Recent advances in dual recognition based surface enhanced Raman scattering for pathogenic bacteria detection: A review

Rapid analysis of Bacillus cereus spore biomarkers based on porous channel cuttlebone SERS substrate

BACKGROUND

Bacillus cereus (B. cereus) is a widespread conditional pathogen that affects food safety and human health. Conventional methods such as bacteria culture and polymerase chain reaction (PCR) are difficult to use for rapid identification of bacterial spores because of the relatively long analysis times. From a human health perspective, there is an urgent need to develop an ultrasensitive, rapid, and accurate method for the detection of B. cereus spores.

RESULTS

The study proposed a new method for rapidly and sensitively detecting the biomarkers of bacterial spores via surface-enhanced Raman spectroscopy (SERS) combined with electrochemical enrichment. The 2,6-Pyridinedicarboxylic acid (DPA) was used as the model analyte to acts as a biomarker of B. cereus spores. The SERS substrate was developed via the in-situ generation of Ag nanoparticles (AgNPs) in a cuttlebone-derived organic matrix (CDOM). Because of the depletion of chitin reduction sites on the CDOM, the pores of the porous channels expanded. The pores diameter of the AgNPs/CDOM porous channel was found to be in the range of 0.7-1.3 nm through molecular diffusion experiments. Based on the porosity of AgNPs/CDOM substrates and the high sensitivity of SERS substrates, the sensor can rapidly and accurately electronically enrich DPA in 40 s with the limit of detection (LOD) of 0.3 nM.

SIGNIFICANCE

The results demonstrate that electrochemically assisted SERS substrates can be served as a high sensitivity electrochemical-enrichment device for the rapid and sensitive detection of bacterial spores with minimal interference from potentially coexisting species in biological samples. In this study, it opens up a platform to explore the application of porous channels in natural bio-derived materials in the field of food safety.

Laser polarization as a critical factor in the SERS-based molecular sensing performance of nano-gapped Au nanowires

Nowadays, Au dimer-based nanostructures are exhaustively studied due to their outstanding potential as plasmonic nanoantennas for future applications in high-sensitivity molecular sensing by Surface-Enhanced Raman Spectroscopy (SERS). In this work, we analyze nano-gapped Au nanowires (NWs) or Au-NW dimers for designing efficient nanoantennas, reporting an exhaustive study about dimer length and laser polarization orientation effects on their SERS-based molecular sensing performance. Arrays of nanoantennas with gaps of about 22 ± 4 nm, nominal square cross-sections of 60 nm × 60 nm, and different segment lengths from 300 nm up to 1200 nm were fabricated by Au evaporation and subsequent e-beam lithography. The SERS performance was studied by confocal Raman microscopy using a linearly-polarized 633 nm laser. A critical impact of the polarization alignment on the spectral resolution of the studied Raman marker imprint was observed. The results show that the Raman signal is maximized by aligning the polarization orientation with the nanowire long axis, it is reduced by increasing the relative angle, and it is abruptly minimized when both are perpendicular. These observations were consistent with numerical simulations carried out by the FDTD method, which predicts a similar dependence between the orientation of linearly-polarized light and electric-near field amplification in the nano-gap zone. Our results provide an interesting paradigm and relevant insights in determining the role of laser polarization in the Raman signal enhancement in nano-gapped Au nanowires, showing the key role of this measurement condition on the SERS-based molecular sensing efficiency of this kind of nanostructure.

Programmable and ultra-efficient Argonaute protein-mediated nucleic acid tests: A review

With the attributes of high sensitivity, single-base resolution, multiplex detection capability, and programmability upon nucleic acid recognition, Argonaute (Ago)-based biosensing assays are increasingly recognized as one of the most promising tools for precise identification and quantification of target analytes. Employed as highly specific sequence recognition elements of these robust diagnostic methods, Agos are revolutionizing how nucleic acid targets are detected. A systematic and comprehensive summary of this emerging and rapid-advancing technology is necessary to give play to the potential of Ago-based biosensing assays. The structure and function of Agos were briefly overviewed at the beginning of the work, followed by a review of the recent advancements in employing Agos sensing for detecting various targets with a comprehensive analysis such as viruses, tumor biomarkers, pathogens, mycoplasma, and parasite. The significance and benefits of these platforms were then deliberated. In addition, the authors shared subjective viewpoints on the existing challenges and offered relevant guidance for the future progress of Agos assays. Finally, the future research outlook regarding Ago-based sensing in this field was also outlined. As such, this review is expected to offer valuable information and fresh perspectives for a broader group of researchers.

RamanCluster: A deep clustering-based framework for unsupervised Raman spectral identification of pathogenic bacteria

Raman spectroscopy serves as a powerful and reliable tool for the characterization of pathogenic bacteria. The integration of Raman spectroscopy with artificial intelligence techniques to rapidly identify pathogenic bacteria has become paramount for expediting disease diagnosis. However, the development of prevailing supervised artificial intelligence algorithms is still constrained by costly and limited well-annotated Raman spectroscopy datasets. Furthermore, tackling various high-dimensional and intricate Raman spectra of pathogenic bacteria in the absence of annotations remains a formidable challenge. In this paper, we propose a concise and efficient deep clustering-based framework (RamanCluster) to achieve accurate and robust unsupervised Raman spectral identification of pathogenic bacteria without the need for any annotated data. RamanCluster is composed of a novel representation learning module and a machine learning-based clustering module, systematically enabling the extraction of robust discriminative representations and unsupervised Raman spectral identification of pathogenic bacteria. The extensive experimental results show that RamanCluster has achieved high accuracy on both Bacteria-4 and Bacteria-6, with ACC values of 77 % and 74.1 %, NMI values of 75 % and 73 %, as well as AMI values of 74.6 % and 72.6 %, respectively. Furthermore, compared with other state-of-the-art methods, RamanCluster exhibits the superior accuracy on handling various complicated pathogenic bacterial Raman spectroscopy datasets, including situations with strong noise and a wide variety of pathogenic bacterial species. Additionally, RamanCluster also demonstrates commendable robustness in these challenging scenarios. In short, RamanCluster has a promising prospect in accelerating the development of low-cost and widely applicable disease diagnosis in clinical medicine.

Nanotechnology improves the detection of bacteria: Recent advances and future perspectives

Nanotechnology has advanced significantly, particularly in biomedicine, showing promise for nanomaterial applications. Bacterial infections pose persistent public health challenges due to the lack of rapid pathogen detection methods, resulting in antibiotic overuse and bacterial resistance, threatening the human microbiome. Nanotechnology offers a solution through nanoparticle-based materials facilitating early bacterial detection and combating resistance. This study explores recent research on nanoparticle development for controlling microbial infections using various nanotechnology-driven detection methods. These approaches include Surface Plasmon Resonance (SPR) Sensors, Surface-Enhanced Raman Scattering (SERS) Sensors, Optoelectronic-based sensors, Bacteriophage-Based Sensors, and nanotechnology-based aptasensors. These technologies provide precise bacteria detection, enabling targeted treatment and infection prevention. Integrating nanoparticles into detection approaches holds promise for enhancing patient outcomes and mitigating harmful bacteria spread in healthcare settings.

Recent advances in microfluidic-based spectroscopic approaches for pathogen detection

Rapid identification of pathogens with higher sensitivity and specificity plays a significant role in maintaining public health, environmental monitoring, controlling food quality, and clinical diagnostics. Different methods have been widely used in food testing laboratories, quality control departments in food companies, hospitals, and clinical settings to identify pathogens. Some limitations in current pathogens detection methods are time-consuming, expensive, and laborious sample preparation, making it unsuitable for rapid detection. Microfluidics has emerged as a promising technology for biosensing applications due to its ability to precisely manipulate small volumes of fluids. Microfluidics platforms combined with spectroscopic techniques are capable of developing miniaturized devices that can detect and quantify pathogenic samples. The review focuses on the advancements in microfluidic devices integrated with spectroscopic methods for detecting bacterial microbes over the past five years. The review is based on several spectroscopic techniques, including fluorescence detection, surface-enhanced Raman scattering, and dynamic light scattering methods coupled with microfluidic platforms. The key detection principles of different approaches were discussed and summarized. Finally, the future possible directions and challenges in microfluidic-based spectroscopy for isolating and detecting pathogens using the latest innovations were also discussed.

PoreGlow: A split green fluorescent protein-based system for rapid detection of Listeria monocytogenes

Listeria monocytogenes, a severe foodborne pathogen causing severe diseases underscores the necessity for the development of a detection system with high specificity, sensitivity and utility. Herein, the PoreGlow system, based on split green fluorescent protein (GFP), was developed and assessed for the fast and accurate detection of L. monocytogenes. Split GFP-encapsulated liposomes were optimized for targeted analysis. The system utilizes listeriolysin O (LLO), a toxin produced by L. monocytogenes that enlarges the pores split GFP-encapsulated liposomes, to detect L. monocytogenes by measuring the fluorescent signal generated when the encapsulated GFP is released and reacted with the externally added fragment of the split GFP. The system exhibited a limit of detection of 0.17 μg/ml for LLO toxin and 10 CFU/mL for L. monocytogenes with high sensitivity and specificity and no cross-reactivity with other bacteria. The PoreGlow system is practical, rapid, and does not require sample pre-treatment, making it a promising tool for the early detection of L. monocytogenes in food products, which is crucial for preventing outbreaks and protecting public health.

Bimetallic AuNR@AgNCs for ultrasensitive surface-enhanced Raman scattering sensing of dithianon in apple juice

In this study, a bimetallic surfaced-enhanced Raman spectroscopy (SERS)-active substrate consisting of AuNR@AgNCs was proposed for the rapid detection of dithianon. Due to the significant synergistic enhancement of the core-shell nanocuboids, the obtained AuNR@AgNC substrate exhibited excellent SERS performance. The simulation findings supported the practical SERS results and demonstrated that interactions were mainly maintained by the nitrile functional group. The AuNR@AgNCs could be used to detect dithianon with an LOD value of 20 nM. Moreover, dithianon in river water and apple juice could be detected with recovery in the satisfactory ranges of 97.41%-98.35% and 97.77%-98.70%, respectively, by using this substrate under optimal conditions, indicating that the AuNR@AgNC substrate could serve as an excellent SERS detection platform for pesticide residues in fruit.

Key steps for improving bacterial SERS signals in complex samples: Separation, recognition, detection, and analysis

Rapid and reliable detection of pathogenic bacteria is absolutely essential for research in environmental science, food quality, and medical diagnostics. Surface-enhanced Raman spectroscopy (SERS), as an emerging spectroscopic technique, has the advantages of high sensitivity, good selectivity, rapid detection speed, and portable operation, which has been broadly used in the detection of pathogenic bacteria in different kinds of complex samples. However, the SERS detection method is also challenging in dealing with the detection difficulties of bacterial samples in complex matrices, such as interference from complex matrices, confusion of similar bacteria, and complexity of data processing. Therefore, researchers have developed some technologies to assist in SERS detection of bacteria, including both the front-end process of obtaining bacterial sample data and the back-end data processing process. The review summarizes the key steps for improving bacterial SERS signals in complex samples: separation, recognition, detection, and analysis, highlighting the principles of each step and the key roles for SERS pathogenic bacteria analysis, and the interconnectivity between each step. In addition, the current challenges in the practical application of SERS technology and the development trends are discussed. The purpose of this review is to deepen researchers' understanding of the various stages of using SERS technology to detect bacteria in complex sample matrices, and help them find new breakthroughs in different stages to facilitate the detection and control of bacteria in complex samples.

Optical Sensors for Bacterial Detection

Analytical devices for bacterial detection are an integral part of modern laboratory medicine, as they permit the early diagnosis of diseases and their timely treatment. Therefore, special attention is directed to the development of and improvements in monitoring and diagnostic methods, including biosensor-based ones. A promising direction in the development of bacterial detection methods is optical sensor systems based on colorimetric and fluorescence techniques, the surface plasmon resonance, and the measurement of orientational effects. This review shows the detecting capabilities of these systems and the promise of electro-optical analysis for bacterial detection. It also discusses the advantages and disadvantages of optical sensor systems and the prospects for their further improvement.

pH-Triggered visual detection of Escherichia coli based on the co-assembly of bacitracin and thymolphthalein

A novel probe for bacteria was simply synthesized through the solvent-induced co-assembly of bacitracin (AMP) and thymolphthalein (TP) without complicated modification. Combining with aptamer-Fe3O4, AMP/TP nanoparticles were used for the colorimetric detection of Escherichia coli with good sensitivity through the NaOH-triggered blue color and a smartphone-based App.

D-tartaric acid doping improves the performance of whole-cell bacteria imprinted polymer for sensing Vibrio parahaemolyticus

Whole-cell bacteria imprinted polymer-based sensors still face challenges in the form of the difficulty of removing the template entirely, low affinity, and poor sensitivity. To further improve their performance, it is pivotal to modulate the morphology and chemical properties of imprintied polymer by taking advantage of doping engineering. Here we introduced D-tartaric acid (D-TA) as a dopant and employed pyrrole as a functional monomer to construct D-TA/polypyrrole (PPy)-based bacteria imprinted polymer (DPBIP) sensor for Vibrio parahaemolyticus (VP) detection. It is demonstrated that D-TA doping can synergistically accelerate the removal of template bacteria from imprinted polymers (1.5 h), improve bacteria affinity of imprinted sites (the recognition time of 30 min), and enhance the sensitivity of DPBIP sensor (a detection limit of 19 CFU mL-1). The DPBIP sensor had a linear range of 102∼106 CFU mL-1 and exhibited high selectivity and good repeatability. Moreover, a recovery of 94.8%-105.3% was achieved in drinking water and oyster samples. Therefore, small functional molecules doping opens a new avenue to engineering BIP-based sensors with high performance, holding potential applications in securing food safety.

Nano-Biotechnology for Bacteria Identification and Potent Anti-bacterial Properties: A Review of Current State of the Art

Sepsis is a critical disease caused by the abrupt increase of bacteria in human blood, which subsequently causes a cytokine storm. Early identification of bacteria is critical to treating a patient with proper antibiotics to avoid sepsis. However, conventional culture-based identification takes a long time. Polymerase chain reaction (PCR) is not so successful because of the complexity and similarity in the genome sequence of some bacterial species, making it difficult to design primers and thus less suitable for rapid bacterial identification. To address these issues, several new technologies have been developed. Recent advances in nanotechnology have shown great potential for fast and accurate bacterial identification. The most promising strategy in nanotechnology involves the use of nanoparticles, which has led to the advancement of highly specific and sensitive biosensors capable of detecting and identifying bacteria even at low concentrations in very little time. The primary drawback of conventional antibiotics is the potential for antimicrobial resistance, which can lead to the development of superbacteria, making them difficult to treat. The incorporation of diverse nanomaterials and designs of nanomaterials has been utilized to kill bacteria efficiently. Nanomaterials with distinct physicochemical properties, such as optical and magnetic properties, including plasmonic and magnetic nanoparticles, have been extensively studied for their potential to efficiently kill bacteria. In this review, we are emphasizing the recent advances in nano-biotechnologies for bacterial identification and anti-bacterial properties. The basic principles of new technologies, as well as their future challenges, have been discussed.

Culture-Independent Multiplexed Detection of Drug-Resistant Bacteria Using Surface-Enhanced Raman Scattering

The rapid and accurate detection of bacteria resistance to β-lactam antibiotics is critical to inform optimal treatment and prevent overprescription of potent antibiotics. Here, we present a fast, culture-independent method for the detection of extended-spectrum β-lactamases (ESBLs) using surface-enhanced Raman scattering (SERS). The method uses Raman probes that release sulfur-based Raman active molecules in the presence of β-lactamases. The released thiol molecules can be captured by gold nanoparticles, leading to amplified Raman signals. A broad-spectrum cephalosporin probe R1G and an ESBL-specific probe R3G are designed to enable duplex detection of bacteria expressing broad-spectrum β-lactamases or ESBLs with a detection limit of 103 cfu/mL in 1 h incubation. Combined with a portable Raman microscope, our culturing-free SERS assay has reduced screening time to 1.5 h without compromising sensitivity and specificity.

Recent Progress of Surface-Enhanced Raman Spectroscopy for Bacteria Detection

There are various pathogenic bacteria in the surrounding living environment, which not only pose a great threat to human health but also bring huge losses to economic development. Conventional methods for bacteria detection are usually time-consuming, complicated and labor-intensive, and cannot meet the growing demands for on-site and rapid analyses. Sensitive, rapid and effective methods for pathogenic bacteria detection are necessary for environmental monitoring, food safety and infectious bacteria diagnosis. Recently, benefiting from its advantages of rapidity and high sensitivity, surface-enhanced Raman spectroscopy (SERS) has attracted significant attention in the field of bacteria detection and identification as well as drug susceptibility testing. Here, we comprehensively reviewed the latest advances in SERS technology in the field of bacteria analysis. Firstly, the mechanism of SERS detection and the fabrication of the SERS substrate were briefly introduced. Secondly, the label-free SERS applied for the identification of bacteria species was summarized in detail. Thirdly, various SERS tags for the high-sensitivity detection of bacteria were also discussed. Moreover, we emphasized the application prospects of microfluidic SERS chips in antimicrobial susceptibility testing (AST). In the end, we gave an outlook on the future development and trends of SERS in point-of-care diagnoses of bacterial infections.

Advances in surface-enhanced Raman spectroscopy technology for detection of foodborne pathogens

Rapid control and prevention of diseases caused by foodborne pathogens is one of the existing food safety regulatory issues faced by various countries and has received wide attention from all sectors of society. The development of rapid and reliable detection methods for foodborne pathogens remains a hot research area for food safety and public health because of the limitations of complex steps, time-consuming, low sensitivity, or poor selectivity of commonly used methods. Surface-enhanced Raman spectroscopy (SERS), as a novel spectroscopic technique, has the advantages of high sensitivity, selectivity, rapid and nondestructive detection and has exhibited broad application prospects in the determination of pathogenic bacteria. In this study, the enhancement mechanisms of SERS are briefly introduced, then the characteristics and properties of liquid-phase, rigid solid-phase, and flexible solid-phase are categorized. Furthermore, a comprehensive review of the advances in label-free or label-based SERS strategies and SERS-compatible techniques for the detection of foodborne pathogens is provided, and the advantages and disadvantages of these methods are reviewed. Finally, the current challenges of SERS technology applied in practical applications are listed, and the possible development trends of SERS in the field of foodborne pathogens detection in the future are discussed.

Recent advances of fluorescent sensors for bacteria detection-A review

Bacterial infections have become a global public health problem. Rapid and sensitive bacterial detection is of great importance for human health. Among various sensor systems, fluorescence sensor is rapid, portable, multiplexed, and cost-efficient. Herein, we reviewed the current trends of fluorescent sensors for bacterial detection from three aspects (response materials, target and recognition way). The fluorescent materials have the advantages of high fluorescent strength, high stability, and good biocompatibility. They provide a new path for bacterial detection. Several recent fluorescent nanomaterials for bacterial detection, including semiconductor quantum dots (QDs), carbon dots (CDs), up-conversion nanoparticles (UCNPs) and metal organic frameworks (MOFs), were introduced. Their optical properties and detection mechanisms were analyzed and compared. For different response targets in the detection process, we studied the fluorescence strategy using DNA, bacteria, and metabolites as the response target. In addition, we classified the recognition way between nanomaterial and target, including specific recognition methods based on aptamers, antibodies, bacteriophages, and non-specific recognition methods based on biological functional materials. The characteristics of different recognition methods were summarized. Finally, the weaknesses and future development of bacterial fluorescence sensor were discussed. This review provides new insights into the application of fluorescent sensing systems as an important tool for bacterial detection.

Integration of three non-interfering SERS probes combined with ConA-functionalized magnetic nanoparticles for extraction and detection of multiple foodborne pathogens

A sandwich-structured SERS biosensor has been constructed for simultaneous detection of multiple pathogenic bacteria, consisting of non-interfering SERS probes for bacterial labeling and ConA-functionalizd magnetic nanoparticles for bacteria extraction. A the preparation method of PP3 SERS probe with high Raman activity is reported for the first time. Since the PP3 SERS probe has a very strong Raman peak at 2081 cm^-1 in the "Raman silent region," the mixed SERS probe formed with MP1 and DP2 can meet the needs of multiple foodborne pathogen detection. Significantly, S. aureus, E. coli, and P. aeruginosa can be successfully extracted upon external magnetic field, and the limit of detection (LOD) is 1 CFU‧mL^-1, lower than that of the congeneric detectors. This work paves a new way for the construction of a novel detector and absorbent for different bacteria in complex samples by using SERS probe.

Engineering a SERS Sensing Nanoplatform with Self-Sterilization for Undifferentiated and Rapid Detection of Bacteria

The development of a convenient, sensitive, rapid and self-sterilizing biosensor for microbial detection is important for the prevention and control of foodborne diseases. Herein, we designed a surface-enhanced Raman scattering (SERS) sensing nanoplatform based on a capture-enrichment-enhancement strategy to detect bacteria. The gold-Azo@silver-cetyltrimethylammonium bromide (Au-Azo@Ag-CTAB) SERS nanotags were obtained by optimizing the synthesis process conditions. The results showed that the modification of CTAB enabled the nanotags to bind to different bacteria electrostatically. This SERS sensing nanoplatform was demonstrated to be fast (15 min), accurate and sensitive (limit of detection (LOD): 300 and 400 CFU/mL for E. coli and S. aureus, respectively). Of note, the excellent endogenous antibacterial activity of CTAB allowed the complete inactivation of bacteria after the assay process, thus effectively avoiding secondary contamination.

Reliable and Rapid Detection and Quantification of Enrofloxacin Using a Ratiometric SERS Aptasensor

Reliable detection and quantification of antibiotic residues in food using surface-enhanced Raman spectroscopy remain challenging, since the intensities of SERS signals are vulnerable to matrix and experimental factors. In this work, a ratiometric SERS aptasensor using 6-Carboxyl-X-Rhodamine (ROX)-labeled aptamers and 4-mercaptobenzonitrile (4-MBN)-functionalized gold nanoparticles (Au NPs) as SERS probes was established for the reliable and rapid detection and quantification of enrofloxacin. In the presence of enrofloxacin, the conformational transform of aptamers took place, and the distance between ROX and Au NP increased, which resulted in a decrease in the SERS signal intensity of ROX. Meanwhile, the intensity of the SERS signal of 4-MBN was used as an internal standard. Reliable determination of enrofloxacin was realized using the ratio of the SERS signal intensities of ROX to 4-MBN. Under optimal conditions, the developed ratiometric SERS aptasensor provided a wide linear range from 5 nM to 1 µM, with a correlation coefficient (R²) of 0.98 and a limit of detection (LOD) of 0.12 nM (0.043 ppb). In addition, the developed ratiometric SERS aptasensor was successfully applied for the determination of enrofloxacin in fish and chicken meat, with recovery values of 93.6-112.0%. Therefore, the established ratiometric SERS aptasensor is sensitive, reliable, time-efficient, and has the potential to be applied in the on-site detection of enrofloxacin in complex matrices.

Aptamer-based biosensors for virus protein detection

Virus threatens life health seriously. The accurate early diagnosis of the virus is vital for clinical control and treatment of virus infection. Aptamers are small single-stranded oligonucleotides (DNAs or RNAs). In this review, we summarized aptasensors for virus detection in recent years according to the classification of the viral target protein, and illustrated common detection mechanisms in the aptasensors (colorimetry, fluorescence assay, surface plasmon resonance (SPR), surface-enhanced raman spectroscopy (SERS), electrochemical detection, and field-effect transistor (FET)). Furthermore, aptamers against different target proteins of viruses were summarized. The relationships between the different biomarkers of the viruses and the detection methods, and their performances were revealed. In addition, the challenges and future directions of aptasensors were discussed. This review will provide valuable references for constructing on-site aptasensors for detecting viruses, especially the SARS-CoV-2.

Rapid and reliable detection and quantification of organophosphorus pesticides using SERS combined with dispersive liquid-liquid microextraction

Rapid and reliable detection and quantification of pesticide residues in complex matrices by surface enhanced Raman spectroscopy (SERS) remain challenging due to the low level of target molecules and the interference of nontarget components. In this study, SERS was combined with dispersive liquid-liquid microextraction (DLLME) to develop a rapid and reliable method for the detection of organophosphorus pesticides (OPPs). In this method, DLLME was used to extract and enrich two representative OPPs (triazophos and parathion-methyl) from a liquid sample, and a portable Raman spectrometer was used to analyze the separated sediment using homemade gold nanoparticles colloids as enhancing substrates. The results showed that the developed method displayed good sensitivity and stability for the detection and quantification of triazophos and parathion-methyl with R² ≥ 0.98. The calculated limits of detection (LODs) in the simultaneous detection of triazophos and parathion-methyl were 2.17 × 10^-9 M (0.679 ppb) and 2.28 × 10^-8 M (5.998 ppb), and the calculated limits of quantification (LOQs) were 7.23 × 10^-9 M (2.26 ppb) and 7.62 × 10^-8 M (19.098 ppb), respectively. Furthermore, the developed SERS method was successfully applied to the detection of triazophos and parathion-methyl in apple juice with recoveries between 78.07% and 110.87% and relative standard deviations (RSDs) ≤ 2.06%. Therefore, the developed DLLME facilitated liquid SERS method exhibited good sensitivity and stability for the rapid detection and quantification of OPPs and had the potential to be applied to the rapid detection of OPPs in complex matrices.

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.

Universal and ultrasensitive detection of foodborne bacteria on a lateral flow assay strip by using wheat germ agglutinin-modified magnetic SERS nanotags

Rapid, direct and sensitive detection of foodborne bacteria in complex samples is still challenging. Here, we reported a universal surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) for highly sensitive detection of foodborne bacteria in food and environmental samples using wheat germ agglutinin (WGA)-modified Fe3O4@Au (Au@MNP-WGA) nanotags. The Au@MNP-WGA tag with numerous intraparticle hotspots was integrated into the LFA system for the first time, which can not only greatly improve the detection sensitivity through the dual amplification effect of magnetic enrichment and SERS enhancement but also achieve the broad-spectrum capture of multiple bacteria. In addition, monoclonal antibodies were separately immobilized onto the test line of different LFA strips to ensure the specific detection of different target pathogens. With this strategy, the proposed assay can achieve the universal and highly sensitive determination of three common foodborne bacteria, namely, Listeria monocytogenes, Campylobacter jejuni, and Staphylococcus aureus, with low detection limit (10 cells mL-1), short testing time (<35 min), and high reproducibility (RSD < 8.14%). Given its good stability and accuracy in complex samples, the Au@MNP-WGA-based SERS-LFA has great potential to be a powerful tool for the universal and on-site detection of different foodborne pathogens.

Biofouling of reverse osmosis membranes: assessment by surface-enhanced Raman spectroscopy and microscopic imaging

The decline in the performance of spiral-wound reverse osmosis (SWRO) membranes is frequently due to biofouling. This study focus on qualitative and quantitative diagnosis of SWRO membrane biofouling. Bacterial counts on the different surfaces of the fouled membranes were carried out. Surface enhanced Raman spectroscopy (SERS) was performed to highlight clogging materials as well as their natures and identity. The topography of the fouled membranes and the structures of biofilms were visualized by fluorescence microscopy (FM) and scanning electron microscopy (SEM). The results indicated the presence of bacteria in the different SWRO membrane areas. Those strongly adhered were significantly higher than those weakly. It varied between 26 × 10⁵ and 262 × 10⁵ CFU m^-2. However, SERS mapping showed different fouling levels and the thickness of the fouling layer was 5 µm. Microscopic imaging revealed biotic and abiotic deposits. These data can together allow better management of the seawater desalination process.

Multifunctional Au@Pt@Ag NPs with color-photothermal-Raman properties for multimodal lateral flow immunoassay

Multimodal lateral flow immunoassay (LFIA) has displayed its potential to improve practicability and elasticity of point-of-care testing. Herein, multifunctional core-shell-shell Au@Pt@Ag NPs loaded with dual-layer Raman reporter molecules of 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) with a characteristic combination of color-photothermal-Raman performance were constructed for colorimetric LFIA (CM-LFIA), photothermal LFIA (PT-LFIA) and surface-enhanced Raman scattering-based LFIA (SERS-LFIA), respectively. The highly specific nanoprobes, being obtained through the combination of the resulted dual-layer DTNB modified Au@Pt@Ag NPs with the antibody, were triumphantly utilized in exploring multimodal LFIA with one visual qualitative and two optional quantitative modes with excellent sensing sensitivity. Under optimal conditions, the limit of detection (LOD) for the model hazardous analyte dehydroepiandrosterone (DHEA) were 1.0 ng mL^-1 for CM-LFIA, 0.42 ng mL^-1 for PT-LFIA, and 0.013 ng mL^-1 for SERS-LFIA, three of which were over 100-fold, 200-fold and 7 000-fold more sensitive than conventional visual AuNPs-based LFIA, respectively. In addition, the quantitative PT-LFIA and SERS-LFIA sensors worked well in spiked real samples with acceptable recoveries of 96.2 - 106.7% and 98.2 - 105.2%, respectively. This assay demonstrated that the developed multimodal LFIA had a great potential to be a powerful tool for accurate tracing hazardous analytes in complex samples.

One-Component Multichannel Sensor Array for Rapid Identification of Bacteria

Bacterial infections routinely cause serious problems to public health. To mitigate the impact of bacterial infections, sensing systems are urgently required for the detection and subsequent epidemiological control of pathogenic organisms. Most conventional approaches are time-consuming and highly instrument- and professional operator-dependent. Here, we developed a novel one-component multichannel array constructed with complex systems made from three modified polyethyleneimine as well as negatively charged graphene oxide, which provided an information-rich multimode response to successfully identify 10 bacteria within minutes via electrostatic interactions and hydrophobic interactions. Furthermore, the concentration of bacteria (from OD₆₀₀ = 0.025 to 1) and the ratio of mixed bacteria were successfully achieved with our smart sensing system. Our designed sensor array also exhibited huge potential in biological samples, such as in urine (OD₆₀₀ = 0.125, 94% accuracy). The way to construct a sensor array with minimal sensor element with abundant signal outputs tremendously saves cost and time, providing a powerful tool for the diagnosis and assessment of bacterial infections in the clinic.

Application of Surface-Enhanced Raman Spectroscopy in the Screening of Pulmonary Adenocarcinoma Nodules

This study is aimed at evaluating the feasibility of a screening method for the pulmonary adenocarcinoma nodules through surface-enhanced Raman spectroscopy (SERS). Objective. Using SERS to measure serum from pulmonary nodules and healthy subjects, intraoperative biopsy pathological diagnosis was regarded as the gold standard for labeling serum samples. To explore the application value of SERS in the differential diagnosis of pulmonary adenocarcinoma nodules, benign nodules, and healthy, we build a machine learning model. Method. We collected 116 serum samples from patients. Radiographically confirmed nodules less than 3 cm in maximum diameter in all patients, including 58 cancer (pathologic diagnosis: adenocarcinoma nodules, labeled as cancer) patients, 58 pathologic diagnoses as benign nodule (labeled as benign) patients, and 63 healthy (labeled as normal) people from the clinical laboratory of Sichuan Cancer Hospital. Gold nanorods were employed as SERS substrates. Support vector machine (SVM) was used to classify the normal, benign, and cancer sample groups, and SVM model evaluated using cross-validation. Results. The average SERS spectra of serum were significantly different between the normal group and the cancer/benign group. While the average SERS spectra of the cancer group and the benign group differed slightly, for the cancer, benign, and normal groups, SVM models can predict with 93.33% accuracy. Conclusion. This exploratory study demonstrates that the SERS technique based on nanoparticles in conjunction with SVM has great potential as a clinical auxiliary diagnosis and screening for pulmonary adenocarcinoma nodules.

Analytical determination of gold ions based on ranelate induced nanoparticle formation

A ranelate ion, an old antiosteoporotic drug, readily reacts with gold(III) ions generating stable gold nanoparticles (AuNP@Ran). The reaction proceeds rapidly under green conditions and is specific for gold ions at room temperature. Their characteristic color associated with the plasmonic resonance effects allows its use in colorimetric/spectrophotometric analysis, as well as in spot test assays. In addition to the color changes, the gold nanoparticles exhibit surface enhanced Raman scattering (SERS), providing another interesting route for the analytical detection of gold ions. Because of the great simplicity, the ranelate method can be very convenient for monitoring gold ions, especially in metal extraction and hydrometallurgical processes.

Aptamer-Based Fluorescence Detection and Selective Disinfection of Salmonella Typhimurium by Using Hollow Carbon Nitride Nanosphere

Hollow carbon nitride nanosphere (HCNS) was synthesized via the hard template method to improve the fluorescence characteristics, drug delivery ability, and photocatalytic activity. Blue fluorescent HCNS was utilized as a quenching agent and an internal reference to combine with Cy5-labelled aptamer (Cy5-Apt), resulting in an off-on fluorescence aptasensing method for the detection of Salmonella typhimurium (S. typhimurium). Under optimum conditions, this fluorescence assay presented a linear range from 30 to 3 × 10⁴ CFU mL^-1 with a detection limit of 13 CFU mL^-1. In addition, HCNS was also used as a drug carrier to load chloramphenicol (Cap) molecules. The Cap-loading amount of HCNS could reach 550 μg mg^-1 within 24 h, whereas the corresponding Cap-release amount is 302.5 μg mg^-1 under acidic and irradiation conditions. The integration of photocatalyst with antibiotic could endow HCNS-Cap with better disinfection performance. The bactericidal efficiency of HCNS-Cap (95.0%) against S. typhimurium within 12 h was better than those of HCNS (85.1%) and Cap (72.9%). In addition, selective disinfection of S. typhimurium was further realized by decorating aptamer. Within 4 h, almost all S. Typhimurium were inactivated by HCNS-Cap-Apt, whereas only 13.3% and 48.2% of Staphylococcus aureus and Escherichia coli cells were killed, respectively. Therefore, HCNS is a promising bio-platform for aptamer-based fluorescence detection and selective disinfection of S. typhimurium.

SERS-based Au@Ag NPs Solid-phase substrate combined with chemometrics for rapid discrimination of multiple foodborne pathogens

In this study, a surface enhanced Raman scattering (SERS) sensor based on Au@Ag NPs solid-phase substrate combined with chemometrics was constructed for the discrimination of three pathogenic bacteria (Staphylococcus aureus, Escherichia coli and Listeria monocytogenes). The Au@Ag NPs were synthesized and self-assembled on filter paper using the dip-coating method. The good absorbency of the filter paper immobilized the bacteria on the substrate, increased the interaction between the bacteria and the substrate, and enhanced the SERS signal of the bacteria. The main peaks of the bacterial spectra were close to each other, but the relative intensities of the vibrational peaks were significantly different, and each strain exhibited unique Raman peaks. The combination of partial least squared discriminant analysis (PLS-DA) method with bacterial SERS allowed the effective identification of the three bacteria. Moreover, the method was applied for the quantitative detection of Staphylococcus aureus with a minimum detection concentration of 10⁴ cfu/mL.

A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.

A review of surface-enhanced Raman spectroscopy in pathological processes

With the continuous growth of the human population and new challenges in the quality of life, it is more important than ever to diagnose diseases and pathologies with high accuracy, sensitivity and in different scenarios from medical implants to the operation room. Although conventional methods of diagnosis revolutionized healthcare, alternative analytical methods are making their way out of academic labs into clinics. In this regard, surface-enhanced Raman spectroscopy (SERS) developed immensely with its capability to achieve single-molecule sensitivity and high-specificity in the last two decades, and now it is well on its way to join the arsenal of physicians. This review discusses how SERS is becoming an essential tool for the clinical investigation of pathologies including inflammation, infections, necrosis/apoptosis, hypoxia, and tumors. We critically discuss the strategies reported so far in nanoparticle assembly, functionalization, non-metallic substrates, colloidal solutions and how these techniques improve SERS characteristics during pathology diagnoses like sensitivity, selectivity, and detection limit. Moreover, it is crucial to introduce the most recent developments and future perspectives of SERS as a biomedical analytical method. We finally discuss the challenges that remain as bottlenecks for a routine SERS implementation in the medical room from in vitro to in vivo applications. The review showcases the adaptability and versatility of SERS to resolve pathological processes by covering various experimental and analytical methods and the specific spectral features and analysis results achieved by these methods.

Advances in Surface-Enhanced Raman Scattering-Based Aptasensors for Food Safety Detection

Owing to the excellent performances of high sensitivity, high specificity, on-site detection, and multiplexing capability, surface-enhanced Raman scattering (SERS)-based aptasensors have performed prosperous applications and gained impressive progress in food safety. Herein, we reviewed the SERS-based aptasensors from the principles to specific applications in food safety. First, the sensor-working principles, SERS label design and preparation are introduced. Then, the popular platforms in the aptasensors are summarized with their advantages and disadvantages, followed by their representative applications. Further, the specific applications of developing SERS-based aptasensors in food safety are systematically provided. Moreover, the multiplex analysis using SERS labels are highlighted. Finally, challenges and perspectives for improving the SERS-based aptasensor performance are also discussed, aiming to give some proposes for researchers to choose suitable SERS-based aptasensors according to specific applications.

An all-in-one magnetic SERS nanosensor for ratiometric detection of Escherichia coli in foods

An all-in-one nanosensor was developed for the magnetic enrichment and ratiometric surface-enhanced Raman scattering (SERS) detection of Escherichia coli (E. coli). The all-in-one nanosensor was constructed through the chemical integration of four components into a single nanoparticle, which include a manganese ferrite nanoparticle serving as the magnetic core, a thin silver shell as the SERS substrate, a self-assembled layer of 4-mercaptobenzoic acid (MBA) molecules as the SERS internal standard, and a MBA-conjugated layer of aptamer sequences as the capture probe of E. coli. In the detection of E. coli in food, the target cells were first captured by the nanosensors and magnetically enriched in a short time of 15 min, and then the ratiometric SERS was performed through the Raman intensity ratio between two specific SERS peaks produced by the captured E. coli and the internal MBA. The pre-concentration and ratiometry enabled the nanosensor to detect E. coli with a detection limit down to 10 CFU/mL. The all-in-one nanosensor was successfully applied for the detection of E. coli in various liquid foods including milk, juice, tea, and coffee, with recoveries ranging from 89 to 110% and relative standard deviation lower than 1.7%. In comparison with the previous sandwich strategy adopted by most SERS sensors, this nanosensor endowed with an easier use and a lower cost is more sensitive and reproducible, leading to a great potential in practical applications.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Modern Analytical Techniques for Detection of Bacteria in Surface and Wastewaters

Contamination of surface waters with pathogens as well as all diseases associated with such events are a significant concern worldwide. In recent decades, there has been a growing interest in developing analytical methods with good performance for the detection of this category of contaminants. The most important analytical methods applied for the determination of bacteria in waters are traditional ones (such as bacterial culturing methods, enzyme-linked immunoassay, polymerase chain reaction, and loop-mediated isothermal amplification) and advanced alternative methods (such as spectrometry, chromatography, capillary electrophoresis, surface-enhanced Raman scattering, and magnetic field-assisted and hyphenated techniques). In addition, optical and electrochemical sensors have gained much attention as essential alternatives for the conventional detection of bacteria. The large number of available methods have been materialized by many publications in this field aimed to ensure the control of water quality in water resources. This study represents a critical synthesis of the literature regarding the latest analytical methods covering comparative aspects of pathogen contamination of water resources. All these aspects are presented as representative examples, focusing on two important bacteria with essential implications on the health of the population, namely Pseudomonas aeruginosa and Escherichia coli.

Combining vancomycin-modified gold nanorod arrays and colloidal nanoparticles as a sandwich model for the discrimination of Gram-positive bacteria and their detection via surface-enhanced Raman spectroscopy (SERS)

This study reports the development of a highly sensitive antibiotic-based discrimination and sensor platform for the detection of Gram-positive bacteria through surface-enhanced Raman spectroscopy (SERS).