Label-free SERS detection of foodborne pathogens based on a flexible PMMA-BP@MoS<sub>2</sub> binary substrate

Foodborne pathogenic bacteria, acting as direct or indirect contaminants of food and water sources, have emerged as a significant global food safety issue. Thus, the advancement of rapid, sensitive, and precise methods for detecting foodborne pathogens is of paramount importance for effective food safety monitoring. In response to this critical need, we have successfully prepared a flexible PMMA-BP@MoS<sub>2</sub>-based surface-enhanced Raman scattering (SERS) substrate through a two-step strategy involving hydrothermal synthesis and spin coating. This novel substrate enables label-free and highly sensitive detection of foodborne pathogens. The synergistic chemical enhancement effect of BP@MoS<sub>2</sub> on target molecules, coupled with the highly efficient molecular enrichment capability endowed by PMMA integration, endows the proposed binary substrate with remarkable SERS enhancement properties and stability. These characteristics significantly reduce the detection limit of model molecules to as low as 6.67 × 10<sup>-7</sup> M. Furthermore, trace levels of <i>Escherichia coli</i> in raw meat samples were effectively detected using the PMMA-BP@MoS<sub>2</sub> flexible substrate, achieving a wide linear detection range from 6.46 × 10<sup>4</sup> to 6.46 × 10<sup>8</sup> CFU mL<sup>-1</sup>. The flexible PMMA-BP@MoS<sub>2</sub> SERS substrate emerged as a promising solution for nondestructive and highly sensitive bacterial detection, paving the way for clinical diagnostics of diseases caused by foodborne pathogens and offering a valuable tool to address food safety challenges.

Authors

Institutions

Publication Details

Journal
The Analyst
Published
2025-01-01
DOI
https://doi.org/10.1039/d5an00454c
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Label-free SERS detection of foodborne pathogens based on a flexible PMMA-BP@MoS2 binary substrate

Tao Jiang, Danting Yang, Chenjie Gu, Xiaohan Liu et al.
The Analyst
Biosensors and Analytical Detection
article

Label-free SERS detection of foodborne pathogens based on a flexible PMMA-BP@MoS2 binary substrate

Tao Jiang, Danting Yang, Chenjie Gu, Xiaohan Liu, Shijiao Fu, Jialong Zhao
article en

Abstract

Foodborne pathogenic bacteria, acting as direct or indirect contaminants of food and water sources, have emerged as a significant global food safety issue. Thus, the advancement of rapid, sensitive, and precise methods for detecting foodborne pathogens is of paramount importance for effective food safety monitoring. In response to this critical need, we have successfully prepared a flexible PMMA-BP@MoS<sub>2</sub>-based surface-enhanced Raman scattering (SERS) substrate through a two-step strategy involving hydrothermal synthesis and spin coating. This novel substrate enables label-free and highly sensitive detection of foodborne pathogens. The synergistic chemical enhancement effect of BP@MoS<sub>2</sub> on target molecules, coupled with the highly efficient molecular enrichment capability endowed by PMMA integration, endows the proposed binary substrate with remarkable SERS enhancement properties and stability. These characteristics significantly reduce the detection limit of model molecules to as low as 6.67 × 10<sup>-7</sup> M. Furthermore, trace levels of <i>Escherichia coli</i> in raw meat samples were effectively detected using the PMMA-BP@MoS<sub>2</sub> flexible substrate, achieving a wide linear detection range from 6.46 × 10<sup>4</sup> to 6.46 × 10<sup>8</sup> CFU mL<sup>-1</sup>. The flexible PMMA-BP@MoS<sub>2</sub> SERS substrate emerged as a promising solution for nondestructive and highly sensitive bacterial detection, paving the way for clinical diagnostics of diseases caused by foodborne pathogens and offering a valuable tool to address food safety challenges.

The AnalystVol. 150(14)
Ningbo University (CN)
National Natural Science Foundation of China, Ningbo University
Zero hunger
Openalex Percentile: Top 87%
Biosensors and Analytical Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.