Portable, Quantitative Detection of Bacillus Bacterial Spores Using Surface-Enhanced Raman Scattering

BSA-AuNPs@Tb-AMP metal-organic frameworks for ratiometric fluorescence detection of DPA and Hg2

An easy and effective strategy for synthesizing a ratiometric fluorescent nanosensor has been demonstrated in this work. Novel fluorescent BSA-AuNPs@Tb-AMP (BSA, bovine serum albumin; AMP, adenosine 5'-monophosphate; AuNPs, Au nanoparticles) metal-organic framework (MOF) nanostructures were synthesized by encapsulating BSA-AuNPs into Tb-AMP MOFs for the detection of 2,6-pyridinedicarboxylic acid (DPA) and Hg²⁺ . DPA could strongly co-ordinate with Tb³⁺ to replace water molecules from the Tb³⁺ center and accordingly enhanced the fluorescence of Tb-AMP MOFs. The fluorescence of BSA-AuNPs at 405 nm remained constant. While the fluorescence of BSA-AuNPs at 635 nm was quenched after Hg²⁺ was added, the fluorescence of Tb-AMP MOFs remained constant. Accordingly, a ratiometric fluorescence nanosensor was constructed for detection of DPA and Hg²⁺ . The ratiometric nanosensor exhibited good selectivity to DPA over other substances. The F₅₄₅ /F₄₀₅ linearly increased with increase of DPA concentration in the range of 50 nM to 10 μM with a detection limit as low as 17.4 nM. F₆₃₅ /F₄₀₅ increased linearly with increase of Hg²⁺ concentration ranging from 50 nM to 1 μM with a detection limit as low as 20.9 nM. Additionally, the nanosensor could be successfully applied for the determination of DPA and Hg²⁺ in running water.

Discrimination of Nosiheptide Sources with Plasmonic Filters

Bacteria identification plays a vital role in the field of clinical diagnosis, food industry, and environmental monitoring, which is in great demand of point of care detection methods. In this paper, in order to discriminate the source of nosiheptide product, a plasmonic filter was fabricated to filtrate, capture and identify Streptomycete spores with Surface enhanced Raman Scattering (SERS). Since the plasmonic filter was derived from self-assembled photonic crystal coated with silver, the plasmonic "hot spots" on the filter surface was distributed evenly in a fare good density and the SERS enhancement factor was 7.49 × 10⁷. With this filter, a stain- and PCR-free detection was realized with only 5 μL sample solution and 5 min in a manner of "filtration and measure". Comparison to traditional Gram stain method and silver-plated nylon filter membrane, the plasmonic filter showed good sensitivity and efficiency in the discrimination of nosiheptide prepared with chemical and biological methods. It is anticipated that this simple SERS detection method with plasmonic filter has promising potentials in food safety, environmental, or clinical applications.

Optical Biosensing of Bacteria and Bacterial Communities

Bacterial sensing is important for understanding the numerous roles bacteria play in nature and in technology, understanding and managing bacterial populations, detecting pathogenic bacterial infections, and preventing the outbreak of illness. Current analytical challenges in bacterial sensing center on the dilemma of rapidly acquiring quantitative information about bacteria with high detection efficiency, sensitivity, and specificity, while operating within a reasonable budget and optimizing the use of ancillary tools, such as multivariate statistics. This review starts from a general description of bacterial sensing methods and challenges, and then focuses on bacterial characterization using optical methods including Raman spectroscopy and imaging, infrared spectroscopy, fluorescence spectroscopy and imaging, and plasmonics, including both extended and localized surface plasmon resonance spectroscopy. The advantages and drawbacks of each method in relation to the others are discussed, as are their applications. A particularly promising direction in bacterial sensing lies in combining multiple approaches to achieve multiplex analysis, and examples where this has been achieved are highlighted.

Absolute Quantification of Uric Acid in Human Urine Using Surface Enhanced Raman Scattering with the Standard Addition Method

High levels of uric acid in urine and serum can be indicative of hypertension and the pregnancy related condition, preeclampsia. We have developed a simple, cost-effective, portable surface enhanced Raman scattering (SERS) approach for the routine analysis of uric acid at clinically relevant levels in urine patient samples. This approach, combined with the standard addition method (SAM), allows for the absolute quantification of uric acid directly in a complex matrix such as that from human urine. Results are highly comparable and in very good agreement with HPLC results, with an average <9% difference in predictions between the two analytical approaches across all samples analyzed, with SERS demonstrating a 60-fold reduction in acquisition time compared with HPLC. For the first time, clinical prepreeclampsia patient samples have been used for quantitative uric acid detection using a simple, rapid colloidal SERS approach without the need for complex data analysis.

Averaging effect on improving signal reproducibility of gap-based and gap-free SERS substrates based on ordered Si nanowire arrays

A gap-free SERS substrate was found to achieve both high reproducibility and high enhancement against the reproducibility/enhancement trade-off in gap-based substrates.

Plasmonic nanoparticles in chemical analysis

In this review various analytical techniques utilising the plasmonic properties of silver and gold nanoparticles have been presented.

Quantitative detection of codeine in human plasma using surface-enhanced Raman scattering via adaptation of the isotopic labelling principle

In this study surface-enhanced Raman scattering (SERS) combined with the isotopic labelling (IL) principle has been used for the quantification of codeine spiked into both water and human plasma.

A monolayer of hierarchical silver hemi-mesoparticles with tunable surface topographies for highly sensitive surface-enhanced Raman spectroscopy

We proposed a facile green synthesis system to synthesize large-scale Ag hemi-mesoparticles monolayer on Cu foil. Ag hemi-mesoparticles have different surface morphologies on their surfaces, including ridge-like, meatball-like, and fluffy-like shapes. In the reaction, silver nitrate was reduced by copper at room temperature in dimethyl sulfoxide via the galvanic displacement reaction. The different surface morphologies of the Ag hemi-mesoparticles were adjusted by changing the reaction time, and the hemi-mesoparticle surface formed fluffy-spherical nanoprotrusions at longer reaction time. At the same time, we explored the growth mechanism of silver hemi-mesoparticles with different surface morphologies. With 4-mercaptobenzoic acid as Raman probe molecules, the fluffy-like silver hemi-mesoparticles monolayer with the best activity of surface enhanced Raman scattering (SERS), the enhancement factor is up to 7.33 × 10(7) and the detection limit can reach 10(-10)M. SERS measurements demonstrate that these Ag hemi-mesoparticles can serve as sensitive SERS substrates. At the same time, using finite element method, the distribution of the localized electromagnetic field near the particle surface was simulated to verify the enhanced mechanism. This study helps us to understand the relationship between morphology Ag hemi-mesoparicles and the properties of SERS.

Detection and quantification of the opioid tramadol in urine using surface enhanced Raman scattering

There is an on going requirement for the detection and quantification of illicit substances. This is in particular the case for law enforcement where portable screening methods are needed and there has been recent interest in breath tests for a range of narcotics. In this study we first developed surface enhanced Raman scattering (SERS) for the detection of tramadol in water and establish robust and reproducible methods based on silver hydroxylamine colloid. We used 0.5 M NaCl as the aggregating agent, with the pH ∼ 7.0 and SERS data were collected immediately (i.e., the analyte association and colloid aggregation times were zero). The limit of detection was rather high and calculated to be 5 × 10(-4) M which would not be practical in the field. Undeterred we continued with spiking tramadol in artificial urine and found that no aggregating agent or modification of pH was necessary. Indeed aggregation occurred spontaneously due to the complexity of the medium which is rich in multiple salts, which are commonly used for SERS. We estimated the limit of detection in artificial urine to be 2.5 × 10(-6) M which is equivalent to 657.5 ng mL(-1) and very close to the levels typically found in individuals who use tramadol for pain relief. We believe this opens up opportunities for testing SERS in real world samples and this will be an area of future study.

SERS of meso-droplets supported on superhydrophobic wires allows exquisitely sensitive detection of dipicolinic acid, an anthrax biomarker, considerably below the infective dose

SERS of <1 μL colloid meso-droplets on superhydrophobic supports allowed detection of a total mass of dipicolinic acid equivalent to 18 anthrax spores.

Chemiresistive/SERS dual sensor based on densely packed gold nanoparticles

Chemiresistors are a class of sensitive electrical devices capable of detecting (bio)chemicals by simply monitoring electrical resistance. Sensing based on surface enhanced Raman scattering (SERS) represents a radically different approach, in which molecules are optically detected according to their vibrational spectroscopic fingerprint. Despite different concepts are involved, one can find in the literature examples from both categories reporting sensors made of gold nanoparticles. The same building blocks appear because both sensor classes share a common principle: nanometric interparticle gaps are needed, for electron tunneling in chemiresistors, and for enhancing electromagnetic fields by plasmon coupling in SERS-based sensors. By exploiting such nano-gaps in self-assembled films of gold nanoparticles, we demonstrate the proof of concept of a dual electrical/optical sensor, with both chemiresistive and SERS capabilities. The proposed device is realized by self-assembling 15 nm gold nanoparticles into few micrometers-wide strips across commercially available interdigitated electrodes. The dual-mode operation of the device is demonstrated by the detection of a biologically relevant model analyte, 4-mercaptophenyl boronic acid.

Analysis of Genomic DNAs from Nine Rosaceae Species Using Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) of genomic DNA was used to determine genetic relationships and species identification of nine plants from three subfamilies of Rosaceae. Genomic DNA was extracted, and the SERS spectra were obtained by using a nanosilver collosol at an excitation wavelength of 785 nm. Adenine and ribodesose were the active sites of genomic DNAs in the silver surface-enhanced Raman spectra. The strong peak at 714 cm(-1) was assigned to the stretching vibration of adenine, the strong peak at 1011cm(-1) contributed to the stretching vibration of the deoxyribose and the scissoring vibrations of cytosine, and the strong peak at 625 cm(-1) is the stretching vibration of glycosidic bond and the scissoring vibrations of guanine. The three-dimensional plot of the first, second, and third principal components showed that the nine species could be classified into three categories (three subfamilies), consistent with the traditional classification. The model of the hierarchical cluster combined with the principal component of the second derivative was more reasonable. The results of the cluster analysis showed that apricot (Prunus armeniaca L.) and cherry (Prunus seudocerasus Lindl.) were clustered into one category (Prunoideae); firethorn (Firethorn fortuneana Li.), loquat (Eriobotrya japonica Lindl.), apple (Malus pumila Mill.), and crabapple (Malus hallianna Koehne.) were clustered into a second category (Pomoideae); and potentilla (Potentilla fulgens Wall.), rose (Rosa chinensis Jacd.), and strawberry (Fragaria chiloensis Duchesne.) were clustered into a third category (Rosoideae). These classifications were in accordance with the traditional classification with a correction rate of clustering of 100%. The correct rate of species identification was 100%. These five main results indicate that the genetic relationship and species identification of nine Rosaceae species could be determined by using SERS spectra of their genomic DNAs.

Simultaneous multiplexed quantification of caffeine and its major metabolites theobromine and paraxanthine using surface-enhanced Raman scattering

Accurate quantitative measurement of drugs and their metabolites is important as this can be used to establish long-term abuse of illicit materials as well as establish accurate drug dosing for legal therapeutics. However, the levels of drugs and xenometabolites found in human body fluids necessitate methods that are highly sensitive as well as reproducible with the potential for portability. Raman spectroscopy does offer excellent reproducibility, portability and chemical specificity, but unfortunately, the Raman effect is generally too weak unless it is enhanced. We therefore developed surface-enhanced Raman scattering (SERS) and combined it with the powerful machine learning technique of artificial neural networks to enable rapid quantification of caffeine and its two major metabolites theobromine and paraxanthine. We established a three-way mixture analysis from 10⁻⁵ to 10⁻⁷ mol/dm³, and excellent predictions were generated for all three analytes in tertiary mixtures. The range we selected reflects the levels found in human body fluids, and the typical errors for our portable SERS analysis were 1.7 × 10⁻⁶ mol/dm³ for caffeine, 8.8 × 10⁻⁷ mol/dm³ for theobromine and 9.6 × 10⁻⁷ mol/dm³ for paraxanthine. We believe this demonstrates the exciting prospect of using SERS for the quantitative analysis of multiple analytes simultaneously without recourse to lengthy and time-consuming chromatography, a method that often has to be combined with mass spectrometry.

Increased SERS detection efficiency for characterizing rare events in flow

Improved surface-enhanced Raman scattering (SERS) measurements of a flowing aqueous sample are accomplished by combining line focus optics with sheath-flow SERS detection. The straightforward introduction of a cylindrical lens into the optical path of the Raman excitation laser increases the efficiency of SERS detection and the reproducibility of SERS signals at low concentrations. The width of the line focus is matched to the width of the sample capillary from which the analyte elutes under hydrodynamic focusing conditions, allowing for increased collection across the SERS substrate while maintaining the power density below the damage threshold at any specific point. We show that a 4× increase in power spread across the line increases the signal-to-noise ratio by a factor of 2 for a variety of analytes, such as rhodamine 6G, amino acids, and lipid vesicles, without any detectable photodamage. COMSOL simulations and Raman maps elucidate the hydrodynamic focusing properties of the flow cell, providing a clearer picture of the confinement effects at the surface where the sample exits the capillary. The lipid vesicle results suggest that the combination of hydrodynamic focusing and increased optical collection enables the reproducible detection of rare events, in this case individual lipid vesicles.

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.

High specific detection and near-infrared photothermal therapy of lung cancer cells with high SERS active aptamer-silver-gold shell-core nanostructures

Lung cancer is the leading cause of cancer death worldwide. Its early detection is of paramount importance for diagnosis, classification, treatment, and improvement of survivorship. However, current methods are not sensitive enough to detect lung cancer in its nascent stage. We reported an aptamer-Ag-Au shell-core nanostructure-based surface-enhanced Raman scattering (SERS) assay for sensitive and specific detection, and near-infrared (NIR) photothermal therapy of lung adenocarcinoma cells (A549 cells). The nanostructures target the cells with high affinity and specificity via the specific interaction between the aptamer (a 45-base oligonucleotide) and the cell, and distinguish A549 cells from other types of cancer cells (HeLa and MCF-7 cells) and subtypes of lung cancer cells (NCI-H157, NCI-H520, NCI-H1299, and NCI-H446 cells). The nanostructures have a high capability to absorb NIR irradiation and are able to perform photothermal therapy of the cells at a very low irradiation power density (0.20 W cm(-2)) without destroying the healthy cells and the surrounding normal tissues. In addition, the nanostructures exhibit a high SERS activity. Based on the SERS signal of the labeled Raman reporter (Rh6G molecules), we can specifically detect A549 cells at a very low abundance (~10 cells per mL) and monitor the therapy process of the cancer cells. Therefore, this nanostructure-based SERS assay has great potential in specific recognition, sensitive detection, and effective photothermal therapy of lung cancer.

Culture-free diagnostics of Pseudomonas aeruginosa infection by silver nanorod array based SERS from clinical sputum samples

Pseudomonas aeruginosa can cause major infection in immunocompromised patients, and successful antibiotic treatment of the infection relies on accurate and rapid identification of the infectious agents. Here, we reported a culture-free diagnostic method based on the surface-enhanced Raman spectroscopy (SERS) of pyocyanin (PCN), a major biomarker of P. aeruginosa. This platform can detect PCN as low as 5 ppb or 2.38 × 10(-8) mol L(-1) in both aqueous solutions and spiked clinical sputum samples. It has also been used to dynamically monitor the excretion of PCN by P. aeruginosa during its growth. The presence of PCN has been detected by SERS in 15 clinical sputum samples, which indicates P. aeruginosa infection, with 95.6% sensitivity and 93.3% specificity. The system can advantageously process multiple specimens rapidly, overcomes the need for bacterial culture and diagnostic microbiology assays, and have widespread implications in the early detection of P. aeruginosa infection.

FROM THE CLINICAL EDITOR

A surface enhanced Raman spectroscopy method optimized for the detection of P. aureginosa infections is presented in this paper. The presence of pyocyanin, a marker of this bacterium has been detected in 15 clinical sputum samples utilizing this method. A sensitivity of 95.6% and 93.3% specificity was reported, which suggests that the method may enable culture-free high throughput rapid detection of this infection.

A comparative investigation of modern feature selection and classification approaches for the analysis of mass spectrometry data

Many analytical approaches such as mass spectrometry generate large amounts of data (input variables) per sample analysed, and not all of these variables are important or related to the target output of interest. The selection of a smaller number of variables prior to sample classification is a widespread task in many research studies, where attempts are made to seek the lowest possible set of variables that are still able to achieve a high level of prediction accuracy; in other words, there is a need to generate the most parsimonious solution when the number of input variables is huge but the number of samples/objects are smaller. Here, we compare several different variable selection approaches in order to ascertain which of these are ideally suited to achieve this goal. All variable selection approaches were applied to the analysis of a common set of metabolomics data generated by Curie-point pyrolysis mass spectrometry (Py-MS), where the goal of the study was to classify the Gram-positive bacteria Bacillus. These approaches include stepwise forward variable selection, used for linear discriminant analysis (LDA); variable importance for projection (VIP) coefficient, employed in partial least squares-discriminant analysis (PLS-DA); support vector machines-recursive feature elimination (SVM-RFE); as well as the mean decrease in accuracy and mean decrease in Gini, provided by random forests (RF). Finally, a double cross-validation procedure was applied to minimize the consequence of overfitting. The results revealed that RF with its variable selection techniques and SVM combined with SVM-RFE as a variable selection method, displayed the best results in comparison to other approaches.

Antitags: SERS-encoded nanoparticle assemblies that enable single-spot multiplex protein detection

Simultaneous detection of multiple proteins on a single spot can be efficiently achieved by using multiplexed surface-enhanced Raman spectroscopy (SERS)-encoded nanoparticle 'antitags' consisting of poly(ethylene glycol) (PEG)-protected silver dimers (and higher aggregates) and antibody-tagging entities. The effective SERS-based multivariate deconvolution approach guarantees an accurate and successful distinguishable identification of single and multiple proteins in complex samples. Their potential application in multiplexed SERS bioimaging technology can be easily envisaged.

Quantitative and sensitive RNA based detection of Bacillus spores

The fast and reliable detection of bacterial spores is of great importance and still remains a challenge. Here we describe a direct RNA-based diagnostic method for the specific detection of viable bacterial spores which does not depends on an enzymatic amplification step and therefore is directly appropriate for quantification. The procedure includes the following steps: (i) heat activation of spores, (ii) germination and enrichment cultivation, (iii) cell lysis, and (iv) analysis of 16S rRNA in crude cell lysates using a sandwich hybridization assay. The sensitivity of the method is dependent on the cultivation time and the detection limit; it is possible to detect 10 spores per ml when the RNA analysis is performed after 6 h of enrichment cultivation. At spore concentrations above 10(6) spores per ml the cultivation time can be shortened to 30 min. Total analysis times are in the range of 2-8 h depending on the spore concentration in samples. The developed procedure is optimized at the example of Bacillus subtilis spores but should be applicable to other organisms. The new method can easily be modified for other target RNAs and is suitable for specific detection of spores from known groups of organisms.

Raman spectroscopy in the analysis of food and pharmaceutical nanomaterials

Raman scattering is an inelastic phenomenon. Although its cross section is very small, recent advances in electronics, lasers, optics, and nanotechnology have made Raman spectroscopy suitable in many areas of application. The present article reviews the applications of Raman spectroscopy in food and drug analysis and inspection, including those associated with nanomaterials. Brief overviews of basic Raman scattering theory, instrumentation, and statistical data analysis are also given. With the advent of Raman enhancement mechanisms and the progress being made in metal nanomaterials and nanoscale metal surfaces fabrications, surface enhanced Raman scattering spectroscopy has become an extra sensitive method, which is applicable not only for analysis of foods and drugs, but also for intracellular and intercellular imaging. A Raman spectrometer coupled with a fiber optics probe has great potential in applications such as monitoring and quality control in industrial food processing, food safety in agricultural plant production, and convenient inspection of pharmaceutical products, even through different types of packing. A challenge for the routine application of surface enhanced Raman scattering for quantitative analysis is reproducibility. Success in this area can be approached with each or a combination of the following methods: (1) fabrication of nanostructurally regular and uniform substrates; (2) application of statistic data analysis; and (3) isotopic dilution.

Simultaneous multiplexed quantification of nicotine and its metabolites using surface enhanced Raman scattering

We have developed a SERS approach that can simultaneously detect the drug nicotine along with its two major metabolites cotinine andtrans-3′-hydroxycotinine without recourse to lengthy chromatography.

Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool

The discovery of the Raman effect in 1928 not only aided fundamental understanding about the quantum nature of light and matter but also opened up a completely novel area of optics and spectroscopic research that is accelerating at a greater rate during the last decade than at any time since its inception. This introductory overview focuses on some of the most recent developments within this exciting field and how this has enabled and enhanced disease diagnosis and biomedical applications. We highlight a small number of stimulating high-impact studies in imaging, endoscopy, stem cell research, and other recent developments such as spatially offset Raman scattering amongst others. We hope this stimulates further interest in this already exciting field, by 'illuminating' some of the current research being undertaken by the latest in a very long line of dedicated experimentalists interested in the properties and potential beneficial applications of light.

Determination of ferric ions using surface-enhanced Raman scattering based on desferrioxamine-functionalized silver nanoparticles

A simple, robust and reproducible spectroscopic method based on surface-enhanced Raman scattering with nanomolar sensitivity has been developed for selective iron(iii) determination in aqueous solutions.