Molecular-level investigation of the structure, transformation, and bioactivity of single living fission yeast cells by time- and space-resolved Raman spectroscopy

The structure, transformation, and bioactivity of single living Schizosaccharomyces pombe cells at the molecular level have been studied in vivo by time- and space-resolved Raman spectroscopy. A time resolution of 100 s and a space resolution of 250 nm have been achieved with the use of a confocal Raman microspectrometer. The space-resolved Raman spectra of living S. pombe cells at different cell cycle stages were recorded in an effort to elucidate the molecular compositions of organelles, including nuclei, cytoplasm, mitochondria, and septa. The time- and space-resolved measurement of the central part of a dividing yeast cell showed continuous spectral evolution from that of the nucleus to those of the cytoplasm and mitochondria and finally to that of the septum, in accordance with the transformation during the cell cycle. A strong Raman band was observed at 1602 cm(-)(1) only when cells were under good nutrient conditions. The effect of a respiration inhibitor, KCN, on a living yeast cell was studied by measuring the Raman spectra of its mitochondria. A sudden disappearance of the 1602 cm(-)(1) band followed by the change in the shape and intensity of the phospholipid bands was observed, indicating a strong relationship between the cell activity and the intensity of this band. We therefore call this band "the Raman spectroscopic signature of life". The Raman mapping of a living yeast cell was also carried out. Not only the distributions of molecular species but also those of active mitochondria in the cell were successfully visualized in vivo.     

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.”     

Single‐cell genomics based on Raman sorting reveals novel carotenoid‐containing bacteria in the Red Sea

Cell sorting coupled with single‐cell genomics is a powerful tool to circumvent cultivation of microorganisms and reveal microbial ‘dark matter’. Single‐cell Raman spectra (SCRSs) are label‐free biochemical ‘fingerprints’ of individual cells, which can link the sorted cells to their phenotypic information and ecological functions. We employed a novel Raman‐activated cell ejection (RACE) approach to sort single bacterial cells from a water sample in the Red Sea based on SCRS. Carotenoids are highly diverse pigments and play an important role in phototrophic bacteria, giving strong and distinctive Raman spectra. Here, we showed that individual carotenoid‐containing cells from a Red Sea sample were isolated based on the characteristic SCRS. RACE‐based single‐cell genomics revealed putative novel functional genes related to carotenoid and isoprenoid biosynthesis, as well as previously unknown phototrophic microorganisms including an unculturable Cyanobacteria spp. The potential of Raman sorting coupled to single‐cell genomics has been demonstrated.     

Deciphering the finger Prints of Brain Cancer Astrocytoma in comparison to Astrocytes by using near infrared Raman Spectroscopy

To explore the biochemical differences between brain cancer cells Astrocytoma and normal cells Astrocyte, we investigated the Raman spectra of single cell from these two cell types and analyzed the difference in spectra and intensity. Raman spectrum shows the banding pattern of different compounds as detected by the laser. Raman intensity measures the intensity of these individual bands. The Raman spectra of brain cancer cells was similar to those of normal cells, but the Raman intensity of cancer cells was much higher than that of normal cells. The Raman spectra of brain cancer Astrocytoma shows that the structural changes of cancer cells happen so that many biological functions of these cells are lost. The results indicate that Raman spectra can offer the experimental basis for the cancer diagnosis and treatment.     

一种酵母细胞生长现象的实时单细胞拉曼光谱观察

用拉曼镊子观察单个即发活性干酵母(Saccharomy cescerevisiae)细胞在2.0%葡萄糖溶液中的活化过程,收集其拉曼光谱。结果发现,在某一批次的产品中,酵母细胞的1364cm-1峰强度随着细胞的活化而显著增加,531cm-1、652cm-1、1053cm-1等源自葡萄糖或葡萄糖基的信号峰也会随细胞的生长而增强,随后增强的还有1432cm-1、1448cm-1、1561cm-1等源自脂类物质的峰,而源自蛋白质及脂类的1000cm-1、1445cm-1、1655cm-1等峰的信号强度基本不变,酵母细胞代谢活跃的标志峰1603cm-1也基本不变。该批次产品中,10次实验有7次观察到上述现象,而在别的批次产品中并没有观察到该现象。用单细胞拉曼光谱实时记录了这一特殊的生长现象。     

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 of DNA packaging in individual human sperm cells distinguishes normal from abnormal cells

Healthy human males produce sperm cells of which about 25–40% have abnormal head shapes. Increases in the percentage of sperm exhibiting aberrant sperm head morphologies have been correlated with male infertility, and biochemical studies of pooled sperm have suggested that sperm with abnormal shape may contain DNA that has not been properly repackaged by protamine during spermatid development. We have used micro‐Raman spectroscopy to obtain Raman spectra from individual human sperm cells and examined how differences in the Raman spectra of sperm chromatin correlate with cell shape. We show that Raman spectra of individual sperm cells contain vibrational marker modes that can be used to assess the efficiency of DNA‐packaging for each cell. Raman spectra obtained from sperm cells with normal shape provide evidence that DNA in these sperm is very efficiently packaged. We find, however, that the relative protein content per cell and DNA packaging efficiencies are distributed over a relatively wide range for sperm cells with both normal and abnormal shape. These findings indicate that single cell Raman spectroscopy should be a valuable tool in assessing the quality of sperm cells for in‐vitro fertilization. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Non-invasive analysis of cell cycle dynamics in single living cells with Raman micro-spectroscopy

Raman micro-spectroscopy is a laser-based technique which enables rapid and non-invasive biochemical analysis of cells and tissues without the need for labels, markers or stains. Previous characterization of the mammalian cell cycle using Raman micro-spectroscopy involved the analysis of suspensions of viable cells and individual fixed and/or dried cells. Cell suspensions do not provide cell-specific information, and fixing/drying can introduce artefacts which distort Raman spectra, potentially obscuring both qualitative and quantitative analytical results. In this article, we present Raman spectral characterization of biochemical changes related to cell cycle dynamics within single living cells in vitro. Raman spectra of human osteosarcoma cells synchronized in G(0)/G(1), S, and G(2)/M phases of the cell cycle were obtained and multivariate statistics applied to analyze the changes in cell spectra as a function of cell cycle phase. Principal components analysis identified spectral differences between cells in different phases, indicating a decrease in relative cellular lipid contribution to Raman spectral signatures from G(0)/G(1) to G(2)/M, with a concurrent relative increase in signal from nucleic acids and proteins. Supervised linear discriminant analysis of spectra was used to classify cells according to cell cycle phase, and exhibited 97% discrimination between G(0)/G(1)-phase cells and G(2)/M-phase cells. The non-invasive analysis of live cell cycle dynamics with Raman micro-spectroscopy demonstrates the potential of this approach to monitoring biochemical cellular reactions and processes in live cells in the absence of fixatives or labels.     

Raman microspectroscopic discrimination of TCam-2 cultures reveals the presence of two sub-populations of cells

TCam-2 cells are the main in vitro model for investigations into seminomatous tumors. However, despite their widespread use, questions remain regarding the cells’ homogeneity and consequently how representative they are of seminomas. We assess the TCam-2 cell line using routine and novel authentication methods to determine its homogeneity, identify any cellular sub-populations and resolve whether any changes could be due to generational differentiation. TCam-2, embryonal carcinoma cells (2102EP) and breast cancer cell (MCF7) lines were assessed using qRT-PCR, immunocytochemistry, flow cytometry and short tandem repeat analyses. Raman maps of individual cells (minimum of 10) and single scan spectra from 200 cells per culture were obtained. TCam-2s displayed the characteristic marker gene expression pattern for seminoma, were uniform in size and granularity and short tandem repeat analysis showed no contamination. However, based only on physical parameters, flowcytometry was unable to differentiate between TCam-2 and 2102EPs. Raman maps of TCam-2s comprised three equally distributed, distinct spectral patterns displaying large intercellular single spectral variation. All other cells showed little variation. Principal component, cluster and local spectral angle analyses indicated that the TCam-2s contained two different types of cells, one of which comprised two subgroups and was similar to some 2102EP cells. Protein expression corroborated the presence of different cells and generational differences. The detailed characterization provided by the Raman spectra, augmented by the routine methods, provide substantiation to the long-held suspicion that TCam-2 are not homogeneous but comprise differing cell populations, one of which may be embryonal carcinoma in origin.     

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.     

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.     

Single cell analysis using surface enhanced Raman scattering (SERS) tags

Fluorescence is a mainstay of bioanalytical methods, offering sensitive and quantitative reporting, often in multiplexed or multiparameter assays. Perhaps the best example of the latter is flow cytometry, where instruments equipped with multiple lasers and detectors allow measurement of 15 or more different fluorophores simultaneously, but increases beyond this number are limited by the relatively broad emission spectra. Surface enhanced Raman scattering (SERS) from metal nanoparticles can produce signal intensities that rival fluorescence, but with narrower spectral features that allow a greater degree of multiplexing. We are developing nanoparticle SERS tags as well as Raman flow cytometers for multiparameter single cell analysis of suspension or adherent cells. SERS tags are based on plasmonically active nanoparticles (gold nanorods) whose plasmon resonance can be tuned to give optimal SERS signals at a desired excitation wavelength. Raman resonant compounds are adsorbed on the nanoparticles to confer a unique spectral fingerprint on each SERS tag, which are then encapsulated in a polymer coating for conjugation to antibodies or other targeting molecules. Raman flow cytometry employs a high resolution spectral flow cytometer capable of measuring the complete SERS spectra, as well as conventional flow cytometry measurements, from thousands of individual cells per minute. Automated spectral unmixing algorithms extract the contributions of each SERS tag from each cell to generate high content, multiparameter single cell population data. SERS-based cytometry is a powerful complement to conventional fluorescence-based cytometry. The narrow spectral features of the SERS signal enables more distinct probes to be measured in a smaller region of the optical spectrum with a single laser and detector, allowing for higher levels of multiplexing and multiparameter analysis.     

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.     

Non-destructive analysis of the nuclei of transgenic living cells using laser tweezers and near-infrared raman spectroscopic technique

Transgenic cell lines of loblolly pine （Pinus taeda L.） were analyzed by a compact laser-tweezers-Raman-spectroscopy （LTRS） system in this investigation. A low power diode laser at 785 nm was used for both laser optical trapping of single transgenic cells and excitation for near-infrared Raman spectroscopy of the nuclei of synchronized cells, which were treated as single organic particles, at the S-phase of the cell cycle. Transgenic living cells with gfp and uidA genes were used as biological samples to test this LTRS technique. As expected, different Raman spectra were observed from the tested biological samples. This technique provides a high sensitivity and enables real-time spectroscopic measurements of transgenic cell lines. It could be a valuable tool for the study of the fundamental cell and molecular biological process by trapping single nucleus and by providing a wealth of molecular information about the nuclei of cells.     

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.     

Single cell studies of the cell cycle and some models

Analysis of growth and division often involves measurements made on cell populations, which tend to average data. The value of single cell analysis needs to be appreciated, and models based on findings from single cells should be taken into greater consideration in our understanding of the way in which cell size and division are co-ordinated. Examples are given of some single cell analyses in mammalian cells, yeast and other microorganisms. There is also a short discussion on how far the results are in accord with simple models.     

Raman and Autofluorescence Spectrum Dynamics along the HRG-Induced Differentiation Pathway of MCF-7 Cells

Cellular differentiation proceeds along complicated pathways, even when it is induced by extracellular signaling molecules. One of the major reasons for this complexity is the highly multidimensional internal dynamics of cells, which sometimes causes apparently stochastic responses in individual cells to extracellular stimuli. Therefore, to understand cell differentiation, it is necessary to monitor the internal dynamics of cells at single-cell resolution. Here, we used a Raman and autofluorescence spectrum analysis of single cells to detect dynamic changes in intracellular molecular components. MCF-7 cells are a human cancer-derived cell line that can be induced to differentiate into mammary-gland-like cells with the addition of heregulin (HRG) to the culture medium. We measured the spectra in the cytoplasm of MCF-7 cells during 12 days of HRG stimulation. The Raman scattering spectrum, which was the major component of the signal, changed with time. A multicomponent analysis of the Raman spectrum revealed that the dynamics of the major components of the intracellular molecules, including proteins and lipids, changed cyclically along the differentiation pathway. The background autofluorescence signals of Raman scattering also provided information about the differentiation process. Using the total information from the Raman and autofluorescence spectra, we were able to visualize the pathway of cell differentiation in the multicomponent phase space.     

Nonresonant confocal Raman imaging of DNA and protein distribution in apoptotic cells

Nonresonant confocal Raman imaging has been used to map the DNA and the protein distributions in individual single human cells. The images are obtained on an improved homebuilt confocal Raman microscope. After statistical analysis, using singular value decomposition, the Raman images are reconstructed from the spectra covering the fingerprint region. The data are obtained at a step interval of approximately 250 nm and cover a field from 8- to 15- micro m square in size. Dwell times at each pixel are between 0.5 and 2 s, depending on the nature and the state of the cell under investigation. High quality nonresonant Raman images can only be obtained under these conditions using continuous wave high laser powers between 60 and 120 mW. We will present evidence that these laser powers can still safely be used to recover the chemical distributions in fixed cells. The developed Raman imaging method is used to image directly, i.e., without prior labeling, the nucleotide condensation and the protein distribution in the so-called nuclear fragments of apoptotic HeLa cells. In the control (nonapoptotic) HeLa cells, we show, for the first time by Raman microspectroscopy, the presence of the RNA in a cell nucleus.     

Structural changes in t-RNA from changes in the Raman scattering intensities

Laser Raman spectra of a mixture of yeast t-RNA's are examined as a function of temperature and after total alkaline hydrolysis to mononucleotides; the data are interpreted on the basis of extensive preliminary studies previously reported from this laboratory on the Raman spectral properties of numerous synthetic model compounds. Since the Raman intensities observed are extremely sensitive to conformational changes in the nucleic acid, much useful structural information can be obtained.