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Food-borne bacteria analysis using a diatomite bioinspired SERS platform.

Yikai Chen1,2, Binggang Ye1, Mengling Ning1,2

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A new surface-enhanced Raman scattering (SERS) sensor uses a bioinspired substrate for rapid detection of food-borne bacteria and dye residues. This SERS platform shows high sensitivity and can differentiate bacterial strains like Staphylococcus aureus and Escherichia coli.

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Area of Science:

  • Analytical Chemistry
  • Materials Science
  • Biotechnology

Background:

  • Sensitive detection of food-borne pathogens remains a significant challenge.
  • Existing methods often lack speed and sensitivity for environmental monitoring.
  • Novel sensing platforms are needed for rapid identification of food contaminants.

Purpose of the Study:

  • To develop a novel surface-enhanced Raman scattering (SERS) sensing strategy for detecting food-borne bacteria and dye residues.
  • To create a bioinspired SERS substrate with enhanced sensitivity and specificity.
  • To demonstrate the platform's capability for identifying specific bacterial strains.

Main Methods:

  • Fabrication of a SERS substrate using a natural diatomite microporous array decorated with a metal-phenolic network.
  • In situ reduction of gold nanoparticles on the substrate for enhanced SERS activity.
  • Analysis of dye molecular residues and food-borne bacteria (Staphylococcus aureus, Escherichia coli) using SERS.
  • Characterization of SERS performance, including limit of detection and Raman enhancement factor.

Main Results:

  • The developed nanocomposite substrate exhibited excellent SERS activity.
  • Achieved a lowest limit of detection of 10^-11 M for dye molecules.
  • Obtained a maximum Raman enhancement factor of 1.18 × 10^7 for dye molecules.
  • Successfully distinguished the biochemical fingerprints of Staphylococcus aureus and Escherichia coli, enabling strain identification.

Conclusions:

  • The novel bioinspired SERS substrate demonstrates high sensitivity and specificity for detecting food-borne bacteria and dye residues.
  • The platform offers a promising tool for rapid and accurate identification of food-borne pathogens.
  • This technology has significant potential for application in food safety and environmental monitoring.