Our Project

We have developed a multicellular, modular biosensor development platform to usher in a new era of biosensors. The platform aims to ease the design, implementation, and characterisation/optimisation stages of biosensor development in the following ways:

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What is a Biosensor?

Biosensors can be thought of as any device which is capable of sensing an analyte (e.g. a molecule or compound) or certain condition (e.g. pH or temperature) through the use of a biological component (Turner, 2013). One example of this would be a canary in a coal mine, where in the presence of carbon monoxide, the canary dies. A perhaps less morbid and more advanced biosensor example are those which have been developed by synthetic biologists. All organisms use native biosensing devices to monitor molecules of interest and initiate cell responses. For example, maintenance of cell homeostasis requires the sensitive detection and subsequent regulation of many molecules, such as metals, fatty acids and hydrogen peroxide (Rensing & Grass, 2003, Zhang & Rock, 2009 and Marinho et al., 2014). Two-component systems are common biosensing systems in bacteria. These systems allow bacteria to respond to extracellular signals by the phosphorylation of a sensor kinase in the presence of a target molecule, which subsequently phosphorylates further response regulator proteins. These response regulators can alter cell behaviour through protein interactions, transcriptional regulation, or RNA binding (Gao et al., 2007).

In recent years, there has been a substantial increase in the number of biosensors produced using synthetic biology methods. Synthetic biology involves the application of engineering principles to the manipulation of biological systems. Biosensors constructed using these methods adapt the native cellular biosensing processes discussed previously, such as protein or RNA binding, and use these interactions to induce transcription of a reporter gene, such as a fluorescent protein.

These sensors may be expressed as living whole-cell sensors, but are also increasingly being expressed in cell-free protein synthesis systems. However, thus far, the costs of these systems has been prohibitive to wide-spread use in synthetic biology (Smith et al., 2017).

Why are Biosensors Useful?

One main advantage of synthetic biology based biosensors is their cost-effectiveness. After the research stages, production of the biosensor relies only on the maintenance of a population of cells expressing an engineered system, which is a relatively cheap process in comparison to other traditional methods such as immunoassays or mass spectrometry. Synthetic biology biosensors can be designed to have no dependence on additional equipment, which not only adds to their cost-effectiveness, but also enables onsite diagnostics (Bhatia & Chugh, 2013). Synthetic biology approaches also enable the introduction of more complex behaviour into biosensor designs, such as logic gates which allow for signal generation in response to a variety of simultaneous triggers (Chappel & Freemont, 2011).

One specific example of a biosensor is an arsenic biosensor, developed by Aleksic et al. (2007). This sensor was able to generate pH changes in response to the presence of arsenic in drinking water. In this system, ArsR, an arsenic responsive transcription factor, represses the pArs promoter in the absence of arsenic. When arsenic is present and bound to ArsR, the protein no longer binds and represses the promoter, enabling the transcription of downstream genes. In this example, the downstream gene is urease, which generates a detectable pH change. Therefore, the presence of arsenic can be detected by the monitoring of pH.

What problems do Biosensor Developers Face?

Our project focuses on the challenges of biosensor development: If synthetic biology biosensors are so much better than the alternatives, which are often expensive and not capable of onsite diagnosis, why isn’t their use more widespread?

In an attempt to answer this question, we consulted various stakeholders in biosensor development: both in and outside the field of synthetic biology, from the early research stage to end-users. We skyped, emailed, attended conferences, and even performed our own experiments. It was determined the problems faced by biosensor developers are in 5 main areas, detailed below.

Part Reusability	Output Comparability	Binding Sequences	Uptake of Technology	GMO Legislation

About the Sensynova Framework

Overview

In this project, it is proposed that modularity, and therefore the ability to use parts “off-the-shelf” without further genetic engineering, could be improved by splitting components of biosensors into different cells which communicate to coordinate responses. The orthogonal quorum sensing systems Rhl and Las will be used as biological “wires”, linking different biosensor components together. This separation of components will enable the decoupling of non-specific components from specific detection systems. Using this approach, production of biosensor variants will not require subsequent engineering steps: cells containing desired components will simply be mixed together.

Background Information

Multicellular systems

The splitting of biosensor components into separate cells may have additional advantages besides ease of variant production. Goni-Moreno et al. (2011) have previously suggested that the use of synthetic quorum sensing circuits enables each cell to be considered an independent logic gate, which may rectify the “fuzzy logic” seen in some biosensors, where stochastic cellular processes may produce false positive results. Quorum sensing has also been previously used to synchronise gene expressions, leading to reduced variability within a population (Danino et al., 2010).

Figure 1: Three-input multicellular biosensor design by Wang et al. 2013. RFP is produced in the presence of arsenic, mercury, and copper. Figure taken from Wang et al. 2013 (figure 4a).

The concept of biosensors in a multicellular environment is not a new idea. Wang et al (2013) used genetic logic gates in multiple cells to integrate signals from the detection of multiple analytes to one output. They used this concept to design a three-input heavy-metal biosensor, which produced a signal only in the presence of mercury, arsenic, and copper (Figure 1). One cell type in the community used a genetic AND gate to activate the expression of luxI in the presence of arsenic and mercury. LuxI synthesises the quorum sensing molecule 3OC₆HSL. A second cell type in the community used the same genetic AND gate to produce red fluorescent protein (RFP) in the presence of the HSL and copper. It was proposed in this study that this approach could lead to easily customisable and modular biosensors. While this design does allow the biosensor to be customised to some extent (e.g. the P_hrpL-rbs30-rfp construct could be replaced with a P_hrpL-rbs30-sfGFP construct), the individual parts are still coupled tightly together on the same DNA molecule, and mostly still within the same cell. Additionally, this design only allows for the design of biosensors with AND gates, and there is no capability to add additional signal processing modules into the system. Nevertheless, this study demonstrates that the principle of making biosensors multicellular and modular is both possible and useful.

Quorum sensing mechanisms

Figure 2: LasIR quorum sensing mechanism. LasI is produced constitutively by a cell. LasI synthesises the C12-HSL quorum sensing molecule. C12-HSL is able to diffuse through the membrane into the extracellular space. When enough LasI positive cells (cells producing LasI) are present in one location, the amount of C12-HSL in the extracellular space reaches a threshold concentration. At this point, the quorum sensing molecule diffuses into the surrounding cells through their membranes. These cells also produce the LasR transcription factor. C12-HSL can bind to LasR, enabling the transcription factor to activate transcription from the P_Las promoter.

In the Sensynova framework, two quorum sensing (QS) mechanisms are employed; the LasIR system and the RhlIR system. Both systems are acyl-homoserine lactone (AHL) based systems found in gram negative bacteria; specifically the Las and Rhl systems were orignially characterised in Pseudomonas aeruginosa as a regulatory mechanism for virulence factors (Pearson et al. 1997).

References:

1) Aleksic et al. such and such (2007)
2) Bhatia, P. & Chugh, A. (2013) Synthetic Biology Based Biosensors and the Emerging Governance Issues Current Synthetic and Systems Biology 1: 108
3) Chappel, J. & Freemont, P. (2011) Synthetic Biology – A new generation of biofilm biosensors Forum on Microbial Threats. The Science and Applications of Synthetic and Systems Biology: Workshop Summary. National Academies: Washington (DC)
4) Danino, T., Mondragon-Palomino, O., Tsimring, L. & Hasty, J. (2010) A synchronized quorum of genetic clocks Nature 463: 326 - 330
5) Gao such and such (2007)
6) Goni-Moreno, A., Redondo, M., Arroyo, F. & Castellanos, J. (2011) Biocircuit design through engineering bacterial logic gates Natural Computing 10: 119 – 127
7) Rensing, C. & Grass, G. (2003) Escherichia coli mechanisms of copper homeostasis in a changing environment FEMS Microbiology Reviews 27: 197 – 213
8) Marinho, S., Real, C., Cyrne, L., Soares, H. & Antunes, F. (2014) Hydrogen Peroxide sensing, signalling and regulation of transcription factors Redox biology 2: 535 – 562
9) Smith such and such (2017)
10) Turner, A. P. F. (2013) Biosensors: sense and sensibility, Chem. Soc. Rev., DOI: 10.1039/C3CS35528D
11) Zhang, Y. & Rock, C. (2009) Transcriptional regulation in bacterial membrane lipid synthesis Journal of Lipid Research 50: S115