Using complementary optical microscopy techniques provides more detailed insight into biological samples. However, misinterpretation can occur by temporal discrepancies due to differences in temporal resolution and switching imaging modalities. Here, we demonstrated multimodal imaging of cryofixed cells using Raman and fluorescence structured illumination microscopy (SIM). Cryofixation preserves structures and chemical states of samples in their near-native states, allowing multimodal imaging without artifacts caused by temporal discrepancy. We demonstrated multimodal imaging of cryofixed HeLa cells stained with an actin probe, where Raman microscope visualized cytochromes, proteins and lipids, and SIM visualized fluorescence-labelled actin filaments.
Raman microscopy provides a variety of insights into molecular composition, chemical state, and environmental conditions in biological samples. However, biological imaging with Raman microscopy have faced challenges such a low signal-to-noise ratio, mainly due to the low scattering efficiency of Raman scattering. To overcome this limitation, we developed a cryo-Raman microscope integrated with a cryostat capable of rapid freezing of biological samples and low-temperature Raman imaging. The spatiotemporal cryofixation of biological samples allows long exposure measurements to accumulate signals without photodamage. We observed both reduction of photobleaching in resonant Raman scattering of cytochromes in cryofixed HeLa cells, and the preservation of redox states of cytochromes in rat heart tissue by cryofixation.
Raman microscopy enables us to obtain molecular information in biological samples but has suffered from low signal-to-noise ratio (SNR) due to low of Raman scattering cross-section. Here we developed a cryo-stat equipped Raman microscope for low temperature measurement, allowing long time accumulation of Raman signals. We confirmed the SNR improvement in Raman imaging of cryofixed HeLa cells without photodamage under long time observation at low temperature. The reduction of photobleaching in resonant Raman scattering of carotenoid and cytochrome significantly increases the SNR, demonstrated by 7-color high SNR Raman imaging with multiple Raman tags, including EdU, MitoBADY, and alkyne-tagged Coenzyme Q (AltQ2). AltQ2 is a mobile small molecule that cannot be fixed by chemical fixation.
KEYWORDS: Raman spectroscopy, Light sources and illumination, Machine learning, Medical research, Random forests, Microscopy, Microscopes, Engineering, Diagnostics, Decision trees
We propose a method that combines high-speed Raman imaging with a machine learning technique, multi-armed bandit, to achieve rapid and accurate identification of samples under observation. First, our method dvides the field of view of the sample into small sections, and it returns either ’positive’ or ’negative’ based on whether the sections with high anomaly indices exceed a certain proportion. Moreover, the points to be measured are determined dynamically and automatically generating a series of optimal illumination patterns.
We developed spontaneous Raman microscopy using Bandit algorithm to realize fast diagnosis of the existence of anomalies or not with guaranteeing accuracy. The algorithm evaluates obtained Raman spectra during measurement to judge if the diagnosis is completed with ensuring an allowance error rate that users decided and also to generate optimal illumination patterns for the next irradiation which are optimized to accelerate the detection of anomaly. We present our simulation and experimental studies to show that our system can accelerate more than a few tens times faster than line-scanning Raman microscopy which requires full scanning over all pixels.
Here, we performed photoinitiator-free two-photon polymerization (TPP) to fabricate 3D cell micro-scaffolds. By using a visible femtosecond pulsed laser as excitation, TPP is induced in deep UV-absorbing moieties without the use of photo-initiators. We fabricated 3D micro-structures of biocompatible materials and glycidyl methacrylate protein without photoinitiators. By using Raman/Brillouin spectroscopy, we quantitatively investigated the molecular and mechanical properties of the 3D structures, which are important factors for cell functions and growth on scaffolds. We seeded cells on the 3D scaffolds and observed their attachment and proliferation without causing numerous cell deaths due to the absence of potentially cytotoxic photoinitiators.
Raman spectroscopy provides a comprehensive molecular information of a biological sample without any invasive and destructive treatment prior to a measurement. However, the slow measurement speed limits imaging applications of Raman spectroscopy. I present acceleration of Raman spectroscopy and imaging by multiplexed spatial sampling. Multiline illumination Raman microscopy, scanning a sample with multiple line-shaped laser foci, improved the imaging speed by 4 orders of magnitude in comparison to conventional confocal Raman microscopy. I also present a selective-sampling approach for accelerating Raman spectroscopy and imaging. I discuss the potential new applications of accelerated Raman spectroscopy and imaging in life sciences.
We present our recent study combined multi-armed Bandits algorithm in reinforcement learning with spontaneous Raman microscope for the acceleration of the measurements by designing and generating optimal illumination pattern “on the fly” during the measurements while keeping the accuracy of diagnosis. We present our simulation and experimental studies using Raman images in the diagnosis of follicular thyroid carcinoma and non-alcoholic fatty liver disease, and show that this protocol can accelerate more than a few tens times in speedy and accurate diagnoses faster than line-scanning Raman microscope that requires the full detailed scanning over all pixels.
The on-the-fly Raman image microscopy designs to accelerate measurements by combining one of reinforcement machine learning techniques, bandit algorithm utilized in the Monte Carlo tree search in alpha-GO, and a programmable illumination system. Given a descriptor based on Raman signals to quantify the likelihood of the predefined quantity to be evaluated, e.g., the degree of cancers, the on-the-fly Raman image microscopy evaluates the upper and lower confidence bounds in addition to the sample average of that quantity based on finite point/line illuminations, and then the bandit algorithm feedbacks the desired illumination pattern to accelerate the detection of the anomaly, during the measurement to the microscope.
Most conventional bandit algorithms assume that infinite number of measurements or samples provides us with 100% accuracy. However, in Raman measurements we should develop both a Raman descriptor to quantify the degree of anomaly, and a new algorithm to take into account the finite accuracy lower than 100%. This microscope can also be applied to other problems, besides detection of cancer cells, such as anomaly or defects of materials. The algorithm itself is also beneficial and transferrable to the other microscopes such as infrared image microscope.
Two-photon fabrication is expected to be a technique for fabricating biological tissues for regenerative medicine and drug discovery because of its capability of fabricating 3D structures on a subcellular scale. In this study, we conducted two-photon fabrication of biocompatible materials without photoinitiators. By using a visible-wavelength femtosecond pulsed laser as excitation light, two-photon polymerization is induced in deep UV absorbing moieties without the use of photo-initiators. We performed 3D micro/nanofabrication of a biocompatible hydrogel material. By using Raman spectral change, we investigated the photo-chemical process of the biocompatible upon the irradiation of visible pulsed laser light.
KEYWORDS: Raman spectroscopy, Raman scattering, Live cell imaging, Microscopy, Molecules, Signal detection, Resonance enhancement, Molecular spectroscopy, Microscopes, Signal to noise ratio
Resonance Raman scattering is useful for improving a signal-to-noise ratio and a data acquisition speed in Raman imaging. However, the detection of non-resonance Raman scattering is often hindered by resonance signals and fluorescent background. To aid this dilemma in using resonance Raman scattering, we have developed a confocal Raman microscope with dual-wavelength excitation. Living HeLa cells were measured simultaneously at two different excitation wavelengths. At 532 nm excitation, cytochromes were detected by the resonance effect. At 660 nm excitation, non-resonance signals from proteins and lipids were obtained without any clear influence from cytochromes and fluorescent background.
We used only a narrow range, 1397-1501 cm-1, for high-throughput analysis of cancerous and noncancerous human cell lines by spontaneous Raman microscopy. With baseline-corrected cellwise spectra in this range, two cell lines were discriminated at accuracy higher than 90%. This narrowband measurement allowed reduction of the signal readout time by 24-folds in comparison to a correspondent wideband measurement detecting 536-3132 cm-1, enabling cell analysis at 2.5 cells/min. To further improve the throughput, we employed detector binning, which allowed reduction not just of the readout time but also of the signal accumulation time with maintaining signal-to-background ratio and the accuracy. Improvement of the imaging speed by this approach reached at 4-folds, enabling a high-throughout analysis at 10 cells/min.
Acceleration of image acquisition rate in Raman microscopy has been required to fully utilize its analytical advantages for biological/medical applications. By introducing the multiple line illumination and parallel spectral detection capability, image acquisition rate in the Raman microscope was improved < 104 times, compared with the conventional confocal Raman. High-resolution spontaneous Raman imaging of cells/tissues was thus enabled with an image acquisition time of a few minutes. Subsequent high-throughput Raman imaging-based analyses were also performed, including multiplex Raman tag imaging, cell classification, microplastic detection.
Terbium ions, Tb3+, fluoresced in a cell at deep-ultraviolet excitation. Intensity of the fluorescence was dropped by RNA decomposition. It was also found that fluorescence intensity of Tb3+ conjugated with DNA increased with strand dissociation. These results indicated specificity of Tb3+ to single-stranded nucleic acid, mostly RNA in cell and tissue. We employed Tb3+ and Hoechst, DNA-specific dyes, for deep-ultraviolet excitation fluorescence imaging. With this imaging, nucleolus, nucleoplasm, and cytoplasm were discriminated. Thanks to the small penetration depth of deep-ultraviolet light into tissue, this imaging modality was useful for slide-free histology and rapid cancer detection in a human lymph node.
Nerve-sparing surgery is essential to avoid functional deficits of the limbs and organs. Raman scattering, a label-free, minimally invasive, and accurate modality, is one of the best candidate technologies to detect nerves for nerve-sparing surgery. However, Raman scattering imaging is too time-consuming to be employed in surgery. Here we present a rapid and accurate nerve visualization method using a multipoint Raman imaging technique that has enabled simultaneous spectra measurement from different locations (n=32) of a sample. Five sec is sufficient for measuring n=32 spectra with good S/N from a given tissue. Principal component regression discriminant analysis discriminated spectra obtained from peripheral nerves (n=863 from n=161 myelinated nerves) and connective tissue (n=828 from n=121 tendons) with sensitivity and specificity of 88.3% and 94.8%, respectively. To compensate the spatial information of a multipoint-Raman-derived tissue discrimination image that is too sparse to visualize nerve arrangement, we used morphological information obtained from a bright-field image. When merged with the sparse tissue discrimination image, a morphological image of a sample shows what portion of Raman measurement points in arbitrary structure is determined as nerve. Setting a nerve detection criterion on the portion of “nerve” points in the structure as 40% or more, myelinated nerves (n=161) and tendons (n=121) were discriminated with sensitivity and specificity of 97.5%. The presented technique utilizing a sparse multipoint Raman image and a bright-field image has enabled rapid, safe, and accurate detection of peripheral nerves.
Raman microscopy enables a sensitive, label-free molecular imaging of cells. Employing deep-UV (DUV) light for Raman excitation allows selective measurement of nucleotide bases and aromatic amino acids in a cell, without spectral overlapping of components with a large quantity (i.e. lipid, peptide), because their Raman scattering are specifically enhanced due to the resonance effect. To implement DUV resonance Raman imaging of cells, I previously established a home-built Raman microscope equipped with a DUV laser (λ = 257.2 nm). Raman image representing the distribution of cellular nucleic acid can be reconstructed with the intensity of a Raman band selectively assigned to adenine and guanine. Unfortunately, DUV resonance Raman imaging of cells is severely hindered by molecular photodegradation that occurs after a molecule absorbs DUV light during Raman measurement, precluding a high signal-to-noise ratio and repetitive measurement. To address this issue, I developed a technique for molecular protection under DUV exposure; the trivalent ions of lanthanide group including terbium, europium, and thulium could significantly suppress the molecular photodegradation by relaxing the DUV-excited molecules. The buffer solution containing any of these lanthanide ions with the concentration of 100 µM or higher could provide less destruction of the cellular structures, including nucleotide bases, than the one without the ions, under DUV exposure. Utilizing such protective effects of the lanthanide ions, I successfully achieved a twice higher signal-to-noise ratio and repetitive DUV Raman imaging of cells.
Deep-UV (DUV) plasmonics can expand the possibilities of DUV-based techniques (i.e. UV lithography, UV spectroscopy, UV imaging, UV disinfection). Here we present that indium is useful for research of DUV plasmonics. According to dielectric function, indium and aluminum are low-loss, DUV plasmonic metals, of which the imaginary parts are far smaller than those of other metals (i.e. rhodium, platinum) in the DUV range. Additionally, the real parts in the whole DUV range are close to but smaller than -2, allowing efficient generation of surface plasmon polaritons on an indium or aluminum nanosphere. In comparison to aluminum, indium provides a distinctive feature for fabricating DUV-resonant substrates. It is highly apt to form a grainy deposition film on a standard, optically transparent substrate (i.e. fused silica). The surface plasmon resonance wavelength becomes promptly tailored by simply varying the deposition thickness of the films, resulting in different grain sizes. Thus, we fabricated indium-coated substrates having different plasmon resonance wavelengths by varying the deposition thicknesses from 10 to 50 nm. DUV resonance Raman scattering of adenine molecules was best enhanced using the 25 nm deposition thickness substrates by the factor of 2. Furthermore, the FDTD calculation simulated the electromagnetic field enhancement over a grainy, indium-coated fused silica substrate. Both results indicate how indium plays an indispensable role in study of DUV plasmonics.
We report the first demonstration of deep ultraviolet (DUV) Raman imaging of a cell. Nucleotide distributions in a HeLa cell were observed without any labeling at 257 nm excitation with resonant bands attributable to guanine and adenine. Obtained images represent DNA localization at nucleoli in the nucleus and RNA distribution in the cytoplasm. The presented technique extends the potential of Raman microscopy as a tool to selectively probe nucleic acids in a cell with high sensitivity due to resonance.
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