4.7 Article

Label-free chemiresistor biosensor based on reduced graphene oxide and M13 bacteriophage for detection of coliforms

期刊

ANALYTICA CHIMICA ACTA
卷 1150, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.aca.2021.338232

关键词

Phage biosensor; Filed-effect transistor; Graphene; Detection of bacteria; M13-rGO-FET; Electrical sensor

资金

  1. DST/Intel(R)/Indo U.S. Science and Technology Forum
  2. Japan Student Services Organization
  3. W. Ruel Johnson Chair

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A novel chemiresistor biosensor using M13 phage-modified reduced graphene oxide was developed for detecting E. coli. The sensor showed a linear and specific response towards E. coli with high selectivity, indicating potential in detecting coliforms.
Coliform bacteria are well known as informative indicators for bacterial contamination in water. This study presents a novel chemiresistor biosensor using M13 phage-modified reduced graphene oxide (rGO) for detection of Escherichia coli (E. coli), as coliform bacteria. M13 phage, as a biorecognition element, was immobilized on the rGO channel, so that it can bind to negatively charged E. coli bacteria, allowing the gating effect on the biosensor and the change in its resistance. The prepared materials and device were characterized using spectroscopic, microscopic, and electrical measurements. FTIR and XRD results proved the successful fabrication of GO and rGO nanosheets. AFM results showed that the prepared nanosheets were monolayer. The SEM micrographs of the M13-functionalized devices, soaked in two different concentrations of E. coli, confirmed the successful capturing of E. coli and that the signal change is concentration-dependent. As a result, a linear and specific response towards E. coli was observed and the limit of detection was determined to be 45 CFU/mL. Further, the proposed sensor system showed selectivity towards the tested coliforms. These results suggested this sensing system could be a promising tool for detecting coliforms with an economic, accurate, rapid, and directly applicable process. (c) 2021 Elsevier B.V. All rights reserved.

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