Biomolecular imaging with coherent nonlinear vibrational microscopy

Polarization-sensitive sum-frequency generation microscopy of collagen fibers

Point-scanning sum-frequency generation (SFG) microscopy enables the generation of images of collagen I fibers in tissues by tuning into specific vibrational resonances of the polypeptide. It is shown that when collagen-rich tissues are visualized near the 2954 cm(-1) stretching vibration of methylene groups, the SFG image contrast is higher compared to the contrast seen in nonresonant second-harmonic generation (SHG) imaging. Polarization and spectrally resolved analysis of the SFG signal as a function of fiber orientation in the CH-stretching range of the vibrational spectrum enabled a comparative characterization of the achiral tensor elements of collagen's second-order susceptibility. This analysis reveals that selected on-resonance tensor elements are enhanced over other elements, giving rise to a much stronger anisotropy ρ of the signal for SFG (ρ ≈ 15) compared to SHG (ρ ≈ 3). The improved anisotropy of the vibrationally resonant signal contributes to the higher contrast seen in the SFG tissue images.

Plant growth conditions alter phytolith carbon

Many plants, including grasses and some important human food sources, accumulate, and precipitate silica in their cells to form opaline phytoliths. These phytoliths contain small amounts of organic matter (OM) that are trapped during the process of silicification. Previous work has suggested that plant silica is associated with compounds such as proteins, lipids, lignin, and carbohydrate complexes. It is not known whether these compounds are cellular components passively encapsulated as the cell silicifies, polymers actively involved in the precipitation process or random compounds assimilated by the plant and discarded into a "glass wastebasket." Here, we used Raman spectroscopy to map the distribution of OM in phytoliths, and to analyze individual phytoliths isolated from Sorghum bicolor plants grown under different laboratory treatments. Using mapping, we showed that OM in phytoliths is distributed throughout the silica and is not related to dark spots visible in light microscopy, previously assumed to be the repository for phytolith OM. The Raman spectra exhibited common bands indicative of C-H stretching modes of general OM, and further more diagnostic bands consistent with carbohydrates, lignins, and other OM. These Raman spectra exhibited variability of spectral signatures and of relative intensities between sample treatments indicating that differing growth conditions altered the phytolith carbon. This may have strong implications for understanding the mechanism of phytolith formation, and for use of phytolith carbon isotope values in dating or paleoclimate reconstruction.

Maximizing throughput in label-free microspectroscopy with hybrid Raman imaging

Raman spectroscopy is an optical method providing sample molecular composition, which can be analyzed (by point measurements) or spatially mapped by Raman imaging. These provide different information, signal-to-noise ratios, and require different acquisition times. Here, we quantitatively assess Raman spectral features and compare the two measurement methods by multivariate analysis. We also propose a hybrid method: scanning the beam through the sample but optically binning the signal at one location on the detector. This approach generates significantly more useful spectral signals in terms of peak visibility and statistical information. Additionally, by combination with a complementary imaging mode such as quantitative phase microscopy, hybrid imaging allows high throughput and robust spectral analysis while retaining sample spatial information. We demonstrate the improved ability to discriminate between cell lines when using hybrid scanning compared to typical point mode measurements, by quantitatively evaluating spectra taken from two macrophage-like cell lines. Hybrid scanning also provides better classification capability than the full Raman imaging mode, while providing higher signal-to-noise signals with shorter acquisition times. This hybrid imaging approach is suited for various applications including cytometry, cancer versus noncancer detection, and label-free discrimination of cell types or tissues.

Localized surface plasmon resonances in nanostructures to enhance nonlinear vibrational spectroscopies: towards an astonishing molecular sensitivity

Vibrational transitions contain some of the richest fingerprints of molecules and materials, providing considerable physicochemical information. Vibrational transitions can be characterized by different spectroscopies, and alternatively by several imaging techniques enabling to reach sub-microscopic spatial resolution. In a quest to always push forward the detection limit and to lower the number of needed vibrational oscillators to get a reliable signal or imaging contrast, surface plasmon resonances (SPR) are extensively used to increase the local field close to the oscillators. Another approach is based on maximizing the collective response of the excited vibrational oscillators through molecular coherence. Both features are often naturally combined in vibrational nonlinear optical techniques. In this frame, this paper reviews the main achievements of the two most common vibrational nonlinear optical spectroscopies, namely surface-enhanced sum-frequency generation (SE-SFG) and surface-enhanced coherent anti-Stokes Raman scattering (SE-CARS). They can be considered as the nonlinear counterpart and/or combination of the linear surface-enhanced infrared absorption (SEIRA) and surface-enhanced Raman scattering (SERS) techniques, respectively, which are themselves a branching of the conventional IR and spontaneous Raman spectroscopies. Compared to their linear equivalent, those nonlinear vibrational spectroscopies have proved to reach higher sensitivity down to the single molecule level, opening the way to astonishing perspectives for molecular analysis.

Biological imaging with coherent Raman scattering microscopy: a tutorial

Coherent Raman scattering (CRS) microscopy is gaining acceptance as a valuable addition to the imaging toolset of biological researchers. Optimal use of this label-free imaging technique benefits from a basic understanding of the physical principles and technical merits of the CRS microscope. This tutorial offers qualitative explanations of the principles behind CRS microscopy and provides information about the applicability of this nonlinear optical imaging approach for biological research.

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.

Stimulated Raman scattering imaging by continuous-wave laser excitation

We demonstrate a low-cost-stimulated Raman scattering (SRS) microscope using continuous-wave (cw) lasers as excitation sources. A dual modulation scheme is used to remove the electronic background. The cw-SRS imaging of lipids in fatty liver is demonstrated by excitation of C─H stretch vibration.

Advances in multiphoton microscopy technology

Multiphoton microscopy has enabled unprecedented dynamic exploration in living organisms. A significant challenge in biological research is the dynamic imaging of features deep within living organisms, which permits the real-time analysis of cellular structure and function. To make progress in our understanding of biological machinery, optical microscopes must be capable of rapid, targeted access deep within samples at high resolution. In this Review, we discuss the basic architecture of a multiphoton microscope capable of such analysis and summarize the state-of-the-art technologies for the quantitative imaging of biological phenomena.