Rapid Detection Of Foodborne Pathogens Research Articles

Identification of Potential Biomarkers and Spectral Fingerprinting for Detection of Foodborne Pathogens in Raw Chicken Meat Matrix Using GCMS and FTIR.

Foodborne illnesses pose a serious threat to public health, with increasing global incidence rates driven by factors such as rising meat consumption. Rapid detection of foodborne pathogens in meat is critical for preventing outbreaks. This study investigates the potential of gas chromatography-mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) for identifying biomarkers and spectral fingerprints indicative of foodborne pathogens in raw chicken meat. Raw broiler chicken meat samples were surface-sterilized and inoculated with foodborne pathogens. The samples were challenge inoculated with the specific pathogen and the physical quality parameters like pH, color, texture, drip loss, and water activity were assessed. GC-MS analysis identified 113 metabolites, including potential biomarkers like ureidopropionic acid, 5-sulfosalicylic acid, 11,14-eicosadienoic acid, methyl ester for E. coli O157:H7; 11-bromoundecanoic acid, neocurdione, glafenin, eicosanoic acid for Salmonella; azepan-1-yl-acetic acid, methyl ester, tramadol, cytarabine, dipipanone for Staphylococcus and cyclopentaneundecanoic acid, phosphonofluoridic acid, î-n-formyl-l-lysine for Pseudomonas. Pathway analysis revealed the involvement of fatty acid metabolism and amino acid degradation pathways. FTIR spectral data showed significant variances between control and spiked samples, particularly in the fatty acid spectral region. The identified metabolites and spectral patterns could serve as biomarkers for developing rapid pathogen detection methods, contributing to enhanced food safety protocols.

Nanobody-Induced Aggregation of Gold Nanoparticles: A Mix-and-Read Strategy for the Rapid Detection of Cronobacter sakazakii.

Protein-nanoparticle interactions play a crucial role in both biomedical applications and the biosafety assessment of nanomaterials. Here, we found that nanobodies can induce citrate-capped gold nanoparticles (AuNPs) to aggregate into large clusters. Subsequently, we explored the mechanism behind this aggregation and proposed the "gold nucleation mechanism" to explain this phenomenon. Building on this observation, we developed a one-step label-free colorimetric method based on nanobody-induced AuNP aggregation. When nanobodies bind to target bacteria, spatial hindrance occurs, preventing further AuNPs aggregation. This alteration in surface plasmon resonance properties results in visible color changes. As an example, we present a simple and sensitive "mix-and-read" chromogenic immunosensor for Cronobacter sakazakii (C. sakazakii). The experiment can be completed within 20 min, with a visual detection limit of 103 CFU/mL and a quantitative detection limit of 136 CFU/mL. Importantly, our method exhibits no cross-reactivity with other bacterial species. This strategy harnesses the excellent properties of nanobodies and the optical characteristics of AuNPs for direct and rapid detection of foodborne pathogen.

SERS-based Ag NCs@PDMS flexible substrate combined with chemometrics for rapid detection of foodborne pathogens on egg surface.

Aninnovative methodis introducedbased on the combination of label-free surface-enhanced Raman scattering with advanced multivariate analysis. This technique allows both quantitative and qualitative assessment of Salmonella typhimurium and Escherichia colion eggshells. Using silver nanocubes embedded in polydimethylsiloxane, we consistently achieved Raman spectra of bacteria. The stability of the Ag NCs@PDMS substrate is confirmed using rhodamine 6G over 30days under standard conditions. Principal component analysis (PCA) effectively distinguishes between S. typhimurium and E. coli spectra. Partial least squares regression (PLS) modelsweredeveloped for quantitative determinationof bacteria on egg surfaces, yielding accurate results with minimal error. The S. typhimurium model achieves Rc2 = 0.9563 and RMSEC = 0.601 in calibration, and Rv2 = 0.9113 and RMSEV = 0.907 in validation. Similarly, the E. coli model achieves Rc2 = 0.9877 and RMSEC = 0.322 in calibration, and Rv2 = 0.9606 and RMSEV = 0.579 in validation. Recoveriesvalidate PLS predictions by inoculating egg surfaces with varying bacterial amounts. Our study demonstrates the feasibility of SERS-PLS for quantitative determinationof S. typhimurium and E. coli on eggshells, promising enhanced food safety protocols.

Sensitive electrochemical immunosensor for rapid detection of Salmonella in milk using polydopamine/CoFe-MOFs@Nafion modified gold electrode

Food contaminated by pathogenic bacteria poses a serious threat to human health. Consequently, we used Salmonella as a model and developed an electrochemical immunosensor based on a polydopamine/CoFe-MOFs@Nafion nanocomposite for the detection of Salmonella in milk. The CoFe-MOFs exhibit good stability, large specific surface area, and high porosity. However, after modification on the electrode surface, they were prone to detachment. This issue was effectively mitigated by incorporating Nafion into the nanocomposite. A polydopamine (PDA) film was deposited onto the surface of CoFe-MOFs@Nafion through cyclic voltammetry (CV), accompanied by an investigation into the polymerization mechanism of the PDA film. PDA contains a substantial number of quinone functional groups, which can covalently bind to amino or sulfhydryl groups via Michael addition reaction or Schiff base reaction, thereby immobilizing anti-Salmonella antibodies onto the modified electrode surface. Under the optimal experimental conditions, the Salmonella concentration exhibited a good linear relationship within the range of 1.38 × 102 to 1.38 × 108 CFU mL−1, with a detection limit of 1.38 × 102 CFU mL−1. Furthermore, the constructed immunosensor demonstrated good specificity, stability, and reproducibility, offering a novel approach for the rapid detection of foodborne pathogens.

RAPID METHODS FOR DETECTION OF FOODBORNE PATHOGENS AND THEIR TOXINS - A REVIEW OF CURRENT TRENDS AND FUTURE PERSPECTIVES

Background: Food safety is of utmost importance to sustaining life and promoting good health and is a main problem in any country, regardless of economic and social development. Unsafe food containing harmful pathogens and their toxins cause hundreds of diseases, particularly affecting infants, young children, the elderly and sick people. Therefore, the rapid detection of foodborne pathogens is of great significance for public health. The aim of this review was to provide comprehensive information regarding methods for the detection of foodborne pathogens as well as genus Fusarium and their toxins, from fundamental to state-of-the-art, presenting their advantages and limitations in order to update current knowledge. Review Results: The traditional culture-based methods for the detection of pathogens in food are usually laborious, limited by complex sample preparation procedures, time-consuming, slow to provide results, and require well-trained professional staff. However, compared to these methods, the new ones - immunological methods, nucleic acid-based assays and biosensor-based methods are rapid, accurate, highly sensitive and specific, and easy to use. Precisely providing accurate real-time results would help limit foodborne disease outbreaks, ensure compliance with legislation setting maximum levels of pathogens in certain food categories, detect and improve the import of food contaminated with dangerous levels of pathogenic microorganisms, and ensure public health safety. Conclusion: The development of rapid and automated methods that detect real-time, small numbers of viable microbial cells within a given volume of food is vital in the prevention, transmission and treatment of foodborne diseases. Such methods would also offer a great commercial advantage in the food industry and related fields.

MassARRAY: a high-throughput solution for rapid detection of foodborne pathogens in real-world settings.

Bacterial foodborne pathogens pose a substantial global public health concern, prompting government agencies and public health organizations to establish food safety guidelines and regulations aimed at mitigating the risk of foodborne illness. The advent of DNA-based amplification coupled with mass spectrometry, known as MassARRAY analysis, has proven to be a highly precise, sensitive, high-throughput, and cost-effective method for bacterial detection. This study aimed to develop, validate, and evaluate a MassARRAY-based assay for the detection and identification of significant enteropathogenic bacteria. The MassARRAY-based assay was developed for the detection of 10 crucial bacterial foodborne pathogens, including Campylobacter coli, Campylobacter jejuni, Clostridium perfringens, Escherichia coli, Enterococcus faecalis, Enterococcus faecium, Listeria monocytogenes, Salmonella spp., Shigella spp., and Staphylococcus aureus. The assay was optimized using the reference gDNA (n = 19), followed by validation using gDNA (n = 85) of reference and laboratory isolates. Additionally, the evaluation of the assay's reaction using a mixture of gDNA from all nine targeted species was performed. The limit of detection of the developed MassARRAY-based assay was determined using bacterial cells. Moreover, the validation method for field samples was evaluated by comparing it with standard microbiological testing methods routinely analyzed. The developed MassARRAY-based assay demonstrated 100% concordance with known bacterial pure cultures. The assay's reaction using a mixture of gDNA from all nine targeted species revealed the MassARRAY's capability to detect all targeted species in a single assay with the lowest concentration of 1 ng/μL of gDNA. The limits of detection of the assay range from 357 ± 101 to 282,000 ± 79,196 cells. Moreover, the validation of the assay in field samples revealed a 100% correlation between the data obtained from the standard microbiological method and the MassARRAY-based assay. These findings suggested that the developed MassARRAY-based assay exhibited the excellence in high-throughput detection of foodborne bacterial pathogens with high accuracy, reliability, and potential applicability within real-world field samples.

Raman-Activated Cell Ejection for Validating the Reliability of the Raman Fingerprint Database of Foodborne Pathogens

Raman spectroscopy for rapid identification of foodborne pathogens based on phenotype has attracted increasing attention, and the reliability of the Raman fingerprint database through genotypic determination is crucial. In the research, the classification model of four foodborne pathogens was established based on t-distributed stochastic neighbor embedding (t-SNE) and support vector machine (SVM); the recognition accuracy was 97.04%. The target bacteria named by the model were ejected through Raman-activated cell ejection (RACE), and then single-cell genomic DNA was amplified for species analysis. The accuracy of correct matches between the predicted phenotype and the actual genotype of the target cells was at least 83.3%. Furthermore, all anticipant sequencing results brought into correspondence with the species were predicted through the model. In sum, the Raman fingerprint database based on Raman spectroscopy combined with machine learning was reliable and promising in the field of rapid detection of foodborne pathogens.

Research progress on the detection of foodborne pathogens based on aptamer recognition.

Foodborne diseases caused by bacterial contamination are a serious threat to food safety and human health. The classical plate culture method has the problems of long detection cycle, low sensitivity and specificity, and complicated operation, which cannot meet the growing demand for rapid quantitative detection of pathogenic bacteria. The frequent outbreak of foodborne diseases has put forward higher requirements for rapid and simple detection technology of foodborne pathogens. Aptamer is a kind of oligonucleotide fragment that can recognize targets with the advantages of high affinity and good specificity. The target can be range from proteins, small molecules, cells bacteria, and even viruses. Herein, the latest advances in sensitive and rapid detection of foodborne pathogens based on aptamer recognition was reviewed. Special attention has been paid to the obtained sequences of aptamers to various foodborne pathogens, the optimization of sequences, and the mechanism of aptamer recognition. Then, the research progress of biosensors for the detection of pathogenic bacteria based on aptamer recognition were summarized. Some challenges and prospects for the detection of foodborne pathogens based on aptamer recognition were prospected. In summary, with the further deepening of aptamer research and improvement of detection technology, aptamer-based recognition can meet the needs of rapid, sensitive, and accurate detection in practical applications.

Boron nitride nanoplate-based strand exchange amplification with enhanced sensitivity and rapidity for quantitative detection of Staphylococcus aureus in food samples.

Staphylococcus aureus is one of the most common foodborne pathogens that can cause serious food poisoning and infectious diseases in humans. Standard identification approaches include nucleic acid amplification, but current amplification tools suffer from low amplification efficiency, resulting in the risk of low sensitivity and long detection time. Herein, boron nitride nanoplates (BNNPs) were chosen as an additive for enhancing the sensitivity and rapidity of strand exchange amplification (SEA), thereby successfully expanding the application of nucleic acid detection for detecting Staphylococcus aureus in food samples. As a result, SEA based on boron nitride nanoplates (BNNP-SEA) was employed for sensitive and rapid detection of foodborne pathogen Staphylococcus aureus. Compared with classical SEA, the BNNP-based SEA assay was more than 10-fold sensitive, and the detection time was reduced by 15 minutes. The optimized BNNP-based SEA shows a wide linear range from 40 pg to 50 ng in a diluted solution of the target DNA with a low detection limit of 40 pg. Moreover, the BNNP-based SEA achieves the quantitative detection of Staphylococcus aureus in different food samples (pork, beef, mutton, duck, milk and shrimp). In contrast to the classical SEA, the BNNP-based SEA method enabled sensitive and rapid detection of Staphylococcus aureus in the above food samples at concentrations as low as 5 × 103 CFU mL-1. The BNNP-based SEA assay is specific, sensitive and reliable, offering a valuable diagnostic technology for routine analysis in food safety research.

A convenient electrochemical biosensor mediated by filtration-assisted pretreatment and multi-TEs amplification system for Staphylococcus aureus detection in complex matrices

Rapid detection of foodborne pathogens plays a more and more significant role in the field of public health. In this research, we developed a convenient electrochemical biosensor mediated by filtration-assisted pretreatment and multiple thermostatic enzymes (Multi-TEs) amplification system for the detection of Staphylococcus aureus (S. aureus) in complex matrices. Firstly, the designed filtration-assisted pretreatment could simultaneously collect and enrich target bacterium from various actual samples within 5 min. Then, the target bacterial genome template was reacted at 37 °C in Multi-TEs amplification system to obtain specific double stranded products. Finally, the specific double stranded products were fixed on the surface of the electrode and the electrochemical indicators (Methylene blue, MB) was combined for the quantitative one-step electrochemical analysis of S. aureus. This assay has great linear calibration curves with the concentration ranging from 101 CFU/mL to 106 CFU/mL. The limit of detections (LOD) was defined as 1.28 CFU/mL, which performance is superior to some commercial ELISA kits. Meanwhile, amazingly, it has excellent specificity for S. aureus against other foodborne pathogens and could be applied for S. aureus analysis in human serum samples with the great recoveries and associated relative standard deviations (RSDs). These features do make the ideal facile electrochemical analytical platform for on-site detection of S. aureus.

E. coli O157:H7 Detection Using Surface Plasmon Resonance Based Biosensor

The detection of foodborne pathogenic bacteria remains a significant challenge, and the need for fast and sensitive detection methods is becoming increasingly important. Escherichia coli is a prevalent bacteria associated with foodborne illness, and this study aimed to evaluate the ability of a surface plasmon resonance (SPR) based biosensor to detect E. coli O157:H7 at low levels in pure culture and artificially contaminated bay leaves (Laurus nobilis) using different injection methods. To develop a biological sensing surface, the sensor surface was functionalized with 3-aminopropyltriethoxysilane (APTES), and polyclonal antibodies were immobilized on the surface for bacteria detection. Bacterial attachment to the antibodies resulted in a change in resonance angle. The biosensor was able to discriminate between cellular concentrations of 103 to 107 CFU/mL and showed potential in detecting different pathogens in various food samples. Before the SPR detection, the sample preparation step was optimized to ensure complex food matrices were suitable for SPR analysis. The results suggest that the SPR based biosensor is a promising tool for the rapid detection of foodborne pathogens in complex food matrices.

Capture antibody imitator MnO2 nanozyme-based dual-signal immunochromatographic assay for rapid detection of Salmonella enteritidis

The sensitive and rapid detection of foodborne pathogens is of great significance to global public health security. Here, with two-dimensional nanomaterial MnO2 NSs as the capture antibody imitator and signal reporter molecules, based on its enzyme-catalyzed signal amplification capability, a label-free, dual-signal output immunochromatographic biosensor was constructed to achieve the sensitive detection of S. enteritidis. The capture antibody imitator of MnO2 capture probe shows an outstanding capture ability, forming a stable immune complex with S. enteritidis. As an in-situ catalytic amplification colorimetric signal trigger, MnO2 NSs exert oxidase-like enzyme activity and obtain satisfactory detection sensitivity. It is worth noting that the proposed dual-signal ICA has high analytical performances for S. enteritidis during the concentration range of 103-107 cfu mL−1 both in standard bacterial solutions and food matrixes.

Rapid detection of foodborne pathogens in diverse foodstuffs by universal electrochemical aptasensor based on UiO-66 and methylene blue composites.

Rapid and sensitive detection of foodborne pathogens in complex environments is essential for food protection. A universal electrochemical aptasensor was fabricated for the detection of three common foodborne pathogens, including Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Salmonella typhimurium (S. typhimurium). The aptasensor was developed based on the homogeneous and membrane filtration strategy. Zirconium-based metal-organic framework (UiO-66)/methylene blue (MB)/aptamer composite was designed as a signal amplification and recognition probe. Bacteria were quantitatively detected by the current changes of MB. By simply changing the aptamer, different bacteria could be detected. The detection limits of E. coli, S. aureus and S. typhimurium were 5, 4 and 3CFU·mL-1, respectively. In humidity and salt environments, the stability of the aptasensor was satisfactory. The aptasensor exhibited satisfactory detection performance in different real samples. This aptasensor has excellent potential for rapid detection of foodborne pathogens in complex environments.

Preparation of a multifunctional and ultrasensitive Au@AgNPs-Van/PDMS film SERS substrate for rapid detection of foodborne pathogens in beef

We present a novel and super-sensitive vancomycin (Van) modified Au@AgNP self-assembly with polydimethylsiloxane (PDMS) (Au@AgNPs/Van-PDMS) film surface-enhanced Raman scattering (SERS) substrate for identification of foodborne pathogens in beef, without the need for in vitro bacterial culture. The results illustrated that the Au@AgNPs/Van-PDMS film exhibited high reproducibility and Raman enhancement effect (1.09 × 105). Clostridium perfringens, Bacillus subtilis and Staphylococcus aureus isolated from beef captured by Au@AgNPs/Van-PDMS film exhibited high reproducibility and significant differences. Principal component analysis score plots distinguished classes of foodborne pathogens, and the qualitative identification of linear discriminant analysis was correct at 100%. The detection limit of S. aureus in beef was as low as 3 CFU/mL. This method could provide an effective means and technical support for realizing the application of SERS technology for quick and highly sensitive detection of foodborne pathogens in complex environments.

Polydopamine-coated two-dimensional nanomaterials as high-affinity photothermal signal tag towards dual-signal detection of Salmonella typhimurium by lateral flow immunoassay

Lateral flow immunoassay (LFIA) with gold nanoparticles (AuNPs) as signal reporters has been extensively utilized for the rapid detection of foodborne pathogens. Nevertheless, it’s challenging for LFIA to obtain sensitive detection, because of the inefficient coupling of AuNPs and antibodies and the poor colorimetric signals. To improve on this, we used a two-dimensional nanomaterial (Cu2MoS4) modified with PDA (CMS@PDA) that provides superior bio-affinity and excellent photothermal signal qualities. With the CMS@PDA material, we successfully constructed a portable LFIA device for specific detection of Salmonella typhimurium (S. typhimurium) using a dual-signal probe that combines colorimetric and photothermal signals (CM/PT). The dynamic detection range of the CMS@PDA-LFIA is 103 to 107 cfu mL−1. Notably, the detection limit of 103 cfu mL−1 is 100 times more sensitive compared to AuNPs-based LFIA. Moreover, the assay exhibits satisfactory recovery rates for S. typhimurium detection in food samples. In this research, the coating of PDA solves the problem of low water-solubility of CMS, making the proposed CMS@PDA nanocomposite showcase better performance in the CM/PT mode detection by LFIA. Beyond all doubt, this work offers a novel supplement for applying multifunctional two-dimensional nanomaterials in LFIAs.

A New Duplex Recombinase Polymerase Amplification (D-RPA) Method for the Simultaneous and Rapid Detection of Shigella and Bacillus cereus in Food.

Shigella and Bacillus cereus are two common foodborne pathogens that cause intestinal diseases and seriously affect human life and health. Traditional microbiological culture methods are time-consuming and laborious, and polymerase chain reaction (PCR)-based methods rely on expensive thermal cyclers and lengthy reaction times. In this study, on the basis of the specific gene ipaH7 of Shigella and the virulence gene nheABC of B. cereus, a duplex detection system was established for the first time by using the recombinase polymerase amplification technique (D-RPA). After optimization, D-RPA could be effectively amplified at 42 °C for 25 min with excellent specificity, and the detection limits of D-RPA for Shigella and B. cereus in artificially contaminated samples were 2.7 × 101 and 5.2 × 102 CFU/mL, respectively. This study provides a certain research basis for multiple detection with RPA, an isothermal amplification technology. Furthermore, it lays a good foundation for high-throughput rapid detection of foodborne pathogens.

Influence of Biological and Environmental Factors in the Extraction and Concentration of Foodborne Pathogens using Glycan-Coated Magnetic Nanoparticles

Rapid detection of foodborne pathogens is essential to preventing foodborne illness outbreaks. Before detection can occur, however, it is often necessary to extract and concentrate bacteria. Conventional methods such as centrifugation, filtration, and immunomagnetic separation can often be time-consuming, ineffective, or costly when working with complex food matrices. This work used cost-effective glycan-coated magnetic nanoparticles (MNPs) for rapid concentration of Escherichia coli O157, Listeria monocytogenes, and Staphylococcus aureus. Glycan-coated MNPs were used to concentrate bacteria from both buffer solution and food matrices while examining the effect of factors including solution pH, bacterial concentration, and target bacterial species. In both pH 7 and reduced pH experiments, successful extraction of bacterial cells occurred in all food matrices and bacteria tested. In neutral pH buffer solution, bacteria were concentrated to 4.55 ± 1.17, 31.68 ± 6.10 and 64.27 ± 16.78 times their initial concentration (mean ± standard deviation) for E. coli, L. monocytogenes and S. aureus, respectively. Successful bacterial concentration occurred in several food matrices, including S. aureus in milk (pH 6), L. monocytogenes in sausage (pH 7), and E. coli O157 in flour (pH 7). The insights gained may facilitate future applications of glycan-coated MNPs to extract foodborne pathogens.

An integrated colorimetric and photothermal lateral flow immunoassay based on bimetallic Ag–Au urchin-like hollow structures for the sensitive detection of E. coli O157:H7

Lateral flow immunoassay (LFIA) with gold nanoparticles (AuNPs) as the signal reporter is widely used for the rapid detection of food-borne pathogens. However, it is difficult for LFIA to achieve sensitive detection due to the insufficient colorimetric signal brightness of AuNPs. Herein, we developed a bimetallic Ag–Au urchin-like hollow nanospheres (BUHNPs) based on the simple and rapid synthesis through co-reduction and galvanic replacement reactions. The BUHNPs exhibit superb colorimetric signal brightness, strong photothermal signals and high antibody coupling efficiency. The obtained colorimetric and photothermal LFIA (BUHNPs-CM-LFIA and BUHNPs-PT-LFIA) based on BUHNPs were used for the sensitive detection of a pathogenic bacterium (Escherichia coli O157:H7). The limit of detection values of the colorimetric and photothermal quantitative analysis were 2.48 × 103 and 5.50 × 102 CFU mL−1, which were approximately 4-fold and 18-fold lower than that of AuNPs-LFIA (9.92 × 103 CFU mL−1), respectively. This work suggests that a dual-readout LFIA with BUHNPs as a promising signal reporter can be used to improve the detection performance of LFIA and construct a more accurate and sensitive detection platform.

Magnetorheological elastomer and smartphone enable microfluidic biosensing of foodborne pathogen

Rapid detection of foodborne pathogens is crucial to prevent the outbreaks of foodborne diseases. In this work, we proposed a novel microfluidic biosensor based on magnetorheological elastomer (MRE) and smartphone. First, micropump and microvalves were constructed by deforming the MRE under magnetic actuation and integrated into the microfluidic biosensor for fluidic control. Then, the micropump was used to deliver immune porous gold@platinum nanocatalysts (Au@PtNCs), bacterial sample, and immunomagnetic nanoparticles (MNPs) into a micromixer, where they were mixed, incubated and magnetically separated to obtain the Au@PtNC-bacteria-MNP complexes. After 3,3′,5,5′-tetramethylbenzidine and hydrogen peroxide were injected and catalyzed by the Au@PtNCs, smartphone was used to measure the color of the catalysate for quantitative analysis of target bacteria. Under optimal conditions, this biosensor could detect Salmonella typhimurium quantitatively and automatically in 1 h with a linear detection range of 8.0 × 101 CFU/mL to 8.0 × 104 CFU/mL and a detection limit of 62 CFU/mL. The microfluidic biosensor was compact in size, simple to use, and efficient for detection, and might be used for in-field screening of foodborne pathogens to prevent food poisoning.

Recent Progress in Spectroscopic Methods for the Detection of Foodborne Pathogenic Bacteria.

Detection of foodborne pathogens at an early stage is very important to control food quality and improve medical response. Rapid detection of foodborne pathogens with high sensitivity and specificity is becoming an urgent requirement in health safety, medical diagnostics, environmental safety, and controlling food quality. Despite the existing bacterial detection methods being reliable and widely used, these methods are time-consuming, expensive, and cumbersome. Therefore, researchers are trying to find new methods by integrating spectroscopy techniques with artificial intelligence and advanced materials. Within this progress report, advances in the detection of foodborne pathogens using spectroscopy techniques are discussed. This paper presents an overview of the progress and application of spectroscopy techniques for the detection of foodborne pathogens, particularly new trends in the past few years, including surface-enhanced Raman spectroscopy, surface plasmon resonance, fluorescence spectroscopy, multiangle laser light scattering, and imaging analysis. In addition, the applications of artificial intelligence, microfluidics, smartphone-based techniques, and advanced materials related to spectroscopy for the detection of bacterial pathogens are discussed. Finally, we conclude and discuss possible research prospects in aspects of spectroscopy techniques for the identification and classification of pathogens.