The effect of cell fixation on the discrimination of normal and leukemia cells with laser tweezers Raman spectroscopy

Laser tweezers Raman spectroscopy (LTRS) was used to characterize the effect of different chemical fixation procedures on the Raman spectra of normal and leukemia cells. Individual unfixed, paraformaldehyde-fixed, and methanol-fixed normal and transformed lymphocytes from three different cell lines were analyzed with LTRS. When compared to the spectra of unfixed cells, the fixed cell spectra show clear, reproducible changes in the intensity of specific Raman markers commonly assigned to DNA, RNA, protein, and lipid vibrations (e.g. 785, 1230, 1305, 1660 cm(-1)) in mammalian cells, many of which are important markers that have been used to discriminate between normal and cancer lymphocytes. Statistical analyses of the Raman data and classification using principal component analysis and linear discriminant analysis indicate that methanol fixation induces a greater change in the Raman spectra than paraformaldehyde. In addition, we demonstrate that the spectral changes as a result of the fixation process have an adverse effect on the accurate Raman discrimination of the normal and cancer cells. The spectral artifacts created by the use of fixatives indicate that the method of cell preparation is an important parameter to consider when applying Raman spectroscopy to characterize, image, or differentiate between different fixed cell samples to avoid potential misinterpretation of the data.     

Raman detection and identification of normal and leukemic hematopoietic cells

The analysis of leukocytes of peripheral blood is a crucial step in hematologic exams commonly used for disease diagnosis and, typically, requires molecular labelling. In addition, only a detailed, laborious phenotypic analysis allows identifying the presence and stage of specific pathologies such as leukemia. Most of the biochemical information is lost in the routine blood tests. In the present study, we tackle 2 important issues of label‐free biochemical identification and classification of leukocytes using Raman spectroscopy (RS). First, we demonstrate that leukocyte subpopulations of lymphocytes (B, T and NK cells), monocytes and granulocytes can be identified by the unsupervised statistical approach of principal component analysis and classified by linear discriminant analysis with approximately 99% of accuracy. Second, we apply the same procedure to identify and discriminate normal B cells and transformed MN60 lymphocyte leukemic cell lines. In addition, we demonstrate that RS can be efficiently used for monitoring the cell response to low‐dose chemotherapy treatment, experimentally eliciting the sensitivity to a dose‐dependent cell response, which is of fundamental importance to determine the efficacy of any treatment. These results largely expand established Raman‐based research protocols for label‐free analysis of white blood cells, leukemic cells and chemotherapy treatment follow‐up.      

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.     

Assessment of Cell Line Models of Primary Human Cells by Raman Spectral Phenotyping

Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures.     

Characterisation of uterine sarcoma cell lines exhibiting MDR phenotype by vibrational spectroscopy

Multidrug resistance (MDR) enables cancer cells to escape cytotoxic insults of anticancer drugs. Rapid identification of cells exhibiting the MDR phenotype is very important since it can lead to an effective and individual patient based treatment plan. We have investigated a combined vibrational spectroscopic approach, using both micro-Raman and FTIR techniques, in order to characterise a sensitive human uterine sarcoma cell line MES-SA and its multidrug-resistant derivative Garf. In this study, these two complementary methods have been evaluated via the use of principal components analysis (PCA), for discrimination of cells exhibiting the MDR phenotype. Our results indicate that, though they inherently have different sensitivities, both Raman and IR methods can provide a good differentiation of cell phenotypes.     

Ramanome technology platform for label-free screening and sorting of microbial cell factories at single-cell resolution

Phenotypic profiling of natural, engineered or synthetic cells has increasingly become a bottleneck in the mining and engineering of cell factories. Single-cell phenotyping technologies are highly promising for tackling this hurdle, yet ideally they should allow non-invasive live-cell probing, be label-free, provide landscape-like phenotyping capability, distinguish complex functions, operate with high speed, sufficient throughput and low cost, and finally, couple with cell sorting so as to enable downstream omics analysis. This review focuses on recent progress in Ramanome Technology Platform (RTP), which consists of Raman spectroscopy based phenotyping, sorting and sequencing of single cells, and discuss the key challenges and emerging trends. In addition, we propose ramanome, a collection of single-cell Raman spectra (SCRS) acquired from individual cells within a cellular population or consortium, as a new type of biological phenome datatype at the single-cell resolution. By establishing the phenome-genome links in a label-free, single-cell manner, RTP should find wide applications in functional screening and strain development of live microbial, plant and animal cell factories.     

Raman spectroscopy as a potential tool for detection of Brucella spp. in milk

Detection of Brucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possible Brucella isolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identify Brucella from agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of different Brucella, Escherichia, Ochrobactrum, Pseudomonas, and Yersinia spp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% for Brucella from medium and 94% for Brucella from milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detecting Brucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.     

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。     

Surface-enhanced Raman imaging of intracellular bioreduction of chromate in Shewanella oneidensis

This proposed research aims to use novel nanoparticle sensors and spectroscopic tools constituting surface-enhanced Raman spectroscopy (SERS) and Fluorescence Lifetime imaging (FLIM) to study intracellular chemical activities within single bioremediating microorganism. The grand challenge is to develop a mechanistic understanding of chromate reduction and localization by the remediating bacterium Shewanella oneidensis MR-1 by chemical and lifetime imaging. MR-1 has attracted wide interest from the research community because of its potential in reducing multiple chemical and metallic electron acceptors. While several biomolecular approaches to decode microbial reduction mechanisms exist, there is a considerable gap in the availability of sensor platforms to advance research from population-based studies to the single cell level. This study is one of the first attempts to incorporate SERS imaging to address this gap. First, we demonstrate that chromate-decorated nanoparticles can be taken up by cells using TEM and Fluorescence Lifetime imaging to confirm the internalization of gold nanoprobes. Second, we demonstrate the utility of a Raman chemical imaging platform to monitor chromate reduction and localization within single cells. Distinctive differences in Raman signatures of Cr(VI) and Cr(III) enabled their spatial identification within single cells from the Raman images. A comprehensive evaluation of toxicity and cellular interference experiments conducted revealed the inert nature of these probes and that they are non-toxic. Our results strongly suggest the existence of internal reductive machinery and that reduction occurs at specific sites within cells instead of at disperse reductive sites throughout the cell as previously reported. While chromate-decorated gold nanosensors used in this study provide an improved means for the tracking of specific chromate interactions within the cell and on the cell surface, we expect our single cell imaging tools to be extended to monitor the interaction of other toxic metal species.     

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.     

Multiplex single‐cell quantification of rare RNA transcripts from protoplasts in a model plant system

Here we demonstrate multiplex and simultaneous detection of four different rare RNA species from plant, Arabidopsis thaliana, using surface‐enhanced Raman spectroscopy (SERS) and gold nanoprobes at single‐cell resolution. We show the applicability of nanoparticle‐based Raman spectroscopic sensor to study intracellular RNA copies. First, we demonstrate that gold‐nanoparticles decorated with Raman probes and carrying specific nucleic acid probe sequences can be uptaken by the protoplasts. We confirm the internalization of gold nanoprobes by transmission electron microscopy, inductively‐coupled plasma‐mass spectrometry and fluorescence imaging. Second, we show the utility of a SERS platform to monitor individual alternatively spliced (AS) variants and miRNA copies within single cells. Finally, the distinctive spectral features of Raman‐active dyes were exploited for multiplex analysis of AtPTB2, AtDCL2, miR156a and miR172a. Furthermore, single‐cell studies were validated by in vitro quantification and evaluation of nanotoxicity of gold probes. Raman tag functionalized gold nanosensors yielded an approach for the tracking of rare RNAs within the protoplasts. The SERS‐based approach for quantification of RNAs has the capability to be a highly sensitive, accurate and discerning method for single‐cell studies including AS variants quantification and rare miRNA detection in specific plant species.     

Study on gastric cancer blood plasma based on surface-enhanced Raman spectroscopy combined with multivariate analysis

A surface-enhanced Raman spectroscopy (SERS) method combined with multivariate analysis was developed for non-invasive gastric cancer detection. SERS measurements were performed on two groups of blood plasma samples: one group from 32 gastric patients and the other group from 33 healthy volunteers. Tentative assignments of the Raman bands in the measured SERS spectra suggest interesting cancer-specific biomolecular changes, including an increase in the relative amounts of nucleic acid, collagen, phospholipids and phenylalanine and a decrease in the percentage of amino acids and saccharide in the blood plasma of gastric cancer patients as compared with those of healthy subjects. Principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and cancer plasma with high sensitivity (79.5%) and specificity (91%). A receiver operating characteristic (ROC) curve was employed to assess the accuracy of diagnostic algorithms based on PCA-LDA. The results from this exploratory study demonstrate that SERS plasma analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of gastric cancers.     

Optimisation of Wavelength Modulated Raman Spectroscopy: Towards High Throughput Cell Screening

In the field of biomedicine, Raman spectroscopy is a powerful technique to discriminate between normal and cancerous cells. However the strong background signal from the sample and the instrumentation affects the efficiency of this discrimination technique. Wavelength Modulated Raman spectroscopy (WMRS) may suppress the background from the Raman spectra. In this study we demonstrate a systematic approach for optimizing the various parameters of WMRS to achieve a reduction in the acquisition time for potential applications such as higher throughput cell screening. The Signal to Noise Ratio (SNR) of the Raman bands depends on the modulation amplitude, time constant and total acquisition time. It was observed that the sampling rate does not influence the signal to noise ratio of the Raman bands if three or more wavelengths are sampled. With these optimised WMRS parameters, we increased the throughput in the binary classification of normal human urothelial cells and bladder cancer cells by reducing the total acquisition time to 6 s which is significantly lower in comparison to previous acquisition times required for the discrimination between similar cell types.     

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.     

Detection and identification of cancerous murine fibroblasts,transformed by murine sarcoma virus in culture,using Raman spectroscopy and advanced statistical methods

Background

Cancer is one of the leading worldwide causes of death. It may be induced by a variety of factors, including carcinogens, radiation, genetic factors, or DNA and RNA viruses. The early detection of cancer is critical for its successful therapy, which can result in complete recovery from some types of cancer.

Methods

Raman spectroscopy has been widely used in medicine and biology. It is a noninvasive, nondestructive, and water-insensitive technique that can detect changes in cells and tissues that are caused by different disorders, such as cancer.In this study, Raman spectroscopy was used for the identification and characterization of murine fibroblast cell lines (NIH/3T3) and malignant fibroblast cells transformed by murine sarcoma virus (NIH-MuSV) cells.

Results

Using principal component analysis and LDA it was possible to differentiate between the NIH/3T3 and NIH-MuSV cells with an 80–85% success rate based on their Raman shift spectra.

Conclusions

The best results for differentiation were achieved from spectra that were obtained from the rich membrane sites.

General significance

Because of its homogeneity and complete control of most factors affecting its growth, cell culture is a preferred model for the detection and identification of specific biomarkers related to cancer transformation or other cellular modifications.     

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.     

Optical diagnosis of laryngeal cancer using high wavenumber Raman spectroscopy

We report the implementation of the transnasal image-guided high wavenumber (HW) Raman spectroscopy to differentiate tumor from normal laryngeal tissue at endoscopy. A rapid-acquisition Raman spectroscopy system coupled with a miniaturized fiber-optic Raman probe was utilized to realize real-time HW Raman (2800-3020 cm(-1)) measurements in the larynx. A total of 94 HW Raman spectra (22 normal sites, 72 tumor sites) were acquired from 39 patients who underwent laryngoscopic screening. Significant differences in Raman intensities of prominent Raman bands at 2845, 2880 and 2920 cm(-1) (CH(2) stretching of lipids), and 2940 cm(-1) (CH(3) stretching of proteins) were observed between normal and cancer laryngeal tissue. The diagnostic algorithms based on principal components analysis (PCA) and linear discriminant analysis (LDA) together with the leave-one subject-out, cross-validation method on HW Raman spectra yielded a diagnostic sensitivity of 90.3% (65/72) and specificity of 90.9% (20/22) for laryngeal cancer identification. This study demonstrates that HW Raman spectroscopy has the potential for the noninvasive, real-time diagnosis and detection of laryngeal cancer at the molecular level.     

Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model

Raman spectroscopy shows potential in differentiating tumors from normal tissue. We used Raman spectroscopy with near-infrared light excitation to study normal breast tissue and tumors from 11 mice injected with a cancer cell line. Spectra were collected from 17 tumors, 18 samples of adjacent breast tissue and lymph nodes, and 17 tissue samples from the contralateral breast and its adjacent lymph nodes. Discriminant function analysis was used for classification with principal component analysis scores as input data. Tissues were examined by light microscopy following formalin fixation and hematoxylin and eosin staining. Discriminant function analysis and histology agreed on the diagnosis of all contralateral normal, tumor, and mastitis samples, except one tumor which was found to be more similar to normal tissue. Normal tissue adjacent to each tumor was examined as a separate data group called tumor bed. Scattered morphologically suspicious atypical cells not definite for tumor were present in the tumor bed samples. Classification of tumor bed tissue showed that some tumor bed tissues are diagnostically different from normal, tumor, and mastitis tissue. This may reflect malignant molecular alterations prior to morphologic changes, as expected in preneoplastic processes. Raman spectroscopy not only distinguishes tumor from normal breast tissue, but also detects early neoplastic changes prior to definite morphologic alteration.     

Membrane structural alterations in malignant and normal avian lymphocytes: a Raman investigation

Resonance and nonresonance Raman spectra have been obtained from neoplastically transformed and normal avian lymphocytes. The acyl chains of membrane phospholipids of neoplastic cells are more highly unsaturated than those of normal cells. The observation of prominent carotenoid bands in both cell populations indicates the availability of a sensitive, intrinsic probe of membrane potential and local membrane environment.