Differentiation of bacteria cell wall using Raman scattering enhanced by nanoparticle array

Recent Advances in Bacterial Detection Using Surface-Enhanced Raman Scattering

Rapid identification of microorganisms with a high sensitivity and selectivity is of great interest in many fields, primarily in clinical diagnosis, environmental monitoring, and the food industry. For over the past decades, a surface-enhanced Raman scattering (SERS)-based detection platform has been extensively used for bacterial detection, and the effort has been extended to clinical, environmental, and food samples. In contrast to other approaches, such as enzyme-linked immunosorbent assays and polymerase chain reaction, SERS exhibits outstanding advantages of rapid detection, being culture-free, low cost, high sensitivity, and lack of water interference. This review aims to cover the development of SERS-based methods for bacterial detection with an emphasis on the source of the signal, techniques used to improve the limit of detection and specificity, and the application of SERS in high-throughput settings and complex samples. The challenges and advancements with the implementation of artificial intelligence (AI) are also discussed.

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen's antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

Optical Methods for Label-Free Detection of Bacteria

Pathogenic bacteria are the leading causes of food-borne and water-borne infections, and one of the most serious public threats. Traditional bacterial detection techniques, including plate culture, polymerase chain reaction, and enzyme-linked immunosorbent assay are time-consuming, while hindering precise therapy initiation. Thus, rapid detection of bacteria is of vital clinical importance in reducing the misuse of antibiotics. Among the most recently developed methods, the label-free optical approach is one of the most promising methods that is able to address this challenge due to its rapidity, simplicity, and relatively low-cost. This paper reviews optical methods such as surface-enhanced Raman scattering spectroscopy, surface plasmon resonance, and dark-field microscopic imaging techniques for the rapid detection of pathogenic bacteria in a label-free manner. The advantages and disadvantages of these label-free technologies for bacterial detection are summarized in order to promote their application for rapid bacterial detection in source-limited environments and for drug resistance assessments.

High Sensitivity SERS Substrate of a Few Nanometers Single-Layer Silver Thickness Fabricated by DC Magnetron Sputtering Technology

Surface-enhanced Raman spectroscopy (SERS) is commonly used for super-selective analysis through nanostructured silver layers in the environment, food quality, biomedicine, and materials science. To fabricate a high-sensitivity but a more accessible device of SERS, DC magnetron sputtering technology was used to realize high sensitivity, low cost, a stable deposition rate, and rapid mass production. This study investigated various thicknesses of a silver film ranging from 3.0 to 12.1 nm by field emission scanning electron microscope, X-ray diffraction, and X-ray photoelectron spectroscopy. In the rhodamine 6G (R6G) testing irradiated by a He-Ne laser beam, the analytical enhancement factor (AEF) of 9.35 × 108, the limit of detection (LOD) of 10-8 M, and the relative standard deviation (RSD) of 1.61% were better than the other SERS substrates fabricated by the same DC sputtering process because the results showed that the 6 nm thickness silver layer had the highest sensitivity, stability, and lifetime. The paraquat and acetylcholine analytes were further investigated and high sensitivity was also achievable. The proposed SERS samples were evaluated and stored in a low humidity environment for up to forty weeks, and no spectrum attenuation could be detected. Soon, the proposed technology to fabricate high sensitivity, repeatability, and robust SERS substrate will be an optimized process technology in multiple applications.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

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

Wavelength-dependent label-free identification of isolated nontuberculous mycobacteria using surface-enhanced Raman spectroscopy

We investigated the effect of Raman excitation wavelengths on the surface-enhanced Raman spectroscopy (SERS)-based identification of isolated nontuberculous mycobacteria (NTM). The SERS spectra with 3 commonly used excitation wavelengths, 532, 638, and 785 nm, were compared across 6 representative NTM species that primarily cause human NTM infections in Korea and the United States; these species were identified. The statistical differences among NTM SERS spectra at each Raman excitation wavelength were verified using 1-way analysis of variance, and the 6 NTM species were identified using principal components-linear discriminant analysis with leave-one-out cross validation. The identification accuracies with aromatic amino acid biomarkers were 99.3%, 91.3%, and 90.7% for 532, 638, and 785 nm, respectively. We believe that the proposed SERS protocol with aromatic amino acid biomarkers at the 532-nm Raman excitation wavelength will enable fast and accurate identification of NTM compared to previous identification methods.

Pathogenic Escherichia coli (E. coli) detection through tuned nanoparticles enhancement study

OBJECTIVE

This study aims to detect pathogenic Escherichia coli (E. coli) bacteria using non-destructive fluorescence microscopy and micro-Raman spectroscopy.

RESULTS

Raman vibrational spectroscopy provides additional information regarding biochemical changes at the cellular level. We have used two nanomaterials zinc oxide nanoparticles (ZnO-NPs) and gold nanoparticles (Au-NPs) to detect pathogenic E. coli. The scanning electron microscope (SEM) with energy dispersive X-ray (EDAX) spectroscopy exhibit surface morphology and the elemental composition of the synthesized NPs. The metal NPs are useful contrast agents due to the surface plasmon resonance (SPR) to detect the signal intensity and hence the bacterial cells. The changes due to the interaction between cells and NPs are further correlated to the change in the surface charge and stiffness of the cell surface with the help of the fluorescence microscopic assay.

CONCLUSIONS

We conclude that when two E. coli strains (MTCC723 and MTCC443) and NPs are respectively mixed and kept overnight, the growth of bacteria are inhibited by ZnO-NPs due to changes in cell membrane permeability and intracellular metabolic system under fluorescence microscopy. However, SPR possessed Au-NPs result in enhanced fluorescence of both pathogens. In addition, with the help of Raman microscopy and element analysis, significant changes are observed when Au-NPs are added with the two strains as compared to ZnO-NPs due to protein, lipid and DNA/RNA induced conformational changes.

Differentiation of Taxonomically Closely Related Species of the Genus Acinetobacter Using Raman Spectroscopy and Chemometrics

In recent years, several efforts have been made to develop quick and low cost bacterial identification methods. Genotypic methods, despite their accuracy, are laborious and time consuming, leaving spectroscopic methods as a potential alternative. Mass and infrared spectroscopy are among the most reconnoitered techniques for this purpose, with Raman having been practically unexplored. Some species of the bacterial genus Acinetobacter are recognized as etiological agents of nosocomial infections associated with high rates of mortality and morbidity, which makes their accurate identification important. The goal of this study was to assess the ability of Raman spectroscopy to discriminate between 16 Acinetobacter species belonging to two phylogroups containing taxonomically closely related species, that is, the Acinetobacter baumannii-Acinetobacter calcoaceticus complex (six species) and haemolytic clade (10 species). Bacterial spectra were acquired without the need for any sample pre-treatment and were further analyzed with multivariate data analysis, namely partial least squares discriminant analysis (PLSDA). Species discrimination was achieved through a series of sequential PLSDA models, with the percentage of correct species assignments ranging from 72.1% to 98.7%. The obtained results suggest that Raman spectroscopy is a promising alternative for identification of Acinetobacter species.

SERS Detection of Biomolecules by Highly Sensitive and Reproducible Raman-Enhancing Nanoparticle Array

This paper describes the preparation of nanoarrays composed of silver nanoparticles (AgNPs: 20-50 nm) for use as surface-enhanced Raman scattering (SERS) substrates. The AgNPs were grown on porous anodic aluminum oxide (AAO) templates by electrochemical plating, and the inter-channel gap of AAO channels is between 10 and 20 nm. The size and interparticle gap of silver particles were adjusted in order to achieve optimal SERS signals and characterized by scanning electron microscopy, atomic force microscopy, and Raman spectroscopy. The fluctuation of SERS intensity is about 10-20% when measuring adenine solutions, showing a great reproducible SERS sensing. The nanoparticle arrays offer a large potential for practical applications as shown by the SERS-based quantitative detection and differentiation of adenine (A), thymine (T), cytosine (C), guanine (G), β-carotene, and malachite green. The respective detection limits are <1 ppb for adenine and <0.63 ppm for β-carotene and malachite green, respectively. Uniform and reproducible Raman enhancement enabled by Ag nanoparticle array embedded in anodic aluminum oxide differentiates and helps quantify DNA canonical nucleobases (adenine, thymine, cytosine, and guanine).

Core-shell of FePt@SiO2-Au magnetic nanoparticles for rapid SERS detection

In this study, multifunctional hybrid nanoparticles composed of iron platinum (FePt), silica (SiO2), and gold nanoparticles (AuNPs) had been developed for surface-enhanced Raman scattering (SERS) application. Core-shell structure of SiO2 and FePt nanoparticles (FePt@SiO2) was fabricated through sol-gel process and then immobilized gold nanoparticles onto the surface of FePt@SiO2, which displays huge Raman enhancement effect and magnetic separation capability. The resulting core-shell nanoparticles were subject to evaluation by transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDX), zeta potential measurement, and X-ray photoelectron spectroscopy (XPS). TEM observation revealed that the particle size of resultant nanoparticles displayed spherical structure with the size ~30 nm and further proved the successful immobilization of Au onto the surface of FePt@SiO2. Zeta potential measurement exhibited the successful reaction between FePt@SiO2 and AuNPs. The rapid SERS detection and identification of small biomolecules (adenine) and microorganisms (gram-positive bacteria, Staphylococcus aureus) was conducted through Raman spectroscopy. In summary, the novel core-shell magnetic nanoparticles could be anticipated to apply in the rapid magnetic separation under the external magnetic field due to the core of the FePt superparamagnetic nanoparticles and label-free SERS bio-sensing of biomolecules and bacteria.

Porous Alumina as a Promising Biomaterial for Public Health

Porous aluminum is a nanostructured material characterized by unique properties, such as chemical stability, regular uniformity, dense hexagonal porous lattice with high aspect ratio nanopores, excellent mechanical strength, and biocompatibility. This overview examines how the structure and properties of porous alumina can be exploited in the field of public health. Porous alumina can be employed for fabricating membranes and filters for bioremediation, water ultrafiltration, and microfiltration/nanofiltration, being a promising technique for having clean and fresh water, which is essential for human health. Porous alumina-based nanobiosensor coated with specific antibodies or peptides seem to be a useful tool to detect and remove pathogens both in food and in water, as well as for environmental monitoring. Further, these applications, being low-energy demanding and cost-effective, are particularly valuable in resource-limited settings and contexts, and can be employed as point of use devices in developing countries, where there is an urgent need of hygiene and safety assurance.

Isolation and identification of bacteria by means of Raman spectroscopy

Bacterial detection is a highly topical research area, because various fields of application will benefit from the progress being made. Consequently, new and innovative strategies which enable the investigation of complex samples, like body fluids or food stuff, and improvements regarding the limit of detection are of general interest. Within this review the prospects of Raman spectroscopy as a reliable tool for identifying bacteria in complex samples are discussed. The main emphasis of this work is on important aspects of applying Raman spectroscopy for the detection of bacteria like sample preparation and the identification process. Several approaches for a Raman compatible isolation of bacterial cells have been developed and applied to different matrices. Here, an overview of the limitations and possibilities of these methods is provided. Furthermore, the utilization of Raman spectroscopy for diagnostic purposes, food safety and environmental issues is discussed under a critical view.

Differentiation and classification of bacteria using vancomycin functionalized silver nanorods array based surface-enhanced Raman spectroscopy and chemometric analysis

Twenty seven different bacteria isolates from 12 species were analyzed using intrinsic surface-enhanced Raman scattering (SERS) spectra with recently developed vancomycin coated silver nanorod (VAN AgNR) substrates. The VAN AgNR substrates could generate reproducible SERS spectra of the bacteria with little to no interference from the environment or bacterial by-products as compared to the pristine substrates. By taking advantage of the structural composition of the cellular wall which varies from species to species, the differentiation of bacterial species is demonstrated by using chemometric analyses on those spectra. A second chemometric analysis step within the species cluster is able to differentiate serotypes and strains. The spectral features used for serotype differentiation arises from the surface proteins, while Raman peaks from adenine dominate the differentiation of strains. In addition, due to the intrinsic structural differences in the cell walls, the SERS spectra can distinguish Gram-positive from Gram-negative bacteria with high sensitivity and specificity, as well as 100% accuracy on predicting test samples. Our results provide important insights for using SERS as a bacterial diagnostic tool and further guide the design of a SERS-based detection platform.

Selective SERS detecting of hydrophobic microorganisms by tricomponent nanohybrids of silver-silicate-platelet-surfactant

Nanohybrids consisting of silver nanoparticles (Ag), clay platelets, and a nonionic surfactant were prepared and used as the substrate for surface-enhanced Raman scattering (SERS). The nanoscale silicate platelets (SP) (with dimensions of 100 × 100 nm(2) and a thickness of ∼1 nm) were previously prepared from exfoliation of the natural layered silicates. The tricomponent nanohybrids, Ag-SP-surfactant (Ag-SP-S), were prepared by in situ reduction of AgNO3 in the presence of clay and the surfactant. The clay platelets with a large surface area and ionic charge (ca. 18 000 sodium ions per platelet) allowed for the stabilization of Ag nanoparticles in the range of 10-30 nm in diameter. With the addition of a nonionic surfactant such as poly(oxyethylene) alkyl ether, the tricomponent Ag-SP-S nanohybrids possessed an altered affinity for contacting microorganisms. The particle size and interparticle gaps between neighboring Ag on SP were characterized by TEM. The surface tension of Ag-SP and Ag-SP-S in water implied different interactions between Ag and hydrophobic bacteria ( Escherichia coli and Mycobacterium smegmatis ). By increasing the surfactant content in Ag-SP-S, the SERS peak intensity was dramatically enhanced compared to the Ag-SP counterpart. The nanohybrids, Ag-SP and Ag-SP-S, with the advantages of varying hydrophobic affinity, floating in medium, and 3D hot-junction enhancement could be tailored for use as SERS substrates. The selective detection of hydrophobic microorganisms and larger biological cells makes SERS a possible rapid, label-free, and culture-free method of biodetection.

Nanostructured silver-gold bimetallic SERS substrates for selective identification of bacteria in human blood

Surface-enhanced Raman spectroscopy (SERS) is a potentially important tool in the rapid and accurate detection of pathogenic bacteria in biological fluids. However, for diagnostic application of this technique, it is necessary to develop a highly sensitive, stable, biocompatible and reproducible SERS-active substrate. In this work, we have developed a silver-gold bimetallic SERS surface by a simple potentiostatic electrodeposition of a thin gold layer on an electrochemically roughened nanoscopic silver substrate. The resultant substrate was very stable under atmospheric conditions and exhibited the strong Raman enhancement with the high reproducibility of the recorded SERS spectra of bacteria (E. coli, S. enterica, S. epidermidis, and B. megaterium). The coating of the antibiotic over the SERS substrate selectively captured bacteria from blood samples and also increased the Raman signal in contrast to the bare surface. Finally, we have utilized the antibiotic-coated hybrid surface to selectively identify different pathogenic bacteria, namely E. coli, S. enterica and S. epidermidis from blood samples.

Label-free and culture-free microbe detection by three dimensional hot-junctions of flexible Raman-enhancing nanohybrid platelets

A novel flexible SERS substrate with 3D hot-junction capability by employing the nanohybrids of silver nanoparticles and silicate platelets.