Nanoengineered Raman Sensors Push Food Pathogen Detection to New Limits

Surface-enhanced Raman spectroscopy, or SERS, is emerging as one of the most powerful tools in the food safety arsenal, and a new review published in Agricultural Products Processing and Storage lays out why. The technique exploits the interaction of incident light with the electromagnetic fields of nanostructured metal surfaces to amplify otherwise feeble Raman signals by many orders of magnitude. That amplification allows rapid, highly sensitive and specific identification of pathogens and microbial toxins lurking in milk, meat, seafood and infant formula.

The context is sobering. According to the World Health Organization, nearly 600 million people, roughly one in ten worldwide, fall ill each year from contaminated food, resulting in approximately 420,000 deaths. The review adopts what the authors call a material-performance-application framework, tracing the path from nanomaterial synthesis through structural regulation to signal amplification and, increasingly, artificial intelligence-powered analysis.

The story begins with single-component nanostructures. Gold, silver and copper nanoparticles are the workhorses of SERS because their surface plasmons concentrate light into nanoscale hotspots. The review catalogs a range of fabrication routes: chemical reduction, in which sodium citrate reduces gold ions and surfaces are functionalized with Raman reporter molecules such as 4-nitrothiophenol; in-situ synthesis, including a microfluidic approach in which silver nitrate and sodium borohydride mix in a Y-shaped serpentine channel to produce highly uniform silver nanoparticles at scale; in-situ growth directly on substrates, which eliminates transfer steps and controls growth orientation; and light-driven synthesis, in which ultraviolet irradiation at 360 nanometers drives anisotropic growth of gold nanostars, and 532-nanometer laser exposure photoreduces silver onto polymer particles with spatial precision. Biological templating even allows gold nanoparticles to be grown directly on the surface of M13 bacteriophage.

Yet the review is candid about the limits of these single-component systems. They rely solely on electromagnetic enhancement, and their weaknesses are material-intrinsic: silver offers strong enhancement but oxidizes readily, degrading signal reproducibility, while gold is stable but enhances less. Both suffer non-specific adsorption in complex food matrices, generating background that can mask the target signal. Aggregation and cumbersome, non-automatable handling further compromise reliability. The authors conclude that single-component materials typically serve only as foundational substrates, needing surface functionalization or integration into composites to perform in real-world scenarios.

That is where multicomponent nanostructures enter. Core-shell architectures, alloys and satellite structures combine electromagnetic and chemical enhancement mechanisms. Examples include Au@Ag core-shell nanoparticles whose shell thickness is tuned by the amount of added silver nitrate; Fe₃O₄@SiO₂-Au core-shell-satellite composites; graphene oxide loaded with gold nanoparticles to make GO@Au nanosheets; and Fe₃O₄ coated in-situ with a bimetallic iron-copper metal-organic framework and anchored to graphene nanosheets. Seed-mediated growth allows precise control of size and morphology, producing, for instance, Au@Ag core-shell nanorods. Magnetic composites add the ability to separate and enrich targets with an external magnet, reducing matrix interference. The trade-off, the review stresses, is that these sophisticated systems are sensitive to interfacial quality; imperfect gold distribution or lattice defects can cause signal loss and poor reproducibility, challenging scalable manufacturing.

Structural design then sharpens the enhancement. Core-shell structures such as silver nanoflowers coated with silica shells stabilize the metal against aggregation and chemical reactions while preserving hotspot access. Au@Pt nanoparticles pair a gold core, which boosts the Raman signal, with a platinum shell that catalyzes oxidation of TMB into a strongly Raman-active product, forming the basis of a sandwich-like immune complex assay. Engineered nanogaps, created for example by coating gold nanoparticles in silver and then dissolving part of the shell, dramatically amplify local electromagnetic fields. Membrane architectures such as gold nanoparticles uniformly distributed on polydimethylsiloxane films immobilize particles and prevent detachment, and quasi-crystalline gold nanocavity arrays arranged in a Thue-Morse sequence boost light-analyte interaction through strong near- and far-field coupling.

Beyond structure, the review details biochemical signal amplification. Hybridization chain reaction, an isothermal, enzyme-free method in which hairpin DNA probes cascade into long double-stranded polymers, multiplies binding sites for reporter-labeled nanoparticles; reaction time and probe concentration tune signal strength. Rolling circle amplification generates ultra-long single-stranded DNA that hybridizes with SERS probes, and a CRISPR/Cas12a-based workflow with optimized Cas12a concentration and cutting time extends amplification to nucleic acid targets. Magnetic nanoparticles, including Fe₃O₄ systems and Fe-MIL-88 with peroxidase-like activity that converts leuco malachite green to strongly Raman-active malachite green, handle rapid separation and purification. The review concludes that combining magnetic separation with amplification offers the best performance in real food analysis.

Applied to actual targets, the numbers are striking. For Staphylococcus aureus, a MnO₂@Au nanozyme aptamer assay achieved a detection range of 1×10¹ to 1×10⁷ CFU/mL with a SERS limit of 1.561 CFU/mL, while an Au@Ag@SiO₂ and vancomycin-grafted PDMS sandwich biosensor reached a limit of 2 CFU/mL. An HCR-enhanced strategy quantified S. aureus from 28 to 2.8×10⁶ CFU/mL with a limit of 0.25 CFU/mL. Salmonella assays built on Au-core Ag-shell lateral flow immunosensors detected S. enteritidis down to 1.36×10² CFU/mL, and an artificial click enzyme system reached 20 CFU/mL for Salmonella enterica serovar Paratyphi B. For E. coli O157:H7, aptamer-modified Au@macroporous magnetic SiO₂ photonic microspheres delivered a limit of 2.20 CFU/mL, and a wheat germ agglutinin-functionalized raspberry-like Fe₃O₄@Au biosensor reached 8 cells/mL. A plasmonic microneedle patch based on Au nanopopcorn even detected E. coli contamination directly in commercial mutton samples.

The scope extends well beyond the big three bacteria. Listeria monocytogenes was detected in cheese within one hour at a limit of 7.8 CFU/mL using comet-like Au-Ag nanoparticles, and a ZIF-8@Au@Pt dual-mode system reached 5 CFU/mL in SERS mode. Cronobacter sakazakii was quantified in powdered infant formula in 12 minutes without pre-culture, with a limit of 201 CFU/mL. Campylobacter jejuni, Shigella sonnei and Brucella assays followed, alongside detection of Bacillus cereus spore biomarker DPA at 0.3 nanomolar within 40 seconds, norovirus RNA at 0.16 femtomolar, and SARS-CoV-2 in frozen shrimp at 200 copies per milliliter. Microbial toxins fell just as readily: staphylococcal enterotoxin B at 0.2 picograms per milliliter, Stx2 Shiga toxin DNA down to 0.49 attomolar, and microcystin-LR in fish organs at 0.1 nanogram per liter using aptamer-recognized gold tags with magnetic separation. Multiplex platforms simultaneously distinguished pairs and trios of pathogens, with some limits as low as 2 CFU/mL per species.

Artificial intelligence is the accelerating force. Machine-learning classifiers paired with SERS achieved 100 percent accuracy classifying four bacterial species including L. monocytogenes on Au@Ag substrates; a deep CNN identified six pathogenic Vibrio species at 99.7 percent accuracy within 15 minutes; PCA-LDA models discriminated apple spoilage fungus spores at 98.31 percent; and a stacked autoencoder distinguished methicillin-resistant from methicillin-sensitive S. aureus at 97.66 percent. But the review temperately notes the translational hurdles: models depend on large curated spectral datasets that are costly to obtain from real foods, deep networks lack the interpretability regulators need, and most studies use pure cultures, leaving performance in authentic complex matrices under-explored. Standardized spectral libraries remain absent, signal uniformity and environmental sensitivity persist as problems, and current applications rely mostly on relatively simple matrices like milk and minced meat. The authors call for green synthesis of substrates, deeper understanding of combined electromagnetic and chemical enhancement, microfluidic automation, portable IoT-enabled devices, and noise-resistant algorithms, positioning SERS for a systematic transition from laboratory bench to real-time, on-site food safety testing.

Subject of Research: SERS-based nanostructured biosensors for detecting foodborne pathogens and microbial toxins

Article Title: SERS-active nanostructures for food microorganisms and toxins biosensing: compositional tailoring, structural regulation, and signal amplification

Article References: Qu, Z., Yang, E., Zeb, M., Zhu, J., Kim, Y., Simão, J. M. G., & Ma, W. (2026). SERS-active nanostructures for food microorganisms and toxins biosensing: compositional tailoring, structural regulation, and signal amplification. Agricultural Products Processing and Storage, 2(1), Article 37. https://doi.org/10.1007/s44462-026-00073-5

Image Credits: AI Generated

DOI: 10.1007/s44462-026-00073-5

Keywords: SERS, food safety, nanoparticles, foodborne pathogens, biosensors, Staphylococcus aureus, Salmonella, E. coli, microbial toxins, core-shell nanostructures, magnetic separation, artificial intelligence