Therapeutic prognosis of prostate cancer using surface-enhanced Raman scattering of patient urine and multivariate statistical analysis

Surface-enhanced Raman scattering (SERS) is highly sensitive and label-free analytical technique based on Raman spectroscopy aided by field-multiplying plasmonic nanostructures. We report the use of SERS measurements of patient urine in conjunction with biostatistical algorithms to assess the treatment response of prostate cancer (PCa) in 12 recurrent (Re) and 63 nonrecurrent (NRe) patient cohorts. Multiple Raman spectra are collected from each urine sample using monodisperse silver nanoparticles (AgNPs) for Raman signal enhancement. Genetic algorithms-partial least squares-linear discriminant analysis (GA-PLS-LDA) was employed to analyze the Raman spectra. Comprehensive GA-PLS-LDA analyses of these Raman spectral features (p = 3.50 × 10⁻¹⁶ ) yield an accuracy of 86.6%, sensitivity of 86.0%, and specificity 87.1% in differentiating the Re and NRe cohorts. Our study suggests that SERS combined with multivariate GA-PLS-LDA algorithm can potentially be used to detect and monitor the risk of PCa relapse and to aid with decision-making for optimal intermediate secondary therapy to recurred patients.     

Gastric cancer detection based on blood plasma surface-enhanced Raman spectroscopy excited by polarized laser light

We have recently applied surface-enhanced Raman spectroscopy (SERS) for blood plasma analysis for non-invasive nasopharyngeal cancer detection and obtained good preliminary results. The aim of this study was to develop a more robust SERS spectroscopy based blood plasma analysis method for non-invasive gastric cancer detection. The effect of different laser polarizations (non-polarized, linear-polarized, right-handed circularly polarized, and left-handed circularly polarized) on blood plasma SERS spectroscopy was explored for the first time. Silver nanoparticles as the SERS-substrate were directly mixed with blood plasma to enhance the Raman scattering of various biomolecular constituents. High quality SERS spectra were obtained using a fiber optic probe and a dispersive type near infrared Raman system. Blood plasma samples from gastric cancer patients (n=32) and healthy subjects (n=33) were analyzed. The diagnostic performance for differentiating gastric cancer plasma from normal plasma was evaluated. Principal component analysis combined with linear discriminant analysis (LDA) of the obtained spectral data was used to develop diagnostic algorithms. Classification results obtained from cross-validation of the LDA model based on the four spectral data sets of different laser polarizations demonstrated different diagnostic sensitivities and specificities: 71.9% and 72.7% for non-polarized laser excitation, 75% and 87.9% for linear-polarized laser excitation, 81.3% and 78.8% for right-handed circularly polarized laser excitation, 100% and 97% for left-handed circularly polarized laser excitation. The results from this exploratory study demonstrated that plasma SERS spectroscopy with left-handed circularly polarized laser excitation has great promise of becoming a clinically useful diagnostic tool for non-invasive gastric cancer detection.     

Rational design of thiolated polyenes as trifunctional Raman reporter molecules in surface‐enhanced Raman scattering nanotags for cytokine detection in a lateral flow assay

The characteristic vibrational spectroscopic fingerprint of Raman reporter molecules adsorbed on noble metal nanoparticles is employed for the identification of target proteins by the corresponding surface‐enhanced Raman scattering (SERS) nanotag‐labeled antibodies. Here, we present the modular synthesis of thiolated polyenes with two to five C═C double bonds introduced via stepwise Wittig reactions. The experimental characterization of their electronic and vibrational properties is complemented by density functional theory calculations. Highly SERS‐active nanotags are generated by using the thiolated polyenes as Raman reporter molecules in Au/Au core/satellite supraparticles with multiple hot spots. The cytokines IL‐1β and IFN‐γ are detected in a duplex SERS‐based lateral flow assay on a nitrocellulose test strip by Raman microscopy. The thiolated polyenes are suitable for use in immuno‐SERS applications such as point‐of‐care testing as well as cellular and tissue imaging.     

Organelle specific simultaneous Raman/green fluorescence protein microspectroscopy for living cell physicochemical studies

We demonstrate a novel bio‐spectroscopic technique, “simultaneous Raman/GFP microspectroscopy”. It enables organelle specific Raman microspectroscopy of living cells. Fission yeast, Schizosaccharomyces pombe, whose mitochondria are green fluorescence protein (GFP) labeled, is used as a test model system. Raman excitation laser and GFP excitation light irradiate the sample yeast cells simultaneously. GFP signal is monitored in the anti‐Stokes region where interference from Raman scattering is negligibly small. Of note, 13 568 Raman spectra measured from different points of 19 living yeast cells are categorized according to their GFP fluorescence intensities, with the use of a two‐component multivariate curve resolution with alternate least squares (MCR‐ALS) analysis in the anti‐Stokes region. This categorization allows us to know whether or not Raman spectra are taken from mitochondria. Raman spectra specific to mitochondria are obtained by an MCR‐ALS analysis in the Stokes region of 1389 strongly GFP positive spectra. Two mitochondria specific Raman spectra have been obtained. The first one is dominated by protein Raman bands and the second by lipid Raman bands, being consistent with the known molecular composition of mitochondria. In addition, the second spectrum shows a strong band of ergosterol at 1602 cm^?1, previously reported as “Raman spectroscopic signature of life of yeast.”     

Surface‐enhanced Raman scattering analysis of serum albumin via adsorption‐exfoliation on hydroxyapatite nanoparticles for noninvasive cancers screening

Combining serum albumin via adsorption‐exfoliation on hydroxyapatite particles (HAp) with surface‐enhanced Raman scattering (SERS), we developed a novel quantitative analysis of albumin method from blood serum for cancers screening applications. The quantitatively analysis obtained by our HAp method had a good linear relationship from 1 to 10 g/dL, and the lower limit of detection was less than the albumin prognostic factor for disease (3.5 g/dL). Serum albumin was adsorbed and exfoliated by HAp from serum samples of liver cancer patients, breast cancer patients and healthy volunteers and mixed with silver colloids to perform SERS spectral analysis. Based on the PLS‐SVM algorithm, the diagnostic accuracies of liver cancer patients and breast cancer patients were 100% and 96.68%, respectively. Moreover, this algorithm successfully predicted the unidentified subjects with a diagnostic accuracy of 93.75%. This exploratory work demonstrated that HAp‐adsorbed‐exfoliated serum proteins combined with SERS spectroscopy has great potential for cancer screening.     

Reflective FT-NIR and SERS studies of HER-II breast cancer biomarker using plasmonic-active nanostructured thin film immobilized oriented antibody

We describe the fabrication of plasmonic-active nanostructured thin film substrate as a label-free surface-enhanced Raman scattering (SERS)-based biosensor immobilized covalently with monoclonal HER-II antibody (mAb) to detect overexpressed HER-II as a biomarker in breast cancer serum (BCS). Oriented conjugation of mAb via hydrazone linkage to provide higher mAb accessibility was characterized by UV-vis and reflective Fourier transform near-infrared (FT-NIR) spectroscopic techniques. The interaction of BCS with mAb was studied by FT-NIR and nonresonant SERS at 637 nm. The results showed detection of glycoprotein content at different laser powers including a rise in amino acid and glycan content with varying results at higher power. With nonresonant SERS we observed nonlinear behavior of peak intensity. Analysis of variance was implemented to determine the effect of laser power which was found not to be a contributing factor. However, at the nanoscale, factors including the heating effect and aggregation of molecules can contribute to the nonlinearity of peak intensity.     

Label‐free diagnosis for colorectal cancer through coffee ring‐assisted surface‐enhanced Raman spectroscopy on blood serum

Surface‐enhanced Raman spectroscopy (SERS) is garnering considerable attention for the swift diagnosis of pathogens and abnormal biological status, that is, cancers. In this work, a simple, fast and inexpensive optical sensing platform is developed by the design of SERS sampling and data analysis. The pretreatment of spectral measurement employed gold nanoparticle colloid mixing with the serum from patients with colorectal cancer (CRC). The droplet of particle‐serum mixture formed coffee‐ring‐like region at the rim, providing strong and stable SERS profiles. The obtained spectra from cancer patients and healthy volunteers were analyzed by unsupervised principal component analysis (PCA) and supervised machine learning model, such as support‐vector machine (SVM), respectively. The results demonstrate that the SVM model provides the superior performance in the classification of CRC diagnosis compared with PCA. In addition, the values of carcinoembryonic antigen from the blood samples were compiled with the corresponding SERS spectra for SVM calculation, yielding improved prediction results.     

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.

     

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning

Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides rapid and accurate detection of pathogens. Raman spectrum of single cells serves as the “fingerprint” of the cell, revealing its metabolic characteristics. Rapid identification of pathogens can be achieved by combining Raman spectroscopy and deep learning. Traditional classification techniques frequently require lots of data for training, which is time costing to collect Raman spectra. For trace samples and strains that are difficult to culture, it is difficult to provide an accurate classification model. In order to reduce the number of samples collected and improve the accuracy of the classification model, a new pathogen detection method integrating Raman spectroscopy, variational auto-encoder (VAE), and long short-term memory network (LSTM) is proposed in this paper. We collect the Raman signals of pathogens and input them to VAE for training. VAE will generate a large number of Raman spectral data that cannot be distinguished from the real spectrum, and the signal-to-noise ratio is higher than that of the real spectrum. These spectra are input into the LSTM together with the real spectrum for training, and a good classification model is obtained. The results of the experiments reveal that this method not only improves the average accuracy of pathogen classification to 96.9% but also reduces the number of Raman spectra collected from 1000 to 200. With this technology, the number of Raman spectra collected can be greatly reduced, so that strains that are difficult to culture or trace can be rapidly identified.     

Raman and surface enhanced Raman spectroscopy of 2,2,5,5-tetramethyl-3-pyrrolin-1-yloxy-3-carboxamide labeled proteins: bovine serum albumin and cytochrome c

2,2,5,5-Tetramethyl-3-pyrrolin-1-yloxy-3-carboxamide (tempyo) labeled bovine serum albumin and cytochrome c at different pH values were prepared and investigated using Raman-resonance Raman (RR) spectroscopy and surface enhanced Raman scattering (SERS) spectroscopy. The Raman spectra of tempyo labeled proteins in the pH 6.7-11 range were compared to those of the corresponding free species. The SERS spectra were interpreted in terms of the structural changes of the tempyo labeled proteins adsorbed on the silver colloidal surface. The tempyo spin label was found to be inactive in the Raman-RR and SERS spectra of the proteins. The alpha-helix conformation was concluded to be more favorable as the SERS binding site of bovine serum albumin. In the cytochrome c the enhancement of the bands assigned to the porphyrin macrocycle stretching mode allowed the supposition of the N-adsorption onto the colloidal surface.     

Molecular conformation changes along the malignancy revealed by optical nanosensors

An interdisciplinary approach employing functionalized nanoparticles and ultrasensitive spectroscopic techniques is reported here to track the molecular changes in early stage of malignancy. Melanoma tissue tracking at molecular level using both labelled and unlabelled silver and gold nanoparticles has been achieved using surface enhanced Raman scattering (SERS) technique. We used skin tissue from ex vivo mice with induced melanoma. Raman and SERS molecular characterization of melanoma tissue is proposed here for the first time. Optical nanosensors based on Ag and Au nanoparticles with chemisorbed cresyl violet molecular species as labels revealed sensitive capability to tissues tagging and local molecular characterization. Sensitive information originating from surrounding native biological molecules is provided by the tissue SERS spectra obtained either with visible or NIR laser line. Labelled nanoparticles introduced systematic differences in tissue response compared with unlabelled ones, suggesting that the label functional groups tag specific tissue components revealed by proteins or nucleic acids bands. Vibrational data collected from tissue are presented in conjunction with the immunohistochemical analysis. The results obtained here open perspectives in applied plasmonic nanoparticles and SERS for the early cancer diagnostic based on the appropriate spectral databank.     

SERS‐based biosensor for Alzheimer disease evaluation through the fast analysis of human serum

Alzheimer disease (AD) is the most common form of dementia in the elderly, progressively affecting the cognitive functions with a complex diagnostic procedure that limits the time for a prompt intervention. In this study we optimized a reliable protocol for the analysis of AD patients and healthy subjects' serum using the Surface Enhanced Raman Spectroscopy (SERS), taking into consideration the effect of different variables on the final spectra, analyzed and compared through multivariate analysis and correlated with hippocampus volume. As results, we demonstrated a statistical difference between the spectra collected from the two investigated groups, with an accuracy, precision and specificity of respectively 83%, 86%, and 86%. The correlation of these data with those obtained from MRI, demonstrated a direct correlation between Raman spectra and hippocampus degeneration showing the Raman Spectroscopy (RS) as a potential tool for the monitoring of AD progression and rehabilitation treatments.     

Inside Cover: Localization of PD‐L1 on single cancer cells by iSERS microscopy with Au/Au core/satellite nanoparticles (J. Biophotonics 3/2020)

iSERS (SERS=surface‐enhanced Raman scattering) microscopy is an emerging Raman‐based staining technique for the selective localization of target proteins on cells and tissues using antibody‐ SERS nanotag conjugates. In this contribution we demonstrate the feasibility of iSERS for imaging of programmed cell death‐ligand 1 (PD‐L1), an important predictive biomarker, on single SkBr‐3 breast cancer cells. Further details can be found in the article by Elzbieta Stepula, Matthias König, Xin‐Ping Wang, et al. ( e201960034 ).

     

Raman spectroscopy investigation of biological materials by use of etched and silver coated glass fiber tips

The results for surface enhanced Raman scattering (SERS) studies on biological samples are reported. Etched and silver coated glass fiber tips were used as a SERS substrate. This method enabled the recording of spectra of biological samples, such as plant tissue or microbiological cells, with a high spatial resolution. Because of the low laser power used with the fiber tips, it was even possible to investigate tissues that are very sensitive toward laser power as it is used in a common micro-Raman setup.     

SERS观察在Pd OECC薄膜中β-胡萝卜素的基频和高阶拉曼模

利用有极高检测灵敏度的表面增强拉曼散射(SERS)技术,对吸附在银镜表面上的浓度较低的纯化的放氧核心复合物(Pd OECC)薄层进行了频移在250～3 100 cm-1范围内的拉曼光谱测量,除得到β-胡萝卜素分子的基频拉曼振动模外,在高频端还得到了许多弱峰.根据泛音和组合谱带选择定则分析,这些振动模式来自β-胡萝卜素分子的高阶拉曼光谱.还进行了Pd OECC在强光破坏前后的SERS光谱研究.在强光照射下,β-胡萝卜素分子的SERS光谱的散射强度明显降低,且线宽增加,说明强光照射不但改变了β-胡萝卜素的构象,而且也改变了β-胡萝卜素分子所处的微环境.其结果与强光照射前后吸收光谱的变化一致.另外,没有观察到Pd OECC薄层与银镜相互作用的其他新振动峰或Pd OECC中其他振动峰峰型的变化,可见Pd OECC在银镜表面保持原来的状态.这证明SERS技术在光合作用光破坏机理研究中的可行性.     

Identification of aqueous pollen extracts using surface enhanced Raman scattering (SERS) and pattern recognition methods

Aqueous pollen extracts of varying taxonomic relations were analyzed with surface enhanced Raman scattering (SERS) by using gold nanoparticles in aqueous suspensions as SERS substrate. This enables a selective vibrational characterization of the pollen water soluble fraction (mostly cellular components) devoid of the spectral contributions from the insoluble sporopollenin outer layer. The spectra of the pollen extracts are species‐specific, and the chemical fingerprints can be exploited to achieve a classification that can distinguish between different species of the same genus. In the simple experimental procedure, several thousands of spectra per species are generated. Using an artificial neural network (ANN), it is demonstrated that analysis of the intrinsic biochemical information of the pollen cells in the SERS data enables the identification of pollen from different plant species at high accuracy. The ANN extracts the taxonomically‐relevant information from the data in spite of high intra‐species spectral variation caused by signal fluctuations and preparation specifics. The results show that SERS can be used for the reliable characterization and identification of pollen samples. They have implications for improved investigation of pollen physiology and for allergy warning.

     

Nanoplasmonic sensor for foodborne pathogens detection. Towards development of ISO‐SERS methodology for taxonomic affiliation of Campylobacter spp.

According to EU summary report on zoonoses, zoonotic agents and food‐borne outbreaks in 2017, Campylobacter was the most commonly reported gastrointestinal bacterial pathogen in humans in the EU. Unfortunately, the standard methods for the detection of thermotolerant Campylobacter spp. in foods are time‐consuming. Additionally, the qualified staff is obligatory. For this reason, new methods of pathogens detection are needed. The present work demonstrates that surface‐enhanced Raman scattering (SERS) is a reliable and fast method for detection of Campylobacter spp. in food samples. The proposed method combines the SERS measurements performed on an Ag/Si substrate with two initial steps of the ISO standard procedure. Finally, the principal component analysis (PCA) allows for statistical classification of the studied bacteria. By applying the proposed ISO‐SERS‐PCA method in the case of Campylobacter bacteria the total detection time may be reduced from 7 to 8 days required by ISO method to 3 to 4 days in the case of SERS‐based approach.     

Determination of inclusion depth in ex vivo animal tissues using surface enhanced deep Raman spectroscopy

This work presents recent developments in spatially offset and transmission Raman spectroscopy for noninvasive detection and depth prediction of a single SERS inclusion located deep inside ex vivo biological tissues. The concept exploits the differential attenuation of Raman bands brought about by their different absorption due to tissue constituents enabling to predict the inclusion depth. Four different calibration models are tested and evaluated to predict the depth of surface enhanced Raman scattering labelled nanoparticles, within an up to 40 mm slab of porcine tissue. An external measurement carried out in transmission mode, with a noninvasively built model on the analysed sample, is shown to be insensitive to variations of the overall thickness of the tissue yielding an average root‐mean‐square error of prediction of 6.7%. The results pave the way for future noninvasive deep Raman spectroscopy in vivo enabling to localise cancer biomarkers for an early diagnosis of multiple diseases.      

Surface enhanced Raman scattering for narcotic detection and applications to chemical biology

Raman spectroscopy is rapidly finding favour for applications in the life science because of the ease with which it can be used to extract significant data from tissue and cells. However, the Raman effect is an inherently weak effect, which hinders the analysis of low concentration analytes. Raman sensitivity can be improved via the surface enhanced Raman scattering (SERS) effect. In SERS, Raman spectra are dramatically amplified when a molecule is adsorbed onto nano-roughened noble metal surfaces such as silver and gold. The degree of enhancement enables single-molecule detection, which offers the potential for the unambiguous identification of analytes at concentrations that are useful in both a forensic and a chemical biology context. Here we discuss some of the practical applications of SERS to both low-level narcotic detection, and how this can be applied to chemical biology.     

SERS-based sensor for direct L-selectin level determination in plasma samples as alternative method of tumor detection

Selectin ligands are present on the surface of tumor cells, for this reason lowering the L-selectin level in the blood and lymph can indicate presence of the tumor. Therefore the selectin level in the plasma are potential targets for anticancer therapy. We demonstrate the surface enhanced Raman spectroscopy (SERS)-based sensor for the determination of L-selectin level in biological samples that can be used in medical diagnosis. The combination of SERS with the method of multivariate analysis as principle component analysis (PCA) allows to strengthen the presented data analysis. The loadings of PCA permit to indicate those vibration modes, that are the most important for the assumed identification (bands at 1574, 1450, 1292 cm⁻¹). Two bands at 1286 and 1580 cm⁻¹ were selected for the determination of the calibration curve (bands intensities I₁₂₈₆/I₁₅₈₀ ratio). The L-selectin level of biological samples can be read, directly from the calibration curve. The presented sensor is as a sensitive tool with good specificity and selectivity of L-selectin, even in the case of coexistence of P- and E-selectin.