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Lee Y, Kim SJ, Kim YJ, Kim YH, Yoon JY, Shin J, Ok SM, Kim EJ, Choi EJ, Oh JW. Sensor development for multiple simultaneous classifications using genetically engineered M13 bacteriophages. Biosens Bioelectron 2023; 241:115642. [PMID: 37703643 DOI: 10.1016/j.bios.2023.115642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/17/2023] [Accepted: 08/25/2023] [Indexed: 09/15/2023]
Abstract
Sensors for detecting infinitesimal amounts of chemicals in air have been widely developed because they can identify the origin of chemicals. These sensing technologies are also used to determine the variety and freshness of fresh food and detect explosives, hazardous chemicals, environmental hormones, and diseases using exhaled gases. However, there is still a need to rapidly develop portable and highly sensitive sensors that respond to complex environments. Here, we show an efficient method for optimising an M13 bacteriophage-based multi-array colourimetric sensor for multiple simultaneous classifications. Apples, which are difficult to classify due to many varieties in distribution, were selected for classifying targets. M13 was adopted to fabricate a multi-array colourimetric sensor using the self-templating process since a chemical property of major coat protein p8 consisting of the M13 body can be manipulated by genetic engineering to respond to various target substances. The twenty sensor units, which consisted of different types of manipulated M13, exhibited colour changes because of the change of photonic crystal-like nanostructure when they were exposed to target substances associated with apples. The classification success rate of the optimal sensor combinations was achieved with high accuracy for the apple variety (100%), four standard fragrances (100%), and aging (84.5%) simultaneously. We expect that this optimisation technique can be used for rapid sensor development capable of multiple simultaneous classifications in various fields, such as medical diagnosis, hazardous environment monitoring, and the food industry, where sensors need to be developed in response to complex environments consisting of various targets.
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Affiliation(s)
- Yujin Lee
- Department of Nano Fusion Technology, Pusan National University, 46241, Busan, Republic of Korea.
| | - Sung-Jo Kim
- Bio-IT Fusion Technology Research Institute, Pusan National University, 46241, Busan, Republic of Korea
| | - Ye-Ji Kim
- Department of Nano Fusion Technology, Pusan National University, 46241, Busan, Republic of Korea
| | - You Hwan Kim
- Department of Nano Fusion Technology, Pusan National University, 46241, Busan, Republic of Korea
| | - Ji-Young Yoon
- Dental Research Institute, Dental and Life Science Institute, Pusan National University, 50612, Yangsan, Republic of Korea; Department of Dental Anesthesia and Pain Medicine, School of Dentistry, Pusan National University, 50612, Yangsan, Republic of Korea
| | - Jonghyun Shin
- Dental Research Institute, Dental and Life Science Institute, Pusan National University, 50612, Yangsan, Republic of Korea; Department of Pediatric Dentistry, School of Dentistry, Pusan National University, 50612, Yangsan, Republic of Korea
| | - Soo-Min Ok
- Dental Research Institute, Dental and Life Science Institute, Pusan National University, 50612, Yangsan, Republic of Korea; Department of Oral Medicine, School of Dentistry, Pusan National University, 50612, Yangsan, Republic of Korea
| | - Eun-Jung Kim
- Dental Research Institute, Dental and Life Science Institute, Pusan National University, 50612, Yangsan, Republic of Korea; Department of Dental Anesthesia and Pain Medicine, School of Dentistry, Pusan National University, 50612, Yangsan, Republic of Korea
| | - Eun Jung Choi
- Bio-IT Fusion Technology Research Institute, Pusan National University, 46241, Busan, Republic of Korea; Korea Nanobiotechnology Center, Pusan National University, 46241, Busan, Republic of Korea
| | - Jin-Woo Oh
- Department of Nano Fusion Technology, Pusan National University, 46241, Busan, Republic of Korea; Bio-IT Fusion Technology Research Institute, Pusan National University, 46241, Busan, Republic of Korea; Korea Nanobiotechnology Center, Pusan National University, 46241, Busan, Republic of Korea; Department of Nanoenergy Engineering and Research Center for Energy Convergence Technology, Pusan National University, 46241, Busan, Republic of Korea
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