In collaboration with : VistaMilk SFI Research Centre, University of Essex, Tyndall, LIFE Farm4more, University of Nebraska-Lincoln, PMBRC
Outline the paper
Bacterial populations naturally use and produce molecules. While some of these molecules include compounds that might be toxic to the environment in large quantities, they also help other cells to produce substances required for survival – such as helping in an animal’s digestive process. In this paper we consider the act of processing molecules by bacterial populations as molecular computing, and propose their integration into a microchip containing tubes and liquids, to allow the free movement of molecules, and to create a new breed of sensors for the dairy industry. This work describes how we designed a bacteria-based molecular computing microchip observing both theoretical and experimental aspects required by such a system.
A variety of systems have been created using electronic circuits integrated into small silicon chips. The same knowledge is being used as the basis for building novel biology systems with a similar design to these silicon chips. As such, we propose the design of a computing chip that integrates both biology and electronics, using both their strengths to create biocompatible sensors for smart farming.
Fig. 1- Representation of microfluidic-based bacterial molecular computing on a chip. Here we highlight the biological computing of molecules using bacterial populations and the detection of their produced signal by electrochemical sensors.
Who will it help?
The microchip design proposed in this research opens up the possibility of integrating multiple bacterial populations into a single bioelectronic device to compute and sense different molecules related to pollution, animal health, and soil quality. Our research focuses on simpler scenarios to demonstrate the feasibility of our idea, however, due to its computing nature, the microchip can be used to produce more complex diagnostics. For instance, it can combine the result of multiple measurements to identify particular diseases in animals, which are often detected by observing levels of multiple health indicators. Our proposed system is particularly useful to monitor farm soil quality, as it can be used to create a profile based on the amount of the different molecules found in the soil. The system can then signal whenever an expected variation of those amounts occurs to prevent soil degradation caused by natural cycles or human intervention.
What is the future of this research?
The integration of biology and electronics will continue to grow, and we plan to make our initial design more robust and flexible to be used in a wide variety of sensing applications for the dairy industry. For instance, the reliability of the computing process needs to be improved to reach electronic levels (99%). Another step in this process includes the creation of a prototype to improve our design, investigate its functionality, and identify its real-world limitations. Finally, with the prototype in hand we expect to perform experiments in realistic scenarios to characterise its application and potential future commercialisation.
The control of chemical levels in soil, and the detection of low molecular concentrations of compounds that indicate the health status of an animal are open challenges to the dairy industry. The microchip design proposed in this research deals with such challenges by integrating biological processes into electronics. Similarly, other industrial applications can benefit from the integration of biology and electronics, where there is a need to make decisions based on detected chemical compound concentrations – particularly for very low values. We expect that further developments for the technology introduced in this research will support the maintenance of soil quality and inspire other researchers to create more complex bioelectronic systems to benefit the dairy industry.
Publication Title: Microfluidic-based Bacterial Molecular Computing on a Chip
Authors: Daniel Perez Martins, Michael Taynnan Barros, Benjamin O’Sullivan, Ian Seymour, Alan O’Riordan, Lee Coffey, Joseph B. Sweeney and Sasitharan Balasubramaniam
Publication Date: 25 July 2022
Name of Journal: IEEE Sensors Journal
Link to publication: https://doi.org/10.1109/JSEN.2022.3192511