., Arter, M., Lapique, N., Haefliger, B. & Benenson, Y. Model-guided combinatorial optimization of complex synthetic gene networks. Molecular Systems Biology 12, 899 (2016).call_made

external pageMohammadi, P., Beerenwinkel, N*. & Benenson, Y*. Automated design of synthetic cell classifier circuits using a two-step optimization strategy. Cell Systems 4, 1-12 (2017)call_made

Sensing and logic integration of transcriptional inputs

external pageLeisner et al. Rationally designed logic integration of regulatory signals in mammalian cells. Nature Nanotechnology 5, 666-670 (2010)call_made

external pageAngelici, B., Mailan, E., Haefliger, B. & Benenson, Y. Synthetic biology platform for sensing and integrating endogenous transcriptional inputs in mammalian cells. Cell Reports 16, 2525-2537 (2016).call_made

Compression and decompression of genetic programs

external pageLapique, N & Benenson, Y. Genetic programs can be compressed and autonomously decompressed in live cells. Nature Nanotechnology, doi:10.1038/s41565-017-0004-z (2017)call_made

Highly robust, leakage-free sensing

external pageLapique and Benenson. Digital switching in a biosensor circuit via programmable timing of gene availability. Nature Chemical Biology 10, 1020-1027 (2014)call_made

Scalable circuit desing using bow-tie network architecture

external pageProchazka et al. Highly modular bow-tie gene circuits with programmable dynamic behaviour. Nature Communications 5: 4729 (2014)call_made

Logic using transplanted prokaryotic signaling

external pageHansen et al. Transplantation of prokaryotic two-component signaling pathways into mammalian cells. PNAS 111, 15705-15710 (2014)call_made