Feasibility of Raman spectroscopic identification of gall bladder cancer using extracellular vesicles extracted from bile

Extracellular vesicles (EVs), which are heterogeneous membrane-based vesicles with bilayer cell membrane structures, could be versatile biomarkers for the identification of diverse diseases including cancers. With this potential, this study has attempted the Raman spectroscopic identification of gall bladder (GB) cancer by directly measuring the EV solution extracted from human bile without further sample drying. For this purpose, bile samples were obtained from four normal individuals and 21 GB polyp, eight hepatocellular carcinoma (HCC), and five GB cancer patients, and EVs were extracted from each of the bile samples. The Raman peak shapes of the EVs extracted from the GB cancer samples, especially the relative intensities of peaks in the 1560-1340 cm-1 range, were dissimilar to those of the samples from the normal, GB polyp, and HCC groups. The intensity ratios of peaks at 1537 and 1453 cm-1 and at 1395 and 1359 cm-1 of the GB cancer samples were lower and higher, respectively, than those of the samples of the remaining three groups. The differences of peak intensity ratios were statistically significant based on the Mann-Whitney U test. DNA/RNA bases, amino acids, and bile salts contributed to the spectra of EVs, and their relative abundances seemed to vary according to the occurrence of GB cancer. The varied metabolite compositions and/or structures of EVs were successfully demonstrated by the dissimilar peak intensity ratios in the Raman spectra, thereby enabling the discrimination of GB cancer.

SERS for Detection of Proteinuria: A Comparison of Gold, Silver, Al Tape, and Silicon Substrates for Identification of Elevated Protein Concentration in Urine

Excessive protein excretion in human urine is an early and sensitive marker of diabetic nephropathy and primary and secondary renal disease. Kidney problems, particularly chronic kidney disease, remain among the few growing causes of mortality in the world. Therefore, it is important to develop an efficient, expressive, and low-cost method for protein determination. Surface enhanced Raman spectroscopy (SERS) methods are potential candidates to achieve these criteria. In this paper, a SERS method was developed to distinguish patients with proteinuria from the healthy group. Commercial gold nanoparticles (AuNPs) with diameters of 60 nm and 100 nm, and silver nanoparticles (AgNPs) with a diameter of 100 nm were tested on the surface of four different substrates including silver and gold films, silicon, and aluminum tape. SERS spectra were acquired from 111 unique human urine samples prepared and measured for each of the seven different nanoparticle plus substrate combinations. Data analysis by the PCA-LDA algorithm and the ROC curves gave results for the diagnostic figures of merits. The best sensitivity, specificity, accuracy, and AUC were 0.91, 0.84, 0.88, and 0.94 for the set with 100 nm Au NPs on the silver substrate, respectively. Among the three metal substrates, the substrate with AuNPs and Al tape performed slightly worse than the other three substrates, and 100 nm gold nanoparticles on average produced better results than 60 nm gold nanoparticles. The 60 nm diameter AuNPs and silicon, which is about one order of magnitude more cost-effective than AuNPs and gold film, showed a relative performance close to the performance of 60 nm AuNPs and Au film (average AUC 0.88 (Si) vs. 0.89 (Au)). This is likely the first reported application of unmodified silicon in SERS substrates applied for direct detection of proteins in any biofluid, particularly in urine. These results position silicon and AuNPs@Si in particular as a perspective SERS substrate for direct urine analysis, including clinical diagnostics of proteinuria.

In situ identification of environmental microorganisms with Raman spectroscopy

Microorganisms in natural environments are crucial in maintaining the material and energy cycle and the ecological balance of the environment. However, it is challenging to delineate environmental microbes' actual metabolic pathways and intraspecific heterogeneity because most microorganisms cannot be cultivated. Raman spectroscopy is a culture-independent technique that can collect molecular vibration profiles from cells. It can reveal the physiological and biochemical information at the single-cell level rapidly and non-destructively in situ. The first part of this review introduces the principles, advantages, progress, and analytical methods of Raman spectroscopy applied in environmental microbiology. The second part summarizes the applications of Raman spectroscopy combined with stable isotope probing (SIP), fluorescence in situ hybridization (FISH), Raman-activated cell sorting and genomic sequencing, and machine learning in microbiological studies. Finally, this review discusses expectations of Raman spectroscopy and future advances to be made in identifying microorganisms, especially for uncultured microorganisms.

Terahertz, infrared and Raman absorption spectra of tyrosine enantiomers and racemic compound

The application of terahertz (THz)-based techniques in biomolecule study is very promising but still in its infancy. In the present work, we employed THz time-domain spectroscopy (THz-TDS) and THz time-domain attenuated total reflection (THz-TD-ATR) spectroscopy to investigate the properties of tyrosine (Tyr) enantiomers (L- and D-Tyr) and racemate (DL-Tyr) in solid state and aqueous solutions, respectively. THz absorption spectra of solid L- and D-Tyr show similar absorption spectra with peaks at 0.95, 1.92, 2.06 and 2.60 THz, which are obviously different from the spectrum of DL-Tyr with peaks at 1.5, 2.15 and 2.40 THz. In contrast, although THz absorption spectra of L-Tyr solution and D-Tyr solution are similar and different from the spectrum of DL-Tyr solution, both of them have no observable peaks. Interestingly, it was found that the solution containing equal amounts of L- and D-Tyr has a similar spectrum as that of DL-Tyr solution, as far as the mass concentrations of the two types of solutions are kept the same. On other hand, solid L-, D- and DL-Tyr were also investigated with infrared spectroscopy and Raman spectroscopy, respectively. The results show that the spectra of L- and D-Tyr can be regarded the same but they are slightly different from the spectrum of DL-Tyr. With the aid of principal component analysis (PCA), the difference between L-/D-Tyr and DL-Tyr can be confirmed without any ambiguity. Overall, this work systematically interrogated and evaluated the performance of THz-based techniques in the detection of the chirality of tyrosine.

Intelligent spectral algorithm for pigments visualization, classification and identification based on Raman spectra

Raman spectroscopy is a molecular vibrational spectroscopic technique has developed rapidly in recent years, especially in rapid field detection. In this paper, we discuss the Raman spectral pretreatment method and classification algorithm by using nearly 300 pigments spectral data as an example. Here, more than 5 kinds of classification algorithms such as SVM, KNN, ANN and et al are used to sovle the problem of pigments visualization, classification and identification via Raman spectral, and the results show that most of the algorithms fit well, with an accuracy of 90%. Moreover, SNR (Signal to noise ratio) is introduced to evaluate the stability of our algorithm. When the SNR is low, the accuracy of the algorithm decreases sharply. When the SNR was 1, the accuracy rate reached the highest value of 39.46%. In order to slove this problem, the flattopwin, hanning, blackman algorithm was introduced to denoise the signal with low SNR, even when SNR = 1, the signal is 80% accurate. It is proved that in the extreme case of this application, the algorithm still maintains good accuracy, and our research pave the way to use interlligent algorithms to solve the problems in the fields of Raman spectral detection.

Chiral discrimination of amino acids using phosphorene assisted graphene-enhanced Raman spectroscopy

Discrimination of enantiomers poses a scientific challenge as the chemical and physical properties of enantiomers are nearly identical. The chiral analysis is usually performed by separation techniques, including chromatography, electrophoresis, or optical instrumentation based on an interaction of the analyzed sample with a polarized beam of light. Here we present a novel method for a chiral screening based on a combination of the black phosphorus@Graphene nanocomposite and Raman spectroscopy. The nanocomposite allows to enhance the Raman signal with factors higher than 100 asymmetrically and provide altered signals for mixtures containing varying enantiomeric ratios of target compounds. Tryptophan, Phenylalanine, DOPA, Isoleucine, and Leucine were selected as model compounds; the method allows us to discriminate between mixtures with 10, 25, 50, 75, and 100% enantiomeric purity.

Monitor Ionizing Radiation-Induced Cellular Responses with Raman Spectroscopy, Non-Negative Matrix Factorization, and Non-Negative Least Squares

Radiation therapy (RT) is one of the most commonly prescribed cancer treatments. New tools that can accurately monitor and evaluate individual patient responses would be a major advantage and lend to the implementation of personalized treatment plans. In this study, Raman spectroscopy (RS) was applied to examine radiation-induced cellular responses in H460, MCF7, and LNCaP cancer cell lines across different dose levels and times post-irradiation. Previous Raman data analysis was conducted using principal component analysis (PCA), which showed the ability to extract biological information of glycogen. In the current studies, the use of non-negative matrix factorization (NMF) allowed for the discovery of multiplexed biological information, specifically uncovering glycogen-like and lipid-like component bases. The corresponding scores of glycogen and previously unidentified lipids revealed the content variations of these two chemicals in the cellular data. The NMF decomposed glycogen and lipid-like bases were able to separate the cancer cell lines into radiosensitive and radioresistant groups. A further lipid phenotype investigation was also attempted by applying non-negative least squares (NNLS) to the lipid-like bases decomposed individually from three cell lines. Qualitative differences found in lipid weights for each lipid-like basis suggest the lipid phenotype differences in the three tested cancer cell lines. Collectively, this study demonstrates that the application of NMF and NNLS on RS data analysis to monitor ionizing radiation-induced cellular responses can yield multiplexed biological information on bio-response to RT not revealed by conventional chemometric approaches.

Principal component analysis to enhance enantioselective Raman spectroscopy

Enantioselective Raman (esR) spectroscopy is an innovative technique with a high potential for online process monitoring in chiral media, e.g. in the pharmaceutical industry. A prerequisite for an effective application is to combine the experimental approach with suitable concepts for data analysis. In this work, we present a chemometric approach to analyze the esR spectra recorded in an automatized polarization-resolved Raman set-up. It is demonstrated that the proposed method is capable of distinguishing between the enantiomers of the chiral alcohol 4-methylpentan-2-ol in a fully unsupervised fashion. Furthermore, it is shown that the difficulty of facing only small intensity differences between the esR spectra of the enantiomers can be overcome by feeding difference spectra between the pure enantiomers and the racemate into the principal component analysis (PCA) algorithm. The enantiomers are clearly discriminable along the first principal component.

Enantioselective Raman spectroscopy (esR) for distinguishing between the enantiomers of 2-butanol

The first experimental application of enantioselective Raman spectroscopy (esR) is demonstrated using the example of the chiral alcohol 2-butanol. Samples of the neat enantiomers and the racemic mixture were analyzed in a self-built Raman set-up. The Raman spectrum allows the discrimination of the chemical species. It is shown that the optical rotation of a Raman peak with a small depolarization ratio can be measured. In addition, without any sample modification, e.g. chiral solvent, the enantiomers are distinguishable at a suitable half-wave retarder angle detecting only the vertically polarized component of the Raman signal.