Fiber Optics-Based Surface Enhanced Raman Spectroscopy Sensors for Rapid Multiplex Detection of Foodborne Pathogens in Raw Poultry

Academic Background

Foodborne illnesses are a significant global public health challenge, with Salmonella being one of the leading pathogens causing such diseases. In the United States alone, Salmonella results in 1.35 million infections, 26,500 hospitalizations, and 420 deaths annually. Despite national improvement goals, the incidence of Salmonella infections in the U.S. has remained largely unchanged over the past three decades. Poultry products, particularly chicken and turkey, are the primary sources of Salmonella infections, accounting for approximately 23.4% of Salmonella cases. The Centers for Disease Control and Prevention (CDC) estimates that one out of every 25 chicken packages sold in grocery stores is contaminated with Salmonella. The economic impact of Salmonella in the U.S. amounts to $4.1 billion annually, including medical costs, productivity losses, and deaths.

Current Salmonella detection methods heavily rely on Polymerase Chain Reaction (PCR), which requires at least 24 hours (including enrichment, sample preparation, and nucleic acid extraction) and an additional 5-7 days for confirmation using traditional microbiological culture methods. Although PCR is considered the “gold standard” for pathogen detection, it is time-consuming and expensive. Additionally, immunological methods such as ELISA, while rapid, typically require an enrichment culture step, and the lack of timely results hinders poultry manufacturers from promptly implementing Salmonella intervention measures to enhance food safety.

In recent years, various rapid detection methods for foodborne pathogens have been investigated, including electrochemical, impedance, optical, lateral flow assay, potentiometric, and quartz crystal microbalance techniques. However, these methods often require complex instrumentation, lengthy sample preparation, and high costs. Surface Enhanced Raman Spectroscopy (SERS), as a highly sensitive, rapid, and label-free analytical tool, can identify molecules based on their vibrational modes and has broad application prospects. However, traditional SERS sensors, typically based on flat substrates or fiber tips, suffer from uneven signal enhancement and high fabrication costs.

Paper Source

This paper was co-authored by Mai Abuhelwa, Arshdeep Singh, Jiayu Liu, Mohammed Almalaysha, Anna V. Carlson, Kate E. Trout, Amit Morey, E. Kinzel, Lakshmikantha H. Channaiah, and Mahmoud Almasri, from the Department of Electrical Engineering and Computer Science, the Division of Food, Nutrition & Exercise Sciences at the University of Missouri, Cargill, Inc., the College of Health Sciences at the University of Missouri, the Department of Poultry Science at Auburn University, and the Department of Mechanical and Aerospace Engineering at the University of Notre Dame. The paper was published in 2024 in the journal Microsystems & Nanoengineering.

Research Process

1. Biosensor Design

This study designed a fiber optics-based SERS sensor for highly sensitive detection and identification of Salmonella in poultry products. For the first time, the sensor integrated metal nanoantenna arrays onto a side-polished multimode optical fiber core, combined with a 3D-printed plastic microstructure, enabling high-sensitivity detection of Salmonella in less than 10 minutes. The sensor identifies Salmonella by detecting its fingerprint Raman spectra, which are primarily based on the molecular composition of the bacteria, such as proteins, lipids, nucleic acids, and cell wall components.

2. Sensor Fabrication

The nanoantenna arrays were fabricated on the side-polished multimode optical fiber core using Microsphere Photolithography (MPL). First, the middle portion of the fiber was stripped to expose the cladding for polishing. The fiber was then inserted into a 3D-printed microstructure and polished to achieve a flat and smooth surface. Subsequently, the nanoantenna arrays were patterned on the polished surface using MPL, and gold nanodisk arrays were formed through a lift-off process.

3. Sample Preparation and Testing

Raw poultry rinsate was filtered and spiked with Salmonella Typhimurium and Escherichia coli O157:H7. The sensor detected the pathogens in the spiked samples using a Raman spectrometer, recording the Raman spectra and analyzing their fingerprint features.

Main Results

1. Sensitivity Testing

Experimental results demonstrated that the sensor achieved a sensitivity range of 0.4–0.5 cells/mL for Salmonella in raw poultry rinsate. By adjusting the sensing surface area and nanodisk diameter, the relative light intensity of the sensor increased with higher Salmonella concentrations. Larger sensing surface areas and smaller nanogaps enhanced the electric field intensity, forming SERS hotspots and thereby improving the Raman signal.

2. Multiplex Detection

The sensor was capable of simultaneously detecting Salmonella and E. coli O157:H7 with high specificity. By comparing the Raman spectra of the two pathogens, certain peaks were found to be specific to E. coli O157:H7, while others were specific to Salmonella, indicating that the technique could detect multiple pathogens simultaneously.

3. Optimal Detection Time

Experiments showed that the optimal detection time for the sensor was 10 minutes. Beyond this time, the signal intensity stabilized, and further extension of the detection time did not significantly improve sensitivity.

Conclusion

This study designed, fabricated, and validated a transformative fiber optics-based SERS sensor for the rapid detection of Salmonella in raw poultry. The sensor, which integrates highly uniform and repeatable nanoantenna arrays onto a side-polished multimode optical fiber core, demonstrated high sensitivity, specificity, and multiplex detection capabilities. Experimental results showed that the sensor could detect Salmonella at concentrations as low as 0.4–0.5 cells/mL in 10 minutes and could simultaneously detect Salmonella and E. coli O157:H7. This sensor has the potential to revolutionize food safety by reducing detection time and enhancing the poultry industry’s ability to implement timely interventions to improve food safety.

Research Highlights

1. High Sensitivity: The sensor can detect Salmonella at concentrations as low as 0.4–0.5 cells/mL in 10 minutes, far exceeding the detection limits of traditional methods.
2. Multiplex Detection: The sensor can simultaneously detect Salmonella and E. coli O157:H7 with high specificity.
3. Low-Cost Fabrication: The use of microsphere photolithography and 3D printing significantly reduces the sensor’s fabrication cost, making it suitable for large-scale production.
4. Rapid Detection: The sensor’s optimal detection time of 10 minutes is much faster than traditional PCR methods, providing timely results to help poultry manufacturers quickly implement intervention measures.

Research Significance

This study provides a new technological approach for food safety monitoring, significantly improving the detection efficiency of foodborne pathogens such as Salmonella. The sensor’s rapid detection capability enables the poultry industry to implement timely interventions, reducing the incidence of foodborne illnesses and safeguarding public health. Additionally, the sensor can be adapted to detect other bacterial and viral pathogens, such as E. coli O157:H7, Campylobacter, Listeria, and avian influenza, demonstrating broad application prospects.