A dynamically optical and highly stable pNIPAM @ Au NRs nanohybrid substrate for sensitive SERS detection of malachite green in fish fillet

A core-satellite self-assembled SERS aptasensor used for ultrasensitive detection of AFB1

A surface-enhanced Raman scattering (SERS) aptasensor was developed using gold nanostars (Au NSs) and Fe3O4@Au nanoparticles (NPs) for the highly sensitive detection of aflatoxin B1 (AFB1). Au NSs were modified by the Raman reporter 4-aminothiophenol (PATP) and then coupled with cDNA to act as the capture probes (Au NSs@PATP-cDNA). Fe3O4@Au NPs were modified with the AFB1 aptamer (AFB1 Apt) and used as signal probes (Fe3O4@Au NPs-AFB1 Apt). The SERS peak of PATP at 1078 cm-1 was used for quantitative analysis. When the core-satellite nanostructures (Fe3O4@Au NPs-AFB1 Apt/cDNA-Au NSs@PATP) were self-assembled by oligonucleotide hybridization, the SERS intensity was significantly enhanced. When AFB1 was present, AFB1 Apt specifically binds to AFB1, causing the Fe3O4@Au NPs-AFB1 Apt and Au NSs@PATP-cDNA to dissociate, resulting in a decrease in the SERS intensity measured after magnetic separation. Under optimal conditions, the limit of detection (LOD) of AFB1 can be reduced to 0.24 pg/mL. This is attributed to the high affinity of AFB1 Apt, excellent magnetic separation characteristics, and multiple SERS hotspots. The assay has been validated to perform well in recovery and accuracy by evaluating spiked samples (rice, corn, and wheat) and positive samples (corn, brown rice, and wheat).

Advances and applications of dynamic surface-enhanced Raman spectroscopy (SERS) for single molecule studies

Dynamic surface-enhanced Raman spectroscopy (SERS) is nowadays one of the most interesting applications of SERS, in particular for single molecule studies. In fact, it enables the study of real-time processes at the molecular level. This review summarizes the latest developments in dynamic SERS techniques and their applications, focusing on new instrumentation, data analysis methods, temporal resolution and sensitivity improvements, and novel substrates. We highlight the progress and applications of single-molecule dynamic SERS in monitoring chemical reactions, catalysis, biomolecular interactions, conformational dynamics, and real-time sensing and detection. We aim to provide a comprehensive review on its advancements, applications as well as its current challenges and development frontiers.

Recyclable NiO/g-C3N4/ag hybrid substrates for sensitive SERS detection and photo-degradation of residual pesticides in beverages

In this research, we fabricated an innovative NiO/CN/Ag composite through the straightforward electrostatic assembly of Ag nanoparticles and g-C3N4 sheets onto NiO nanoflowers. This composite enables both surface enhanced Raman spectroscopy (SERS) detection and photo-degradation of pesticides. The results reveal NiO/CN/Ag can quantitatively detect thiram (TRM) and diquat dibromide (DQDB) in water, with a limit of detection (LOD) of 10-9 M, and also exhibit outstanding photo-degradation efficiency, exceeding 95 % for TRM and DQDB within 90 min under simulated sunlight. Significantly, after the organic reagent (citric acid) on NiO/CN/Ag was completely removed through simulated solar irradiation, the signal-to-noise ratios of SERS spectra on NiO/CN/Ag were enhanced, achieving LODs of 10-8 M for TRM and DQDB in different fruit juices and dried flower teas. Additionally, the composite demonstrate impressive recyclability, maintaining robust SERS signals and high degradation rates even after five cycles of "detection-degradation" processes.

Elevating electron transfer of recyclable SERS sensor using AuNPs/TiO2/Ti3C2 heterostructures for detection of malachite green in sunfish

Malachite green (MG)-contaminated aquatic products pose a serious threat to animal and human health. Hence, a novel recyclable surface-enhanced Raman scattering (SERS) substrate based on AuNPs/TiO2/Ti3C2 heterostructures was developed for the detection and degradation of MG in aquatic products. Specifically, AuNPs/TiO2/Ti3C2 heterostructures were synthesized by in situ oxidation and electrostatic adsorption based on Ti3C2 nanosheets. The excellent photocatalytic and SERS performance of the AuNPs/TiO2/Ti3C2 was demonstrated by Density functional theory (DFT) calculations and experimental results, which was attributed to the enhancement of charge transfer (CT) after the formation of heterostructures. The results demonstrate that AuNPs/TiO2/Ti3C2 is highly sensitive and recyclable. The detection limit of the sensor for MG is 8.91 × 10-5 mg/L. The sensor can be recycled for five times under the condition of light, and shows satisfactory self-cleaning performance in the food matrix, providing a possible alternative solution for the recyclable detection of MG.

A semiconductor SERS sensor of corrosion-resistant PPy/GO composite film by electrochemical growth for detecting crystal violet residues in fresh fish tissue

Crystal violet (CV) residues in Marine food have produced a severe health threat in human life. In this study, we proposed a semiconductor surface-enhanced Raman scattering (SERS) sensor of corrosion-resistant Polyaniline/Graphene oxide (PPy/GO) film by electrochemical growth method to detect CV residues in fresh fish tissue. A PPy/GO dispersion solution was one-step deposited on a stainless steel sheet surface by electrochemical polymerization process to form a PPy/GO composite film acting as a semiconductor SERS substrate. Since the substrate of PPy/GO film was mainly composed of GO sheet without other metals, it had a good corrosion resistance. The SERS enhancement factor and charge transfer intensity PCT of PPy/Go SERS substrate for CV molecules were up to 1.18 × 106 and 0.903, respectively. Furthermore, the limit of detection (LOD) of PPy/GO SERS substrate could reach 1.58 nM. In addition, SERS sensor of PPy/GO film could identify CV residues in fresh fish tissues, and its recovery rate was 91.8 %-107 %. This preparing method and detecting method we proposed PPy/GO SERS substrate provide a new pathway for detecting CV residues in Marine food.

High sensitive Ratiometric fluorescent Aptasensor with AIE properties for Deoxynivalenol (DON) detection

An emerging fluorescent ratiometric aptasensor based on gold nanoclusters (AuNCs) with aggregation-induced emission (AIE) properties was prepared and studied for deoxynivalenol (DON) detection. The ratiometric aptasensor used red fluorescent AuNCs620 labelled with DON aptamer (Apt-AuNCs620) as an indicator and green fluorescent AuNCs519 modified by complementary DNA (cDNA) and magnetic beads (MBs) as internal reference, namely MBs-cDNA-AuNCs519. Under the optimal conditions, the aptasensor exhibited two good linear ranges of 0.1-50 and 50-5000 pg/mL for DON detection with coefficient of determination (R2) of 0.9937 and 0.9928, respectively, and the low detection limit (LOD) of 4.09 pg/mL was achieved. Furthermore, this aptasensor was feasible to detect DON in positive wheat samples, and the results were in line with those from HPLC and ELISA, thus providing a promising route to detect DON with high sensitivity in cereals, even for other mycotoxins by replacing the suitable aptamer and cDNA.

Reliable detection of malachite green by self-assembled SERS substrates based on gold-silicon heterogeneous nano pineapple structures

Morphology regulation of heterodimer nanoparticles and the use of their asymmetric features for further practical applications are crucial because of the rich optical properties and various combinations of heterodimers. This work used silicon to asymmetrically wrap half of a gold sphere and grew gold branches on the bare gold surface to form heterogeneous nano pineapples (NPPs) which can effectively improve Surface-enhanced Raman scattering (SERS) properties through chemical enhancement and lightning-rod effect respectively. The asymmetric structures of NPPs enabled them to self-assemble into the monolayer membrane with consistent branch orientation. The prepared substrate had high homogeneity and better SERS ability than disorganized substrates, and achieved reliable detection of malachite green (MG) in clams with a detection limit of 7.8 × 10-11 M. This work provided a guide to further revise the morphology of heterodimers and a new idea for the use of asymmetric dimers for practically photochemical and biomedical sensing.

Fast real-time monitoring of meat freshness based on fluorescent sensing array and deep learning: From development to deployment

A fluorescent sensor array (FSA) combined with deep learning (DL) techniques was developed for meat freshness real-time monitoring from development to deployment. The array was made up of copper metal nanoclusters (CuNCs) and fluorescent dyes, having a good ability in the quantitative and qualitative detection of ammonia, dimethylamine, and trimethylamine gases with a low limit of detection (as low as 131.56 ppb) in range of 5 ∼ 1000 ppm and visually monitoring the freshness of various meats stored at 4 °C. Moreover, SqueezeNet was applied to automatically identify the fresh level of meat based on FSA images with high accuracy (98.17 %) and further deployed in various production environments such as personal computers, mobile devices, and websites by using open neural network exchange (ONNX) technique. The entire meat freshness recognition process only takes 5 ∼ 7 s. Furthermore, gradient-weighted class activation mapping (Grad-CAM) and uniform manifold approximation and projection (UMAP) explanatory algorithms were used to improve the interpretability and transparency of SqueezeNet. Thus, this study shows a new idea for FSA assisted with DL in meat freshness intelligent monitoring from development to deployment.

Elevating nanomaterial optical sensor arrays through the integration of advanced machine learning techniques for enhancing visual inspection of food quality and safety

Food quality and safety problems caused by inefficient control in the food chain have significant implications for human health, social stability, and economic progress and optical sensor arrays (OSAs) can effectively address these challenges. This review aims to summarize the recent applications of nanomaterials-based OSA for food quality and safety visual monitoring, including colourimetric sensor array (CSA) and fluorescent sensor array (FSA). First, the fundamental properties of various advanced nanomaterials, mainly including metal nanoparticles (MNPs) and nanoclusters (MNCs), quantum dots (QDs), upconversion nanoparticles (UCNPs), and others, were described. Besides, the diverse machine learning (ML) and deep learning (DL) methods of high-dimensional data obtained from the responses between different sensing elements and analytes were presented. Moreover, the recent and representative applications in pesticide residues, heavy metal ions, bacterial contamination, antioxidants, flavor matters, and food freshness detection were comprehensively summarized. Finally, the challenges and future perspectives for nanomaterials-based OSAs are discussed. It is believed that with the advancements in artificial intelligence (AI) techniques and integrated technology, nanomaterials-based OSAs are expected to be an intelligent, effective, and rapid tool for food quality assessment and safety control.

Developing a magnetic SERS nanosensor utilizing aminated Fe-Based MOF for ultrasensitive trace detection of organophosphorus pesticides in apple juice

The unreasonable use of organophosphorus pesticides leads to excessive pesticide residues in food, seriously threatening public health, and the potential of surface-enhanced Raman spectroscopy (SERS) technology, incorporating a metal-organic framework, is substantial for the rapid detection of trace pesticide residues. Here, a novel Fe3O4@NH2-MIL-101(Fe)@Ag (FNMA) SERS nanosensor was developed. Results indicated that the FNMA had a high enhancement factor of 1.53 × 108, a low limit of detection (LOD) of 4.55 × 10-12 M, and a relative standard deviation of 7.73 % for 4-nitrothiophenol, demonstrating its good SERS sensitivity and uniformity, and also possessed good storage stability for one month. In quantifying fenthion and methyl parathion in standard solutions and apple juice in the range of 0.05/0.02-20 mg/L, it showed LODs of 3.02 × 10-3 mg/L and 1.43 × 10-3 mg/L, and 0.0407 and 0.0075 mg/L, respectively, demonstrating potentials in ultrasensitive trace detection of pesticides in food.

Hydrogel-integrated sensors for food safety and quality monitoring: Fabrication strategies and emerging applications

Food safety is a global issue in public hygiene. The accurate, sensitive, and on-site detection of various food contaminants performs significant implications. However, traditional methods suffer from the time-consuming and professional operation, restricting their on-site application. Hydrogels with the merits of highly porous structure, high biocompatibility, good shape-adaptability, and stimuli-responsiveness offer a promising biomaterial to design sensors for ensuring food safety. This review describes the emerging applications of hydrogel-based sensors in food safety inspection in recent years. In particular, this study elaborates on their fabrication strategies and unique sensing mechanisms depending on whether the hydrogel is stimuli-responsive or not. Stimuli-responsive hydrogels can be integrated with various functional ligands for sensitive and convenient detection via signal amplification and transduction; while non-stimuli-responsive hydrogels are mainly used as solid-state encapsulating carriers for signal probe, nanomaterial, or cell and as conductive media. In addition, their existing challenges, future perspectives, and application prospects are discussed. These practices greatly enrich the application scenarios and improve the detection performance of hydrogel-based sensors in food safety detection.

Visible detection of chilled beef freshness using a paper-based colourimetric sensor array combining with deep learning algorithms

This study developed an innovative approach that combines a colourimetric sensor array (CSA) composed of twelve pH-response dyes with advanced algorithms, aiming to detect amine gases and assess the freshness of chilled beef. With the assistance of multivariate statistical analysis, the sensor array can effectively distinguish five amine gases and enable rapid quantification of trimethylamine vapour with a limit of detection (LOD) of 8.02 ppb and visually monitor the fresh levels of chilled beef. Moreover, the utilization of deep learning models (ResNet34, VGG16, and GoogleNet) for chilled beef freshness evaluation achieved an overall accuracy of 98.0 %. Furthermore, t-distributed stochastic neighbour embedding (t-SNE) visualized the feature extraction process and provided explanations to understand the classification process of deep learning. The results demonstrated that applying deep learning techniques in the process of pattern recognition of CSA can help in realizing the rapid, robust, and accurate assessment of chilled beef freshness.

Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications

Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.

Recent Studies and Applications of Hydrogel-Based Biosensors in Food Safety

Food safety has increasingly become a human health issue that concerns all countries in the world. Some substances in food that can pose a significant threat to human health include, but are not limited to, pesticides, biotoxins, antibiotics, pathogenic bacteria, food quality indicators, heavy metals, and illegal additives. The traditional methods of food contaminant detection have practical limitations or analytical defects, restricting their on-site application. Hydrogels with the merits of a large surface area, highly porous structure, good shape-adaptability, excellent biocompatibility, and mechanical stability have been widely studied in the field of food safety sensing. The classification, response mechanism, and recent application of hydrogel-based biosensors in food safety are reviewed in this paper. Furthermore, the challenges and future trends of hydrogel biosensors are also discussed.

Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy (SERS) coupled with deep learning models

Surface-enhanced Raman spectroscopy (SERS) and deep learning models were adopted for detecting zearalenone (ZEN) in corn oil. First, gold nanorods were synthesized as a SERS substrate. Second, the collected SERS spectra were augmented to improve the generalization ability of regression models. Third, five regression models, including partial least squares regression (PLSR), random forest regression (RFR), Gaussian progress regression (GPR), one-dimensional convolutional neural networks (1D CNN), and two-dimensional convolutional neural networks (2D CNN), were developed. The results showed that 1D CNN and 2D CNN models possessed the best prediction performance, i.e., determination of prediction set (R_P²) = 0.9863 and 0.9872, root mean squared error of prediction set (RMSEP) = 0.2267 and 0.2341, ratio of performance to deviation (RPD) = 6.548 and 6.827, limit of detection (LOD) = 6.81 × 10^-4 and 7.24 × 10^-4 μg/mL. Therefore, the proposed method offers an ultrasensitive and effective strategy for detecting ZEN in corn oil.

Aggregates-based fluorescence sensing technology for food hazard detection: Principles, improvement strategies, and applications

Aggregates often exhibit modified or completely new properties compared with their molecular elements, making them an extraordinarily advantageous form of materials. The fluorescence signal change characteristics resulting from molecular aggregation endow aggregates with high sensitivity and broad applicability. In molecular aggregates, the photoluminescence properties at the molecular level can be annihilated or elevated, leading to aggregation-causing quenching (ACQ) or aggregation-induced emission (AIE) effects. This change in photoluminescence properties can be intelligently introduced in food hazard detection. Recognition units can combine with the aggregate-based sensor by joining the aggregation process, endowing the sensor with the high specificity of analytes (such as mycotoxins, pathogens, and complex organic molecules). In this review, aggregation mechanisms, structural characteristics of fluorescent materials (including ACQ/AIE-activated), and their applications in food hazard detection (with/without recognition units) are summarized. Because the design of aggregate-based sensors may be influenced by the properties of their components, the sensing mechanisms of different fluorescent materials were described separately. Details of fluorescent materials, including conventional organic dyes, carbon nanomaterials, quantum dots, polymers and polymer-based nanostructures and metal nanoclusters, and recognition units, such as aptamer, antibody, molecular imprinting, and host-guest recognition, are discussed. In addition, future trends of developing aggregate-based fluorescence sensing technology in monitoring food hazards are also proposed.

SERS-active plasmonic metal NP-CsPbX3 films for multiple veterinary drug residues detection

Sensitive and multiple veterinary drug residues detection is of important for food safety. Herein, uniform plasmonic Au nanobipyramids@Ag nanorods (Au NBP@Ag NR)-CsPbX₃ films with strong surface-enhanced Raman scattering (SERS) activity were constructed. The effects of different CsPbX₃ (X = Cl, Br, I, or mixed halogens) quantum dots (QDs) on the SERS performances of plasmonic metal NP films were investigated. CsPbI₃ QDs with large dielectric constant could be served as the dielectric media to retard the attenuation of electromagnetic evanescent wave, inducing strong electromagnetic strength for SERS enhancement. Plasmon-induced metal-to-perovskite interfacial charge transfer transition also contributed to SERS enhancement. SERS-active plasmonic Au NBP@Ag NR-CsPbI₃ films had excellent sensitivity and high reproducibility for quantitative, accurate and multiple detection of chloramphenicol, diazepam and malachite green in food matrix. This work deepened the understanding of the SERS enhancement mechanisms of plasmonic metal NP-perovskite hybrid heterostructures, showing potential prospects in food safety monitoring.

Facile and portable multimodal sensing platform driven by photothermal-controlled release system for biomarker detection

Portable, maneuverable and reliable versatile-integrated analytical devices are urgently demanded but still extremely challenging to meet the requirements of point-of-care testing in resource-limited areas. Herein, a multifunctional sensing platform with excellent photothermal performance was implanted into the miniature zone of a paper-based electrochemiluminescent (ECL) biosensor for accurate detection of interleukin-6, which could flexibly interconnect the visualized distance and temperature readout with ultrasensitive ECL response. Concretely, the multipurpose MBene and TaSe₂ composites (MBene@TaSe₂) prepared via self-assembly approach as target-associated photothermal element was introduced in the paper-based analytical device (PAD) and served as multi-signals trigger. Under the laser irradiation, MBene@TaSe₂ probe not only generated heat for rapid temperature output, but also triggered the phase transition behavior of thermoresponsive poly (N-isopropylacrylamide) (pNIPAM) hydrogel to release loaded malachite green (MG) dye for distance-based visual readout. Simultaneously, the released MG was also utilized as effective quencher to decrease the ECL signal of luminol. Benefitting from this dexterous architecture, the speedy preliminary screening and precise quantitative analysis could be subsequently obtained in single-drop sample through one-step sandwich immunoreaction, which avoids additional separation operations and greatly simplifies the analysis procedure. Undeniably, this work provides ingenious insights for advancing the development of convenient and fast multifunction-integrated PAD in family surveillance and intelligent diagnosis.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

A highly sensitive surface-enhanced Raman scattering sensor with MIL-100(Fe)/Au composites for detection of malachite green in fish pond water

Concerns about food safety have been arisen due to the improper use of chemicals in aquaculture. Malachite green (MG) has attracted attention because of its illegal usage and its potential negative impacts on the environment and public health. Surface-enhanced Raman scattering (SERS) platforms coupled with different SERS substrates have been employed for rapid analysis of MG residues in food. However, the most commonly used SERS substrates were non-reusable and showed limited detection sensitivity. In this study, a novel SERS substrate with a good recyclability and a high sensitivity was prepared by electrostatically assembling together a metal-organic framework material called materials of institute lavoisie-100(Fe) (MIL-100(Fe)) and Au NPs. The lowest detectable concentration of MG was 10^-13 M based on the optimal substrate. The SERS sensor was applied for the detection of the trace MG in fish pond water, which was accomplished with the correlation coefficients R² = 0.991-0.996 in a concentration range of 10^-6-10^-13 M. Moreover, MIL-100(Fe)/Au was recycled at least five times, realizing a "detection to degradation", showing great potential for food contamination monitoring due to its distinguished performance.

Aflatoxin B1 can aggravate BALB/c mice allergy to ovalbumin through changing their Th2 cells immune responses

Foods contaminated by Aflatoxin B₁ (AFB₁) frequently happen in the world and can cause a lot healthy damages to human beings, meanwhile, some of these foods are easily irritate food allergy. To investigate the effect of AFB₁ exposure on food allergy, three doses of AFB₁ were set, including 0.3 μg/kg · bw (LDAF), 7.5 μg/kg · bw (MDAF), and 100.0 μg/kg · bw (HDAF), respectively; food allergy model was constructed by the BALB/c mice allergy to ovalbumin (OVA). The changes of titer in OVA-specific immunoglobulin E (IgE), IgG, IgG1, IgG2a, as well as level of the mMCP-1 in sera were determined by enzyme linked immunosorbent assay (ELISA), respectively; the levels of interleukin (IL-4, IL-5, IL-13) and interferon (IFN)-γ in spleen were separately assessed using ELISA kits, and their relative genes expression were verified by Real-time fluorescence quantitative PCR (Q-PCR); the population of Th1/Th2/Treg cells were analyzed by flow cytometry. Results showed that when OVA-allergic mice were exposed to AFB₁, the production of OVA-specific IgE, IL-4, IL-5 and IL-13, and mMCP-1 were all increased, whereas the level of IFN-γ was decreased; the Th1/Th2 balance was disrupted and the development of Th cells tilted to the Th2 phenotype. The study would contribute to further understand the risk of fungal toxins in food allergy.

Flexible Au@AgNRs/CMC/qPCR film with enhanced sensitivity, homogeneity and stability for in-situ extraction and SERS detection of thiabendazole on fruits

In this study, a high-performance, stable and homogeneous Au@AgNRs/CMC/qPCR flexible film surface-enhanced Raman scattering (SERS) substrate was constructed by synergistically stabilizing and protecting bimetallic core-shell Au@Ag nanorods (Au@AgNRs) with carboxymethylcellulose (CMC) and fluorescent-quantitative-polymerase-chain-reaction (qPCR) film. The network structure of CMC immobilized and aligned Au@AgNRs through coordination of carboxyl groups with surface Ag atoms to provide intensive and stable 'hot spots', and the qPCR bilayer film performed as carrier and barrier to protect Au@AgNRs from oxidation, humidity and optical damage and improved the robustness and stability. The Au@AgNRs/CMC/qPCR film was used for in-situ extraction and SERS detection of thiabendazole on nectarine (0.24 ppm) and lemon (0.27 ppm) with low detection of limits. Furthermore, it retained 98.6% SERS performance after storage for 90 days under ambient conditions, revealing the great potential in promoting the commercialization of the SERS technique for sensitive contaminants sensing with simple fabrication procedures, homogeneity, reproducibility and long-term stability.

Dummy Template-Based Molecularly Imprinted Membrane Coating for Rapid Analysis of Malachite Green and Its Metabolic Intermediates in Shrimp and Fish

A novel malachite green molecularly imprinted membrane (MG-MIM) with specific selectivity for malachite green (MG) and leucomalachite green (LMG) was prepared using a hydrophobic glass fiber membrane as the polymer substrate, methyl violet as a template analog, 4-vinyl benzoic acid as the functional monomer, and ethyleneglycol dimethacrylate as the crosslinking agent. MG-MIM and non-imprinted membrane (NIM) were structurally characterized using scanning electron microscopy, surface area analyzer, Fourier-transform infrared spectrometer and synchronous thermal analyzer. The results showed that MG-MIM possessed a fluffier surface, porous and looser structure, and had good thermal stability. Adsorption properties of MG-MIM were investigated under optimal conditions, and adsorption equilibrium was reached in 20 min. The saturated adsorption capacities for MG and LMG were 24.25 ng·cm^-2 and 13.40 ng·cm^-2, and the maximum imprinting factors were 2.41 and 3.20, respectively. Issues such as "template leakage" and "embedding" were resolved. The specific recognition ability for the targets was good and the adsorption capacity was stable even after five cycles. The proposed method was successfully applied for the detection of MG and LMG in real samples, and it showed good linear correlation in the range of 0 to 10.0 μg·L^-1 (R² = 0.9991 and 0.9982), and high detection sensitivity (detection limits of MG and LMG of 0.005 μg/kg and 0.02 μg·kg^-1 in shrimp, and 0.005 μg/kg and 0.02 μg/kg in fish sample). The recoveries and relative standard deviations were in the range of 76.31-93.26% and 0.73-3.72%, respectively. The proposed method provides a simple, efficient and promising alternative for monitoring MG and LMG in aquatic products.

Green Synthesis of Three-Dimensional Au Nanorods@TiO2 Nanocomposites as Self-Cleaning SERS Substrate for Sensitive, Recyclable, and In Situ Sensing Environmental Pollutants

In this work, a simple, low-cost, green, and mild method for the preparation of three-dimensional nanocomposite materials of gold nanorods (Au NRs)@TiO₂ is reported. The surface of Au NRs was coated with TiO₂ in situ reduction at room temperature without a complicated operation. The synthetic Au NRs@TiO₂ nanocomposites were used as surface-enhanced Raman spectroscopy (SERS) active substrates for the reusable and sensitive detection of environmental pollutants. The results showed that the pollutants on Au NRs@TiO₂ nanocomposites have higher SERS activity and reproducibility than those on the Au NR substrate without the presence of TiO₂. Moreover, the SERS substrate can be readily recycled by UV-assisted self-cleaning to remove residual analyte molecules. Malachite green (MG) and crystal violet (CV) were used as examples to demonstrate the feasibility of the proposed sensor for the sensitive detection of environmental pollutants. The results showed that the limit of detections (LODs) were 0.75 μg/L and 0.50 μg/L for MG and CV, respectively, with the recoveries ranging from 86.67% to 91.20% and 83.70% to 89.00%. Meanwhile, the SERS substrate can be easily regenerated by UV light irradiation. Our investigation revealed that within three cycles, the Au NRs@TiO₂ substrates still maintained the high SERS enhancement effect that they showed when first used for SERS detection. These results indicated that the method can be used to detect MG and CV in really complex samples. Due to the high sensitivity, reusability, and portability and the rapid detection property of the proposed sensor, it can have potential applications in the on-site detection of environmental pollutants in a complex sample matrix.

Ultra-trace and quantitative SERS detection of polycyclic aromatic hydrocarbons based on Au nanoscale convex polyhedrons with embedded probe molecules

Surface-enhanced Raman scattering (SERS) has great potential for the detection of marine pollutants, but it is still restricted in ultra-trace and quantitative analysis. Here, a strategy for the detection of polycyclic aromatic hydrocarbons (PAHs) was proposed based on Au nanoscale convex polyhedrons (Au NCPs) coated with high-energy facets and embedded with 4-ATP as a probe molecule. Au NCPs acted as SERS substrates and led to limits of detection (LODs) for six common PAHs that reached 0.01 nM. Using internal calibration, the relative standard deviations (RSD) of the spectral stability and reproducibility were as low as 3.36% and 5.11%, respectively. The maximum mean relative errors (AREs) of the predicted and true values were 6.28%. The results indicate that the resulting Au NCPs improved the ultra-trace and quantitative detection of SERS, thus suggesting that the Au NCPs have practical application value in SERS.

Surface-enhanced Raman spectroscopy combined with stable isotope probing to assess the metabolic activity of Escherichia coli cells in chicken carcass wash water

Rapid evaluation of the metabolic activity of microorganisms is crucial in the assessment of the disinfection ability of various antimicrobial agents in the food industry. In this study, surface-enhanced Raman spectroscopy combined with isotope probing was employed for the analysis of the disinfection of single bacterial cells in the chicken carcass wash water. The Raman signals from single Escherichia coli O157:H7 cells were enhanced by in situ synthesis of silver nanoparticles. The ΔCD of the cells grown in presence of 0.5% hydrogen peroxide and 50 ppm chlorine was 5.86 ± 1.86% and 5.1 ± 2.3%, respectively, which showed significant reduction compared with cells grown in the absence of disinfecting agents (19.86 ± 2.51%) after 2 h of incubation. The study proved that the proposed method had the potential to assess the metabolic activity of microorganisms in other food products and optimize the disinfection process.

Functional cotton fabric-based TLC-SERS matrix for rapid and sensitive detection of mixed dyes

A facile cotton fabric with a built-in TLC-SERS structure was fabricated to demonstrate an integrated TLC separation and SERS identification of mixed dyes. The soft and flexible SERS fabric was firstly fabricated using a simple method in which gold nanoparticles were in-situ synthesized on cotton fabrics by heating. β-CD was then grafted onto cotton fabric through crosslinking with citric acid in presence of sodium hypophosphite monohydrate via esterification reaction. The adsorption and TLC development performance of β-CD grafted fabrics were comprehensively investigated with two organic dyes, one anionic dye and one nonionic dye. Besides, the recyclable adsorption and separation performance were tested to evaluate its sustainable application prospects. It displayed less adsorption capacity loss and reusable separation performance after several cycles than the pristine cotton fabrics. Finally, two sets of mixed dyes were successfully separated on the TLC fabrics and then identified via on-site SERS according to their different migration distance. The developed TLC-SERS fabric shows the advantage of quick, easy to handle, low-cost, sensitive, and could be exploited in on-site study of synthetic dyes in art objects, textile and packaging products or forensic applications.

Intelligent and thermo-responsive Au-pluronic® F127 nanocapsules for Raman-enhancing detection of biomolecules

Thermo-responsive Raman-enhanced nanocapsules were successfully fabricated by Pluronic® F127 (F127) decorated with gold nanoparticles (AuNPs) for surface-enhanced Raman scattering (SERS) detection of biomolecules. F127 nanocapsules changes from hydrophilicity (swelling) to hydrophobicity (de-swelling) when the temperature increases from 15 °C to 37 °C, owing to the lower critical solution temperature (LCST) of F127 is about 26.5 °C. The size of nanocapsules would be enormous shrinking from 160 nm to 20 nm, resulting in a significant decrease in the distance between AuNPs to enhance hot spot effect, which increases the sensitivity of SERS detection. Based on the thermo-sensitive behavior, the ratio of AuNPs and F127 would be manipulated to find the optimal SERS enhancement effect. SERS nanocapsules can rapidly detect biomolecules (adenine and R6G) with limit of detection (LOD) lower than 10^-6 M. In addition, the relatively difficult to detect clinical samples, carboxyl-terminal parathyroid hormone fragments (C-PTH), can also be measured by the thermo-responsive SERS nanocapsules developed in this work. It is expected the biomolecules can be adsorbed at low temperature (15 °C), as well as collected and concentrated at high temperature (37 °C) for SERS detection, to increase the sensitivity and stability of SERS detection.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Detection of Bioactive Metabolites in Escherichia Coli Cultures Using Surface-Enhanced Raman Spectroscopy

Detection of bioactive metabolites produced by bacteria is important for identifying biomarkers for infectious diseases. In this study, a surface-enhanced Raman spectroscopy (SERS)-based technique was developed for the detection of bioactive metabolite indole produced by Escherichia coli (E. coli) in biological media. The use of highly sensitive Au@Ag core-shell nanoparticles resulted in the detection of indole concentration as low as 0.0886 mM in standard solution. The supplementation of growth media with 5 mM of exogenous tryptophan resulted in the production of a maximum yield of indole of 3.139 mM by E. coli O157:H7 at 37 °C. The growth of bacterial cells was reduced from 47.73 × 10⁸ to 1.033 × 10⁶ CFU/mL when the cells were grown in 0 and 10 mM exogenous tryptophan, respectively. The amount of indole in the Luria-Bertani (LB) media had an inverse correlation with the growth of cells, which resulted in a three-log reduction in the colony-forming unit when the indole concentration in the media was 20 times higher than normal. This work demonstrates that SERS is an effective and highly sensitive method for rapid detection of bioactive metabolites in biological matrix.

Temperature-Responsive Covalent Organic Framework-Encapsulated Carbon Dot-Based Sensing Platform for Pyrethroid Detection via Fluorescence Response and Smartphone Readout

In this paper, carbon dot (CD)-encapsulated 1,3,5-tris(4-formylphenyl)benzene (TFB)/2,5-dihydroxyterephthalohydrazide (DHTH) covalent organic frameworks (TDCOFs) grafted with thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) (CDs@TDCOFs@PNIPAM) were fabricated for the detection of pyrethroids. CDs@TDCOFs@PNIPAM achieved a temperature-responsive "on/off" detection of pyrethroids based on the target-triggered electron-transfer mechanism. The detection limit of pyrethroids was as low as 0.69 μg/L in the wide linear range of 5-400 μg/L (R² > 0.9523). Simultaneously, CDs@TDCOFs@PNIPAM with red, green, and blue (RGB) fluorescence emissions were integrated with a smartphone-assisted device, enabling the visual smart quantitative detection of pyrethroids with a detection limit of 4.875 μg/L. Ultimately, agricultural products were chosen as actual samples to verify the applicability of both recognition modes, and the calculated recovery rate was 105.48-113.40%. Accordingly, CDs@TDCOFs@PNIPAM featuring temperature-responsive switching behavior and RGB fluorescence emission provided a promising analytical strategy for ensuring agricultural and food safety.

Photosensitized Peroxidase Mimicry at the Hierarchical 0D/2D Heterojunction-Like Quasi Metal-Organic Framework Interface for Boosting Biocatalytic Disinfection

Metal-organic frameworks (MOFs) are a versatile toolbox for the bioinspired design of nanozymes for antibacterial applications and beyond, however, designing a nanozyme by the hierarchical quasi-MOF scheme remains largely unpracticed. This work exemplifies the preferential structure-activity correlation of a bimetallic quasi-MOF (Q-MOF_Ce0.5 ) among three series of MOF-derived peroxidase (POD) mimics. The biomimetic quasi-MOF_Ce0.5 nanosheets accommodate both oxygen vacancy-coupled multivalent redox cycles and photosensitive energy band layout, benefiting from the hierarchical heterojunction-like 0D/2D interface featuring isolated nodes-derived CeOCu sites upon the 2D decarboxylated MOF scaffold. These integrated unique merits enable the POD-like Q-MOF_Ce0.5 to generate sustained reactive oxygen species to effectively eradicate the surface-adhered bacteria under visible light, resulting in significant inactivation of Escherichia coli (99.74 %) and Staphylococcus aureus (99.35%) in vitro, and potent disinfection of skin wounds in vivo in safe and on-demand manners. It is hoped that this work can intensify the interventions of MOF nanozymes against the microbial world.

A fluorescence aptasensor based on carbon quantum dots and magnetic Fe3O4 nanoparticles for highly sensitive detection of 17β-estradiol

Trace amounts of 17β-estradiol (E2) in food and the environment poses a threat to human health, which has created the demand for sensitive analytical methods to detect E2. In this study, a novel fluorescent aptasensor was developed for sensitive detection of E2 based on double-chain hybridization between carbon quantum dots-labelled with E2 aptamer (CQDs-aptamer) and Fe₃O₄ nanoparticles modified by complementary DNA (Fe₃O₄-cDNA). Under the optimal conditions, the aptasensor displayed a good linear range of 10^-11-10^-6 M for E2 with the coefficient of determination (R²) of 0.996, and a low detection limit of 3.48 × 10^-12 M was obtained. Besides, the aptasensor showed high selectivity and good reproducibility for E2 detection, which was successfully applied to the sensitive detection of E2 in milk as compared with tap water and lake water with satisfactory recoveries from 85.21% to 114.80%, suggesting the great significance of this aptasensor for detecting food contaminants in the food industry.

Interfacing metal-polyphenolic networks upon photothermal gold nanorods for triplex-evolved biocompatible bactericidal activity

Gold nanorods (GNRs) outstand in photothermal disinfection but are faced with severe surface chemistry and dose relevant biotoxicity. Herein, a naturally green building block, metal-phenolic networks (MPNs), was employed to functionalize GNRs via coordination reaction, yielding a tunable and biocompatible core-shell photothermal nano-bactericide (GNRs@MPNs). The bioactive GNRs@MPNs built with iron and polyphenols (tannic acid, epigallocatechin gallate, and procyanidins) exhibited superior light-to-heat conversion efficiencies with η = 29.29-44.00%, remarkably preceding that of GNRs (η = 12.24%), which could rapidly ablate 99.8% of Escherichia coli O157: H7 and 98.6% of Staphylococcus aureus bacteria in relatively low efficacy doses (10 ppm of Au). Moreover, local heat triggered by GNRs@MPNs accelerated the healing of the cutaneous wound of a mice model infected by methicillin-resistant S. aureus. The facile synthesis, photothermal synergy, polyphenolic bioactivity, and significantly low efficacy dose of GNRs@MPNs empower them satisfactory efficiency and biosafety in the future broad-spectrum photothermal sterilization applications.

Ti3C2Tx MXenes loaded with Au nanoparticle dimers as a surface-enhanced Raman scattering aptasensor for AFB1 detection

Mycotoxin B1 (AFB1) contamination in agricultural products pose a deadlydangertoanimal and human health and its rapid and reliable detection is thus very important. Herein, a ratiometric surface-enhanced Raman scattering (SERS) aptasensor for AFB1 detection was developed, in which 1,2-bis(4-pyridyl) ethylene (BPE) was used to trigger the assembly of Au nanoparticle dimers (AuNP dimers) and form intensive SERS "hot spots", and MXenes nanosheets could load aptamer-modified AuNP dimers due to the hydrogen bonding and the chelation between the phosphate groups of aptamers and the Ti ion of MXenes. With the presence of AFB1 preferentially binding to AFB1 aptamer, AuNP dimers were separated from MXenes nanosheets, leading to a decrease in SERS intensity. Regression analysis in the range from 0.001 to 100 ng·mL^-1 showed the limit of detection (LOD) being 0.6 pg·mL^-1 in standard solution, indicating that the great prospects of the AuNP dimers/MXenes SERS substrate for detecting AFB1.

Highly sensitive and selective rGO based Non-Enzymatic electrochemical sensor for propamocarb fungicide pesticide detection

In this study, reduced graphene oxide (rGO) was prepared using a green ultrasonic microwave assisted method and investigated rGO based non-enzymatic electrochemical sensor for detecting a synthetic fungicide as a propamocarb (PM) pesticide. The rGO-based sensor exhibited rapid response within 1 min, low detection limit of 0.6 μM and wide linear range of (1-5) μM with a high sensitivity of 101.1 μAμM^-1 cm^-2 for PM. Besides this, the sensor detected the propamocarb pesticide on the real cucumber sample with high sensitivity in the concentration range of (1-5) μM within a 1-minute cycle. The sensor is highly selective against propamocarb pesticide. The prepared non-enzymatic electrochemical sensor exhibited high sensitivity, high selectivity, reproducibility, and rapid response.

A portable smartphone-assisted ratiometric fluorescence sensor for intelligent and visual detection of malachite green

Developing intelligent, sensitive, and visual methods for rapidly detecting veterinary drug residues is essential for ensuring food quality and safety. A portable smartphone-assisted ratiometric fluorescent sensor was successfully designed using fluorescent Al-MOF nanosheet and rhodamine B (RhB) as fluorescent probes to adjust to the requirement of malachite green (MG) detection. The developed ratiometric fluorescent sensor allowed sensitive and selective detection of MG with good linear relationships in a wide range of 0.5-200 μg/mL. The Quantitative linearrange is 5.3 μg/mL to 200 μg/mL. The limit of detection (LOD) and limit of quantification (LOQ) were calculated to be 1.6 μg/mL and 5.3 μg/mL respectively. The practicability of the proposed method was verified using high performance liquid chromatography (HPLC) in spiked fish tissues with satisfying recoveries and RSD. Moreover, portable smartphone-assisted fluorescent test papers were fabricated for the intelligent detection of MG. This integration of smartphones and fluorescent test papers was economical and saved time, providing an alternative strategy for the qualitative discernment and semi-quantitative analysis of MG on-site.

Photothermal card reader assay using the commercial colloidal gold test strip for the rapid quantitative detection of food hazards

The simple and rapid commercial colloidal gold test strip can only be used for qualitative or semi-quantitative detection, accompanied by weak detectability and false negative experimental results. Herein, a photothermal test strip assay which combined test strip with a portable photothermal card reader was established to achieve quantitative detection with excellent detectability. According to the photothermal effect produced by gold nanoparticles (GNPs) captured on the test line, the signal could be recorded by the reader. Thirteen food hazards including veterinary drug residues and pesticide residues were tested; the photothermal detectability in actual samples were about 23 (methyl parathion), 7 (enrofloxacin), 6 (sarafloxacin), 8 (sulfadiazine), 12 (sulfamethazine), 7 (paraquat), 6 (malachite green), 11 (amantadine), 13 (nitrofurazone), 6 (diethylstilbestrol), 12 (estriol), 21 (estrone), and 26 (17β-estradiol) times better than the visual detectability. Our results demonstrated that the photothermal test strip assay could be used for sensitive, rapid, and quantitative detection of residues of food hazards.

Aerosol Dry Printing for SERS and Photoluminescence-Active Gold Nanostructures Preparation for Detection of Traces in Dye Mixtures

We proposed a novel method of nanostructure preparation for observation of surface-enhanced Raman spectroscopy (SERS) and metal-enhanced fluorescence (MEF) based on the deposition of gold nanoparticles (GNPs) above the thin dye film by dry aerosol printing. We detected various enhanced SERS and MEF signals of films of malachite green (MG) and rhodamine B (RhB) mixtures, depending on the surface packing density of Au NPs on the strip, and found the optimum one to achieve the 3.5 × 105 SERS enhancement. It was shown that statistical methods of chemometrics such as projection on latent structures provided the opportunity to distinguish SERS of MG from 100 ppm RhB in a mixture, whereas separation of MEF signals are feasible even for a mixture of MG and 1 ppm RhB due to two-photon excitation.

In-Situ Synthesis of Methyl Cellulose Film Decorated with Silver Nanoparticles as a Flexible Surface-Enhanced Raman Substrate for the Rapid Detection of Pesticide Residues in Fruits and Vegetables

The purpose of this study was to develop a flexible substrate methylcellulose-decorated silver nanoparticles (MC/Ag NPs) film and explore its application in fruits and vegetables by surface enhanced Raman spectroscopy (SERS) technology for rapid detection of pesticides. The performance of the MC/Ag NPs film substrate was characterized by Nile blue A (NBA), and the detection limit was as low as 10⁻⁸ M. The substrate also exhibited satisfactory Raman signal strength after two months of storage. The impressive sensitivity and stability were due to the excellent homogeneity of the silver nanoparticles that were grown in situ in the methylcellulose matrix, which generated “hot spots” between the silver nanoparticles without a large amount of aggregation, and resulted in the ultra-high sensitivity and excellent stability of the MC/Ag NPs film substrate. The MC/Ag NPs film substrate was used to detect thiram pesticides on tomato and cucumber peels, and the minimum detectable level of thiram was 2.4 ng/cm², which was much lower than the maximum residue level. These results indicate that the MC/Ag NPs film is sensitive to rapid detection of multiple pesticides in food.

Macroscopical monolayer films of ordered arrays of gold nanoparticles as SERS substrates for in situ quantitative detection in aqueous solutions

In this work, macroscopical monolayer films of ordered arrays of gold nanoparticles (MMF-OA-Au NPs) are successfully prepared at the interfaces of toluene-diethylene glycol (DEG) with a water volume fraction of 10% (no more than 25%), which can greatly reduce the electrostatic repulsion among NPs during the self-assembly due to the quick transfer of the remaining citrate ions into the DEG solutions containing water. Thanks to the uniformity in the intensity of SERS signals, the as-prepared MMF-OA-Au NPs transferred onto polydimethylsiloxane (PDMS) as SERS substrates (MMF-OA-Au NP@PDMS) can achieve in situ quantitative detection of the analytes (such as crystal violet and malachite green) in aqueous solutions. Moreover, MMF-OA-Au NP@PDMS as SERS-based pH sensors can directly determine the pH value of the aqueous solution in the range of 3 to 10 by means of the established well-defined linear relationship with the intensity of the peak of νCOO^- without any calibration, instead of the intensity ratio of the Raman peaks of νCOO^- to ν8a with further calculation. In addition, the as-prepared SERS-based pH sensors can still have excellent long-term durability.

SERS diagnosis of liver fibrosis in the early stage based on gold nanostar liver targeting tags

In order to realize the accurate and early diagnosis of liver fibrosis, a long slow pathological process which may lead to cirrhosis or even liver cancer, liver targeting tags made up of gold nanostars and glycyrrhetinic acid are reported in this paper. Gold nanostars (GNSs) and GNS liver targeting tags (GLTTs) were injected into model mice with stage S1 liver fibrosis and normal mice via the tail vein respectively, then the SERS spectra were collected. GLTTs had a better detection effect on liver tissue than unmodified GNSs (12.85 times), and better detection reproducibility as well. Moreover, according to the MTT and survival analysis experiments, GLTTs also had better biocompatibility. Hence, the changes of 10 SERS signals and other substances in the early stage of liver fibrosis were analyzed at the molecular level, and the SERS characteristic peaks that could be used for the diagnosis of early liver fibrosis were screened out. Revealed by the experimental results, the GLTTs designed and prepared were applicable to the efficient SERS detection of early liver fibrosis in mice, and the strategy we have proposed might be a potential approach for the early diagnosis of this disease in clinics.

Recent developments in Raman spectral analysis of microbial single cells: Techniques and applications

The conventional microbial cell analyses are mostly population-averaged methods that conceal the characteristics of single-cell in the community. Single-cell analysis can provide information on the functional and structural variation of each cell, resulting in the elimination of long and tedious microbial cultivation techniques. Raman spectroscopy is a label-free, noninvasive, and in-vivo method ideal for single-cell measurement to obtain spatially resolved chemical information. In the current review, recent developments in Raman spectroscopic techniques for microbial characterization at the single-cell level are presented, focusing on Raman imaging of single cells to study the intracellular distribution of different components. The review also discusses the limitation and challenges of each technique and put forward some future outlook for improving Raman spectroscopy-based techniques for single-cell analysis. Raman spectroscopic methods at the single-cell level have potential in precision measurements, metabolic analysis, antibiotic susceptibility testing, resuscitation capability, and correlating phenotypic information to genomics for cells, the integration of Raman spectroscopy with other techniques such as microfluidics, stable isotope probing (SIP), and atomic force microscope can further improve the resolution and provide extensive information. Future focuses should be given to advance algorithms for data analysis, standardized reference libraries, and automated cell isolation techniques in future.