Selective-plane-activation structured illumination microscopy.

The background light from out-of-focus planes hinders resolution enhancement in structured illumination microscopy when observing volumetric samples. Here we used selective plane illumination and reversibly photoswitchable fluorescent proteins to realize structured illumination within the focal plane and eliminate the out-of-focus background. Theoretical investigation of the imaging properties and experimental demonstrations show that selective plane activation is beneficial for imaging dense microstructures in cells and cell spheroids.

Femtosecond Laser Maskless Optical Projection Lithography of Cartilage PCM Inspired 3D Protein Matrix to Chondrocyte Phenotype.

Hydrogels containing chondrocytes have exhibited excellent potential in regenerating hyaline cartilage. However, chondrocytes are vulnerable to dedifferentiation during in vitro culture, leading to fibrosis and mechanical degradation of newly formed cartilage. It is proposed to modulate cartilage formation via the developed chondrocyte pericellular matrix (PCM) -like scaffolds for the first time, in which the S, M, and L-sized scaffolds are fabricated by femtosecond laser maskless optical projection lithography (FL-MOPL) of bovine serum albumin-glyceryl methacrylate hydrogel. Chondrocytes on the M PCM-like scaffold can maintain round morphology and synthesize extracellular matrix (ECM) to induce regeneration of hyaline cartilage microtissues by geometrical restriction. A series of M PCM-like scaffolds is fabricated with different stiffness and those with a high Young's modulus are more effective in maintaining the chondrocyte phenotype. The proposed PCM-like scaffolds are effective in modulating cartilage formation influenced by pore size, depth, and stiffness, which will pave the way for a better understanding of the geometric cues of mechanotransduction interactions in regulating cell fate and open up new avenues for tissue engineering.

Imaging vs Nonimaging Raman Spectroscopy for High-Throughput Single-Cell Phenotyping.

Raman spectroscopy can provide nonbiased single-cell analysis based on the endogenous ensemble of biomolecules, with alterations in cellular content indicative of cell state and disease. The measurements themselves can be performed in a variety of modes: generally, full imaging takes the most time but can provide the most information. By reducing the imaging resolution and generating the most characteristic single-cell Raman spectrum in the shortest time, we optimize the utility of the Raman measurement for cell phenotyping. Here, we establish methods to compare these different measurement approaches and assess what, if any, undesired effects occur in the cell. Assuming that laser-induced damage should be apparent as a change in molecular spectra across sequential measurements, and by defining the information content as the Raman-based separability of two cell lines, we thereby establish a parameter range for optimum measurement sensitivity and single-cell throughput in single-cell Raman spectroscopic analysis. While the work here uses 532 nm irradiation, the same approach can be generalized to Raman analysis at other wavelengths.

On-the-fly Raman microscopy guaranteeing the accuracy of discrimination.

Accelerating the measurement for discrimination of samples, such as classification of cell phenotype, is crucial when faced with significant time and cost constraints. Spontaneous Raman microscopy offers label-free, rich chemical information but suffers from long acquisition time due to extremely small scattering cross-sections. One possible approach to accelerate the measurement is by measuring necessary parts with a suitable number of illumination points. However, how to design these points during measurement remains a challenge. To address this, we developed an imaging technique based on a reinforcement learning in machine learning (ML). This ML approach adaptively feeds back "optimal" illumination pattern during the measurement to detect the existence of specific characteristics of interest, allowing faster measurements while guaranteeing discrimination accuracy. Using a set of Raman images of human follicular thyroid and follicular thyroid carcinoma cells, we showed that our technique requires 3,333 to 31,683 times smaller number of illuminations for discriminating the phenotypes than raster scanning. To quantitatively evaluate the number of illuminations depending on the requisite discrimination accuracy, we prepared a set of polymer bead mixture samples to model anomalous and normal tissues. We then applied a home-built programmable-illumination microscope equipped with our algorithm, and confirmed that the system can discriminate the sample conditions with 104 to 4,350 times smaller number of illuminations compared to standard point illumination Raman microscopy. The proposed algorithm can be applied to other types of microscopy that can control measurement condition on the fly, offering an approach for the acceleration of accurate measurements in various applications including medical diagnosis.

Ratiometric analysis of reversible thia-Michael reactions using nitrile-tagged molecules by Raman microscopy.

Ratiometric Raman analysis of reversible thia-Michael reactions was achieved using α-cyanoacrylic acid (αCNA) derivatives. Among αCNAs, the smallest derivative, ThioRas (molecular weight: 167 g mol-1), and its glutathione adduct were simultaneously detected in various subcellular locations using Raman microscopy.

Deflectometry based calibration of a deformable mirror for aberration correction and remote focusing in microscopy.

Adaptive optics (AO) techniques enhance the capability of optical microscopy through precise control of wavefront modulations to compensate phase aberrations and improves image quality. However, the aberration correction is often limited due to the lack of dynamic range in existing calibration methods, such as interferometry or Shack-Hartmann (SH) wavefront sensors. Here, we use deflectometry (DF) as a calibration method for a deformable mirror (DM) to extend the available range of aberration correction. We characterised the dynamic range and accuracy of the DF-based calibration of DMs depending on the spatial frequency of the test pattern used in DF. We also demonstrated the capability of large magnitude phase control for remote-focusing over a range larger than was possible with SH sensing.

Multifocal Raman Spectrophotometer for Examining Drug-Induced and Chemical-Induced Cellular Changes in 3D Cell Spheroids.

Cell spheroids offer alternative in vitro cell models to monolayer cultured cells because they express complexities similar to those of in vivo tissues, such as cellular responses to drugs and chemicals. Raman spectroscopy emerged as a powerful analytical tool for detecting chemical changes in living cells because it nondestructively provides vibrational information regarding a target. Although multiple iterations are required in drug screening to determine drugs to treat cell spheroids and assess the inter-spheroid heterogeneity, current Raman applications used in spheroids analysis allow the observation of only a few spheroids owing to the low throughput of Raman spectroscopy. In this study, we developed a multifocal Raman spectrophotometer that enables simultaneous analysis of multiple spheroids in separate wells of a regular 96-well plate. By utilizing 96 focal spots excitation and parallel signal collection, our system can improve the throughput by approximately 2 orders of magnitude compared to a conventional single-focus Raman microscope. The Raman spectra of HeLa cell spheroids treated with anticancer drugs and HepG2 cell spheroids treated with free fatty acids were measured simultaneously, and concentration-dependent cellular responses were observed in both studies. Using the multifocal Raman spectrophotometer, we rapidly observed chemical changes in spheroids, and thus, this system can facilitate the application of Raman spectroscopy in analyzing the cellular responses of spheroids.

Correction for Extrinsic Background in Raman Hyperspectral Images.

Raman hyperspectral microscopy is a valuable tool in biological and biomedical imaging. Because Raman scattering is often weak in comparison to other phenomena, prevalent spectral fluctuations and contaminations have brought advancements in analytical and chemometric methods for Raman spectra. These chemometric advances have been key contributors to the applicability of Raman imaging to biological systems. As studies increase in scale, spectral contamination from extrinsic background, intensity from sources such as the optical components that are extrinsic to the sample of interest, has become an emerging issue. Although existing baseline correction schemes often reduce intrinsic background such as autofluorescence originating from the sample of interest, extrinsic background is not explicitly considered, and these methods often fail to reduce its effects. Here, we show that extrinsic background can significantly affect a classification model using Raman images, yielding misleadingly high accuracies in the distinction of benign and malignant samples of follicular thyroid cell lines. To mitigate its effects, we develop extrinsic background correction (EBC) and demonstrate its use in combination with existing methods on Raman hyperspectral images. EBC isolates regions containing the smallest amounts of sample materials that retain extrinsic contributions that are specific to the device or environment. We perform classification both with and without the use of EBC, and we find that EBC retains biological characteristics in the spectra while significantly reducing extrinsic background. As the methodology used in EBC is not specific to Raman spectra, correction of extrinsic effects in other types of hyperspectral and grayscale images is also possible.

Synthesis of biocompatible BSA-GMA and two-photon polymerization of 3D hydrogels with free radical type I photoinitiator.

Although the development of three-dimensional (3D) printing technology is growing rapidly in the biomedical field, it remains a challenge to achieve arbitrary 3D structures with high resolution and high efficiency. Protein hydrogels fabricated by two- photon polymerization (TPP) have excellent mechanical properties, high precision, and 3D architecture. However, a large number of the amino acid group in bovine serum albumin (BSA) would be consumed when the protein-based hydrogels use dyes of free radical type II photoinitiators. In this study, we use glycidyl methacrylate (GMA) to modify BSA molecules to obtain a series of BSA-GMA materials, allowing the protein material to be two-photon polymerized with a water-soluble free radical type I photoinitiator. The precisely controllable 3D structure of the BSA-GMA hydrogel was fabricated by adjusting the concentration of the precursor solution, the degree of methacrylation, and the processing parameters of the TPP technique. Importantly, BSA-GMA materials are free of acidic hazardous substances. Meanwhile, the water-soluble initiator lithium phenyl (2,4,6-trimethylbenzoyl) phosphite (LAP) allows TPP on the vinyl group of the GMA chain and thus without consuming its amino acid group. The as-prepared BSA-GMA hydrogel structure exhibits excellent autofluorescence imaging, pH responsiveness, and biocompatibility, which would provide new avenues for potential applications in tissue engineering and biomedical fields to meet specific biological requirements.

Differentiability of cell types enhanced by detrending a non-homogeneous pattern in a line-illumination Raman microscope.

A line illumination Raman microscope extracts the underlying spatial and spectral information of a sample, typically a few hundred times faster than raster scanning. This makes it possible to measure a wide range of biological samples such as cells and tissues - that only allow modest intensity illumination to prevent potential damage - within feasible time frame. However, a non-uniform intensity distribution of laser line illumination may induce some artifacts in the data and lower the accuracy of machine learning models trained to predict sample class membership. Here, using cancerous and normal human thyroid follicular epithelial cell lines, FTC-133 and Nthy-ori 3-1 lines, whose Raman spectral difference is not so large, we show that the standard pre-processing of spectral analyses widely used for raster scanning microscopes introduced some artifacts. To address this issue, we proposed a detrending scheme based on random forest regression, a nonparametric model-free machine learning algorithm, combined with a position-dependent wavenumber calibration scheme along the illumination line. It was shown that the detrending scheme minimizes the artifactual biases arising from non-uniform laser sources and significantly enhances the differentiability of the sample states, i.e., cancerous or normal epithelial cells, compared to the standard pre-processing scheme.

Label-Free Evaluation of Maturation and Hepatotoxicity of Human iPSC-Derived Hepatocytes Using Hyperspectral Raman Imaging.

To promote the clinical application of human induced pluripotent stem cell (hiPSC)-derived hepatocytes, a method capable of monitoring regenerative processes and assessing differentiation efficiency without harming or modifying these cells is important. Raman microscopy provides a powerful tool for this as it enables label-free identification of intracellular biomolecules in live samples. Here, we used label-free Raman microscopy to assess hiPSC differentiation into hepatocyte lineage based on the intracellular chemical content. We contrasted these data with similar phenotypes from the HepaRG and from commercially available hiPSC-derived hepatocytes (iCell hepatocytes). We detected hepatic cytochromes, lipids, and glycogen in hiPSC-derived hepatocyte-like cells (HLCs) but not biliary-like cells (BLCs), indicating intrinsic differences in biomolecular content between these phenotypes. The data show significant glycogen and lipid accumulation as early as the definitive endoderm transition. Additionally, we explored the use of Raman imaging as a hepatotoxicity assay for the HepaRG and iCell hepatocytes, with data displaying a dose-dependent reduction of glycogen accumulation in response to acetaminophen. These findings show that the nondestructive and high-content nature of Raman imaging provides a promising tool for both quality control of hiPSC-derived hepatocytes and hepatotoxicity screening.

High-throughput line-illumination Raman microscopy with multislit detection.

Raman microscopy is an emerging tool for molecular imaging and analysis of living samples. Use of Raman microscopy in life sciences is, however, still limited because of its slow measurement speed for spectral imaging and analysis. We developed a multiline-illumination Raman microscope to achieve ultrafast Raman spectral imaging. A spectrophotometer equipped with a periodic array of confocal slits detects Raman spectra from a sample irradiated by multiple line illuminations. A comb-like Raman hyperspectral image is formed on a two-dimensional detector in the spectrophotometer, and a hyperspectral Raman image is acquired by scanning the sample with multiline illumination array. By irradiating a sample with 21 simultaneous illumination lines, we achieved high-throughput Raman hyperspectral imaging of mouse brain tissue, acquiring 1108800 spectra in 11.4 min. We also measured mouse kidney and liver tissue as well as conducted label-free live-cell molecular imaging. The ultrafast Raman hyperspectral imaging enabled by the presented technique will expand the possible applications of Raman microscopy in biological and medical fields.

Raman imaging of rat nonalcoholic fatty liver tissues reveals distinct biomolecular states.

An essential challenge in diagnosing states of nonalcoholic fatty liver disease (NAFLD) is the early prediction of progression from nonalcoholic fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) before the disease progresses. Histological diagnoses of NAFLD rely on the appearance of anomalous tissue morphologies, and it is difficult to segment the biomolecular environment of the tissue through a conventional histopathological approach. Here, we show that hyperspectral Raman imaging provides diagnostic information on NAFLD in rats, as spectral changes among disease states can be detected before histological characteristics emerge. Our results demonstrate that Raman imaging of NAFLD can be a useful tool for histopathologists, offering biomolecular distinctions among tissue states that cannot be observed through standard histopathological means.

Lipid droplet accumulation and adipophilin expression in follicular thyroid carcinoma.

Follicular neoplasms of the thyroid include follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA). However, the differences in cytological findings between FTC and FTA remain undetermined. Here, we aimed to evaluate the accumulation of lipid droplets (LDs) and the expression of adipophilin (perilipin 2/ADRP/ADFP), a known LD marker, in cultured FTC cells. We also immunohistochemically compared adipophilin expression in the FTC and FTA of resected human thyroid tissues. Cultured FTC (FTC-133 and RO82W-1) possessed increased populations of LDs compared to thyroid follicular epithelial (Nthy-ori 3-1) cells. In vitro treatment with phosphatidylinositol-3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling inhibitors (LY294002, MK2206, and rapamycin) in FTC-133 cells downregulated the PI3K/Akt/mTOR/sterol regulatory element-binding protein 1 (SREBP1) signaling pathway, resulting in a significant reduction in LD accumulation. SREBP1 is a master transcription factor that controls lipid metabolism. Fluorescence immunocytochemistry revealed adipophilin expression in the LDs of FTC-133 cells. Immunohistochemical analysis of surgically resected human thyroid tissues revealed significantly increased expression of adipophilin in FTC compared with FTA and adjacent non-tumorous thyroid epithelia. Taken together, LDs and adipophilin were abundant in cultured FTC; the evaluation of adipophilin expression can help distinguish FTC from FTA in surgical specimens.

Roadmap on Label-Free Super-Resolution Imaging.

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Raman Spectroscopy for Chemical Biology Research.

In chemical biology research, various fluorescent probes have been developed and used to visualize target proteins or molecules in living cells and tissues, yet there are limitations to this technology, such as the limited number of colors that can be detected simultaneously. Recently, Raman spectroscopy has been applied in chemical biology to overcome such limitations. Raman spectroscopy detects the molecular vibrations reflecting the structures and chemical conditions of molecules in a sample and was originally used to directly visualize the chemical responses of endogenous molecules. However, our initial research to develop "Raman tags" opens a new avenue for the application of Raman spectroscopy in chemical biology. In this Perspective, we first introduce the label-free Raman imaging of biomolecules, illustrating the biological applications of Raman spectroscopy. Next, we highlight the application of Raman imaging of small molecules using Raman tags for chemical biology research. Finally, we discuss the development and potential of Raman probes, which represent the next-generation probes in chemical biology.

Label-free chemical imaging of cytochrome P450 activity by Raman microscopy.

Although investigating drug modulation of cytochrome P450 (CYP) activity under physiological conditions is crucial in drug development to avoid severe adverse drug reactions, the current evaluation approaches that rely on the destructive and end-point analysis can be misleading due to invasive treatments and cellular heterogeneity. Here, we propose a non-destructive and high-content method for visualizing and quantifying intracellular CYP activity under drug administration by Raman microscopy. The redox-state and spin-state sensitive Raman measurement indicated that the induced CYPs in living hepatocytes were in oxidized and low-spin state, which is related to monooxygenase function of CYP. Moreover, glycogen depletion associated with CYP induction was simultaneously observed, indicating a relevant effect on glucose metabolism. By deciphering the overall changes in the biochemical fingerprints of hepatocytes, Raman microscopy offers a non-destructive and quantitative chemical imaging method to evaluate CYP activity at the single-cell level with the potential to facilitate future drug development schemes.

Bessel-beam illumination Raman microscopy.

We demonstrate the use of Bessel beams for side illumination slit-scanning Raman imaging for label-free and hyperspectral analysis of cell spheroids. The background elimination by the side illumination and the aberration-resistant Bessel beam drastically improves the image contrast in Raman observation, allowing label-free investigation of intracellular molecules in thick biological samples. Live cell spheroids were observed to confirm the improvement in image contrast and background reduction with Bessel illumination compared to conventional epi-line illumination.

Label-Free Monitoring of Drug-Induced Cytotoxicity and Its Molecular Fingerprint by Live-Cell Raman and Autofluorescence Imaging.

Simultaneous observation of drug distribution at the effector site and subsequent cell response are essential in the drug development process. However, few studies have visualized the drug itself and biomolecular interactions in living cells. Here, we used label-free Raman microscopy to investigate drug-induced cytotoxicity and visualize drug uptake and subcellular localization by its specific molecular fingerprint. A redox-sensitive Raman microscope detected the decrease of reduced cytochrome c (cyt c) after Actinomycin D (ActD) treatment in a time-dependent and dose-dependent format. Immunofluorescence staining of cyt c suggested that the release of cyt c was not the major cause. Combining Raman microscopy with conventional biological methods, we reported that the oxidization of cyt c is an early cytotoxicity marker prior to the release of cyt c. Moreover, as the spectral properties of ActD are sensitive to the surrounding environment, subcellular localization of ActD was visualized sensitively by the weak autofluorescence, and the intercalation of ActD into DNA was detected by shifted Raman peaks, allowing for parallel observation of drug uptake and the mechanism of action. In this research, we achieved simultaneous observation of cytotoxicity and cellular drug uptake by Raman microscopy, which could facilitate a precise understanding of pharmacological effects and predict potential drug toxicity in the future.