| Summary: | Synthetic biology is one of the new frontiers in research. It distinguished itself through the quantification of biological interactions that enables genetic circuit modelling for a better understanding of the system. In this study, the genetic circuit models of biosensors (quorum sensing, metal sensors) and biological amplifiers (gain-tunable genetic amplifier) were constructed in-silico to study its detection efficacy and gain tuning amplification capabilities. Modelling is performed based on ODE representations of the biological processes and the parameters associated are derived primarily from literature along with the experimental data. Genetic circuits are drawn using MATLAB Simulink and sensitivity analysis were ran to identify the sensitive parameters. From this study, the models of quorum sensing, gold metal sensing and arsenic tunable gain amplifier are successfully validated with the experimental based modelling from their respectively literatures. The model of quorum sensing model has displayed a good dynamic range within 1.0e-7 to 1.0e1M AHL which reflects the detection capabilities of experimental model in the AHL range of 1.0e-6 to 1.0e4M. Likewise for the model of the gold metal sensing, a similar gold detection range from 8e-9M up to 8e-6M is also reflected as in the experimental model. Furthermore, the model of arsenic metal-tunable gain amplifier displayed a wide tuning range up to 98.62% signal reduction with a similar linearity profile as in the experimental model. Finally via its assembly with previously validated gold metal sensing, a wide tuning control up to 99.99% signal reduction and modularity are also displayed as in the experimental model.
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