Chemical contrast for imaging living systems: molecular vibrations drive CARS microscopy

Cellular biomolecules contain unique molecular vibrations that can be visualized by coherent anti-Stokes Raman scattering (CARS) microscopy without the need for labels. Here we review the application of CARS microscopy for label-free imaging of cells and tissues using the natural vibrational contrast that arises from biomolecules like lipids as well as for imaging of exogenously added probes or drugs. High-resolution CARS microscopy combined with multimodal imaging has allowed for dynamic monitoring of cellular processes such as lipid metabolism and storage, the movement of organelles, adipogenesis and host-pathogen interactions and can also be used to track molecules within cells and tissues. The CARS imaging modality provides a unique tool for biological chemists to elucidate the state of a cellular environment without perturbing it and to perceive the functional effects of added molecules.     

Label-free imaging of lipid dynamics using Coherent Anti-stokes Raman Scattering (CARS) and Stimulated Raman Scattering (SRS) microscopy

The recently developed Coherent Anti-stokes Raman Scattering (CARS) microscopy and Stimulated Raman Scattering (SRS) microscopy have provided new methods to visualize the localization and regulation of biological molecules without the use of invasive and potentially perturbative labels. They allow rapid imaging of specific molecules with high resolution and sensitivity. These tools have been effectively applied to the study of lipid metabolism using Caenorhabditis elegans as a genetic model, unraveling new lipid storage phenotypes and their regulatory mechanisms. Here we review the underlying principle of CARS and SRS microscopy, as well as their recent applications in lipid biology research in C. elegans.     

Vibrational imaging of lipid droplets in live fibroblast cells with coherent anti-Stokes Raman scattering microscopy

A new vibrational imaging method based on coherent anti-Stokes Raman scattering (CARS) has been used for high-speed, selective imaging of neutral lipid droplets (LDs) in unstained live fibroblast cells. LDs have a high density of C-H bonds and show a high contrast in laser-scanning CARS images taken at 2,845 cm-1, the frequency for aliphatic C-H vibrations. The contrast from LDs was confirmed by comparing CARS and Oil Red O (ORO)-stained fluorescence images. The fluorescent labeling processes were examined with CARS microscopy. It was found that ORO staining of fixed cells caused aggregation of LDs, whereas fixing with formaldehyde or staining with Nile Red did not affect LDs. CARS microscopy was also used to monitor the 3T3-L1 cell differentiation process, revealing that there was an obvious clearance of LDs at the early stage of differentiation. After that, the cells started to differentiate and reaccumulate LDs in the cytoplasm in a largely unsynchronized manner. Differentiated cells formed small colonies surrounded by undifferentiated cells that were devoid of LDs. These observations demonstrate that CARS microscopy can follow dynamic changes in live cells with chemical selectivity and noninvasiveness. CARS microscopy, in tandem with other techniques, provides exciting possibilities for studying LD dynamics under physiological conditions without perturbation of cell functions.     

Interpreting CARS images of tissue within the C–H‐stretching region

Single band coherent anti‐Stokes Raman scattering (CARS) microscopy is one of the fastest implementation of nonlinear vibrational imaging allowing for video‐rate image acquisition of tissue. This is due to the large Raman signal in the C—H‐stretching region. However, the chemical specificity of such images is conventionally assumed to be low. Nonetheless, CARS imaging within the C—H‐stretching region enables detection of single cells and nuclei, which allows for histopathologic grading of tissue. Relevant information such as nucleus to cytoplasm ratio, cell density, nucleus size and shape is extracted from CARS images by innovative image processing procedures. In this contribution CARS image contrast within the C—H‐stretching region is interpreted by direct comparison with Raman imaging and correlated to the tissue composition justifying the use of CARS imaging in this wavenumber region for biomedical applications. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Shedding new light on lipid functions with CARS and SRS microscopy

Modern optical microscopy has granted biomedical scientists unprecedented access to the inner workings of a cell, and revolutionized our understanding of the molecular mechanisms underlying physiological and disease states. In spite of these advances, however, visualization of certain classes of molecules (e.g. lipids) at the sub-cellular level has remained elusive. Recently developed chemical imaging modalities – Coherent Anti-Stokes Raman Scattering (CARS) microscopy and Stimulated Raman Scattering (SRS) microscopy – have helped bridge this gap. By selectively imaging the vibration of a specific chemical group, these non-invasive techniques allow high-resolution imaging of individual molecules in vivo, and circumvent the need for potentially perturbative extrinsic labels. These tools have already been applied to the study of fat metabolism, helping uncover novel regulators of lipid storage. Here we review the underlying principle of CARS and SRS microscopy, and discuss the advantages and caveats of each technique. We also review recent applications of these tools in the study of lipids as well as other biomolecules, and conclude with a brief guide for interested researchers to build and use CARS/SRS systems for their own research. This article is part of a Special Issue entitled Tools to study lipid functions.     

Assessing the efficacy of coherent anti‐Stokes Raman scattering microscopy for the detection of infiltrating glioblastoma in fresh brain samples

Coherent anti‐Stokes Raman scattering (CARS) microscopy is an emerging technique for identification of brain tumors. However, tumor identification by CARS microscopy on bulk samples and in vivo has been so far verified retrospectively on histological sections, which only provide a gross reference for the interpretation of CARS images without matching at cellular level. Therefore, fluorescent labels were exploited for direct assessment of the interpretation of CARS images of solid and infiltrative tumors. Glioblastoma cells expressing green fluorescent protein (GFP) were used for induction of tumors in mice (n = 7). The neoplastic nature of cells imaged by CARS microscopy was unequivocally verified by addressing two‐photon fluorescence of GFP on fresh brain slices and in vivo. In fresh unfixed biopsies of human glioblastoma (n = 10), the fluorescence of 5‐aminolevulinic acid‐induced protoporphyrin IX was used for identification of tumorous tissue. Distinctive morphological features of glioblastoma cells, i.e. larger nuclei, evident nuclear membrane and nucleolus, were identified in the CARS images of both mouse and human brain tumors. This approach demonstrates that the chemical contrast provided by CARS allows the localization of infiltrating tumor cells in fresh tissue and that the cell morphology in CARS images is useful for tumor recognition.

Experimental glioblastoma expressing green fluorescent protein.     

Label-free live-cell imaging with confocal Raman microscopy

Confocal Raman spectroscopy is a noninvasive alternative to established cell imaging methods because it does not require chemical fixation, the use of fluorescent markers, or genetic engineering. In particular, single live-cell, high-resolution imaging by confocal Raman microscopy is desirable because it allows further experiments concerning the individually investigated cells. However, to derive meaningful images from the spectroscopic data, one must identify cell components within the dataset. Using immunofluorescence images as a reference, we derive Raman spectral signatures by means of information measures to identify cell components such as the nucleus, the endoplasmic reticulum, the Golgi apparatus, and mitochondria. The extracted signatures allow us to generate representations equivalent to conventional (immuno)fluorescence images with more than three cell components at a time, exploiting the Raman spectral information alone.     

Polyglutamine aggregate structure in vitro and in vivo; new avenues for coherent anti-stokes Raman scattering microscopy

Coherent anti-Stokes Raman scattering (CARS) microscopy is applied for the first time for the evaluation of the protein secondary structure of polyglutamine (polyQ) aggregates in vivo. Our approach demonstrates the potential for translating information about protein structure that has been obtained in vitro by X-ray diffraction into a microscopy technique that allows the same protein structure to be detected in vivo. For these studies, fibres of polyQ containing peptides (D(2)Q(15)K(2)) were assembled in vitro and examined by electron microscopy and X-ray diffraction methods; the fibril structure was shown to be cross β-sheet. The same polyQ fibres were evaluated by Raman spectroscopy and this further confirmed the β-sheet structure, but indicated that the structure is highly rigid, as indicated by the strong Amide I signal at 1659 cm(-1). CARS spectra were simulated using the Raman spectrum taking into account potential non-resonant contributions, providing evidence that the Amide I signal remains strong, but slightly shifted to lower wavenumbers. Combined CARS (1657 cm(-1)) and multi-photon fluorescence microscopy of chimeric fusions of yellow fluorescent protein (YFP) with polyQ (Q40) expressed in the body wall muscle cells of Caenorhabditis elegans nematodes (1 day old adult hermaphrodites) revealed diffuse and foci patterns of Q40-YFP that were both fluorescent and exhibited stronger CARS (1657 cm(-1)) signals than in surrounding tissues at the resonance for the cross β-sheet polyQ in vitro.     

Coherent anti-stokes Raman scattering microscopy: a biological review.

Microscopic imaging of cells and tissues are generated by the interaction of light with either the sample itself or contrast agents that label the sample. Most contrast agents, however, alter the cell in order to introduce molecular labels, complicating live cell imaging. The interaction of light from multiple laser sources has given rise to microscopy, based on Raman scattering or vibrational resonance, which demonstrates selectivity to specific chemical bonds while imaging unmodified live cells. Here, we discuss the nonlinear optical technique of coherent anti-Stokes Raman scattering (CARS) microscopy, its instrumentation, and its status in live cell imaging.     

Laser-scanning coherent anti-Stokes Raman scattering microscopy and applications to cell biology

Laser-scanning coherent anti-Stokes Raman scattering (CARS) microscopy with fast data acquisition and high sensitivity has been developed for vibrational imaging of live cells. High three-dimensional (3D) resolution is achieved with two collinearly overlapped near infrared picosecond beams and a water objective with a high numerical aperture. Forward-detected CARS (F-CARS) and epi-detected CARS (E-CARS) images are recorded simultaneously. F-CARS is used for visualizing features comparable to or larger than the excitation wavelength, while E-CARS allows detection of smaller features with a high contrast. F-CARS and E-CARS images of live and unstained cells reveal details invisible in differential interference-contrast images. High-speed vibrational imaging of unstained cells undergoing mitosis and apoptosis has been carried out. For live NIH 3T3 cells in metaphase, 3D distribution of chromosomes is mapped at the frequency of the DNA backbone Raman band, while the vesicles surrounding the nucleus is imaged by E-CARS at the frequency of the C-H stretching Raman band. Apoptosis in NIH 3T3 cells is monitored using the CARS signal from aliphatic C-H stretching vibration.     

Spectral imaging and its applications in live cell microscopy

In biological microscopy, the ever expanding range of applications requires quantitative approaches that analyze several distinct fluorescent molecules at the same time in the same sample. However, the spectral properties of the fluorescent proteins and dyes presently available set an upper limit to the number of molecules that can be detected simultaneously with common microscopy methods. Spectral imaging and linear unmixing extends the possibilities to discriminate distinct fluorophores with highly overlapping emission spectra and thus the possibilities of multicolor imaging. This method also offers advantages for fast multicolor time-lapse microscopy and fluorescence resonance energy transfer measurements in living samples. Here we discuss recent progress on the technical implementation of the method, its limitations and applications to the imaging of biological samples.     

Automated Identification of Subcellular Organelles by Coherent Anti-Stokes Raman Scattering

Coherent anti-Stokes Raman scattering (CARS) is an emerging tool for label-free characterization of living cells. Here, unsupervised multivariate analysis of CARS datasets was used to visualize the subcellular compartments. In addition, a supervised learning algorithm based on the “random forest” ensemble learning method as a classifier, was trained with CARS spectra using immunofluorescence images as a reference. The supervised classifier was then used, to our knowledge for the first time, to automatically identify lipid droplets, nucleus, nucleoli, and endoplasmic reticulum in datasets that are not used for training. These four subcellular components were simultaneously and label-free monitored instead of using several fluorescent labels. These results open new avenues for label-free time-resolved investigation of subcellular components in different cells, especially cancer cells.     

Automated Identification of Subcellular Organelles by Coherent Anti-Stokes Raman Scattering

Coherent anti-Stokes Raman scattering (CARS) is an emerging tool for label-free characterization of living cells. Here, unsupervised multivariate analysis of CARS datasets was used to visualize the subcellular compartments. In addition, a supervised learning algorithm based on the “random forest” ensemble learning method as a classifier, was trained with CARS spectra using immunofluorescence images as a reference. The supervised classifier was then used, to our knowledge for the first time, to automatically identify lipid droplets, nucleus, nucleoli, and endoplasmic reticulum in datasets that are not used for training. These four subcellular components were simultaneously and label-free monitored instead of using several fluorescent labels. These results open new avenues for label-free time-resolved investigation of subcellular components in different cells, especially cancer cells.     

Multimodal nonlinear optical imaging of collagen arrays

We report multimodal nonlinear optical imaging of fascia, a rich collagen type I sheath around internal organs and muscle. We show that second harmonic generation (SHG), third harmonic generation (THG) and Coherent anti-Stokes Raman scattering (CARS) microscopy techniques provide complementary information about the sub-micron architecture of collagen arrays. Forward direction SHG microscopy reveals the fibrillar arrangement of collagen type I structures as the main matrix component of fascia. SHG images detected in the backward direction as well as images of forward direction CARS microscopy show that the longitudinal collagen fiber bundles are further arranged in sheet-like bands. Forward-THG microscopy reveals the optically homogeneous content of the collagen sheet on a spatial scale of the optical wavelength. This is supported by the fact that the third harmonic signal is observed only at the boundaries between the sheets as well as by the CARS data obtained in both directions. The observations made with THG and CARS microscopy are explained using atomic force microscopy images.     

A comparative Raman and CARS imaging study of colon tissue

An experimental evaluation of the information content of two complimentary techniques, linear Raman and coherent anti‐Stokes Raman scattering (CARS) microscopy, is presented. CARS is a nonlinear variant of Raman spectroscopy that enables rapid acquisition of images within seconds in combination with laser scanning microscopes. CARS images were recorded from thin colon tissue sections at 2850, 1660, 1450 and 1000 cm^–1 and compared with Raman images. Raman images were obtained from univariate and multivariate (k‐means clustering) methods, whereas all CARS images represent univariate results. Variances within tissue sections could be visualized in chemical maps of CARS and Raman images. However, identification of tissue types and characterization of variances between different tissue sections were only possible by analysis of cluster mean spectra, obtained from k‐means cluster analysis. This first comparison establishes the foundation for further development of the CARS technology to assess tissue. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Intrinsic Indicator of Photodamage during Label-Free Multiphoton Microscopy of Cells and Tissues

Multiphoton imaging has evolved as an indispensable tool in cell biology and holds prospects for clinical applications. When addressing endogenous signals such as coherent anti-Stokes Raman scattering (CARS) or second harmonic generation, it requires intense laser irradiation that may cause photodamage. We report that increasing endogenous fluorescence signal upon multiphoton imaging constitutes a marker of photodamage. The effect was studied on mouse brain in vivo and ex vivo, on ex vivo human brain tissue samples, as well as on glioblastoma cells in vitro, demonstrating that this phenomenon is common to a variety of different systems, both ex vivo and in vivo. CARS microscopy and vibrational spectroscopy were used to analyze the photodamage. The development of a standard easy-to-use model that employs rehydrated cryosections allowed the characterization of the irradiation-induced fluorescence and related it to nonlinear photodamage. In conclusion, the monitoring of endogenous two-photon excited fluorescence during label-free multiphoton microscopy enables to estimate damage thresholds ex vivo as well as detect photodamage during in vivo experiments.     

NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure

Background

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively.

Results

We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest.

Conclusions

The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.     

Imaging growth of neurites in conditioned hydrogel by coherent anti-Stokes Raman scattering microscopy

Cultured DRGs in different gel scaffolds were analyzed using CARS microscopy to determine its possible use as a label-free imaging option for tracking cellular growth in a gel scaffold. This study demonstrates for the first time the applicability of CARS microscopy to the imaging of live neuronal cells in GAG hydrogels. By tuning the laser beating frequency, ωp ? ωs, to match the vibration of C-H bonds in the cell membrane, the CARS signal yields detailed, high-quality images of neurites with single membrane detection sensitivity. The results demonstrate that CARS imaging allows monitoring of cellular growth in a tissue scaffold over time, with a contrast that shows comparable cellular structures to those obtained using standard fluorescent staining techniques. These findings show the potential of CARS microscopy to assist in the understanding of organogenesis processes in a tissue scaffold.     

Struggle for photostability: Bleaching mechanisms of fluorescent proteins

In modern biotechnological science, there is a need for visualization of objects under study at the levels of cells, organelles, and individual molecules. Prominent among imaging methods are the methods based on the detection of fluorescence from the fluorophores with which objects under study are labeled. Fluorescent proteins (FPs) are very popular as genetically encoded fluorescent labels for lifetime imaging of target structures and processes in living systems. One of the key characteristics of FPs is their photostability, i.e., their resistance to photochemical reactions that quench the fluorescence signal. This review describes the currently known molecular mechanisms underlying photobleaching and the methods used to improve the photostability of fluorescent proteins.     

Photoswitchable fluorescent proteins enable monochromatic multilabel imaging and dual color fluorescence nanoscopy

Fluorescent proteins that can be reversibly photoswitched between a fluorescent and a nonfluorescent state are important for innovative microscopy schemes, such as protein tracking, fluorescence resonance energy transfer imaging, sub-diffraction resolution microscopy and others. However, all available monomeric reversibly switchable fluorescent proteins (RSFPs) have similar properties and switching characteristics, thereby limiting their use. Here, we introduce two bright green fluorescent RSFPs, bsDronpa and Padron, generated by extensive mutagenesis of the RSFP Dronpa, with unique absorption and switching characteristics. Whereas bsDronpa features a broad absorption spectrum extending into the UV, Padron displays a switching behavior that is reversed to that of all green fluorescent RSFPs known to date. These two RSFPs enable live-cell fluorescence microscopy with multiple labels using a single detection color, because they can be distinguished by photoswitching. Furthermore, we demonstrate dual-color fluorescence microscopy with sub-diffraction resolution using bsDronpa and Dronpa whose emission maxima are separated by <20 nm.