Open Access
CAPACITANCE BIOSENSORS FOR THE RAPID DETECTION OF ESCHERICHIA COLI IN WATER
4
Department of Biotechnology, Indian Institute of Technology (IIT) Delhi, India
4
Institute of Microengineering and Nanoelectronics (IMEN), Universiti Kebangsaan Malaysia (UKM), Malaysia
4
PhD, School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore
Abstract
Ensuring the safety of drinking water and environmental water sources is a critical public health priority, with microbial contamination, particularly by fecal indicator bacteria like Escherichia coli (E. coli), posing significant risks. Traditional methods for detecting E. coli are often time-consuming, labor-intensive, and require specialized laboratory facilities, hindering rapid response to contamination events. This article explores the potential of capacitance biosensors as a rapid, label-free, and sensitive alternative for E. coli detection in water. The introduction highlights the importance of water quality monitoring and the limitations of current detection techniques. The methods section details the fundamental principles of impedance/capacitance microbiology and the design considerations for capacitance biosensors tailored for bacterial detection. The results synthesize current research demonstrating the efficacy of these biosensors in real-time monitoring of bacterial activity and specific pathogen identification. The discussion interprets the advantages and challenges of capacitance biosensors, emphasizing their potential for decentralized, on-site water quality assessment, and outlines future directions for research and development to achieve widespread adoption.
Keywords
Escherichia coli,
Water Quality,
Capacitance Biosensor,
Rapid Detection
References
Quiroz, K. L., Rodriguez, N. G., Murinda, S., & Ibekwe, M. (2018). Determination of the water quality of a constructed wetland monitoring fecal indicator bacteria.
Lazcka, O., Del Campo, F. J., & Munoz, F. X. (2007). Pathogen detection: A perspective of traditional methods and biosensors. Biosensors and Bioelectronics, 22(7), 1205–1217. https://doi.org/10.1016/j.bios.2006.06.036
Toze, S. (1999). PCR and the detection of microbial pathogens in water and wastewater. Water Research, 33(17), 3545–3556. https://doi.org/10.1016/S0043-1354(99)00071-8
Haglund, J. R., Ayres, J. C., Paton, A. M., Kraft, A. A., & Quinn, L. Y. (1964). Detection of Salmonella in eggs and egg products with fluorescent antibody. Applied Microbiology, 12(5), 447–450. https://doi.org/10.1128/am.12.5.447-450.1964
Ates, M. (2011). Review study of electrochemical impedance spectroscopy and equivalent electrical circuits of conducting polymers on carbon surfaces. Progress in Organic Coatings, 71, 1–10. https://doi.org/10.1016/j.porgcoat.2010.12.015
Yang, L., & Bashir, R. (2008). Electrical/electrochemical impedance for rapid detection of foodborne pathogenic bacteria. Biotechnology Advances, 26, 135–150. https://doi.org/10.1016/j.biotechadv.2007.10.003
Pethig, R., & Markx, G. H. (1997). Applications of dielectrophoresis in biotechnology. Trends in Biotechnology, 15, 426–432. https://doi.org/10.1016/S0167-7799(97)01096-2
Pethig, R. (1979). Dielectric and electronic properties of biological materials. Wiley.
Borkholder, D. A. (1998). Cell-based biosensors using microelectrodes (Ph.D. dissertation). Rochester Institute of Technology.
Firstenberg-Eden, R., & Eden, G. (1984). Impedance microbiology. Research Studies Press Ltd.
Wawerla, M., Stolle, A., Schalch, B., & Eisgruber, H. (1999). Impedance microbiology: Applications in food hygiene. Journal of Food Protection, 62, 1488–1496. https://doi.org/10.4315/0362-028X-62.12.1488
Ur, A., & Brown, D. F. J. (1975). Impedance monitoring of bacterial activity. Journal of Medical Microbiology, 8, 19–28. https://doi.org/10.1099/00222615-8-1-19
Silley, P., & Forsythe, S. (1996). Impedance microbiology: A rapid change for microbiologists. Journal of Applied Bacteriology, 80, 233–243. https://doi.org/10.1111/j.1365-2672.1996.tb03215.x
Owens, J. D., Thomas, D. S., Thompson, P. S., & Timmerman, W. (1989). Indirect conductimetry: A novel approach to the conductimetric enumeration of microbial populations. Letters in Applied Microbiology, 9, 245–249. https://doi.org/10.1111/j.1472-765X.1989.tb00337.3x
Ghafar-Zadeh, E., Sawan, M., Chodavarapu, V. P., & Hosseini-Nia, T. (2010). Bacteria growth monitoring through a differential CMOS capacitive sensor. IEEE Transactions on Biomedical Circuits and Systems, 4(4), 232–238. https://doi.org/10.1109/TBCAS.2010.2048430
Yao, L., Hajj-Hassan, M., Ghafar-Zadeh, E., Shabani, A., Chodavarapu, V., & Zourob, M. (2008, May). CMOS capacitive sensor system for bacteria detection using phage organisms. 2008 Canadian Conference on Electrical and Computer Engineering, 000877–000880. IEEE.
Rydosz, A., Brzozowska, E., Górska, S., Wincza, K., Gamian, A., & Gruszczynski, S. (2016). A broadband capacitive sensing method for label-free bacterial LPS detection. Biosensors and Bioelectronics, 75, 328–336. https://doi.org/10.1016/j.bios.2015.08.019
Jo, N., Kim, B., Lee, S. M., Oh, J., Park, I. H., Lim, K. J., Shin, J. S., & Yoo, K. H. (2018). Aptamer-functionalized capacitance sensors for real-time monitoring of bacterial growth and antibiotic susceptibility. Biosensors and Bioelectronics, 102, 164–170.
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