Background & Inspiration

Foodborne pathogens pose a significant public health concern, transmitted through contaminated food and water [1]. Common foodborne pathogens include Bacillus cereus, Vibrio parahaemolyticus, Staphylococcus aureus (S. aureus), Salmonella, Campylobacter jejuni, Listeria monocytogenes, Shigella, and Escherichia coli (E. coli) [2]. These pathogens can survive in food or water sources, leading to gastrointestinal illnesses or food poisoning upon consumption, and in severe cases, may result in death. Current bacterial detection methods primarily include:

    1. Colony Counting: Based on traditional culturing methods, is considered the gold standard for bacterial detection due to its accuracy [3-4]. However, it is labor-intensive, time-consuming, and has low throughput.
    2. Nucleic Acid-Based Detection: Techniques such as Polymerase Chain Reaction (PCR) can detect specific gene expressions of bacteria to identify bacterial contamination in food [5]. However, this method typically requires expensive equipment and well-trained operators.
    3. Immunoassays: Enzyme-linked immunosorbent assay (ELISA), which detects specific bacterial antigens using antibodies, is also commonly used for bacterial detection [4]. However, it is relatively time-consuming and less sensitive.

Most existing bacterial detection methods focus on identification but neglect bactericidal capabilities. Therefore, developing a method that can both detect and eliminate pathogens is crucial.

Gold nanoparticles (AuNPs) have attracted significant interest in rapid and visual sensing due to their simple synthesis, easy surface modification, and excellent biocompatibility. AuNPs exhibit unique surface plasmon resonance (SPR) properties, displaying corresponding red or purple colors when dispersed or aggregated [6]. Additionally, several studies have demonstrated that AuNPs possess significant near-infrared (NIR) absorption capabilities, which can convert light energy into heat, making them promising candidates for targeted photothermal therapy [7]. Current literature also indicates that AuNPs can be conjugated with various substances such as proteins and antibodies for the recognition of target bacteria [8-9].

Leveraging these unique properties, we aim to exploit the unique SPR and photothermal conversion properties of AuNPs to develop a novel colorimetric biosensor for the direct detection and inactivation of foodborne pathogens. This innovative approach promises to combine the rapid and visual detection capabilities of AuNPs with the bactericidal potential of photothermal therapy, offering a comprehensive solution for food safety.

Design

In this project, we screened three phage-derived bacterial-binding proteins (PBPs) that specifically bind to E. coli, Salmonella, and S. aureus. These include the tail fiber protein (TFP) from T3 bacteriophage, the tailspike protein (TSP) from Salmonella phage CKT1, and the cell wall binding domain (CBD) from S. aureus phage plyV12. After producing these proteins through synthetic biology, we coupled the three proteins to the surface of AuNPs via electrostatic adsorption, resulting in three types of AuNPs@PBP.

The resulting AuNPs@PBP exhibit strong binding affinity to E. coli, Salmonella, and S. aureus, causing a color change in the detection system and demonstrating significant bactericidal activity upon exposure to NIR radiation. This biosensor can rapidly detect these three bacteria within 30 minutes through colorimetric detection. The RGB values of the color change are analyzed via a smartphone app, which outputs the detection results on the smartphone. Furthermore, the biosensor exhibits efficient antibacterial effects under 808 nm light irradiation for 10 minutes.

Goal

In this study, we propose a novel colorimetric biosensor comprising three types of AuNPs@PBP for the direct detection and inactivation of three foodborne pathogens. The aggregation of AuNPs@PBP on the surface of foodborne pathogens induces a color change in the detection system. Based on the RGB value analysis, the bacterial concentration is directly determined and displayed on a smartphone app. Finally, the pathogens are killed by the photothermal effect generated by AuNPs@PBP under NIR irradiation.

References
      1.Y. Song, W.Q. Li, H.Y. Xu, Recent advances and trends in aptasensors for sensitive detection of foodborne pathogens in various foods, Trac. Trends Anal. Chem. 167 (2023), https://doi.org/10.1016/j.trac.2023.117268.
      2.X. Zhao, C.W. Lin, J. Wang, D.H. Oh, Advances in rapid detection methods for foodborne pathogens, J. Microbiol. Biotechnol. 24 (3) (2014) 297–312, https:// doi.org/10.4014/jmb.1310.10013.
      3.Mandal, P. K., Biswas, A. K., Choi, K., and Pal, U. K. (2011). Methods for rapid detection of foodborne pathogens: an overview. Am. J. Food. Technol. 6, 87–102. doi: 10.3923/ajft.2011.87.102
      4.Zhao, X., Lin, C. W., Wang, J., and Oh, D. H. (2014). Advances in rapid detection methods for foodborne pathogens. J. Microbiol. Biotechn. 24, 297–312. doi: 10.4014/jmb.1310.10013
      5.Velusamy, V., Arshak, K., Korostynska, O., Oliwa, K., and Adley, C. An overview of foodborne pathogen detection: in the perspective of biosensors. Biotechnol. Adv. 28, 232–254. doi: 10.1016/j.biotechadv.2009.12.004
      6.Q. Yang, D. Wu, A. Aziz, S. Deng, L. Zhou, W. Chen, M. Asif, S. Wang, Colorimetric platform based on synergistic effect between bacteriophage and AuPt nanozyme for determination of Yersinia pseudotuberculosis, Microchim. Acta 190 (2) (2023), https://doi.org/10.1007/s00604-023-05643-z.
      7.M.J. Hajipour, A.A. Saei, E.D. Walker, B. Conley, Y. Omidi, K.B. Lee, M. Mahmoudi, Nanotechnology for targeted detection and removal of bacteria: opportunities and challenges, Adv. Sci. 8 (21) (2021), https://doi.org/10.1002/advs.202100556.
      8. G. Rabbani, M.E. Khan, A.U. Khan, S.K. Ali, M.A. Zamzami, A. Ahmad, A. H. Bashiri, W. Zakri, Label-free and ultrasensitive electrochemical transferrin detection biosensor based on a glassy carbon electrode and gold nanoparticles, Int. J. Biol. Macromol. 256 (2024) 128312, https://doi.org/10.1016/j. ijbiomac.2023.128312.
      9.L. Liu, Y. Xing, H. Zhang, R.L. Liu, H.J. Liu, N. Xia, Amplified voltammetric detection of glycoproteins using 4-mercaptophenylboronic acid/biotin-modified multifunctional gold nanoparticles as labels, Int. J. Nanomed. 9 (2014) 2619–2626, https://doi.org/10.2147/ijn.s62343.