Microfluidic-based bacterial molecular computing on a chip

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dc.contributor.authorMartins, Daniel P.en
dc.contributor.authorTaynnan Barros, Michaelen
dc.contributor.authorO’Sullivan, Benjamin J.en
dc.contributor.authorSeymour, Ianen
dc.contributor.authorO’Riordan, Alanen
dc.contributor.authorCoffey, Leeen
dc.contributor.authorSweeney, Joseph B.en
dc.contributor.authorBalasubramaniam, Sasitharanen
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderDepartment of Agriculture, Food, and Marineen
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2023-03-27T14:50:17Z
dc.date.available2023-03-27T14:50:17Z
dc.date.issued2022-07-25en
dc.description.abstractBiocomputing 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.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDaniel P. Martins; Barros, M. T., O’Sullivan, B. J., Seymour, I., O’Riordan, A., Coffey, L., Sweeney, J. B. and Balasubramaniam, S. (2022) 'Microfluidic-based bacterial molecular computing on a chip', IEEE Sensors Journal, 22(17), pp. 16772-16784. doi: 10.1109/JSEN.2022.3192511en
dc.identifier.doi10.1109/JSEN.2022.3192511en
dc.identifier.eissn1558-1748en
dc.identifier.endpage16784en
dc.identifier.issn1530-437Xen
dc.identifier.issued17en
dc.identifier.journaltitleIEEE Sensors Journalen
dc.identifier.startpage16772en
dc.identifier.urihttps://hdl.handle.net/10468/14327
dc.identifier.volume22en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.project16/RC/3835en
dc.rights© 2022, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectBacterial molecular computingen
dc.subjectBiosensorsen
dc.subjectElectrochemical sensingen
dc.subjectMicrofluidicsen
dc.subjectMolecular communicationsen
dc.subjectSynthetic logic gatesen
dc.titleMicrofluidic-based bacterial molecular computing on a chipen
dc.typeArticle (peer-reviewed)en
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