Optical fiber sensor enables highly sensitive detection of deadly foodborne bacteria

Shigella sonnei (S. sonnei) is one of the major bacteria responsible for dysentery, which plagues millions of people every year, mostly in developing countries. S. sonnei is commonly spread through contaminated food or water, making detection of the bacteria essential for eliminating outbreaks and saving lives.

Zhang et al. developed an optical fiber sensor for S. sonnei detection that is faster, simpler, and more accurate than existing methods.

“Our sensor design is simple to operate, eliminating the need for the user to perform a complex labeling process,” said author Santosh Kumar. “It is highly specific and can accurately identify the target bacterium, and its high sensitivity allows for the effective detection of even very low concentrations of S. sonnei.”

Their sensor relies on the localized surface plasmon resonance (LSPR) effect, which is highly sensitive to the surrounding refractive index. When adding S. sonnei solution into a reaction vessel filled with S. sonnei antibodies, there will be a change in the refractive index of the surrounding environment, affecting the LSPR peak shift. Their design incorporates a crayfish-type optical fiber structure to improve the evanescent field and further increase the LSPR effect.

By designing their sensor to be easy to use, the researchers hope to expand their availability in developing regions. They next plan to adapt their method to detect other foodborne pathogens.

“Our goal is to delve into key issues in the field of food safety, especially regarding the detection of harmful substances,” said Kumar. “Through these studies, we hope to raise awareness of the potential risks of foodborne bacteria and develop more effective detection methods to protect public health and improve food safety standards.”

Source: “Multimodal LSPR-enhanced crayfish-type optical fiber sensor for ultra-sensitive detection of Shigella sonnei using hybrid nanomaterials,” by Qi Zhang, Ragini Singh, Jan Nedoma, Rui Min, Carlos A. F. Marques, Bingyuan Zhang, and Santosh Kumar, APL Photonics (2024). The article can be accessed at https://doi.org/10.1063/5.0242975 .