4.7 Article

Microfluidic-Based Bacterial Molecular Computing on a Chip

Journal

IEEE SENSORS JOURNAL
Volume 22, Issue 17, Pages 16772-16784

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2022.3192511

Keywords

Sensors; Microorganisms; Statistics; Sociology; Electron tubes; Reliability; Molecular computing; Bacterial molecular computing; biosensors; electrochemical sensing; microfluidics; molecular communications; synthetic logic gates

Funding

  1. Science Foundation Ireland (SFI)
  2. Department of Agriculture, Food and Marine on behalf of the Government of Ireland [16/RC/3835-VistaMilk]

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This paper proposes a biocomputing system based on engineered bacteria for environmental monitoring and detection of metabolic diseases. The authors present a prototype of a Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. They demonstrate that electrochemical sensors can detect small changes in pH and dissolved oxygen concentrations created by engineered bacterial populations. Theoretical modeling analysis shows that variations in production delay and molecular output signal concentration can impact the computation reliability.
Biocomputing systems based on engineered bacteria can lead to novel tools for environmental monitoring and detection of metabolic diseases. In this paper, we propose a Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. The computing can be flexibly integrated into the chip, but we focus on engineered bacterial AND Boolean logic gate and ON-OFF switch sensors that produces secondary signals to change the pH and dissolved oxygen concentrations. We present a prototype with experimental results that shows the electrochemical sensors can detect small pH and dissolved oxygen concentration changes created by the engineered bacterial populations' molecular signals. Additionally, we present a theoretical model analysis of the BMCoC computation reliability when subjected to unwanted effects, i.e., molecular signal delays and noise, and electrochemical sensors threshold settings that are based on either standard or blind detectors. Our numerical analysis found that the variations in the production delay and the molecular output signal concentration can impact on the computation reliability for the AND logic gate and ON-OFF switch. The molecular communications of synthetic engineered cells for logic gates integrated with sensing systems can lead to a new breed of biochips that can be used for numerous diagnostic applications.

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