Micro-Raman spectroscopy detects individual neoplastic and normal hematopoietic cells

Current methods for identifying neoplastic cells and discerning them from their normal counterparts are often nonspecific, slow, biologically perturbing, or a combination thereof. Here, we show that single-cell micro-Raman spectroscopy averts these shortcomings and can be used to discriminate between unfixed normal human lymphocytes and transformed Jurkat and Raji lymphocyte cell lines based on their biomolecular Raman signatures. We demonstrate that single-cell Raman spectra provide a highly reproducible biomolecular fingerprint of each cell type. Characteristic peaks, mostly due to different DNA and protein concentrations, allow for discerning normal lymphocytes from transformed lymphocytes with high confidence (p < 0.05). Spectra are also compared and analyzed by principal component analysis to demonstrate that normal and transformed cells form distinct clusters that can be defined using just two principal components. The method is shown to have a sensitivity of 98.3% for cancer detection, with 97.2% of the cells being correctly classified as belonging to the normal or transformed type. These results demonstrate the potential application of confocal micro-Raman spectroscopy as a clinical tool for single cancer cell detection based on intrinsic biomolecular signatures, therefore eliminating the need for exogenous fluorescent labeling.     

Micro-Raman spectroscopy of silver nanoparticle induced stress on optically-trapped stem cells

We report here results of a single-cell Raman spectroscopy study of stress effects induced by silver nanoparticles in human mesenchymal stem cells (hMSCs). A high-sensitivity, high-resolution Raman Tweezers set-up has been used to monitor nanoparticle-induced biochemical changes in optically-trapped single cells. Our micro-Raman spectroscopic study reveals that hMSCs treated with silver nanoparticles undergo oxidative stress at doping levels in excess of 2 μg/ml, with results of a statistical analysis of Raman spectra suggesting that the induced stress becomes more dominant at nanoparticle concentration levels above 3 μg/ml.     

拉曼光谱检测微生物的研究方法和进展北大核心

快速准确地识别和鉴定微生物对于环境科、食品质量以及医学诊断等领域研究至关重要。拉曼光谱(Raman spectroscopy)已经被证明是一种能够实现微生物快速诊断的新技术,在提供微生物指纹图谱信息的同时,能够快速、非标记、无创、敏感地在固体和液体环境中实现微生物单细胞水平的检测。本文简单介绍了拉曼光谱的基本概念和原理,重点综述了拉曼光谱微生物检测应用中的样品处理方法及光谱数据处理方法。除此之外,本文概括了拉曼光谱在细菌、病毒和真菌中的应用,其中单独概括了拉曼在细菌快速鉴定和抗生素药敏检测中的应用。最后,本文阐述了拉曼光谱在微生物检测中的挑战和展望。     

Identification of water-conditioned Pseudomonas aeruginosa by Raman microspectroscopy on a single cell level

The identification of Pseudomonas aeruginosa from samples of bottled natural mineral water by the analysis of subcultures is time consuming and other species of the authentic Pseudomonas group can be a problem. Therefore, this study aimed to investigate the influence of different aquatic environmental conditions (pH, mineral content) and growth phases on the cultivation-free differentiation between water-conditioned Pseudomonas spp. by applying Raman microspectroscopy. The final dataset was comprised of over 7500 single-cell Raman spectra, including the species Pseudomonas aeruginosa, P. fluorescens and P. putida, in order to prove the feasibility of the introduced approach. The collection of spectra was standardized by automated measurements of viable stained bacterial cells. The discrimination was influenced by the growth phase at the beginning of the water adaptation period and by the type of mineral water. Different combinations of the parameters were tested and they resulted in accuracies of up to 85% for the identification of P. aeruginosa from independent samples by applying chemometric analysis.     

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.     

基于单细菌共焦拉曼光谱的细菌快速检测

【背景】目前利用共焦拉曼光谱技术进行成像和成分鉴别方面的研究较多,但如何快速检测与鉴别多种细菌方面的研究较少。【目的】基于共焦拉曼光谱技术,建立一种在单细菌水平上实现病原微生物快速分类鉴定的方法。【方法】以大肠杆菌为研究对象,利用共焦拉曼光谱技术在单细菌水平上进行了激发波长的优化试验,并研究了大肠杆菌存放时间对单细菌拉曼光谱信息的影响。同时,对白色葡萄球菌、大肠杆菌、金黄色葡萄球菌、沙门氏菌和铜绿假单胞菌进行了共焦拉曼光谱测试,并对5种细菌进行单细菌拉曼光谱的归属分析,设计共焦拉曼光谱技术结合支持向量机(support vector machine,SVM)模型学习算法,进行了5种细菌的快速分类鉴别。【结果】对于单细菌拉曼光谱探测,532、633和785 nm这3种常见的拉曼探测波长中,532 nm具有更好的激发效率和光谱信噪比。结合SVM模型对5种细菌的识别分类,SVM模型的灵敏度和特异性达到了96.00%以上,整体准确率为98.25%。不同存放时间下大肠杆菌拉曼光谱的重复性和稳定性都很好,且SVM模型匹配率均在90.00%以上。【结论】单细菌拉曼光谱结合SVM模型可对5种细菌进行快...     

Raman Tweezers Spectroscopy of Live,Single Red and White Blood Cells

An optical trap has been combined with a Raman spectrometer to make high-resolution measurements of Raman spectra of optically-immobilized, single, live red (RBC) and white blood cells (WBC) under physiological conditions. Tightly-focused, near infrared wavelength light (1064 nm) is utilized for trapping of single cells and 785 nm light is used for Raman excitation at low levels of incident power (few mW). Raman spectra of RBC recorded using this high-sensitivity, dual-wavelength apparatus has enabled identification of several additional lines; the hitherto-unreported lines originate purely from hemoglobin molecules. Raman spectra of single granulocytes and lymphocytes are interpreted on the basis of standard protein and nucleic acid vibrational spectroscopy data. The richness of the measured spectrum illustrates that Raman studies of live cells in suspension are more informative than conventional micro-Raman studies where the cells are chemically bound to a glass cover slip.     

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.     

Detection of Vero Cells Infected with Herpes Simplex Types 1 and 2 and Varicella Zoster Viruses Using Raman Spectroscopy and Advanced Statistical Methods

Of the eight members of the herpes family of viruses, HSV1, HSV2, and varicella zoster are the most common and are mainly involved in cutaneous disorders. These viruses usually are not life-threatening, but in some cases they might cause serious infections to the eyes and the brain that can lead to blindness and possibly death. An effective drug (acyclovir and its derivatives) is available against these viruses. Therefore, early detection and identification of these viral infections is highly important for an effective treatment. Raman spectroscopy, which has been widely used in the past years in medicine and biology, was used as a powerful spectroscopic tool for the detection and identification of these viral infections in cell culture, due to its sensitivity, rapidity and reliability. Our results showed that it was possible to differentiate, with a 97% identification success rate, the uninfected Vero cells that served as a control, from the Vero cells that were infected with HSV-1, HSV-2, and VZV. For that, linear discriminant analysis (LDA) was performed on the Raman spectra after principal component analysis (PCA) with a leave one out (LOO) approach. Raman spectroscopy in tandem with PCA and LDA enable to differentiate among the different herpes viral infections of Vero cells in time span of few minutes with high accuracy rate. Understanding cell molecular changes due to herpes viral infections using Raman spectroscopy may help in early detection and effective treatment.     

基于拉曼技术的单细胞生长检测方法

目的 单细胞生长检测可以更加科学地揭示微生物代谢变化的规律,为后期微生物工程应用提供指导。针对微生物生长应用于食品安全期和最佳食用期的精准检测问题,本文提出一种基于拉曼技术的单细胞生长检测方法。方法 首先,通过同步培养实验采集了枯草芽孢杆菌两个批次共900个单细胞拉曼光谱（SCRS）数据,其中600个用于训练和测试,另一批次300个用于模型验证。其次,基于主成分分析的特征关系矩阵,提出CP-SP特征评估方法以筛选SCRS特征用于模型检测。再基于XGBoost构建检测模型,并应用网格搜索和交叉验证对检测模型进行调优。最后,应用混淆矩阵、ROC曲线评估模型对细胞滞后期、对数期和稳定期的检测准确率、敏感性和特异性。结果 选用CP-SP筛选的第一、第二和第四主成分较特征贡献率前3个主成分的分类性能提高了3.1%,调优后的细胞生长检测模型测试准确率为96.0%,验证准确率为92.3%。结论 基于拉曼技术的单细胞生长检测方法能准确识别单细胞生长状态且具有较高的泛化能力,可为食品安全和保鲜制定精准调控机制提供科学指导。     

Resonance Raman spectroscopy in malaria research

In recent years, the field of Raman spectroscopy has witnessed a surge in technological development, with the incorporation of ultrasensitive, charge-coupled devices, improved laser sources and precision Rayleigh-filter systems. This has led to the development of sensitive confocal micro-Raman spectrometers and imaging spectrometers that are capable of obtaining high spatial-resolution spectra and images of subcellular components within single living cells. This review reports on the application of resonance micro-Raman spectroscopy to the study of malaria pigment (hemozoin), a by-product of hemoglobin catabolization by the malaria parasite, which is an important target site for antimalarial drugs. The review aims to briefly describe recent studies on the application of this technology, elucidate molecular and electronic properties of the malaria pigment and its synthetic analog β-hematin, provide insight into the mechanism of hemozoin formation within the food vacuole of the parasite, and comment on developing strategies for using this technology in drug-screening protocols.     

拉曼光谱在皮肤领域的研究进展

拉曼光谱是一种新型的光学检测技术,常用于材料鉴定。近年来,随着无创检测需求的增加,拉曼光谱逐渐应用于疾病诊断、物质鉴别等生物领域。综述了拉曼光谱在皮肤领域的研究进展,及其对皮肤组织成分鉴别和皮肤疾病诊断的价值,以期推动拉曼光谱广泛应用于皮肤病学的机理研究和临床诊断。     

Resonance Raman spectroscopy in malaria research

In recent years, the field of Raman spectroscopy has witnessed a surge in technological development, with the incorporation of ultrasensitive, charge-coupled devices, improved laser sources and precision Rayleigh-filter systems. This has led to the development of sensitive confocal micro-Raman spectrometers and imaging spectrometers that are capable of obtaining high spatial-resolution spectra and images of subcellular components within single living cells. This review reports on the application of resonance micro-Raman spectroscopy to the study of malaria pigment (hemozoin), a by-product of hemoglobin catabolization by the malaria parasite, which is an important target site for antimalarial drugs. The review aims to briefly describe recent studies on the application of this technology, elucidate molecular and electronic properties of the malaria pigment and its synthetic analog beta-hematin, provide insight into the mechanism of hemozoin formation within the food vacuole of the parasite, and comment on developing strategies for using this technology in drug-screening protocols.     

Detection of Receptor-Induced Glycoprotein Conformational Changes on Enveloped Virions by Using Confocal Micro-Raman Spectroscopy

Conformational changes in the glycoproteins of enveloped viruses are critical for membrane fusion, which enables viral entry into cells and the pathological cell-cell fusion (syncytia) associated with some viral infections. However, technological capabilities for identifying viral glycoproteins and their conformational changes on actual enveloped virus surfaces are generally scarce, challenging, and time-consuming. Our model, Nipah virus (NiV), is a syncytium-forming biosafety level 4 pathogen with a high mortality rate (40 to 75%) in humans. Once the NiV attachment glycoprotein (G) (NiV-G) binds the cell receptor ephrinB2 or -B3, G triggers conformational changes in the fusion glycoprotein (F) that result in membrane fusion and viral entry. We demonstrate that confocal micro-Raman spectroscopy can, within minutes, simultaneously identify specific G and F glycoprotein signals and receptor-induced conformational changes in NiV-F on NiV virus-like particles (VLPs). First, we identified reproducible G- and F-specific Raman spectral features on NiV VLPs containing M (assembly matrix protein), G, and/or F or on NiV/vesicular stomatitis virus (VSV) pseudotyped virions via second-derivative transformations and principal component analysis (PCA). Statistical analyses validated our PCA models. Dynamic temperature-induced conformational changes in F and G or receptor-induced target membrane-dependent conformational changes in F were monitored in NiV pseudovirions in situ in real time by confocal micro-Raman spectroscopy. Advantageously, Raman spectroscopy can identify specific protein signals in relatively impure samples. Thus, this proof-of-principle technological development has implications for the rapid identification and biostability characterization of viruses in medical, veterinary, and food samples and for the analysis of virion glycoprotein conformational changes in situ during viral entry.     

Identification of insulin variants using Raman spectroscopy

Drop coating deposition Raman (DCDR) spectroscopy is used to obtain high-quality normal Raman spectra from small volumes (10 microl) of dilute insulin solutions (3-400 microM) for spectral identification and chromatographic detection. The results are used to demonstrate the spectroscopic classification (identification) of three natural insulin variants-human, bovine, and porcine-that differ by between one and three amino acid residues. DCDR measurements were performed on solutions obtained from reverse phase high-performance liquid chromatography (RP-HPLC) eluent fractions, either before or after lyophilization. Classification is demonstrated using replicate DCDR measurements, followed by normalized Savitsky-Golay second derivative preprocessing and partial least squares training with either leave-one-out or batch-to-batch testing.     

Combining near-infrared-excited autofluorescence and Raman spectroscopy improves in vivo diagnosis of gastric cancer

This study aims to evaluate the diagnostic utility of the combined near-infrared (NIR) autofluorescence (AF) and Raman spectroscopy for improving in vivo detection of gastric cancer at clinical gastroscopy. A rapid Raman endoscopic technique was employed for in vivo spectroscopic measurements of normal (n=1098) and cancer (n=140) gastric tissues from 81 gastric patients. The composite NIR AF and Raman spectra in the range of 800-1800 cm(-1) were analyzed using principal component analysis (PCA) and linear discriminant (LDA) to extract diagnostic information associated with distinctive spectroscopic processes of gastric malignancies. High quality in vivo composite NIR AF and Raman spectra can routinely be acquired from the gastric within 0.5s. The integrated intensity over the range of 800-1800 cm(-1) established the diagnostic implications (p=1.6E-14) of the change of NIR AF intensity associated with neoplastic transformation. PCA-LDA diagnostic modeling on the in vivo tissue NIR AF and Raman spectra acquired yielded a diagnostic accuracy of 92.2% (sensitivity of 97.9% and specificity of 91.5%) for identifying gastric cancer from normal tissue. The integration area under the receiver operating characteristic (ROC) curve using the combined NIR AF and Raman spectroscopy was 0.985, which is superior to either the Raman spectroscopy or NIR AF spectroscopy alone. This work demonstrates that the complementary Raman and NIR AF spectroscopy techniques can be integrated together for improving the in vivo diagnosis and detection of gastric cancer at endoscopy.     

Improved method for purification of bacterial DNA from bovine milk for detection of Brucella spp. by PCR.

Different methods of extraction of bacterial DNA from bovine milk to improve the direct detection of Brucella by PCR were evaluated. We found that the use of a lysis buffer with high concentrations of Tris, EDTA, and NaCl, high concentrations of sodium dodecyl sulfate and proteinase K, and high temperatures of incubation was necessary for the efficient extraction of Brucella DNA. The limit of detection by PCR was 5 to 50 Brucella CFU/ml of milk.     

Raman spectroscopic monitoring of Lactarius latex

Lactarius is a genus of Basidiomycotina with mainly agaricoid representatives, which are characterised by the excretion of a typical milky fluid. In particular, the colour, changes and taste of this latex-like milk are often used as a taxonomically important character. When it is exuded several chemical reactions occur. To date, NMR spectroscopy is generally used for chemical investigation of this latex. However, as a vibrational spectroscopic technique Raman spectroscopy has several advantageous properties for this type of research. The aim of this study is to investigate whether Raman spectroscopy can be used as an alternative analytical technique to monitor the chemical reactions in Lactarius latex. Therefore, this paper presents the first Raman spectra of Lactarius latex and provides an interpretation of the Raman bands that are present. L. lacunarum latex spectra are thoroughly investigated by 2D correlation analysis and are compared with latex spectra of other species (L. chrysorrheus, L. deterrimus, L. fluens, L. glyciosmus and L. salmonicolor).     

Single-cell analysis of bacteria by Raman microscopy: spectral information on the chemical composition of cells and on the heterogeneity in a culture

In the acetone-butanol (ABE) fermentation process, the utilised organisms from the group of the solventogenic Clostridia go through a complex cell-cycle. The role of different cell types in product formation is not understood in detail yet. We aim to use Raman spectroscopy to characterise the population distribution in Clostridium cultures. Cell suspensions were dried on calcium fluoride carriers. Raman spectra of single cells were obtained using a confocal Raman microscope (Dilor, Lille, France). The laser beam was focused on individual cells through the microscope objective. Spectra with good signal-to-noise ratio were obtained. Cells of different morphology, but also apparently similar cells, showed different spectra. Several cell components could be detected and varied in quantity. Compared to other methods for single-cell analysis, the new method is much more time-consuming to analyse one individual cell. However, a large amount of chemical information is obtained from each single cell in a non-destructive, non-invasive way. Raman microscopy appears to be a suitable method for studying population distributions in bacterial cultures.     

Raman spectroscopy‐based detection of RNA viruses in saliva: A preliminary report

Several non‐invasive Raman spectroscopy‐based assays have been reported for rapid and sensitive detection of pathogens. We developed a novel statistical model for the detection of RNA viruses in saliva, based on an unbiased selection of a set of 65 Raman spectral features that mostly attribute to the RNA moieties, with a prediction accuracy of 91.6% (92.5% sensitivity and 88.8% specificity). Furthermore, to minimize variability and automate the downstream analysis of the Raman spectra, we developed a GUI‐based analytical tool “RNA Virus Detector (RVD).” This conceptual framework to detect RNA viruses in saliva could form the basis for field application of Raman Spectroscopy in managing viral outbreaks, such as the ongoing COVID‐19 pandemic. ( http://www.actrec.gov.in/pi-webpages/AmitDutt/RVD/RVD.html ).