An enzyme-free multi-stage hybridization chain reaction for the electrochemiluminescence detection of MRSA using MoS2

Yudie Sun1, Kehong Quan2, Ruilai Zhang2

  • 1School of Chemistry and Chemical Engineering, Anhui University of Technology, Ma Xiang Road, Maanshan, Anhui 243032, PR China; Key Laboratory of Optic-Electric Sensing and Analytical Chemistry for Life Science, MOE, Qingdao University of Science and Technology, Qingdao 266042, PR China.

Food Chemistry
|March 29, 2025
PubMed

Insights

A novel biosensor detects Methicillin-resistant Staphylococcus aureus (MRSA) with high sensitivity. This advanced electrochemiluminescence (ECL) method uses MoS2 NF@AuNPs for rapid and accurate foodborne pathogen identification.

Area of Science:

  • Nanomaterials Science
  • Biosensor Technology
  • Food Safety

Background:

  • Methicillin-resistant Staphylococcus aureus (MRSA) is a significant foodborne pathogen.
  • MRSA causes food poisoning and illnesses like vomiting, diarrhea, and pneumonia.
  • Accurate and sensitive detection methods for MRSA are crucial for public health.

Purpose of the Study:

  • To develop a highly sensitive and specific biosensor for MRSA detection.
  • To utilize MoS2 NF@AuNPs and DNA branching for enhanced signal amplification.
  • To validate the biosensor's performance in real food and water samples.

Main Methods:

  • Fabrication of a MoS2 NF@AuNPs enhanced electrochemiluminescence (ECL) biosensor.
  • Integration of bacterial aptamers and enzyme-free hybridization chain reaction (HCR) for signal amplification.
  • Detection of MRSA based on DNA branching tree structures and synergistic catalysis.

Main Results:

  • The biosensor achieved a wide linear detection range from 10^0 to 10^7 cfu/mL for MRSA.
  • A low detection limit of 1 cfu/mL was established.
  • The biosensor demonstrated excellent selectivity and sensitivity in real samples (water, juice, milk).

Conclusions:

  • The developed MoS2 NF@AuNPs enhanced ECL biosensor offers a promising tool for sensitive and specific MRSA detection.
  • This method provides a robust platform for identifying foodborne pathogens in complex matrices.
  • The biosensor's high performance supports its application in food safety and public health monitoring.