GenePhLo: Genetic Phase-based Logic

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Just like electronic computers can take input and employ algorithms to get an output, so can living cells react to some input molecule and produce another in response. Instead of electric circuits, cells have a network of linked biological processes, at the base of which we have the central dogma - DNA is transcribed into RNA, RNA is translated into proteins, and proteins can regulate DNA transcription (Brophy and Voigt, 2014). Using DNA with known functions, we can assemble genetic logical circuits.The most common approach to both electronic and bio-computing is level-based: when a signal (electric voltage or a biomolecule concentration) is under one threshold, the signal is counted as low, or binary 0, and when it is above another, it is counted as high, or binary 1. While this computation method is widespread and can even be found in natural systems like Ca2+ signalling (Berridge, Lipp and Bootman, 2000), it is not very robust to noise. This can be a problem in intrinsically noisy biological systems. For example, the same protein can be expressed differently across the bacterial colony under the same growing conditions (Beal, 2017), which could result in conflicting computing outcome. What is more, in level-based logic the signal between the thresholds is not determined, neither 0 nor 1.Another way to encode binary logic is to use phases of oscillating signals. When a signal oscillates in phase with the reference, this is counted as binary 1, and when it is out of phase, 0. Sub-harmonic injection locking (SHIL) can be used to make oscillatory signal bistable, so that the phase could be shifted in response to an input (Roychowdhury, 2015), recording a single bit of information. To reach such bistability, a locking signal of twice higher frequency needs to be added to the system.While phase-based computers are more robust to noise, this approach has not yet been applied in biocomputing. I would like to change this. In my project, I aim to build and characterize basic genetic phase-based logic circuits.Objectives:Characterize phase shifts due to the delays caused by transcription, translation, and diffusion of signalling molecules.Build and characterize a phase-based NOT gate.Compare robustness of phase-based and level-based NOT gates.Build and test phase-based complimentary MAJORITY, NAND and NOR gates.Use Danino et al. (2010) oscillator to test SHIL.In my project, I will apply both computational and lab-based approaches. I will use modelling to explore a range of parameters and determine suitable experimental setups. In the lab, I will use characterized engineered E. coli cells and grow them in microfluidic devices, using a Nikon Ti-E microscope to record their behaviour. When needed, I will edit existing genetic circuits or engineer new using Gibson and Golden Gate assembly methods. I will use small signalling molecules and quorum sensing as inputs and "wires", linking cells with different genetic circuits together. Finally, I will connect cells containing logic gates to a synchronized genetic oscillator colony by Danino et al. (2010) which will act as a state register.References:Beal, J. (2017) 'Biochemical complexity drives log-normal variation in genetic expression', Engineering Biology, 1(1). Available at: https://doi.org/10.1049/enb.2017.0004. Berridge, M.J., Lipp, P. and Bootman, M.D. (2000) 'The versatility and universality of calcium signalling', Nature Reviews Molecular Cell Biology. Available at: https://doi.org/10.1038/35036035.Brophy, J.A.N. and Voigt, C.A. (2014) 'Principles of genetic circuit design', Nature Methods. Available at: https://doi.org/10.1038/nmeth.2926.Danino, T. et al. (2010) 'A synchronized quorum of genetic clocks', Nature 2010 463:7279, 463(7279), pp. 326-330. Available at: https://doi.org/10.1038/nature08753.Roychowdhury, J. (2015) 'Boolean Computation Using Self-Sustaining Nonlinear Oscillators', Proceedings of the IEEE, 103(11). Available at: https: