Reproducible E. coli detection based on label-free SERS and mapping

On-Chip Capture, Raman-Silent Polymer Labeling, and Digital Mapping Analysis of Escherichia coli O157:H7 in Beverages All-in-One

Escherichia coli O157:H7 is one of the most susceptible foodborne pathogens, easily causing food poisoning and other health risks. It is of great significance to establish a quantitative method with higher sensitivity and less time consumption for foodborne pathogens analysis. The Raman-silent signal has a good performance for avoiding interference from the food matrix so as to achieve accurate signal differentiation. In this work, we presented a preparation-mapping all-in-one method for digital mapping analysis. We prepared a functionalized Raman-silent polymer label of Escherichia coli O157:H7, which was captured on a porous 4-mercaptophenylboric acid@Ag foam chip. To improve accuracy and widen the detection range, a digital mapping quantitative strategy was employed in data extraction and processing. By transfer mapping information into digitized statistical results, the limitation of obtaining reproducible intensity values just by randomly selected spots on the substrate can be addressed. With a wide linear range of 1.0 × 101-1.0 × 105 CFU mL-1 and a limit of detection of 4.4 CFU mL-1, this all-in-one method had good sensitivity performance. Also, this method achieved good precision and selectivity in a series of experiments and was successfully applied to the analysis of beverage samples.

A sandwich-structured multifunctional platform based on self-assembled Ti3C2Tx@Au NPs films, antibiotics, and silent region SERS probe for the capture, determination, and drug resistance analysis of Gram-positive bacteria

A multifunctional surface-enhanced Raman scattering (SERS) platform integrating sensitive detection and drug resistance analysis was developed for Gram-positive bacteria. The substrate was based on self-assembled Ti3C2Tx@Au NPs films and capture molecule phytic acid (IP6) to achieve specific capture of Gram-positive bacteria and different bacteria were analyzed by fingerprint signal. It had advantages of good stability and homogeneity (RSD = 8.88%). The detection limit (LOD) was 102 CFU/mL for Staphylococcus aureus and 103 CFU/mL for MRSA, respectively. A sandwich structure was formed on the capture substrate by signal labels prepared by antibiotics (penicillin G and vancomycin) and non-interference SERS probe molecules (4-mercaptobenzonitrile (2223 cm-1) and 2-amino-4-cyanopyridine (2240 cm-1)) to improve sensitivity. The LOD of Au NPs@4-MBN@PG to S. aureus and Au NPs@AMCP@Van to MRSA and S. aureus were all improved to 10 CFU/mL, with a wide dynamic linear range from 108 to 10 CFU/mL (R2 ≥ 0.992). The SERS platform can analyze the drug resistance of drug-resistant bacteria. Au NPs@4-MBN@PG was added to the substrate and captured MRSA to compare the SERS spectra of 4-MBN. The intensity inhomogeneity of 4-MBN at the same concentrations of MRSA and the nonlinearity at the different concentrations of MRSA revealed that MRSA was resistant to PG. Finally, the SERS platform achieved the determination of MRSA in blood. Therefore, this SERS platform has great significance for the determination and analysis of Gram-positive bacteria.

Surface-enhanced Raman spectroscopy for comparison of biochemical profile of bacteriophage sensitive and resistant methicillin-resistant Staphylococcus aureus (MRSA) strains

Methicillin-resistant Staphylococcus aureus (MRSA) is gram positive bacteria and leading cause of a wide variety of diseases. It is a common cause of hospitalized and community-acquired infections. Development of increasing antibiotic-resistance by methicillin-resistant S. aureus (MRSA) strains demand to develop alternate novel therapies. Bacteriophages are now widely used as antibacterial therapies against antibiotic-resistant gram-positive pathogens. So, there is an urgent need to find fast detection techniques to point out phage susceptible and resistant strains of methicillin-resistant S. aureus (MRSA) bacteria. Samples of two separate strains of bacteria, S. aureus, in form of pellets and supernatant, were used for this purpose. Strain-I was resistant to phage, while the other (strain-II) was sensitive. Surface Enhanced Raman Spectroscopy (SERS) has detected significant biochemical changes in these bacterial strains of pellets and supernatants in the form of SERS spectral features. The protein portion of these two types of strains of methicillin-resistant S. aureus (MRSA) in their relevant pellets and supernatants is major distinguishing biomolecule as shown by their representative SERS spectral features. In addition, multivariate data analysis techniques such as principal component analysis (PCA) and a partial least squares-discriminant analysis (PLS-DA) were found to be helpful in identifying and characterizing various strains of S. aureus which are sensitive and resistant to bacteriophage with 100% specificity, 100% accuracy, and 99.8% sensitivity in case of SERS spectral data sets of bacterial cell pellets. Moreover, in case of supernatant samples, the results of PLS-DA model including 95.5% specificity, 96% sensitivity, and 96.5% accuracy are obtained.

Novel Digital SERS-Microfluidic Chip for Rapid and Accurate Quantification of Microorganisms

In this work, we present a simple and novel digital surface-enhanced Raman spectroscopy (SERS)-microfluidic chip designed for the rapid and accurate quantitative detection of microorganisms. The chip employs a high-density inverted pyramid microcavity (IPM) array to separate and isolate microbial samples. The presence or absence of target microorganisms is determined by scanning the IPM array using SERS and identifying the characteristic Raman bands. This approach allows for the "digitization" of the SERS response of each IPM, enabling quantification through the application of mathematical statistical techniques. Significantly, precise quantitative detection of yeast was achieved within a concentration range of 106-109 cells/mL, with the maximum relative standard deviation from the concentration calibrated by the cultivation method being 5.6%. This innovative approach efficiently addresses the issue of irregularities in SERS quantitative detection, which arises due to fluctuations in SERS intensity and poor reproducibility. We strongly believe that this digital SERS-microfluidic chip holds immense potential for diverse applications in the rapid detection of various microorganisms, including pathogenic bacteria and viruses.

FPBA-modified magnetic nanoparticles combined with Au@AgNPs for label-free SERS detection of foodborne pathogens in milk

We report a low-cost and highly sensitive label-free SERS biosensor for pathogen detection. Herein, this study prepared 4-formylphenylboric acid (FPBA) functionalized magnetic nanoparticles to adsorb pathogenic bacteria through boric acid affinity principle, and used aptamer modified Au@AgNPs as SERS substrate to specifically combine with pathogenic bacteria to form a sandwich structure. The pathogenic bacteria were detected by portable Raman spectrometer for SERS detection, and the fingerprint signals of pathogenic bacteria were analyzed by principal component analysis (PCA) to achieve the purpose of classification and identification of pathogenic bacteria. Under the optimized conditions, the SERS detection of Staphylococcus aureus (S. aureus) was 102 ∼ 106 CFU/mL (R2 = 0.9925), and the limit of detection (LOD) was 34 CFU/mL. The linear range of Escherichia coli (E. coli) showed a good linear relationship in the range of 102 ∼ 106 CFU/mL (R2 = 0.9993), and the LOD was 18 CFU/mL. The whole detection process was used the portable Raman spectrometer, which makes it suitable for the application of point-of-care testing (POCT).

Surface Functionalization and Escherichia coli Detection Using Surface-Enhanced Raman Spectroscopy Driven by Functional Organic Polymer/Gold Nanofilm-Based Microfluidic Chip

In this work, a microfluidic prototype based on polymeric materials was developed to monitor surface processes using surface-enhanced Raman spectroscopy (SERS), keeping the reagents free of environmental contamination. The prototype was fabricated on poly(methyl methacrylic acid) (PMMA). A micrometric membrane of a functional organic polymer (FOP) based on p-terphenyl and bromopyruvic acid monomers was formed on the PMMA surface to promote the formation of metal nanoclusters. Au nanosized film was deposited on the FOP membrane to give rise to the SERS effect. A microchannel was formed on another piece of PMMA using micromachining. A representative 3D model of the prototype layer arrangement was built and simulated in COMSOL Multiphysics® to approximate the electric field distribution and calculate the power enhancement factor as the Au film changes over time. The fabrication process was characterized using UV-visible and Raman spectroscopies and XPS. The prototype was tested using a Raman microscope and liquid solutions of cysteamine and Escherichia coli (E. coli). The simulation results demonstrated that the morphological characteristics of the Au layer give rise to the SERS effect, and the power enhancement factor reaches values as high as 8.8 × 105 on the FOP surface. The characterization results showed the formation of the FOP and the Au film on PMMA and the surface functionalization with amine groups. The Raman spectra of the prototype showed temporal evolution as different compounds were deposited on the upper wall of the microchannel. Characteristic peaks associated with these compounds were detected with continuous monitoring over time. This prototype offers many benefits for applications like monitoring biological processes. Some advantages include timely surface evaluation while avoiding environmental harm, decreased use of reagents and samples, minimal interference with the process by measuring, and detecting microorganisms in just 1 h, as demonstrated with the E. coli sample.

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical method that can provide fingerprint-like chemical information at the single-molecule level. Here, the advanced one-dimensional convolutional neural network (1D-CNN) approach was applied to accurately identify the SERS spectral signature of industrial wastewaters for source tracing. A total of 66,000 SERS spectra were acquired from wastewaters of 22 factories across 10 industrial categories at three excitation wavelengths after data augmentation. The dataset was used to train a 1D-CNN model consisting of three convolutional layers to achieve adequate feature extraction of SERS spectra. As a proof-of-concept, multimixed wastewater samples were used to simulate practical pollution scenarios and evaluate the application potential of the model. The SERS-1D-CNN platform can identify the amount and factory information of wastewaters in multimixed samples, which achieves a recognition accuracy rate of 97.33%. The results suggest that even in a complex and unknown water environment, the 1D-CNN model can accurately identify industrial wastewaters in precollected datasets, exhibiting excellent potential in pollution source tracing.

Investigation of the Influence of Stress on Label-Free Bacterial Surface-Enhanced Raman Spectra

Label-free surface-enhanced Raman spectroscopy (SERS) has been proposed as a promising bacterial detection technique. However, the quality of the collected bacterial spectra can be affected by the time between sample acquisition and the SERS measurement. This study evaluated how storage stress stimuli influence the label-free SERS spectra of Pseudomonas syringae samples stored in phosphate buffered saline. The results indicate that when faced with nutrient limitations and changes in osmatic pressure, samples at room temperature (25 °C) exhibit more significant spectral changes than those stored at cold temperature (4 °C). At higher temperatures, bacterial communities secrete extracellular biomolecules that induce programmed cell death and result in increases in the supernatant SERS signals. Surviving cells consume cellular components to support their metabolism, thus leading to measurable declines in cell SERS intensity. Two-dimensional correlation spectroscopy analysis suggests that cellular component signatures decline sequentially in the following order: proteins, nucleic acids, and lipids. Extracellular nucleic acids, proteins, and carbohydrates are secreted in turn. After subtracting the SERS changes resulting from storage, we evaluated bacterial response to viral infection. P. syringae SERS profile changes enable accurate bacteriophage Phi6 quantification over the range of 10⁴-10¹⁰ PFU/mL. The results indicate that storage conditions impact bacterial label-free SERS signals and that such influences need to be accounted for and if possible avoided when detecting bacteria or evaluating bacterial response to stress stimuli.

Plasmonic Bridge Sensor Enabled by Carbon Nanotubes and Au-Ag Nano-Rambutan for Multifunctional Detection of Biomechanics and Bio/Chemical Molecules

Wearable, noninvasive, and simultaneous sensing of subtle strains and eccrine molecules on human body is essential for future health monitoring and personalized medicine. However, there is a huge chasm between biomechanics and bio/chemical molecule detections. Here, a wearable plasmonic bridge sensor with multiple abilities to monitor subtle strains and molecules is developed. Hollow Au-Ag nano-rambutans and carbon nanotubes (CNTs) are adsorbed in the nonwoven fabrics (NWFs) conjointly, where the gap between the conducting network of CNTs is bridged by the Au-Ag nano-rambutans during the subtle strain sensing, and the detection sensitivity for stress is improved at least 1 order of magnitude compared to that with the only CNTs. In order to acquire the accurate human action recognition, a machine learning algorithm (support vector machines) based on output biomechanics data is designed. The average accuracy of our plasmonic bridge sensor reaches 89.0% for human action recognition. Moreover, due to the hollow structure and high nanoroughness, the single Au-Ag nano-rambutan particle has strong localized surface plasmon resonance effect and high surface-enhanced Raman scattering (SERS) activity. Based on their unique SERS spectra introduced by the hollow Au-Ag nano-rambutan adsorbed in the NWFs, noninvasive extraction and "fingerprint" recognition of bio/chemical molecules could be realized during the wearable sensing. In sum, the NWFs/CNTs/Au-Ag sensor bridges the barrier between the bodily strain detection and molecule recognition during the wearable sensing. Such integrated and multifunctional sensing strategy for universal biomechanics and bio/chemical molecules means to assess human health to be of importance.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

Study on direct identification of bacteria by laser-induced breakdown spectroscopy

Bacteria are everywhere in the natural environment. Although most of them are harmless, there are still some hazardous bacteria that will harm human health, so it is particularly important to identify bacteria quickly. Compared with traditional time-consuming and complicated identification methods, laser-induced breakdown spectroscopy (LIBS) is one of the potential technologies for rapid identification of bacteria. In this paper, six weakly active bacteria, including Escherichia coli, Enterococcus faecalis, Bacillus megaterium, Bacillus thuringiensis, Pseudomonas aeruginosa and Bacillus subtilis, are taken as analysis samples. The thawed bacteria are placed in deionized water, and then uniformly smeared on five kinds of substrates to verify the feasibility of using LIBS to identify these bacteria. Spectrum filtering, normalization and principal component analysis (PCA) are used to preprocess the spectra, and a multi-class identification method based on the one-against-all linear kernel function of support vector machine (SVM) is proposed to establish the prediction model. The identification performance is evaluated by using precision and recall. The experimental results show that high-purity graphite is the best substrate with the least interference to the LIBS spectrum of bacteria. The prediction precision of these six bacteria is 77.27%, 92.86%, 84.21%, 94.12%, 81.82% and 76.92%, respectively, recall is 85%, 100%, 94.12%, 80%, 81.82% and 75% respectively, and the identification rate is 84.17%. It can be seen that the direct identification of bacteria can be preliminarily realized by smearing bacteria on the graphite substrate and analyzing its LIBS spectra, which provides a feasible way for simple, rapid and on-site bacterial identification.

Surface-enhanced Raman spectroscopy for characterization of filtrate portions of blood serum samples of typhoid patients

BACKGROUND

Surface-enhanced Raman spectroscopy (SERS) is explored to design a rapid screening method for the characterization and diagnosis of typhoid fever by employing filtrate fractions of blood serum samples obtained by centrifugal filtration with 50 KDa filters.

OBJECTIVES

The purpose of this study, to separate the filtrate portions of blood serum samples in this way contain proteins smaller than 50 kDa and removal of bigger size protein which allows to acquire the SERS spectral features of smaller proteins more effectively which are probably associated with typhoid disease. Disease caused by Salmonella typhi diagnose more effectively by using surface-enhanced Raman spectroscopy (SERS) and multivariate data analysis tools.

METHODS

SERS was used as a diagnostic tool for typhoid fever by comparison between healthy and diseased samples. For this purpose, all the samples were analyzed by comparing their SERS spectral features. Over the spectral range of 400-1800cm^-1, multivariate data analysis techniques such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) are applied to diagnose and differentiate different filtrate fractions of blood serum samples of patients of typhoid fever and healthy ones.

RESULTS

By comparing SERS spectra of healthy filtrate with that of filtrate of typhoid sample, the SERS spectral features associated with disease development are identified including PCA is found to be efficient for the qualitative differentiation of all of the samples analyzed. Moreover, PLS-DA successfully identified and classified healthy and typhoid positive blood serum samples with 97 % accuracy, 99 % specificity, 91 % sensitivity and 0.78 area under the receiver operating characteristic (AUROC) curve.

CONCLUSIONS

Surface enhanced Raman spectroscopy using silver nanoparticles SERS substrate, is found to be useful technique for the quick identification and evaluation of filtrate fractions of the blood serum samples of healthy and typhoid samples for disease diagnosis.

Application of SERS in the Detection of Fungi, Bacteria and Viruses

In this review, we report the recent advances of SERS in fungi, bacteria, and viruses. Firstly, we briefly introduce the advantage of SERS over fluorescence on virus identification and detection. Secondly, we review the feasibility analysis of Raman/SERS spectrum analysis, identification, and fungal detection on SERS substrates of various nanostructures with a signal amplification mechanism. Thirdly, we focus on SERS spectra for nucleic acid, pathogens for the detection of viruses and bacteria, and furthermore introduce SERS-based microdevices, including SERS-based microfluidic devices, and three-dimensional nanostructured plasmonic substrates.

Escherichia coli Enumeration in a Capillary-Driven Microfluidic Chip with SERS

Pathogen detection is still a challenging issue for public health, especially in food products. A selective preconcentration step is also necessary if the target pathogen concentration is very low or if the sample volume is limited in the analysis. Plate counting (24–48 h) methods should be replaced by novel biosensor systems as an alternative reliable pathogen detection technique. The usage of a capillary-driven microfluidic chip is an alternative method for pathogen detection, with the combination of surface-enhanced Raman scattering (SERS) measurements. Here, we constructed microchambers with capillary microchannels to provide nanoparticle–pathogen transportation from one chamber to the other. Escherichia coli (E. coli) was selected as a model pathogen and specific antibody-modified magnetic nanoparticles (MNPs) as a capture probe in a complex milk matrix. MNPs that captured E. coli were transferred in a capillary-driven microfluidic chip consisting of four chambers, and 4-aminothiophenol (4-ATP)-labelled gold nanorods (Au NRs) were used as the Raman probe in the capillary-driven microfluidic chip. The MNPs provided immunomagnetic (IMS) separation and preconcentration of analytes from the sample matrix and then, 4-ATP-labelled Au NRs provided an SERS response by forming sandwich immunoassay structures in the last chamber of the capillary-driven microfluidic chip. The developed SERS-based method could detect 10¹–10⁷ cfu/mL of E. coli with the total analysis time of less than 60 min. Selectivity of the developed method was also tested by using Salmonella enteritidis (S. enteritidis) and Staphylococcus aureus (S. aureus) as analytes, and very weak signals were observed.

Specific and quantitative detection of bacteria based on surface cell imprinted SERS mapping platform

Non-specificity and poor quantitative ability are the main challenges in surface-enhanced Raman scattering (SERS) technique, especially for the detection of bacteria in real samples. In this study, we presented a surface cell imprinted SERS mapping platform which is competent for the specific and quantitative detection of bacteria. The platform based on the fabrication of a surface cell imprinted substrate (SCIS) by which Escherichia coli (E. coli) can be captured and labelled by SERS tags which produces strong characteristic signal to indicate the capture of targets. We highlighted the specificity of this platform in the detection of E. coli, by comparing the performances toward Salmonella paratyphoid A, Bacillus subtilis, Enterococcus faecalis and Staphylococcus aureus. Upon integrating with SERS mapping technique, the platform displayed good quantitative ability toward E. coli with a wide linear range from 10² to 10⁸ CFU/mL and a low detection limit of ∼1.35 CFU/mL. Moreover, this novel SERS analysis platform was proved to be effective for E. coli detection in real probiotic beverage and chicken breast meat samples. By fabricating different SCISs, this platform can be replicated for the detection of other bacteria, which provides a promising application for real sample testing.

Preparation of an AgNPs@Polydimethylsiloxane (PDMS) multi-hole filter membrane chip for the rapid identification of food-borne pathogens by surface-enhanced Raman spectroscopy

The consumption of food infected with food-borne pathogens has become a global public health problem. Therefore, it is monitor food-borne infections to avoid health and financial consequences. The rapid detection and differentiation of bacteria for biomedical and food safety applications continues to be a significant challenge. Herein, we present a label-free surface-enhanced Raman scattering approach for separating harmful bacteria from food. The method relies on the ascorbic acid reduction method to synthesize silver nanoparticles (AgNPs) and a polydimethylsiloxane (PDMS) multi-hole filter membrane chip (AgNPs@PDMS multi-hole filter membrane chip). Surface-enhanced Raman spectroscopy (SERS) was used, followed by multivariate statistical analysis to differentiate five important food-borne pathogens, including Staphylococcus aureus, Salmonella typhimurium, Listeria monocytogenes, Clostridium difficiles and Clostridium perfringens. The results demonstrated that compared to normal Raman signals, the intensity of the SERS signal was greatly enhanced with an analytical enhancement factor of 5.2 × 10³. The spectral ranges of 400-1800 cm^-1 were analyzed using principal component analysis (PCA) and stepwise linear discriminant analysis (SWLDA) were used to determine the optimal parameters for the discrimination of food-borne pathogens. The first three principal components (PC1, PC2, and PC3) accounted for 87.3% of the total variance in the spectra. The established SWLDA model had 100% accuracy and cross-validation accuracy, which accurately distinguished the SERS spectra of the five species. In conclusion, the SERS technology based on the AgNPs@PDMS multi-hole filter membrane chip was useful for the rapid identification of food-borne pathogens and can be employed for food quality management.

A 3D-ACEK/SERS system for highly efficient and selectable electrokinetic bacteria concentration/detection/ antibiotic-susceptibility-test on whole blood

This study demonstrates a novel multi-functional microfluidic system, designated three dimensional Alternative Current Electrokinetic/Surface Enhanced Raman Scattering (3D-ACEK/SERS), which can concentrate bacteria from whole blood, identify bacterial species, and determine antibiotic susceptibilities of the bacteria rapidly. The system consists of a hybrid electrokinetic mechanism, integrating AC-electroosmosis (AC-EO) and dielectrophoresis (DEP) that allows thousand-fold concentration of bacteria, including S. aureus, Escherichia coli, and Chryseobacterium indologenes, in the center of an electrode with a wide range of working distance (hundreds to thousands of μm), while exclusion of blood cells through negative DEP forces. This microchip employs SERS assay to determine the identity of the concentrated bacteria in approximately 2 min with a limit of detection of 3 CFU/ml, 5 orders of magnitude lower than that using standard centrifugation-purification process. Finally, label-free antibiotic susceptibility testing has been successfully demonstrated on the platform using both antibiotic-sensitive and multidrug-resistant bacterial strains illustrating a potential utility of the system to clinical applications.

Recent advances in antibiotic resistance diagnosis using SERS: focus on the “Big 5” challenges

SERS for antibiotic resistance diagnosis.

Attomolar analyte sensing techniques (AttoSens): a review on a decade of progress on chemical and biosensing nanoplatforms

Detecting the ultra-low abundance of analytes in real-life samples, such as biological fluids, water, soil, and food, requires the design and development of high-performance biosensing modalities. The breakthrough efforts from the scientific community have led to the realization of sensing technologies that measure the analyte's ultra-trace level, with relevant sensitivity, selectivity, response time, and sampling efficiency, referred to as Attomolar Analyte Sensing Techniques (AttoSens) in this review. In an AttoSens platform, 1 aM detection corresponds to the quantification of 60 target analyte molecules in 100 μL of sample volume. Herein, we review the approaches listed for various sensor probe design, and their sensing strategies that paved the way for the detection of attomolar (aM: 10^-18 M) concentration of analytes. A summary of the technological advances made by the diverse AttoSens trends from the past decade is presented.

Surface-enhanced Raman spectroscopy for the identification of tigecycline-resistant E. coli strains

Tigecycline (TGC) is recognised as last resort of drugs against several antibiotic-resistant bacteria. Bacterial resistance to tigecycline due to presence of plasmid-mediated mobile TGC resistance genes (tet X3/X4) has broken another defense line. Therefore, rapid and reproducible detection of tigecycline-resistant E. coli (TREC) is required. The current study is designed for the identification and differentiation of TREC from tigecycline-sensitive E. coli (TSEC) by employing SERS by using Ag NPs as a SERS substrate. The SERS spectral fingerprints of E. coli strains associated directly or indirectly with the development of resistance against tigecycline have been distinguished by comparing SERS spectral data of TSEC strains with each TREC strain. Moreover, the statistical analysis including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were employed to check the diagnostic potential of SERS for the differentiation among TREC and TSEC strains. The qualitative identification and differentiation between resistant and sensitive strains and among individual strains have been efficiently done by performing both PCA and HCA. The successful discrimination among TREC and TSEC at the strain level is performed by PLS-DA with 98% area under ROC curve, 100% sensitivity, 98.7% specificity and 100% accuracy.

Nanomaterial application in bio/sensors for the detection of infectious diseases

Infectious diseases are a potential risk for public health and the global economy. Fast and accurate detection of the pathogens that cause these infections is important to avoid the transmission of the diseases. Conventional methods for the detection of these microorganisms are time-consuming, costly, and not applicable for on-site monitoring. Biosensors can provide a fast, reliable, and point of care diagnostic. Nanomaterials, due to their outstanding electrical, chemical, and optical features, have become key players in the area of biosensors. This review will cover different nanomaterials that employed in electrochemical, optical, and instrumental biosensors for infectious disease diagnosis and how these contributed to enhancing the sensitivity and rapidity of the various sensing platforms. Examples of nanomaterial synthesis methods as well as a comprehensive description of their properties are explained. Moreover, when available, comparative data, in the presence and absence of the nanomaterials, have been reported to further highlight how the usage of nanomaterials enhances the performances of the sensor.

Fuzzy characterization and classification of bacteria species detected at single-cell level by surface-enhanced Raman scattering

Advanced chemometric methods, such as fuzzy c-means, a semi-supervised clustering method, and fuzzy linear discriminant analysis (FLDA), a new robust supervised classification method in combination with principal component analysis (PCA), namely PCA-FLDA, have been successfully applied for characterization and classification of bacterial species detected at single-cell level by surface-enhanced Raman scattering (SERS) spectroscopy. SERS spectra of three species (S. aureus, E. faecalis and P. aeruginosa) were recorded in an original fashion, using in situ laser induced silver spot as metallic substrate. The detection process of bacteria was isolated inside a hermetically sealed in-house built microfluidic device, connected to a syringe pump for injecting the analytes and a portable Raman spectrometer as detection tool. The obtained results (fuzzy partitions) and spectra of the prototypes (robust fuzzy spectra mean corresponding to each fuzzy partition) clearly demonstrated the efficiency and information power of the advanced fuzzy methods in bacteria characterization and classification based on SERS spectra, and allowed a rationale assigning to a specific group. Also, this powerful detection and classification methodology generates the premises for future investigations of Raman and other spectroscopic data obtained for various samples.

Towards a point-of-care SERS sensor for biomedical and agri-food analysis applications: a review of recent advancements

The growing demand for reliable and robust methodology in bio-chemical sensing calls for the continuous advancement of sensor technologies. Over the last two decades, surface-enhanced Raman spectroscopy (SERS) has emerged as one of the most promising analytical techniques for sensitive and trace analysis or detection in biomedical and agri-food applications. SERS overcomes the inherent sensitivity limitation associated with Raman spectroscopy, which provides vibrational "fingerprint" spectra of molecules that makes it unique and versatile among other spectroscopy techniques. This paper comprehensively reviews the recent advancements of SERS for biomedical, food and agricultural applications over the last 6 years, and we envision that, in the near future, some of these platforms have the potential to be translated as a point-of-care and rapid sensor for real-life end-user applications. The merits and limitations of various SERS sensor designs are analysed and discussed based on critical features such as sensitivity, specificity, usability, repeatability and reproducibility. We conclude by highlighting the opportunities and challenges in the field while stressing the technological gaps to be addressed in realizing commercially viable point-of-care SERS sensors for practical biomedical and agri-food technological applications.

Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques

The rapid, highly sensitive, and accurate detection of bacteria is the focus of various fields, especially food safety and public health. Surface-enhanced Raman spectroscopy (SERS), with the advantages of being fast, sensitive, and nondestructive, can be used to directly obtain molecular fingerprint information, as well as for the on-line qualitative analysis of multicomponent samples. It has therefore become an effective technique for bacterial detection. Within this progress report, advances in the detection of bacteria using SERS and other compatible techniques are discussed in order to summarize its development in recent years. First, the enhancement principle and mechanism of SERS technology are briefly overviewed. The second part is devoted to a label-free strategy for the detection of bacterial cells and bacterial metabolites. In this section, important considerations that must be made to improve bacterial SERS signals are discussed. Then, the label-based SERS strategy involves the design strategy of SERS tags, the immunomagnetic separation of SERS tags, and the capture of bacteria from solution and dye-labeled SERS primers. In the third part, several novel SERS compatible technologies and applications in clinical and food safety are introduced. In the final part, the results achieved are summarized and future perspectives are proposed.

Improvement of Surface-Enhanced Raman Scattering Method for Single Bacterial Cell Analysis

Surface-enhanced Raman scattering (SERS) is a useful tool for label-free analysis of bacteria at the single cell level. However, low reproducibility limits the use of SERS. In this study, for the sake of sensitive and reproducible Raman spectra, we optimized the methods for preparing silver nanoparticles (AgNPs) and depositing AgNPs onto a cell surface. We found that fast dropwise addition of AgNO₃ into the reductant produced smaller and more stable AgNPs, with an average diameter of 45 ± 4 nm. Compared with that observed after simply mixing the bacterial cells with AgNPs, the SERS signal was significantly improved after centrifugation. To optimize the SERS enhancement method, the centrifugal force, method for preparing AgNPs, concentration of AgNPs, ionic strength of the solution used to suspend the cells, and density of the cells were chosen as impact factors and optimized through orthogonal experiments. Finally, the improved method could generate sensitive and reproducible SERS spectra from single Escherichia coli cells, and the SERS signals primarily arose from the cell envelope. We further verified that this optimal method was feasible for the detection of low to 25% incorporation of ¹³C isotopes by the cells and the discrimination of different bacterial species. Our work provides an improved method for generating sensitive and reproducible SERS spectra.

Ta@Ag Porous Array with High Stability and Biocompatibility for SERS Sensing of Bacteria

The reliable sensing of bacteria by surface-enhanced Raman scattering (SERS) technology necessitates a rational design of a substrate with high sensitivity, stability, and minimal invasion. Hence, a bimetallic Ta@Ag film with a porous array is developed by the magnetron sputtering technique and the structure could be controlled by a Ta dopant. A porous array connected by ligaments with compact granular nanoprotrusions is a fascinating substrate for SERS sensing. It makes steady SERS signals even in harsh chemical environments due to its high structural and chemical stability. The configuration of binary Ta@Ag has higher surface free energy than that of pure Ag, and the strong bactericidal activity of Ag is suppressed efficiently. Using E. coli as a model pathogen, the Ta@Ag porous film could maintain the long-term survival rate of E. coli up to 95% and a limit of SERS detection of E. coli down to 10² CFU/mL, which is measured by the standard colony-counting method. In sum, this work provides a promising strategy to fabricate a corrosion-resistant and biocompatible bimetallic Ta@Ag film with a porous array for the SERS sensing of microbial cells.

Reproducible and Bendable SERS Substrates with Tailored Wettability Using Block Copolymers and Anodic Aluminum Oxide Templates

Surface properties are essential for substrates exhibiting high sensitivity in surface-enhanced Raman scattering (SERS) applications. In this work, novel SERS hybrid substrates using polystyrene-block-poly(methyl methacrylate) and anodic aluminum oxide templates is presented. The hybrid substrates not only possess hierarchical porous nanostructures but also exhibit superhydrophilic surface properties with the water contact angle ≈0°. Such surfaces play an important role in providing uniform enhanced intensities over large areas (relative standard deviation ≈10%); moreover, these substrates are found to be highly sensitive (limit of detection ≈10^-12 m for rhodamine 6G (R6G)). The results show that the hybrid SERS substrates can achieve the simultaneous detection of multicomponent mixtures of different target molecules, such as R6G, crystal violet, and methylene blue. Furthermore, the bending experiments show that about 70% of the SERS intensities are maintained after bending from ≈30° to 150°.

Rapid detection of bacterial infection and viability assessment with high specificity and sensitivity using Raman microspectroscopy

Infectious diseases caused by bacteria still pose major diagnostic challenges in spite of the availability of various molecular approaches. Irrespective of the type of infection, rapid identification of the causative pathogen with a high degree of sensitivity and specificity is essential for initiating appropriate treatment. While existing methods like PCR possess high sensitivity, they are incapable of identifying the viability status of the pathogen and those which can, like culturing, are inherently slow. To overcome these limitations, we developed a diagnostic platform based on Raman microspectroscopy, capable of detecting biochemical signatures from a single bacterium for identification as well as viability assessment. The study also establishes a decontamination protocol for handling live pathogenic bacteria which does not affect identification and viability testing, showing applicability in the analysis of sputum samples containing pathogenic mycobacterial strains. The minimal sample processing along with multivariate analysis of spectroscopic signatures provides an interface for automatic classification, allowing the prediction of unknown samples by mapping signatures onto available datasets. Also, the novelty of the current work is the demonstration of simultaneous identification and viability assessment at a single bacterial level for pathogenic bacteria. Graphical abstract.

Functional Nanomaterials for the Detection and Control of Bacterial Infections

Infections with multidrug-resistant bacteria that are difficult to treat with commonly used antibiotics have spread globally, raising serious public health concerns. Conventional bacterial detection techniques are time-consuming, which may delay treatment for critically ill patients past the optimal time. There is an urgent need for rapid and sensitive diagnosis and effective treatments for multidrug-resistant pathogenic bacterial infections. Advances in nanotechnology have made it possible to design and build nanomaterials with therapeutic and diagnostic capabilities. Functional nanomaterials that can specifically interact with bacteria offer additional options for the diagnosis and treatment of infections due to their unique physical and chemical properties. Here, we summarize the recent advances related to the preparation of nanomaterials and their applications for the detection and treatment of bacterial infection. We pay particular attention to the toxicity of therapeutic nanoparticles based on both in vitro and in vivo assays. In addition, the major challenges that require further research and future perspectives are briefly discussed.

Surface plasmon resonance based biomimetic sensor for urinary tract infections

Tailor-made Escherichia coli (E. coli) receptors were created with microcontact imprinted technique and binding events of E. coli were carried out by a surface plasmon resonance (SPR) sensor in aqueous solution and in urine mimic in real time and label-free. N-methacryloyl-(l)-histidine methyl ester (MAH) was selected as a functional monomer to design tailor-made E. coli receptors on the polymeric film and during the formation of the polymeric film on a chip surface, Ag nanoparticles (AgNPs) were entrapped into the polymer mixture in order to lower the detection limit of biomimetic SPR based sensor. The polymeric film was characterized with atomic force microscopy (AFM), scanning electron microscopy (SEM), ellipsometer and contact angle measurements. Limit of detection (LOD) was found 0.57 CFU/mL and feasibility of the biomimetic sensor was investigated in urine mimic.

Surface stress-induced membrane biosensor based on double-layer stable gold nanostructures for E. coli detection

The surface stress-based biosensor has been applied in fast and sensitive identification of Escherichia coli (E. coli)with significance for public health, food, and water safety. However, the stable sensitive element of flexible biosensor based on surface stress is still crucial and challengeable. Here, the authors reported surface stress-induced biosensors based on double-layer stable gold nanostructures (D-AuNS-SSMB) for E. coli O157:H7 detection. Bacterial detection demonstrates the high stability of the biosensor. The resistance change of biosensor is linear to the logarithmic value of the E. coli O157:H7 concentrations ranging from 10³ to 10⁷ CFU/mL with a limit of detection (LOD) of 43 CFU/mL. The captured signals of D-AuNS-SSMB comes from surface stress generated by antigen-antibody binding. In addition, the biosensor exhibits good stability, reproducibility and specificity in detection of E. coli O157:H7 as well. This study provides a new preparation method of stable sensitive element for the E. coli detection.

Mapping of Pesticide Transmission on Biological Tissues by Surface Enhanced Raman Microscopy with a Gold Nanoparticle Mirror

We presented an improved surface-enhanced Raman scattering (SERS) mapping technique for the imaging of pesticides on biological samples including tomato leaves, fruits, and mouse skin using a gold nanoparticle mirror as the SERS substrate. The gold nanoparticle mirror was fabricated using 50 nm commercial citrate-capped gold nanoparticles upon the interface of water and a mediating solvent that was prepared using acetonitrile and hexane. The properties of the gold nanoparticle mirror were compared with gold nanoparticles, and the mirror displayed higher sensitivity with a limit of detection of 0.07 μg/cm² and better reproducibility with a relative standard deviation of 5.48% for the SERS mapping of pesticide (ferbam) on biological samples. The gold mirror-based SERS mapping technique was also used to investigate pesticide transmission from tomato fruit surfaces to mouse skin after 1 mg/cm² of pesticides was administered upon the fruit, and the results showed that about 23% of the pesticide was transmitted from the fruit to the mouse skin. We also found that pesticides on the contaminated hand could not be completely removed by routine rinsing with tap water for 2 min. This study provides an effective approach for the imaging of pesticides on biological tissues that would facilitate research on pesticide behaviors both on and in biological systems.

'Mixing-and-measuring' surface-enhanced Raman scattering (SERS) detection of Bacillus cereus for potentially aiding gold mine field exploration

Bacillus cereus, a common soil bacterium, has been shown to act as a biogeochemical indicator for concealed mineralisations, e.g., vein-type Au deposits. Field and cultivation-free detection of Bacillus cereus in the presence of Au³⁺ and other metal ions is significantly important but still almost blank in current biogeochemical prospecting of gold mine system. Herein, a self-established simple approach was slightly improved to make silver nanoparticles (Ag NPs) rapidly concentrated on every bacterial cell, and highly strong and distinct surface-enhanced Raman scattering (SERS) signals of Bacillus cereus free from any native fluorescence have been obtained in a so called 'mixing-and-measuring' manner. Furthermore, SERS was used for the first time to our knowledge to investigate the impacts of different concentrations of metal ions on Bacillus cereus, and successfully utilized for distinguishing Au³⁺ ions from other species. A more convincing multi-Raman criterion based on Raman bands, and further the entire Raman spectrum in combination with statistical analysis (e.g., principal component analysis (PCA)) were found capable of detecting spectral differences of Bacillus cereus in the presence of metal ions (Au³⁺, Ag⁺, Cu²⁺ and Zn²⁺) with different concentrations. An interesting phenomenon has been found that except for Au³⁺ ions, the highest permissive concentration of other metal ions for the detected Bacillus cereus is up to 10 μg/mL possibly due to their resistance to Au. The results also indicate that an effective biogeochemical exploration technique of SERS spectral response may be developed, where Bacillus cereus spore counts are measured in the field and used as a pre-screening method to target areas useful for further sampling and complete geochemical analysis.

Development of uncoated near-spherical gold nanoparticles for the label-free quantification of Lactobacillus rhamnosus GG by surface-enhanced Raman spectroscopy

The Surface-enhanced Raman spectroscopy (SERS) method based on gold nanoparticles as SERS substrate was investigated for the label-free detection and quantification of probiotic bacteria that are widely used in various pharmaceutical formulations. Indeed, the development of a simple and fast SERS method dedicated to the quantification of bacteria should be very useful for the characterization of such formulations in a more convenient way than the usually performed tedious and time-consuming conventional counting method. For this purpose, uncoated near-spherical gold nanoparticles were developed at room temperature by acidic treatment of star-like gold nanoparticle precursors. In this study, we first investigated the influence of acidic treatment conditions on both the nanoparticle physicochemical properties and SERS efficiency using Rhodamine 6G (R6G) as "model" analyte. Results highlighted that an effective R6G Raman signal enhancement was obtained by promoting chemical effect through R6G-anion interactions and by obtaining a suitable aggregation state of the nanoparticles. Depending on the nanoparticle synthesis conditions, R6G SERS signals were up to 10²-10³-fold greater than those obtained with star-like gold nanoparticles. The synthesized spherical gold nanoparticles were then successfully applied for the detection and quantification of Lactobacillus rhamnosus GG (LGG). In that case, the signal enhancement was especially due to the combination of anion-induced chemical enhancement and nanoparticle aggregation on LGG cell wall consecutive to non-specific interactions. Both the simplicity and speed of the procedure, achieved under 30 min, including nanoparticle synthesis, sample preparation, and acquisition of SERS spectra, appeared as very relevant for the characterization of pharmaceutical formulations incorporating probiotics. Graphical abstract.

Surface-enhanced Raman scattering method for the identification of methicillin-resistant Staphylococcus aureus using positively charged silver nanoparticles

The article describes a SERS-based method for diagnosis of bacterial infections. Positively charged silver nanoparticles (AgNPs⁺) were employed for identification of methicillin-resistant Staphylococcus aureus (MRSA). It is found that AgNPs⁺ undergo self-assembly on the surface of bacteria via electrostatic aggregation. The assembled AgNPs⁺ are excellent SERS substrates. To prove the capability of SERS to differentiate between S. aureus and other microorganisms, six standard strains including S. aureus 29213, S. aureus 25923, C. albicans, B. cereus, E. coli, and P. aeruginosa were tested. To further demonstrate its applicability for the identification of MRSA in clinical samples, 52 methicillin-sensitive S. aureus (MSSA) isolates and 215 MRSA isolates were detected by SERS. The total measurement time (include incubation) is 45 min when using a 3 μL sample. The method gives a strongly enhanced Raman signal (at 730 cm^-1 and 1325 cm^-1) with good reproducibility and repeatability. It was successfully applied to the discrimination of the six strain microorganisms. The typical Raman peaks of S. aureus at 730, 1154, 1325, and 1457 cm^-1 were observed, which were assigned to the bacterial cell wall components (730 cm^-1- adenine, glycosidic ring mode, 1154 cm^-1- unsaturated fatty acid, 1325 cm^-1- adenine, polyadenine, and 1457 cm^-1 for -COO- stretching). S. aureus was completely separated from other species by partial least squares discriminant analysis (PLS-DA). Moreover, 52 MSSA isolates and 215 MRSA isolates from clinical samples were identified by PLS-DA. The accuracy was almost 100% when compared to the standard broth microdilution method. A classification based on latent structure discriminant analysis provided spectral variability directly. Conceivably, the method offers a potent tool for the identification of bacteria and antibiotics resistance, and for studies on antibiotic-resistance in general. Graphical abstract Schematic of the surface-enhanced Raman scattering (SERS) measurements on Staphylococcus aureus (S. aureus) using positively charged silver nanoparticles (AgNPs⁺). AgNPs⁺ are adsorbed on the bacterial cell wall by electrostatic attraction. SERS spectra were analyzed by PLS-DA for the identification of Staphylococcus aureus (MRSA) and methicillin-resistant Staphylococcus aureus (MSSA). MRSA isolates were divided into four groups, including R1, R2, R3, and R4. MSSA just includes group S.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

Portable bacteria-capturing chip for direct surface-enhanced Raman scattering identification of urinary tract infection pathogens

Acute urinary tract infections (UTIs) are one of the most common nosocomial bacterial infections, which affect almost 50% of the population at least once in their lifetime. UTIs may lead to lethal consequences if they are left undiagnosed and not properly treated. Early, rapid and accurate uropathogens detection methods play a pivotal role in clinical process. In this work, a portable bacteria-grasping surface-enhanced Raman scattering (SERS) chip for identification of three species of uropathogens (Escherichia coli CFT 073, Pseudomonas aeruginosa PAO1 and Proteus mirabilis PRM1) directly from culture matrix was reported. The chip was firstly modified with a positively charged NH3 + group, which enables itself grasp the negatively charged bacterial cells through the electrostatic adsorption principle. After the bacterial cells were captured by the chip, concentrated Ag nanoparticles (NPs) were used to obtain their Raman fingerprint spectra with recognizable characteristic peaks and good reproducibility. With the help of chemometric method such as discriminant analysis (DA), the SERS-based chip allows a rapid, successful identification of three species of UTI bacteria with a minimal bacterial concentration (105 cells ml-1) required for clinical diagnostics. In addition, this chip could spot the bacterial SERS fingerprints information directly from LB culture medium and artificial urine without sample pre-treatment. The portable bacteria-grasping SERS-based chip provides a possibility for fast and easy detection of uropathogens, and viability of future development in healthcare applications.

Facing Challenges in Real-Life Application of Surface-Enhanced Raman Scattering: Design and Nanofabrication of Surface-Enhanced Raman Scattering Substrates for Rapid Field Test of Food Contaminants

Surface-enhanced Raman scattering (SERS) is capable of detecting a single molecule with high specificity and has become a promising technique for rapid chemical analysis of agricultural products and foods. With a deeper understanding of the SERS effect and advances in nanofabrication technology, SERS is now on the edge of going out of the laboratory and becoming a sophisticated analytical tool to fulfill various real-world tasks. This review focuses on the challenges that SERS has met in this progress, such as how to obtain a reliable SERS signal, improve the sensitivity and specificity in a complex sample matrix, develop simple and user-friendly practical sensing approach, reduce the running cost, etc. This review highlights the new thoughts on design and nanofabrication of SERS-active substrates for solving these challenges and introduces the recent advances of SERS applications in this area. We hope that our discussion will encourage more researches to address these challenges and eventually help to bring SERS technology out of the laboratory.

Bare laser-synthesized Au-based nanoparticles as nondisturbing surface-enhanced Raman scattering probes for bacteria identification

The ability of noble metal-based nanoparticles (NPs) (Au, Ag) to drastically enhance Raman scattering from molecules placed near metal surface, termed as surface-enhanced Raman scattering (SERS), is widely used for identification of trace amounts of biological materials in biomedical, food safety and security applications. However, conventional NPs synthesized by colloidal chemistry are typically contaminated by nonbiocompatible by-products (surfactants, anions), which can have negative impacts on many live objects under examination (cells, bacteria) and thus decrease the precision of bioidentification. In this article, we explore novel ultrapure laser-synthesized Au-based nanomaterials, including Au NPs and AuSi hybrid nanostructures, as mobile SERS probes in tasks of bacteria detection. We show that these Au-based nanomaterials can efficiently enhance Raman signals from model R6G molecules, while the enhancement factor depends on the content of Au in NP composition. Profiting from the observed enhancement and purity of laser-synthesized nanomaterials, we demonstrate successful identification of 2 types of bacteria (Listeria innocua and Escherichia coli). The obtained results promise less disturbing studies of biological systems based on good biocompatibility of contamination-free laser-synthesized nanomaterials.

Label-free SERS in biological and biomedical applications: Recent progress, current challenges and opportunities

To achieve an insightful look within biomolecular processes on the cellular level, the development of diseases as well as the reliable detection of metabolites and pathogens, a modern analytical tool is needed that is highly sensitive, molecular-specific and exhibits fast detection. Surface-enhanced Raman spectroscopy (SERS) is known to meet these requirements and, within this review article, the recent progress of label-free SERS in biological and biomedical applications is summarized and discussed. This includes the detection of biomolecules such as metabolites, nucleic acids and proteins. Further, the characterization and identification of microorganisms has been achieved by label-free SERS-based approaches. Eukaryotic cells can be characterized by SERS in order to gain information about the outer cell wall or to detect intracellular molecules and metabolites. The potential of SERS for medically relevant detection schemes is emphasized by the label-free detection of tissue, the investigation of body fluids as well as applications for therapeutic and illicit drug monitoring. The review article is concluded with an evaluation of the recent progress and current challenges in order to highlight the direction of label-free SERS in the future.

Alkaline phosphatase labeled SERS active sandwich immunoassay for detection of Escherichia coli

In this study, a sandwich immunoassay method utilizing enzymatic activity of alkaline phosphatase (ALP) on 5-bromo-4-chloro-3-indolyl phosphate (BCIP) for Escherichia coli (E. coli) detection was developed using surface enhanced Raman spectroscopy (SERS). For this purpose, spherical magnetic gold coated core-shell nanoparticles (MNPs-Au) and rod shape gold nanoparticles (Au-NRs) were synthesized and modified for immunomagnetic separation (IMS) of E. coli from the solution. In order to specify the developed method to ALP activity, Au-NRs were labeled with this enzyme. After successful construction of the immunoassay, BCIP substrate was added to produce the SERS-active product; 5-bromo-4-chloro-3-indole (BCI). A good linearity (R²=0.992) was established between the specific SERS intensity of BCI at 600cm^-1 and logarithmic E. coli concentration in the range of 1.7×10¹-1.7×10⁶cfumL^-1. LOD and LOQ values were also calculated and found to be 10cfumL^-1 and 30cfumL^-1, respectively.

Microfluidic devices for sample preparation and rapid detection of foodborne pathogens

Rapid detection of foodborne pathogens at an early stage is imperative for preventing the outbreak of foodborne diseases, known as serious threats to human health. Conventional bacterial culturing methods for foodborne pathogen detection are time consuming, laborious, and with poor pathogen diagnosis competences. This has prompted researchers to call the current status of detection approaches into question and leverage new technologies for superior pathogen sensing outcomes. Novel strategies mainly rely on incorporating all the steps from sample preparation to detection in miniaturized devices for online monitoring of pathogens with high accuracy and sensitivity in a time-saving and cost effective manner. Lab on chip is a blooming area in diagnosis, which exploits different mechanical and biological techniques to detect very low concentrations of pathogens in food samples. This is achieved through streamlining the sample handling and concentrating procedures, which will subsequently reduce human errors and enhance the accuracy of the sensing methods. Integration of sample preparation techniques into these devices can effectively minimize the impact of complex food matrix on pathogen diagnosis and improve the limit of detections. Integration of pathogen capturing bio-receptors on microfluidic devices is a crucial step, which can facilitate recognition abilities in harsh chemical and physical conditions, offering a great commercial benefit to the food-manufacturing sector. This article reviews recent advances in current state-of-the-art of sample preparation and concentration from food matrices with focus on bacterial capturing methods and sensing technologies, along with their advantages and limitations when integrated into microfluidic devices for online rapid detection of pathogens in foods and food production line.

Combined use of vancomycin-modified Ag-coated magnetic nanoparticles and secondary enhanced nanoparticles for rapid surface-enhanced Raman scattering detection of bacteria

Background

Pathogenic bacteria have always been a significant threat to human health. The detection of pathogens needs to be rapid, accurate, and convenient.

Methods

We present a sensitive surface-enhanced Raman scattering (SERS) biosensor based on the combination of vancomycin-modified Ag-coated magnetic nanoparticles (Fe₃O₄@Ag-Van MNPs) and Au@Ag nanoparticles (NPs) that can effectively capture and discriminate bacterial pathogens from solution. The high-performance Fe₃O₄@Ag MNPs were modified with vancomycin and used as bacteria capturer for magnetic separation and enrichment. The modified MNPS were found to exhibit strong affinity with a broad range of Gram-positive and Gram-negative bacteria. After separating and rinsing bacteria, Fe₃O₄@Ag-Van MNPs and Au@Ag NPs were synergistically used to construct a very large number of hot spots on bacteria cells, leading to ultrasensitive SERS detection.

Results

The dominant merits of our dual enhanced strategy included high bacterial-capture efficiency (>65%) within a wide pH range (pH 3.0–11.0), a short assay time (<30 min), and a low detection limit (5×10² cells/mL). Moreover, the spiked tests show that this method is still valid in milk and blood samples. Owing to these capabilities, the combined system enabled the sensitive and specific discrimination of different pathogens in complex solution, as verified by its detection of Gram-positive bacterium Escherichia coli, Gram-positive bacterium Staphylococcus aureus, and methicillin-resistant S. aureus.

Conclusion

This method has great potential for field applications in food safety, environmental monitoring, and infectious disease diagnosis.