Probing the metabolic heterogeneity of live Euglena gracilis with stimulated Raman scattering microscopy

Fast Real-Time Brain Tumor Detection Based on Stimulated Raman Histology and Self-Supervised Deep Learning Model

In intraoperative brain cancer procedures, real-time diagnosis is essential for ensuring safe and effective care. The prevailing workflow, which relies on histological staining with hematoxylin and eosin (H&E) for tissue processing, is resource-intensive, time-consuming, and requires considerable labor. Recently, an innovative approach combining stimulated Raman histology (SRH) and deep convolutional neural networks (CNN) has emerged, creating a new avenue for real-time cancer diagnosis during surgery. While this approach exhibits potential, there exists an opportunity for refinement in the domain of feature extraction. In this study, we employ coherent Raman scattering imaging method and a self-supervised deep learning model (VQVAE2) to enhance the speed of SRH image acquisition and feature representation, thereby enhancing the capability of automated real-time bedside diagnosis. Specifically, we propose the VQSRS network, which integrates vector quantization with a proxy task based on patch annotation for analysis of brain tumor subtypes. Training on images collected from the SRS microscopy system, our VQSRS demonstrates a significant speed enhancement over traditional techniques (e.g., 20-30 min). Comparative studies in dimensionality reduction clustering confirm the diagnostic capacity of VQSRS rivals that of CNN. By learning a hierarchical structure of recognizable histological features, VQSRS classifies major tissue pathological categories in brain tumors. Additionally, an external semantic segmentation method is applied for identifying tumor-infiltrated regions in SRH images. Collectively, these findings indicate that this automated real-time prediction technique holds the potential to streamline intraoperative cancer diagnosis, providing assistance to pathologists in simplifying the process.

Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level

This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.

Photoswitchable polyynes for multiplexed stimulated Raman scattering microscopy with reversible light control

Optical imaging with photo-controllable probes has greatly advanced biological research. With superb chemical specificity of vibrational spectroscopy, stimulated Raman scattering (SRS) microscopy is particularly promising for super-multiplexed optical imaging with rich chemical information. Functional SRS imaging in response to light has been recently demonstrated, but multiplexed SRS imaging with reversible photocontrol remains unaccomplished. Here, we create a multiplexing palette of photoswitchable polyynes with 16 Raman frequencies by coupling asymmetric diarylethene with super-multiplexed Carbow (Carbow-switch). Through optimization of both electronic and vibrational spectroscopy, Carbow-switch displays excellent photoswitching properties under visible light control and SRS response with large frequency change and signal enhancement. Reversible and spatial-selective multiplexed SRS imaging of different organelles are demonstrated in living cells. We further achieve photo-selective time-lapse imaging of organelle dynamics during oxidative stress and protein phase separation. The development of Carbow-switch for photoswitchable SRS microscopy will open up new avenues to study complex interactions and dynamics in living cells with high spatiotemporal precision and multiplexing capability.

Rapid detection of six Oceanobacillus species in Daqu starter using single-cell Raman spectroscopy combined with machine learning

Many traditional fermented foods and beverages industries around the world request the addition of multi-species starter cultures. However, the microbial community in starter cultures is subject to fluctuations due to their exposure to an open environment during fermentation. A rapid detection approach to identify the microbial composition of starter culture is essential to ensure the quality of the final products. Here, we applied single-cell Raman spectroscopy (SCRS) combined with machine learning to monitor Oceanobacillus species in Daqu starter, which plays crucial roles in the process of Chinese baijiu. First, a total of six Oceanobacillus species (O. caeni, O. kimchii, O. iheyensis, O. sojae, O. oncorhynchi subsp. Oncorhynchi and O. profundus) were detected in 44 Daqu samples by amplicon sequencing and isolated by pure culture. Then, we created a reference database of these Oceanobacillus strains which correlated their taxonomic data and single-cell Raman spectra (SCRS). Based on the SCRS dataset, five machine-learning algorithms were used to classify Oceanobacillus strains, among which support vector machine (SVM) showed the highest rate of accuracy. For validation of SVM-based model, we employed a synthetic microbial community composed of varying proportions of Oceanobacillus species and demonstrated a remarkable accuracy, with a mean error was less than 1% between the predicted result and the expected value. The relative abundance of six different Oceanobacillus species during Daqu fermentation was predicted within 60 min using this method, and the reliability of the method was proved by correlating the Raman spectrum with the amplicon sequencing profiles by partial least squares regression. Our study provides a rapid, non-destructive and label-free approach for rapid identification of Oceanobacillus species in Daqu starter culture, contributing to real-time monitoring of fermentation process and ensuring high-quality products.

High-throughput single-cell sorting by stimulated Raman-activated cell ejection

Single-cell sorting is essential to explore cellular heterogeneity in biology and medicine. Recently developed Raman-activated cell sorting (RACS) circumvents the limitations of fluorescence-activated cell sorting, such as the cytotoxicity of labels. However, the sorting throughputs of all forms of RACS are limited by the intrinsically small cross-section of spontaneous Raman scattering. Here, we report a stimulated Raman-activated cell ejection (S-RACE) platform that enables high-throughput single-cell sorting based on high-resolution multi-channel stimulated Raman chemical imaging, in situ image decomposition, and laser-induced cell ejection. The performance of this platform was illustrated by sorting a mixture of 1 μm polymer beads, where 95% yield, 98% purity, and 14 events per second throughput were achieved. Notably, our platform allows live cell ejection, allowing for the growth of single colonies of bacteria and fungi after sorting. To further illustrate the chemical selectivity, lipid-rich Rhodotorula glutinis cells were successfully sorted from a mixture with Saccharomyces cerevisiae, confirmed by downstream quantitative PCR. Furthermore, by integrating a closed-loop feedback control circuit into the system, we realized real-time single-cell imaging and sorting, and applied this method to precisely eject regions of interest from a rat brain tissue section. The reported S-RACE platform opens exciting opportunities for a wide range of single-cell applications in biology and medicine.

Label-free mid-infrared photothermal live-cell imaging beyond video rate

Advancement in mid-infrared (MIR) technology has led to promising biomedical applications of MIR spectroscopy, such as liquid biopsy or breath diagnosis. On the contrary, MIR microscopy has been rarely used for live biological samples in an aqueous environment due to the lack of spatial resolution and the large water absorption background. Recently, mid-infrared photothermal (MIP) imaging has proven to be applicable to 2D and 3D single-cell imaging with high spatial resolution inherited from visible light. However, the maximum measurement rate has been limited to several frames s^-1, limiting its range of use. Here, we develop a significantly improved wide-field MIP quantitative phase microscope with two orders-of-magnitude higher signal-to-noise ratio than previous MIP imaging techniques and demonstrate live-cell imaging beyond video rate. We first derive optimal system design by numerically simulating thermal conduction following the photothermal effect. Then, we develop the designed system with a homemade nanosecond MIR optical parametric oscillator and a high full-well-capacity image sensor. Our high-speed and high-spatial-resolution MIR microscope has great potential to become a new tool for life science, in particular for live-cell analysis.

Scytonemin redox status in a filamentous cyanobacterium visualized by an excitation-laser-line-scanning spontaneous Raman scattering spectral microscope

Some cyanobacteria produce a UVA-absorbing pigment, scytonemin, at extracellular sheaths. Although scytonemin-containing dark sheaths are recognizable through optical microscopes and its redox changes have been known for decades, there has been no report to obtain images of both oxidized and reduced scytonemins at subcellular resolution. Here, we show that a spontaneous Raman scattering spectral microscopy based on an excitation-laser-line-scanning method unveil 3D subcellular distributions of both the oxidized and reduced scytonemins in a filamentous cyanobacterium. The redox changes of scytonemin were supported by comparison in the Raman spectra between the cyanobacterial cells, solid-state scytonemin and quantum chemical normal mode analysis. Distributions of carotenoids, phycobilins, and the two redox forms of scytonemin were simultaneously visualized with an excitation wavelength at 1064 nm that is virtually free from the optical screening by the dark sheaths. The redox differentiation of scytonemin will advance our understanding of the redox homeostasis and secretion mechanisms of individual cyanobacteria as well as microscopic chemical environments in various microbial communities. The line-scanning Raman microscopy based on the 1064 nm excitation is thus a promising tool for exploring hitherto unreported Raman spectral features and distribution of nonfluorescent molecules embedded below nontransparent layers for visible light, while avoiding interference by autofluorescence.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Simultaneous Imaging and Characterization of Polyunsaturated Fatty Acids, Carotenoids, and Microcrystalline Guanine in Single Aurantiochytrium limacinum Cells with Linear and Nonlinear Raman Microspectroscopy

Thraustochytrids are heterotrophic marine protists known for their high production capacity of various compounds with health benefits, such as polyunsaturated fatty acids and carotenoids. Although much effort has been focused on developing optimal cultivation methods for efficient microbial production, these high-value compounds and their interrelationships are not well understood at the single-cell level. Here we used spontaneous (linear) Raman and multiplex coherent anti-Stokes Raman scattering (CARS) microspectroscopy to visualize and characterize lipids (e.g., docosahexaenoic acid) and carotenoids (e.g., astaxanthin) accumulated in single living Aurantiochytrium limacinum cells. Spontaneous Raman imaging with the help of multivariate curve resolution-alternating least-squares enabled us to make unambiguous assignments of the molecular components we detected and derive their intracellular distributions separately. Near-IR excited CARS imaging yielded the Raman images at least an order of magnitude faster than spontaneous Raman imaging, with suppressed contributions of carotenoids. As the culture time increased from 2 to 5 days, the lipid amount increased by a factor of ∼7, whereas the carotenoid amount did not change significantly. Furthermore, we observed a highly localized component in A. limacinum cells. This component was found to be mixed crystals of guanine and other purine derivatives. The present study demonstrates the potential of the linear-nonlinear Raman hybrid approach that allows for accurate molecular identification and fast imaging in a label-free manner to link information derived from single cells with strategies for mass culture of useful thraustochytrids.

Optofluidic imaging meets deep learning: from merging to emerging

Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative "smart" engine. A suite of advanced optical microscopes now enables imaging over a range of spatial scales (from molecules to organisms) and temporal window (from microseconds to hours). On the other hand, the staggering diversity of DL algorithms has revolutionized image processing and analysis at the scale and complexity that were once inconceivable. Recognizing these exciting but overwhelming developments, we provide a timely review of their latest trends in the context of lab-on-a-chip imaging, or coined optofluidic imaging. More importantly, here we discuss the strengths and caveats of how to adopt, reinvent, and integrate these imaging techniques and DL algorithms in order to tailor different lab-on-a-chip applications. In particular, we highlight three areas where the latest advances in lab-on-a-chip imaging and DL can form unique synergisms: image formation, image analytics and intelligent image-guided autonomous lab-on-a-chip. Despite the on-going challenges, we anticipate that they will represent the next frontiers in lab-on-a-chip imaging that will spearhead new capabilities in advancing analytical chemistry research, accelerating biological discovery, and empowering new intelligent clinical applications.

Euglena International Network (EIN): Driving euglenoid biotechnology for the benefit of a challenged world

Euglenoids (Euglenida) are unicellular flagellates possessing exceptionally wide geographical and ecological distribution. Euglenoids combine a biotechnological potential with a unique position in the eukaryotic tree of life. In large part these microbes owe this success to diverse genetics including secondary endosymbiosis and likely additional sources of genes. Multiple euglenoid species have translational applications and show great promise in production of biofuels, nutraceuticals, bioremediation, cancer treatments and more exotically as robotics design simulators. An absence of reference genomes currently limits these applications, including development of efficient tools for identification of critical factors in regulation, growth or optimization of metabolic pathways. The Euglena International Network (EIN) seeks to provide a forum to overcome these challenges. EIN has agreed specific goals, mobilized scientists, established a clear roadmap (Grand Challenges), connected academic and industry stakeholders and is currently formulating policy and partnership principles to propel these efforts in a coordinated and efficient manner.

Specific intracellular signature of SARS-CoV-2 infection using confocal Raman microscopy

SARS-CoV-2 infection remains spread worldwide and requires a better understanding of virus-host interactions. Here, we analyzed biochemical modifications due to SARS-CoV-2 infection in cells by confocal Raman microscopy. Obtained results were compared with the infection with another RNA virus, the measles virus. Our results have demonstrated a virus-specific Raman molecular signature, reflecting intracellular modification during each infection. Advanced data analysis has been used to distinguish non-infected versus infected cells for two RNA viruses. Further, classification between non-infected and SARS-CoV-2 and measles virus-infected cells yielded an accuracy of 98.9 and 97.2 respectively, with a significant increase of the essential amino-acid tryptophan in SARS-CoV-2-infected cells. These results present proof of concept for the application of Raman spectroscopy to study virus-host interaction and to identify factors that contribute to the efficient SARS-CoV-2 infection and may thus provide novel insights on viral pathogenesis, targets of therapeutic intervention and development of new COVID-19 biomarkers.

Bringing Vibrational Imaging to Chemical Biology with Molecular Probes

As an emerging optical imaging modality, stimulated Raman scattering (SRS) microscopy provides invaluable opportunities for chemical biology studies using its rich chemical information. Through rapid progress over the past decade, the development of Raman probes harnessing the chemical biology toolbox has proven to play a key role in advancing SRS microscopy and expanding biological applications. In this perspective, we first discuss the development of biorthogonal SRS imaging using small tagging of triple bonds or isotopes and highlight their unique advantages for metabolic pathway analysis and microbiology investigations. Potential opportunities for chemical biology studies integrating small tagging with SRS imaging are also proposed. We next summarize the current designs of highly sensitive and super-multiplexed SRS probes, as well as provide future directions and considerations for next-generation functional probe design. These rationally designed SRS probes are envisioned to bridge the gap between SRS microscopy and chemical biology research and should benefit their mutual development.

A review of paramylon processing routes from microalga biomass to non-derivatized and chemically modified products

Paramylon is a linear β-1,3-glucan, similar to curdlan, produced as intracellular granules by the microalga Euglena gracilis, a highly versatile and robust strain, able to grow under various trophic conditions, with valorization of CO_2, wastewaters, or food byproducts as nutrients. This review focuses in particular on the various processing routes leading to new potential paramylon based products. Due to its crystalline structure, involving triple helices stabilized by internal intermolecular hydrogen bonds, paramylon is neither water-soluble nor thermoplastic. The few solvents able to disrupt the triple helices, and to fully solubilize the polymer as random coils, allow non derivatizing shaping into films, fibers, and even nanofibers by a specific self-assembly mechanism. Chemical modification in homogeneous or heterogeneous conditions is also possible. The non-selective or regioselective substitution of the hydroxyl groups of glucosidic units leads to water-soluble ionic derivatives and thermoplastic paramylon esters with foreseen applications ranging from health to bioplastics.

Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology

Gastroscopic biopsy provides the only effective method for gastric cancer diagnosis, but the gold standard histopathology is time-consuming and incompatible with gastroscopy. Conventional stimulated Raman scattering (SRS) microscopy has shown promise in label-free diagnosis on human tissues, yet it requires the tuning of picosecond lasers to achieve chemical specificity at the cost of time and complexity. Here, we demonstrate that single-shot femtosecond SRS (femto-SRS) reaches the maximum speed and sensitivity with preserved chemical resolution by integrating with U-Net. Fresh gastroscopic biopsy is imaged in <60 s, revealing essential histoarchitectural hallmarks perfectly agreed with standard histopathology. Moreover, a diagnostic neural network (CNN) is constructed based on images from 279 patients that predicts gastric cancer with accuracy >96%. We further demonstrate semantic segmentation of intratumor heterogeneity and evaluation of resection margins of endoscopic submucosal dissection (ESD) tissues to simulate rapid and automated intraoperative diagnosis. Our method holds potential for synchronizing gastroscopy and histopathological diagnosis.

Diagnosis of gastric cancer currently requires gastroscopic biopsy, which requires time and expertize to perform. Here, the authors demonstrate a femto-SRS imaging method which showed high accuracy in diagnosing gastric cancer without the need for pathologistbased diagnosis.

SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level

One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.

One Cell at a Time: Advances in Single-Cell Methods and Instrumentation for Discovery in Aquatic Microbiology

Studying microbes from a single-cell perspective has become a major theme and interest within the field of aquatic microbiology. One emerging trend is the unfailing observation of heterogeneity in activity levels within microbial populations. Wherever researchers have looked, intra-population variability in biochemical composition, growth rates, and responses to varying environmental conditions has been evident and probably reflect coexisting genetically distinct strains of the same species. Such observations of heterogeneity require a shift away from bulk analytical approaches and development of new methods or adaptation of existing techniques, many of which were first pioneered in other, unrelated fields, e.g., material, physical, and biomedical sciences. Many co-opted approaches were initially optimized using model organisms. In a field with so few cultivable models, method development has been challenging but has also contributed tremendous insights, breakthroughs, and stimulated curiosity. In this perspective, we present a subset of methods that have been effectively applied to study aquatic microbes at the single-cell level. Opportunities and challenges for innovation are also discussed. We suggest future directions for aquatic microbiological research that will benefit from open access to sophisticated instruments and highly interdisciplinary collaborations.

Stimulated Raman scattering spectroscopy with quantum-enhanced balanced detection

Quantum-enhanced stimulated Raman scattering (QE-SRS) is a promising technique for highly sensitive molecular vibrational imaging and spectroscopy surpassing the shot noise limit. However, the previous demonstrations of QE-SRS utilized rather weak optical power which hinders from competing with the sensitivity of state-of-the-art SRS microscopy and spectroscopy using relatively high-power optical pulses. Here, we demonstrate SRS spectroscopy with quantum-enhanced balanced detection (QE-BD) scheme, which works even when using high-power optical pulses. We used 4-ps pulses to generate pulsed squeezed vacuum at a wavelength of 844 nm with a squeezing level of -3.28 ± 0.12 dB generated from a periodically-poled stoichiometric LiTaO₃ waveguide. The squeezed vacuum was introduced to an SRS spectrometer employing a high-speed spectral scanner to acquire QE-SRS spectrum in the wavenumber range of 2000-2280 cm^-1 within 50 ms. Using SRS pump pulses with an average power of 11.3 mW, we successfully obtained QE-SRS spectrum whose SNR was better than classical SRS with balanced-detection by 2.27 dB.

Fluorogenic "on-off" nanosensor based on dual-quenching effect for imaging intracellular metabolite of various microalgae

Sensing intracellular compounds such as ATP in living microalgal cells is of great importance in diverse fields. To achieve this, nanosensing platform composed of graphene oxide (GO) and ATP aptamer (APT) was applied to diverse microalgal cells (Chlamydomonas reinhardtii, Chlorella vulgaris, Anabaena flos-aquae, and Ochromonas danica). The nanosized GO was characterized with atomic force microscopy (AFM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). The nanosensing platform (GO-APT) was prepared by attaching fluorophore-labeled APT to GO. GO-APT was applicable to only cell wall-deficient species (O. danica and mutant strains of C. reinhardtii) and the existence of flagella did not affect the uptake of the GO-APT by the cells. These results indicate that the cell wall is the primary barrier of GO-APT internalization for sensing application. To reduce the background fluorescence signal elicited by nonspecific displacement of the fluorophore-labeled probe, APT was modified as molecular beacon (MB) type (APTMB). Owing to the double quenching effect (by GO and quencher-labeled complementary sequence), the background signal significantly reduced. Cytotoxicity of GO-APTMB on the microalgal species was also tested. The application of GO-APTMB had no effect on the growth of microalgae. Given that diverse aptamer sequences had been screened, the sensing platform is not limited for detecting ATP only, but also can be applied to other metabolite imaging by simply changing the aptamer sequences. Our research will contribute to broadening the application of GO and aptamer beacon complex for intracellular metabolite imaging and detecting.

Probing the Biogenesis of Polysaccharide Granules in Algal Cells at Sub-Organellar Resolution via Raman Microscopy with Stable Isotope Labeling

Phototrophs assimilate CO₂ into organic compounds that accumulate in storage organelles. Elucidation of the carbon dynamics of storage organelles could enhance the production efficiency of valuable compounds and facilitate the screening of strains with high photosynthetic activity. To comprehensively elucidate the carbon dynamics of these organelles, the intraorganellar distribution of the carbon atoms that accumulate at specific time periods should be probed. In this study, the biosynthesis of polysaccharides in storage organelles was spatiotemporally probed via stimulated Raman scattering (SRS) microscopy using a stable isotope (¹³C) as the tracking probe. Paramylon granules (a storage organelle of β-1,3-glucan) accumulated in a unicellular photosynthetic alga, Euglena gracilis, were investigated as a model organelle. The carbon source of the culture medium was switched from NaH¹²CO₃ to NaH¹³CO₃ during the production of the paramylon granules; this resulted in the distribution of the ¹²C and ¹³C constituents in the granules, so that the biosynthetic process could be tracked. Taking advantage of high-resolution SRS imaging and label switching, the localization of the ¹²C and ¹³C constituents inside a single paramylon granule could be visualized in three dimensions, thus revealing the growth process of paramylon granules. We propose that this method can be used for comprehensive elucidation of the dynamic activities of storage organelles.

Multiwindow SRS Imaging Using a Rapid Widely Tunable Fiber Laser

Spectroscopic stimulated Raman scattering (SRS) imaging has become a useful tool finding a broad range of applications. Yet, wider adoption is hindered by the bulky and environmentally sensitive solid-state optical parametric oscillator (OPO) in a current SRS microscope. Moreover, chemically informative multiwindow SRS imaging across C-H, C-D, and fingerprint Raman regions is challenging due to the slow wavelength tuning speed of the solid-state OPO. In this work, we present a multiwindow SRS imaging system based on a compact and robust fiber laser with rapid and wide tuning capability. To address the relative intensity noise intrinsic to a fiber laser, we implemented autobalanced detection, which enhances the signal-to-noise ratio of stimulated Raman loss imaging by 23 times. We demonstrate high-quality SRS metabolic imaging of fungi, cancer cells, and Caenorhabditis elegans across the C-H, C-D, and fingerprint Raman windows. Our results showcase the potential of the compact multiwindow SRS system for a broad range of applications.

Ultrahigh-speed multiplex coherent anti-Stokes Raman scattering microspectroscopy using scanning elliptical focal spot

We present a beam-scanning multiplex coherent anti-Stokes Raman scattering (CARS) microspectroscopy system using parallel excitation and parallel detection schemes based on an elliptical focal spot, which enables highly efficient signal acquisition even for short exposures. The elliptical focal spot was used to simultaneously observe the CARS signals of an enlarged region and reduce the peak irradiance. The developed system realized an acquisition rate of 34 139 spectra/s and enabled ultrahigh-speed acquisition of a vibrational spectroscopic image, covering the fingerprint region of 930-1 830 cm^-1 with 256_(x) × 256_(y) × 512_(spectrum) pixels in 1.92 s or with 128_(x) × 128_(y) × 256_(spectrum) pixels in 0.54 s. We demonstrated ultrahigh-speed hyperspectral imaging of a mixture of polymer beads in liquid linoleic acid and living adipocytes using the developed system. All of the present demonstrations were performed with a low-peak irradiance excitation of ∼19 GW/cm², which has been reported in previous studies to cause less photodamage to living cells. The label-free and ultrahigh-speed identification and visualization of various molecules made possible by the present system will accelerate the development of practical live-cell investigation.

Multi-window sparse spectral sampling stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) is a nondestructive and rapid technique for imaging of biological and clinical specimens with label-free chemical specificity. SRS spectral imaging is typically carried out either via broadband methods, or by tuning narrowband ultrafast light sources over narrow spectral ranges thus specifically targeting vibrational frequencies. We demonstrate a multi-window sparse spectral sampling SRS (S4RS) approach where a rapidly-tunable dual-output all-fiber optical parametric oscillator is tuned into specific vibrational modes across more than 1400 cm-1 during imaging. This approach is capable of collecting SRS hyperspectral images either by scanning a full spectrum or by rapidly tuning into select target frequencies, hands-free and automatically, across the fingerprint, silent, and high wavenumber windows of the Raman spectrum. We further apply computational techniques for spectral decomposition and feature selection to identify a sparse subset of Raman frequencies capable of sample discrimination. Here we have applied this novel method to monitor spatiotemporal dynamic changes of active pharmaceutical ingredients in skin, which has particular relevance to topical drug product delivery.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.

In Vivo Monitoring of Intracellular Metabolite in a Microalgal Cell Using an Aptamer/Graphene Oxide Nanosheet Complex

Real-time sensing and imaging of intracellular metabolites in living cells are crucial tools for the characterization of complex biological processes, including the dynamic fluctuation of metabolites. Therefore, additional efforts are required to develop in vivo detection strategies for the visualization and quantification of specific target metabolites, particularly in microalgae. In this study, we developed a strategy to monitor a specific microalgal metabolite in living cells using an aptamer/graphene oxide nanosheet (GOnS) complex. As a proof-of-concept, β-carotene, an antioxidant pigment that accumulates in most microalgal species, was chosen as a target metabolite. To achieve this, a β-carotene-specific aptamer was selected through graphene oxide-assisted systematic evolution of ligands by exponential enrichment (GO-SELEX) and characterized thereafter. The aptamer could sensitively sense the changes in the concentration of β-carotene (i.e., the target metabolite) and more specifically bind to β-carotene than to nontargets. The selected aptamer was labeled with a fluorophore (fluorescein; FAM) and allowed to form an aptamer/GOnS complex that protected the aptamer from nucleic cleavages. The aptamer/GOnS complex was delivered into the cells via electroporation, thus enabling the sensitive monitoring of β-carotene in the cell by quantifying the aptamer fluorescence intensity. The results suggest that our biocompatible strategy could be employed to visualize and semiquantify intracellular microalgae metabolites in vivo, which holds a great potential in diverse fields such as metabolite analysis and mutant screening.

On-Chip Multicolor Photoacoustic Imaging Flow Cytometry

On-chip imaging flow cytometry has been widely used in cancer biology, immunology, microbiology, and drug discovery. Pure optical imaging combined with flow cytometry to derive chemical, structural, and morphological features of cells provides systematic insights into biological processes. However, due to the high concentration and strong optical attenuation of red blood cells, preprocessing is necessary for optical flow cytometry while dealing with whole blood. In this study, we develop an on-chip photoacoustic imaging flow cytometry (PAIFC), which combines multicolor high-speed photoacoustic microscopy and microfluidics for cell imaging. The device employs a micro-optical scanner to achieve a miniaturized outer size of 30 × 17 × 24 mm³ and ultrafast cross-sectional imaging at a frame rate of 1758 Hz and provides lateral and axial resolutions of 2.2 and 33 μm, respectively. Using a multicolor strategy, PAIFC is able to differentiate cells labeled by external contrast agents, detect melanoma cells with an endogenous contrast in whole blood, and image melanoma cells in blood samples from tumor-bearing mice. The results suggest that PAIFC has sufficient sensitivity and specificity for future cell-on-chip applications.

Direct Imaging of Integrated Circuits in CPU with 60 nm Super-Resolution Optical Microscope

Far-field super-resolution optical microscopies have achieved incredible success in life science for visualization of vital nanostructures organized in single cells. However, such resolution power has been much less extended to material science for inspection of human-made ultrafine nanostructures, simply because the current super-resolution optical microscopies modalities are rarely applicable to nonfluorescent samples or unlabeled systems. Here, we report an antiphase demodulation pump-probe (DPP) super-resolution microscope for direct optical inspection of integrated circuits (ICs) with a lateral resolution down to 60 nm. Because of the strong pump-probe (PP) signal from copper, we performed label-free super-resolution imaging of multilayered copper interconnects on a small central processing unit (CPU) chip. The label-free super-resolution DPP optical microscopy opens possibilities for easy, fast, and large-scale electronic inspection in the whole pipeline chain for designing and manufacturing ICs.

High-Throughput Raman Flow Cytometry and Beyond

Flow cytometry is a powerful tool with applications in diverse fields such as microbiology, immunology, virology, cancer biology, stem cell biology, and metabolic engineering. It rapidly counts and characterizes large heterogeneous populations of cells in suspension (e.g., blood cells, stem cells, cancer cells, and microorganisms) and dissociated solid tissues (e.g., lymph nodes, spleen, and solid tumors) with typical throughputs of 1,000-100,000 events per second (eps). By measuring cell size, cell granularity, and the expression of cell surface and intracellular molecules, it provides systematic insights into biological processes. Flow cytometers may also include cell sorting capabilities to enable subsequent additional analysis of the sorted sample (e.g., electron microscopy and DNA/RNA sequencing), cloning, and directed evolution. Unfortunately, traditional flow cytometry has several critical limitations as it mainly relies on fluorescent labeling for cellular phenotyping, which is an indirect measure of intracellular molecules and surface antigens. Furthermore, it often requires time-consuming preparation protocols and is incompatible with cell therapy. To overcome these difficulties, a different type of flow cytometry based on direct measurements of intracellular molecules by Raman spectroscopy, or "Raman flow cytometry" for short, has emerged. Raman flow cytometry obtains a chemical fingerprint of the cell in a nondestructive manner, allowing for single-cell metabolic phenotyping. However, its slow signal acquisition due to the weak light-molecule interaction of spontaneous Raman scattering prevents the throughput necessary to interrogate large cell populations in reasonable time frames, resulting in throughputs of about 1 eps. The remedy to this throughput limit lies in coherent Raman scattering methods such as stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS), which offer a significantly enhanced light-sample interaction and hence enable high-throughput Raman flow cytometry, Raman imaging flow cytometry, and even Raman image-activated cell sorting (RIACS). In this Account, we outline recent advances, technical challenges, and emerging opportunities of coherent Raman flow cytometry. First, we review the principles of various types of SRS and CARS and introduce several techniques of coherent Raman flow cytometry such as CARS, multiplex CARS, Fourier-transform CARS, SRS, SRS imaging flow cytometry, and RIACS. Next, we discuss a unique set of applications enabled by coherent Raman flow cytometry, from microbiology and lipid biology to cancer detection and cell therapy. Finally, we describe future opportunities and challenges of coherent Raman flow cytometry including increasing sensitivity and throughput, integration with droplet microfluidics, utilizing machine learning techniques, or achieving in vivo flow cytometry. This Account summarizes the growing field of high-throughput Raman flow cytometry and the bright future it can bring.

Recent Development of Rapid Antimicrobial Susceptibility Testing Methods through Metabolic Profiling of Bacteria

Due to the inappropriate use and overuse of antibiotics, the emergence and spread of antibiotic-resistant bacteria are increasing and have become a major threat to human health. A key factor in the treatment of bacterial infections and slowing down the emergence of antibiotic resistance is to perform antimicrobial susceptibility testing (AST) of infecting bacteria rapidly to prescribe appropriate drugs and reduce the use of broad-spectrum antibiotics. Current phenotypic AST methods based on the detection of bacterial growth are generally reliable but are too slow. There is an urgent need for new methods that can perform AST rapidly. Bacterial metabolism is a fast process, as bacterial cells double about every 20 to 30 min for fast-growing species. Moreover, bacterial metabolism has shown to be related to drug resistance, so a comparison of differences in microbial metabolic processes in the presence or absence of antimicrobials provides an alternative approach to traditional culture for faster AST. In this review, we summarize recent developments in rapid AST methods through metabolic profiling of bacteria under antibiotic treatment.

Low-loss microscope optics with an axicon-based beam shaper

We present low-loss microscope optics using an axicon-based beam shaper, which can convert a Gaussian beam to a ring beam to minimize the optical loss from blocking by the back aperture of the objective lens while maintaining spatial resolution. To design the beam shaper, we characterize the position-dependent transmittance of high-transmittance objective lenses and numerically calculate the beam propagation in the beam shaper. We also clarify the effect of misalignments of the beam shaper and wavefront distortion of the input beam. Furthermore, we experimentally demonstrate a low-loss microscope optical system with a high transmittance of 86.6% and high spatial resolution using the full numerical aperture of the objective lenses.

Mitochondrial movement during its association with chloroplasts in Arabidopsis thaliana

Plant mitochondria move dynamically inside cells and this movement is classified into two types: directional movement, in which mitochondria travel long distances, and wiggling, in which mitochondria travel short distances. However, the underlying mechanisms and roles of both types of mitochondrial movement, especially wiggling, remain to be determined. Here, we used confocal laser-scanning microscopy to quantitatively characterize mitochondrial movement (rate and trajectory) in Arabidopsis thaliana mesophyll cells. Directional movement leading to long-distance migration occurred at high speed with a low angle-change rate, whereas wiggling leading to short-distance migration occurred at low speed with a high angle-change rate. The mean square displacement (MSD) analysis could separate these two movements. Directional movement was dependent on filamentous actin (F-actin), whereas mitochondrial wiggling was not, but slightly influenced by F-actin. In mesophyll cells, mitochondria could migrate by wiggling, and most of these mitochondria associated with chloroplasts. Thus, mitochondria migrate via F-actin-independent wiggling under the influence of F-actin during their association with chloroplasts in Arabidopsis.

Oikawa et al. investigate the rate and trajectory of mitochondria in Arabidopsis thaliana mesophyll cells, using confocal laser-scanning microscopy. They find that mitochondria migrate via wiggling during their association with chloroplasts, providing insights into how mitochondria-chloroplast interaction affects the movement of mitochondria.

Multicolour chemical imaging of plant tissues with hyperspectral stimulated Raman scattering microscopy

Recent development of stimulated Raman scattering (SRS) microscopy allows for label-free biological imaging with chemical specificity based on molecular-vibrational signatures. In particular, hyperspectral SRS imaging can acquire a molecular-vibrational spectrum at each pixel, allowing us not only to investigate the spectral difference of various biological molecules but also to discriminate different constituents based on their spectral difference. However, the number of constituents discriminated in previous label-free SRS imaging was limited to four because of the subtleness of spectral difference. Here, we report hyperspectral SRS imaging of plant tissues including leaves of Camellia japonica, roots of Arabidopsis thaliana, and thalli of a liverwort Marchantia polymorpha L. We show that SRS can discriminate as many as six components in Marchantia polymorpha L. without labeling. Our results demonstrate the effectiveness of hyperspectral SRS imaging as a tool for label-free multicolour imaging analysis of various biomolecules in plant tissues.

Single Cell Array Enclosed with a Photodegradable Hydrogel in Microwells for Image-Based Cell Classification and Selective Photorelease of Cells

Single cell arrays provide an accurate classification of analyte cells through an image-based analysis of cellular phenotypes. Light-guided cell retrieval from a single cell array is a promising approach for the rapid and simple sorting of difficult to distinguish cells. In this study, we developed a single cell array enclosed with a photodegradable hydrogel in microwells to enable both comprehensive image-based single cell analysis and light-guided cell retrieval. In this system, individual cells became trapped in the microwells together with the photodegradable hydrogel at a high cell density on a chip regardless of cell type, adhesiveness, and motility. Fluorescence-stained model cells and vaccinated dendritic cells were identified by microscopic imaging and then selectively released through the light-induced degradation of the cell-embedding hydrogels. The target cells were selectively retrieved with a purity of >95% from the cell mixture through rapid photorelease, and the retrieved cells were confirmed to grow normally. Our results provide proof-of-principle that the photoresponsive microwell array serves as a versatile tool for image-based cell sorting in cellular researches and the manufacturing processes of high-performance cells.

Raman image-activated cell sorting

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

Most current cell sorting methods are based on fluorescence detection with no imaging capability. Here the authors generate and use Raman image-activated cell sorting with a throughput of around 100 events per second, providing molecular images with no need for labeling.

Large-scale label-free single-cell analysis of paramylon in Euglena gracilis by high-throughput broadband Raman flow cytometry

Microalga-based biomaterial production has attracted attention as a new source of drugs, foods, and biofuels. For enhancing the production efficiency, it is essential to understand its differences between heterogeneous microalgal subpopulations. However, existing techniques are not adequate to address the need due to the lack of single-cell resolution or the inability to perform large-scale analysis and detect small molecules. Here we demonstrated large-scale single-cell analysis of Euglena gracilis (a unicellular microalgal species that produces paramylon as a potential drug for HIV and colon cancer) with our recently developed high-throughput broadband Raman flow cytometer at a throughput of >1,000 cells/s. Specifically, we characterized the intracellular content of paramylon from single-cell Raman spectra of 10,000 E. gracilis cells cultured under five different conditions and found that paramylon contents in E. gracilis cells cultured in an identical condition is given by a log-normal distribution, which is a good model for describing the number of chemicals in a reaction network. The capability of characterizing distribution functions in a label-free manner is an important basis for isolating specific cell populations for synthetic biology via directed evolution based on the intracellular content of metabolites.

Virtual-freezing fluorescence imaging flow cytometry

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s⁻¹ without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

High throughput imaging flow cytometry suffers from trade-offs between throughput, sensitivity and spatial resolution. Here the authors introduce a method to virtually freeze cells in the image acquisition window to enable 1000 times longer signal integration time and improve signal-to-noise ratio.

Rapid and Accurate Quantification of Paramylon Produced from Euglena gracilis Using an ssDNA Aptamer

The functional ingredients of microalgal biomass are receiving substantial recognition as the global demands for health supplements produced from natural sources are on the rise. Paramylon, a conglomerate of β-1,3-glucans, is one of the major valuable sources derived from Euglena gracilis having multiple applications, thus necessitating the development of an efficient quantification method. Here, we employed a DNA aptamer to quantify the amount of paramylon produced by E. gracilis. Paramylon-specific aptamers were isolated by the systematic evolution of ligands by exponential enrichment (SELEX) process. To evaluate the potential aptamers, the binding affinity between aptamer candidates and paramylon granules was confirmed by a confocal laser scanning microscope and the dissociation constants of the selected aptamers were determined by nonlinear regression analysis. The selected DNA aptamer was successfully used for the quantification of paramylon, and the results were compared to those obtained by the standard methods. The new approach was also used for quantification of paramylon from E. gracilis cells cultured to different cell stages and physiologies. It can be concluded that the aptamer-based protocol for the measurement of paramylon proposed in this study is highly accurate and comparatively less time-consuming.

Spatiotemporal monitoring of intracellular metabolic dynamics by resonance Raman microscopy with isotope labeling

We probed production process of a cellular metabolite with a stable isotope-labeled substrate exposed to various conditions.

Biological imaging of chemical bonds by stimulated Raman scattering microscopy

All molecules consist of chemical bonds, and much can be learned from mapping the spatiotemporal dynamics of these bonds. Since its invention a decade ago, stimulated Raman scattering (SRS) microscopy has become a powerful modality for imaging chemical bonds with high sensitivity, resolution, speed and specificity. We introduce the fundamentals of SRS microscopy and review innovations in SRS microscopes and imaging probes. We highlight examples of exciting biological applications, and share our vision for potential future breakthroughs for this technology.

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering

Imaging flow cytometry is a powerful tool for analyzing every single cell in a large heterogeneous population but relies on fluorescent labeling, which comes with cytotoxicity, nonspecific binding, and interference with natural cellular functions. This paper presents label-free multicolor chemical imaging flow cytometry based on stimulated Raman scattering (SRS), a highly sensitive method of molecular vibrational spectroscopy. With the help of deep learning, it demonstrates high-precision characterization and classification of microalgal cells and cancer cells without the need for fluorescent labeling.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

Cellular Imaging Using Stimulated Raman Scattering Microscopy

Cellular imaging is an active area of research that enables researchers to monitor cellular dynamics, as well as responses to various external stimuli (physiological stress, exogenous compounds, etc.). Stimulated Raman scattering (SRS) microscopy is one popular experimental tool used to image cells, largely because of its chemical specificity, high spatial resolution, and high image acquisition speed. In this Perspective, the theoretical background and experimental implementation of SRS microscopy are discussed and recent developments in the field of cellular imaging with SRS are highlighted and summarized.

Visualizing wax ester fermentation in single Euglena gracilis cells by Raman microspectroscopy and multivariate curve resolution analysis

BACKGROUND

Global demand for energy is on the rise at a time when limited natural resources are fast depleting. To address this issue, microalgal biofuels are being recommended as a renewable and eco-friendly substitute for fossil fuels. Euglena gracilis is one such candidate that has received special interest due to their ability to synthesize wax esters that serve as precursors for production of drop-in jet fuel. However, to realize economic viability and achieve industrial-scale production, development of novel methods to characterize algal cells, evaluate its culture conditions, and construct appropriate genetically modified strains is necessary. Here, we report a Raman microspectroscopy-based method to visualize important metabolites such as paramylon and ester during wax ester fermentation in single Euglena gracilis cells in a label-free manner.

RESULTS

We measured Raman spectra to obtain intracellular biomolecular information in Euglena under anaerobic condition. First, by univariate approach, we identified Raman markers corresponding to paramylon/esters and constructed their time-lapse chemical images. However, univariate analysis is severely limited in its ability to obtain detailed information as several molecules can contribute to a Raman band. Therefore, we further employed multivariate curve resolution analysis to obtain chain length-specific information and their abundance images of the produced esters. Accumulated esters in Euglena were particularly identified to be myristyl myristate (C28), a wax ester candidate suitable to prepare drop-in jet fuel. Interestingly, we found accumulation of two different forms of myristyl myristate for the first time in Euglena through our exploratory multivariate analysis.

CONCLUSIONS

We succeeded in visualizing molecular-specific information in Euglena during wax ester fermentation by Raman microspectroscopy. It is obvious from our results that simple univariate approach is insufficient and that multivariate curve resolution analysis is crucial to extract hidden information from Raman spectra. Even though we have not measured any mutants in this study, our approach is directly applicable to other systems and is expected to deepen the knowledge on lipid metabolism in microalgae, which eventually leads to new strategies that will help to enhance biofuel production efficiency in the future.

Absorbance spectra of the hematochrome-like granules and eyespot of Euglena gracilis by scan-free absorbance spectral imaging A(x, y, λ) within the live cells

Euglena gracilis has an organelle resembling hematochrome, with an appearance similar to the eyespot and the absorption band spectrally overlapped with that of the carotenoid. To discriminate the hematochrome-like granules and eyespot, scan-free, non-invasive, absorbance spectral imaging A(x, y, λ) microscopy of single live cells, where A(x, y, λ) means absorbance at a position (x, y) on a two-dimensional image at a specific wavelength λ was applied. This technique was demonstrated to be a powerful tool for basic research on intracellular structural analysis. By this method, characteristic absorption spectra specific to the hematochrome-like granule or eyespot were identified among a variety of spectra observed depending on the location inside the organelles. The hematochrome-like granule was dark orange and deep green in its outline and had a characteristic absorption peak at 620 nm as well as at 676 to 698 nm, suggesting that its origin is a component of chloroplast including chlorophyll a. Furthermore, the representative spectra of these organelles were derived by principal component analysis of the absorbance and its position in absorbance image, indicating that they can be distinguished from each other and other regions. It was also confirmed that even in areas where these organelles and chloroplasts overlap, one can distinguish them from each other. The present research clarified the absorption spectra of the eyespot with 1 × 1 µm spatial resolution and those unpublished of hematochrome-like granules of E. gracilis, and indicated that one can statistically distinguish these organelles by this method.

Demonstration of wavelength-scan-free action spectroscopy in pump/probe measurement with supercontinuum pump light

We devise and introduce the principle of wavelength-scan-free spectroscopy for the pump light in pump/probe measurement (action spectroscopy) using supercontinuum light; we demonstrate its implementation by measuring transmission spectra. We use the supercontinuum light noise as a code in order to discriminate wavelength. We extract the stimulation at the desired wavelength by correlating the noise at that wavelength observed separately and the observed total stimulation carried by the probe light. The wavelength-scan-free spectroscopy is enabled with a simultaneous procedure for multiple wavelengths.