In Silico Design and Analysis of Genetic Circuit-Based Whole-Cell Biosensors for Detecting Groundwater Contaminants

Abstract

AbstractContaminants of emerging concern (CEC) such as tetracycline, erythromycin, and salicylic acid in groundwater can seriously endanger the environment and human health due to their widespread and everlasting harmful effects. Thus, continuous monitoring of various CEC concentrations in groundwater is essential to ensure the safety, security, and biodiversity of natural habitats. CECs can be detected using whole-cell biosensors for environmental surveillance and monitoring purposes, as they provide a cheaper and more robust alternative to traditional and expensive analytical techniques. In this study, various genetic circuit designs are considered to model three biosensors using the genetic design automation (GDA) software, iBioSim. The genetic circuits were designed to detect multiple CECs, including atrazine, salicylic acid, and tetracycline simultaneously to produce quantitative fluorescent outputs. The biosensor responses and the viability of the genetic circuit designs were further analysed using ODE-based mathematical simulations in iBioSim. The designed circuits and subsequent biosensor modelling presented here, thus, not only show the usefulness and importance of GDA tools, but also highlight their limitations and shortcomings that need to overcome in the future; thereby, providing a practical guidance for further improvement of such tools, so that they can be more effectively and routinely used in synthetic biology research.