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.     

Resonance Raman microscopy of rod and cone photoreceptors

We have constructed a Raman microscope that has enabled us to obtain resonance Raman vibrational spectra from single photoreceptor cells. The laser beam which excites the Raman scattering is focused on the outer segment of the photoreceptor through the epiillumination system of a light microscope. Raman scattering from the visual pigment in the photoreceptor is collected by the objective and then dispersed onto a multichannel detector. High-quality spectra are recorded easily from individual outer segments that are 5 x 50 micrometer in size, and we have obtained spectra from cells as small as 1 x 10 micrometer. We have used the Raman microscope to study photostationary steady-state mixtures in pigments from toad (Bufo marinus) and goldfish (Carassius auratus) photoreceptors; these photoreceptors were frozen in glycerol glasses at 77 degrees K. Comparison of our toad red rod spectra with previously published spectra of bovine rod pigments demonstrates that the conformation of the chromophore in the first photointermediate, bathorhodopsin, is sensitive to variations in protein structure. We have also studied the first photointermediate in the goldfish rod photostationary steady-state. This bathoporphyropsin has a much lower ethylenic stretching frequency (1,507 cm-1) than that observed in the toad and bovine bathoproducts (approximately 1,535 cm-1). Preliminary results of our work on goldfish cone pigments are also reported. These are the first vibrational studies on the vertebrate photoreceptors responsible for color vision.     

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.     

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)     

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.     

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.     

Monitoring dynamic protein expression in living E. coli. Bacterial cells by laser tweezers Raman spectroscopy.

BACKGROUND: Laser tweezers Raman spectroscopy (LTRS) is a novel, nondestructive, and label-free method that can be used to quantitatively measure changes in cellular activity in single living cells. Here, we demonstrate its use to monitor changes in a population of E. coli cells that occur during overexpression of a protein, the extracellular domain of myelin oligodendrocyte glycoprotein [MOG(1-120)]. METHODS: Raman spectra were acquired from individual E. coli cells suspended in solution and trapped by a single tightly focused laser beam. Overexpression of MOG(1-120) in transformed E. coli Rosetta-Gami (DE3)pLysS cells was induced by addition of isopropyl thiogalactoside (IPTG). Changes in the peak intensities of the Raman spectra from a population of cells were monitored and analyzed over a total duration of 3 h. Data were also collected for concentrated purified MOG(1-120) protein in solution, and the spectra compared with that obtained for the MOG(1-120) expressing cells. RESULTS: Raman spectra of individual, living E. coli cells exhibit signatures due to DNA and protein molecular vibrations. Characteristic Raman markers associated with protein vibrations, such as 1,257, 1,340, 1,453, and 1,660 cm(-1), are shown to increase as a function of time following the addition of IPTG. Comparison of these spectra and the spectra of purified MOG protein indicates that the changes are predominantly due to the induction of MOG protein expression. Protein expression was found to occur mostly within the second hour, with a 470% increase relative to the protein expressed in the first hour. A 230% relative increase between the second and third hour indicates that protein expression begins to level off within the third hour. CONCLUSION: It is demonstrated that LTRS has sufficient sensitivity for real-time, nondestructive, and quantitative monitoring of biological processes, such as protein expression, in single living cells. Such capabilities, which are not currently available in flow cytometry, open up new possibilities for analyzing cellular processes occurring in single microbial and eukaryotic cells.     

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.     

Preparation of single cells from aggregated Taxus suspension cultures for population analysis

A method for the isolation of single plant cells from Taxus suspension cultures has been developed for the analysis of single cells via rapid throughput techniques such as flow cytometry. Several cell wall specific enzymes, such as pectinase, pectolyase Y-23, macerozyme, Driselase(R), and cellulase were tested for efficacy in producing single cell suspensions. The method was optimized for single cell yield, viability, time, and representivity of aggregated cell cultures. The best combination for single cell isolation was found to be 0.5% (w/v) pectolyase Y-23 and 0.04% (w/v) cellulase. High viability (>95%) and high yields of single cell aggregates (>90%) were obtained following 4 hours of digestion for four separate Taxus cell lines. In addition, methyl jasmonate elicitation (200 microM) was found to have no effect on three of the four tested Taxus lines. Isolated single cells were statistically similar to untreated cell cultures for peroxidase activity (model cell wall protein) and paclitaxel content (secondary metabolite produced in Taxus cell cultures). In comparison, protoplasts showed marked changes in both peroxidase activity and paclitaxel content as compared to untreated cultures. The use of flow cytometry was demonstrated with isolated cells that were found to have > 99% viability upon staining with fluorescein diacetate. The development of a method for the isolation of single plant cells will allow the study of population dynamics and culture variability on a single cell level for the development of population models of plant cell cultures and secondary metabolism.     

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.     

Near-infrared Raman Microspectroscopy Detects High-risk Human Papillomaviruses

BACKGROUND: Detecting human papillomaviruses (HPVs) infection in cervical cells is an exceedingly important part of the clinical management of cervical dysplasia. Current guidelines in women's health outline the need for both the Papanicolaou test as well as high-risk HPV testing. Testing for HPV is expensive, is time-consuming, and requires experienced technicians. METHODS: Two sets of near-infrared Raman microspectroscopy experiments were conducted using a Raman confocal microscope system. First, Raman spectra were acquired from four different cell culture lines, two positive for HPV (HeLa, SiHa), one negative for HPV, but malignant (C33A), and one normal, HPV-negative line (NHEK). The three malignant lines were all derived from cervical cells. Second, Raman spectra were acquired from deidentified patient samples that were previously tested for the presence of high-risk HPV. RESULTS: The spectra from the cell culture lines and the patient samples contained many statistically significant differences. Using sparse multinomial logistic regression to classify the data led to classification accuracies of 89% to 97% for the cell culture samples and 98.5% for the patient samples. CONCLUSIONS: Raman micro-spectroscopy can be used to detect HPV and differentiate among specific HPV strains. This technique may provide health providers with a new method for quickly testing cell samples for the presence of HPV.     

Label-free detection of mitochondrial distribution in cells by nonresonant Raman microspectroscopy

High spatial resolution Raman maps of fixed cells in an aqueous environment are reported. These maps were obtained by collecting individual Raman spectra via a Raman microspectrometer in a raster pattern on a 0.5-microm grid and assembling pseudocolor maps from the spectral hypercubes by multivariate methods. The Raman maps show the nucleus and the nucleoli of cells as well as subcellular organization in the cytoplasm. In particular, the distribution of mitochondria in the perinuclear region could be demonstrated by correlating distinct areas of the Raman maps with corresponding areas of fluorescence maps of the same cells after staining with mitochondria-specific labels. To the best of our knowledge, this is the first report of label-free detection of mitochondria inside a somatic mammalian cell using Raman microspectroscopy.     

In vivo prediction of the nutrient status of individual microalgal cells using Raman microspectroscopy

An in vivo method for predicting the nutrient status of individual algal cells using Raman microspectroscopy is described. Raman spectra of cells using 780 nm laser excitation show enhanced bands mainly attributable to chlorophyll a and beta-carotene. The relative intensities of chlorophyll a and beta-carotene bands changed under nitrogen limitation, with chlorophyll a bands becoming less intense and beta-carotene bands more prominent. Although spectra from N-replete and N-starved cell populations varied, each distribution was distinct enough such that multivariate classification methods, such as partial least squares discriminant analysis, could accurately predict the nutrient status of the cells from the Raman spectral data.     

Impact of cell cycle dynamics on pathology recognition: Raman imaging study

Confocal Raman imaging combined with fluorescence‐activated cell sorting was used for in vitro studies of cell cultures to look at biochemical differences between the cells in different cell phases. To answer the question what is the impact of the cell cycle phase on discrimination of pathological cells, the combination of several factors was checked: a confluency of cell culture, the cell cycle dynamics and development of pathology. Confluency of 70% and 100% results in significant phenotypic cell changes that can be also diverse for different batches. In 100% confluency cultures, cells from various phases become phenotypically very similar and their recognition based on Raman spectra is not possible. For lower confluency, spectroscopic differences can be found between cell cycle phases (G₀/G₁, S and G₂/M) for control cells and cells incubated with tumor necrosis factor alpha (TNF‐α), but when the mycotoxin cytochalasin B is used the Raman signatures of cell phases are not separable. Generally, this work shows that heterogeneity between control and inflamed cells can be bigger than heterogeneity between cell cycle phases, but it is related to several factors, and not always can be treated as a rule.      

Cell volume distributions reveal cell growth rates and division times

A population of cells in culture displays a range of phenotypic responses even when those cells are derived from a single cell and are exposed to a homogeneous environment. Phenotypic variability can have a number of sources including the variable rates at which individual cells within the population grow and divide. We have examined how such variations contribute to population responses by measuring cell volumes within genetically identical populations of cells where individual members of the population are continuously growing and dividing, and we have derived a function describing the stationary distribution of cell volumes that arises from these dynamics. The model includes stochastic parameters for the variability in cell cycle times and growth rates for individual cells in a proliferating cell line. We used the model to analyze the volume distributions obtained for two different cell lines and one cell line in the absence and presence of aphidicolin, a DNA polymerase inhibitor. The derivation and application of the model allows one to relate the stationary population distribution of cell volumes to extrinsic biological noise present in growing and dividing cell cultures.     

Identification of single eukaryotic cells with micro-Raman spectroscopy

For a fast identification of eukaryotic cells such as yeast species without a cultivation step it should be possible to perform the investigation on only one single cell. Since yeasts as eukaryotes are heterogeneous and their Raman spectra are therefore dependent on the measuring position, one Raman spectra is not representative of the whole cell. In this contribution we demonstrate the application of average Raman spectra of a line scan over single yeast cells. These average spectra are used for classification with the help of a support vector machine.