Raman Imaging of Small Biomolecules

Raman microscopy allows to follow internalization, subcellular accumulation and fate of iron oxide nanoparticles in cells

An important issue in the context of both potenial toxicity of iron oxide nanoparticles (IONP) and their medical applications is tracking of the internalization process of these nanomaterials into living cells, as well as their localization and fate within them. The typical methods used for this purpose are transmission electron microscopy, confocal fluorescence microscopy as well as light-scattering techniques including dark-field microscopy and flow cytometry. All the techniques mentioned have their advantages and disadvantages. Among the problems it is necessary to mention complicated sample preparation, difficult interpretation of experimental data requiring qualified and experienced personnel, different behavior of fluorescently labeled IONP comparing to those label-free or finally the lack of possibility of chemical composition characteristics of nanomaterials. The purpose of the present investigation was the assessment of the usefulness of Raman microscopy for the tracking of the internalization of IONP into cells, as well as the optimization of this process. Moreover, the study focused on identification of the potential differences in the cellular fate of superparamagnetic nanoparticles having magnetite and maghemite core. The Raman spectra of U87MG cells which internalized IONP presented additional bands which position depended on the used laser wavelength. They occurred at the wavenumber range 1700-2400 cm-1 for laser 488 nm and below the wavenumber of 800 cm-1 in case of laser 532 nm. The intensity of the mentioned Raman bands was higher for the green laser (532 nm) and their position, was independent and not characteristic on the primary core material of IONP (magnetite, maghemite). The obtained results showed that Raman microscopy is an excellent, non-destructive and objective technique that allows monitoring the process of internalization of IONP into cells and visualizing such nanoparticles and/or their metabolism products within them at low exposure levels. What is more, the process of tracking IONP using the technique may be further improved by using appropriate wavelength and power of the laser source.

Click-free imaging of carbohydrate trafficking in live cells using an azido photothermal probe

Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.

Glycosylation: mechanisms, biological functions and clinical implications

Protein post-translational modification (PTM) is a covalent process that occurs in proteins during or after translation through the addition or removal of one or more functional groups, and has a profound effect on protein function. Glycosylation is one of the most common PTMs, in which polysaccharides are transferred to specific amino acid residues in proteins by glycosyltransferases. A growing body of evidence suggests that glycosylation is essential for the unfolding of various functional activities in organisms, such as playing a key role in the regulation of protein function, cell adhesion and immune escape. Aberrant glycosylation is also closely associated with the development of various diseases. Abnormal glycosylation patterns are closely linked to the emergence of various health conditions, including cancer, inflammation, autoimmune disorders, and several other diseases. However, the underlying composition and structure of the glycosylated residues have not been determined. It is imperative to fully understand the internal structure and differential expression of glycosylation, and to incorporate advanced detection technologies to keep the knowledge advancing. Investigations on the clinical applications of glycosylation focused on sensitive and promising biomarkers, development of more effective small molecule targeted drugs and emerging vaccines. These studies provide a new area for novel therapeutic strategies based on glycosylation.

Viewing 3D spatial biology with highly-multiplexed Raman imaging: from spectroscopy to biotechnology

Understansding complex biological systems requires the simultaneous characterization of a large number of interacting components in their native 3D environment with high spatial resolution. Highly-multiplexed Raman imaging is an emerging general strategy for detecting biomarkers with scalable multiplexity and ultra-sensitivity based on a series of stimulated Raman scattering (SRS) techniques. Here we review recent advances in highly-multiplexed Raman imaging and how they contribute to the technological revolution in 3D spatial biology, focusing on the developmental pathway from spectroscopy study to biotechnology invention. We envision highly-multiplexed Raman imaging is taking off, which will greatly facilitate our understanding in biological and medical research fields.

The Duality of Raman Scattering

ConspectusFirst predicted more than 100 years ago, Raman scattering is a cornerstone of photonics, spectroscopy, and imaging. The conventional framework of understanding Raman scattering was built on Raman cross section σRaman. Carrying a dimension of area, σRaman characterizes the interaction strength between light and molecules during inelastic scattering. The numerical values of σRaman turn out to be many orders of magnitude smaller in comparison to the linear absorption cross sections σAbsorption of similar molecular systems. Such an enormous gap has been the reason for researchers to believe the extremely feeble Raman scattering ever since its discovery. However, this prevailing picture is conceptually problematic or at least incomplete due to the fact that Raman scattering and linear absorption belong to different orders of light-matter interaction.In this Account, we will summarize an alternate way to think about Raman scattering, which we term stimulated response formulation. To capture the third-order interaction nature of Raman scattering, we introduced stimulated Raman cross section, σSRS, defined as the intrinsic molecular property in response to the external photon fluxes. Foremost, experimental measurement of σSRS turns out to be not weak at all or even larger when fairly compared with electronic counterparts of the same order. The analytical expression for σSRS derived from quantum electrodynamics also supports the measurement and proves that σSRS is intrinsically strong. Hence, σRaman and σSRS can be extremely small and large, respectively, for the same molecule at the same time. Our subsequent theoretical studies show that stimulated response formulation can unify spontaneous emission, stimulated emission, spontaneous Raman, and stimulated Raman via eq 10, in a coherent and symmetric way. In particular, an Einstein-coefficient-like equation, eq 12a, was derived, showing that σRaman can be explicitly expressed as σSRS multiplied by an effective photon flux arising from zero-point fluctuation of the vacuum. The feeble vacuum fluctuation hence explains how σSRS can be intrinsically strong while, at the same time, σRaman ends up being many orders of magnitude smaller when both compared to the electronic counterparts. These two sides of the same coin prompted us to propose "the duality of Raman scattering" (Table 1). Finally, this formulation naturally leads to a quantitative treatment of stimulated Raman scattering (SRS) microscopy, providing an intuitive, molecule-centric explanation as to how SRS microscopy can outperform regular Raman microscopy. Hence, as unveiled by the new formulation, a duality of Raman scattering has emerged, with implications for both fundamental science and practical technology.

Label-free optical imaging for brain cancer assessment

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

Click-free imaging of carbohydrate trafficking in live cells using an azido photothermal probe

Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.

Dynamic repulsive interaction enables an asymmetric electron-phonon coupling for improving Raman scattering

Two-dimensional (2D) materials are an excellent platform for surface-enhanced Raman spectroscopy (SERS). For ReS2, the Raman enhancement effect can be highly improved through the dipole-dipole interactions and synergistic resonance effects in the phase-engineering ReS2 films. However, the performance of the substrate can be improved further through regulating the electronic interaction between the ReS2 and probe molecules. Herein, a dynamic coulomb repulsion strategy is proposed to trigger an electronic state redistribution by asymmetric electrostatic interactions. With the phase-engineering ReS2/graphene heterostructure as a prototype, under laser excitation, the generated hot electrons in graphene and ReS2 can repel each other due to Coulomb interaction, which breaks the symmetrical distribution of hot electrons in ReS2, and increases the electronic concentration at the interface between ReS2 and the probe molecule. With R6G as the probe molecule, the asymmetric electron distribution and synergistic resonance effects on their interface improve the limit of detection to 10-12 M with an EF of 2.15 × 108. Meanwhile, the heterostructure also shows good uniformity, stability as well as unique anisotropy. This strategy can be generalized to other 2D heterostructures to obtain the ultrasensitive SERS substrates.

Development of a universal method for vibrational analysis of the terminal alkyne C≡C stretch

The terminal alkyne C≡C stretch has a large Raman scattering cross section in the "silent" region for biomolecules. This has led to many Raman tag and probe studies using this moiety to study biomolecular systems. A computational investigation of these systems is vital to aid in the interpretation of these results. In this work, we develop a method for computing terminal alkyne vibrational frequencies and isotropic transition polarizabilities that can easily and accurately be applied to any terminal alkyne molecule. We apply the discrete variable representation method to a localized version of the C≡C stretch normal mode. The errors of (1) vibrational localization to the terminal alkyne moiety, (2) anharmonic normal mode isolation, and (3) discretization of the Born-Oppenheimer potential energy surface are quantified and found to be generally small and cancel each other. This results in a method with low error compared to other anharmonic vibrational methods like second-order vibrational perturbation theory and to experiments. Several density functionals are tested using the method, and TPSS-D3, an inexpensive nonempirical density functional with dispersion corrections, is found to perform surprisingly well. Diffuse basis functions are found to be important for the accuracy of computed frequencies. Finally, the computation of vibrational properties like isotropic transition polarizabilities and the universality of the localized normal mode for terminal alkynes are demonstrated.

Cancer detection in dogs using rapid Raman molecular urinalysis

Introduction

The presence of cancer in dogs was detected by Raman spectroscopy of urine samples and chemometric analysis of spectroscopic data. The procedure created a multimolecular spectral fingerprint with hundreds of features related directly to the chemical composition of the urine specimen. These were then used to detect the broad presence of cancer in dog urine as well as the specific presence of lymphoma, urothelial carcinoma, osteosarcoma, and mast cell tumor.

Methods

Urine samples were collected via voiding, cystocentesis, or catheterization from 89 dogs with no history or evidence of neoplastic disease, 100 dogs diagnosed with cancer, and 16 dogs diagnosed with non-neoplastic urinary tract or renal disease. Raman spectra were obtained of the unprocessed bulk liquid urine samples and were analyzed by ISREA, principal component analysis (PCA), and discriminant analysis of principal components (DAPC) were applied using the Rametrix®Toolbox software.

Results and discussion

The procedure identified a spectral fingerprint for cancer in canine urine, resulting in a urine screening test with 92.7% overall accuracy for a cancer vs. cancer-free designation. The urine screen performed with 94.0% sensitivity, 90.5% specificity, 94.5% positive predictive value (PPV), 89.6% negative predictive value (NPV), 9.9 positive likelihood ratio (LR+), and 0.067 negative likelihood ratio (LR-). Raman bands responsible for discerning cancer were extracted from the analysis and biomolecular associations were obtained. The urine screen was more effective in distinguishing urothelial carcinoma from the other cancers mentioned above. Detection and classification of cancer in dogs using a simple, non-invasive, rapid urine screen (as compared to liquid biopsies using peripheral blood samples) is a critical advancement in case management and treatment, especially in breeds predisposed to specific types of cancer.

Applications of Raman spectroscopy in the diagnosis and monitoring of neurodegenerative diseases

Raman scattering is an inelastic light scattering that occurs in a manner reflective of the molecular vibrations of molecular structures and chemical conditions in a given sample of interest. Energy changes in the scattered light can be assessed to determine the vibration mode and associated molecular and chemical conditions within the sample, providing a molecular fingerprint suitable for sample identification and characterization. Raman spectroscopy represents a particularly promising approach to the molecular analysis of many diseases owing to clinical advantages including its instantaneous nature and associated high degree of stability, as well as its ability to yield signal outputs corresponding to a single molecule type without any interference from other molecules as a result of its narrow peak width. This technology is thus ideally suited to the simultaneous assessment of multiple analytes. Neurodegenerative diseases represent an increasingly significant threat to global public health owing to progressive population aging, imposing a severe physical and social burden on affected patients who tend to develop cognitive and/or motor deficits beginning between the ages of 50 and 70. Owing to a relatively limited understanding of the etiological basis for these diseases, treatments are lacking for the most common neurodegenerative diseases, which include Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. The present review was formulated with the goal of briefly explaining the principle of Raman spectroscopy and discussing its potential applications in the diagnosis and evaluation of neurodegenerative diseases, with a particular emphasis on the research prospects of this novel technological platform.

Activatable organic probes for in situ imaging of biomolecules

Biomolecules are fundamental for various chemical and biological processes of living organisms. High-resolution in situ imaging of the dynamics and local distribution of biomolecules may facilitate better interpretation of diverse complex cell events in the biomedicine field. In different advanced imaging tools, fluorescence imaging-based activatable organic probes can be noninvasively and effortlessly internalized into cells and can be easily modified, which is essential for the in situ imaging of targets in living organisms. We here briefly summarize the existing general design strategies of activatable organic probes for retaining the fluorescence signal inside cells. We particularly describe the bioapplication of these probes for the in situ bioimaging. This review is expected to promote the development of new molecular tools for extending the application of these in situ imaging strategies to other biomolecules.

Shedding light on ultrasound in action: Optical and optoacoustic monitoring of ultrasound brain interventions

Monitoring brain responses to ultrasonic interventions is becoming an important pillar of a growing number of applications employing acoustic waves to actuate and cure the brain. Optical interrogation of living tissues provides a unique means for retrieving functional and molecular information related to brain activity and disease-specific biomarkers. The hybrid optoacoustic imaging methods have further enabled deep-tissue imaging with optical contrast at high spatial and temporal resolution. The marriage between light and sound thus brings together the highly complementary advantages of both modalities toward high precision interrogation, stimulation, and therapy of the brain with strong impact in the fields of ultrasound neuromodulation, gene and drug delivery, or noninvasive treatments of neurological and neurodegenerative disorders. In this review, we elaborate on current advances in optical and optoacoustic monitoring of ultrasound interventions. We describe the main principles and mechanisms underlying each method before diving into the corresponding biomedical applications. We identify areas of improvement as well as promising approaches with clinical translation potential.

Triple-Bond Vibrations: Emerging Applications in Energy and Biological Sciences

Triple bonds, such as that formed between two carbon atoms (i.e., C≡C) or that formed between one carbon atom and one nitrogen atom (i.e., C≡N), afford unique chemical bonding and hence vibrational characteristics. As such, they are not only frequently used to construct molecules with tailored chemical and/or physical properties but also employed as vibrational probes to provide site-specific chemical and/or physical information at the molecular level. Herein, we offer our perspective on the emerging applications of various triple-bond vibrations in energy and biological sciences with a focus on C≡C and C≡N triple bonds.

Chemical Approaches for Measuring and Manipulating Lipids at the Organelle Level

As the products of complex and often redundant metabolic pathways, lipids are challenging to measure and perturb using genetic tools. Yet by virtue of being the major constituents of cellular membranes, lipids are highly regulated in space and time. Chemists have stepped into this methodological void, developing an array of techniques for the precise quantification and manipulation of lipids at the subcellular, organelle level. Here, we survey the landscape of these methods. For measuring lipids, we summarize the use of metabolic labeling and click chemistry tagging, photoaffinity labeling, isotopic tagging for Raman microscopy, and chemoenzymatic labeling for tracking lipid production and interorganelle transport. For perturbing lipids, we describe synthetic photocaged lipids and membrane editing approaches using optogenetic enzymes for precise manipulation of lipid signaling. Collectively, these chemical and biochemical tools are revealing phenomena and mechanisms underlying lipid functions at the subcellular level.

Raman scattering and vacuum fluctuation: An Einstein-coefficient-like equation for Raman cross sections

Since it was first predicted 100 years ago, Raman scattering has been a cornerstone of molecular spectroscopy with a widespread impact on science and technology. Nearly all theoretical frameworks have employed Raman cross sections (σRaman) to characterize and quantify molecular Raman response. The recently introduced absolute stimulated Raman scattering cross section (σSRS), on the other hand, provides an alternative way of interpreting molecular responses under two coherent laser sources. However, the theoretical connection between σRaman and σSRS remains unclear. Herein, we are inspired by Einstein's A and B coefficients for spontaneous and stimulated emissions and derived an analogous equation [Eq. (16)] for Raman scattering from an approach along quantum electrodynamics. Equation (16) decomposes Raman cross sections into a contribution from the vacuum electromagnetic field and an underlying molecular response captured by stimulated Raman cross sections (in the unit of Göppert-Mayer). This theoretical relation is supported by recent experimental measurements on methanol as a model compound. Foremost, it provides a connection between experimentally defined σRaman and σSRS under certain approximations. In addition, it quantitatively shows that it is the weak vacuum field of the Stokes channel that makes Raman cross sections appear so small, corroborating the conventional Raman theory. Moreover, it suggests stimulated Raman cross sections to be a vacuum-decoupled intrinsic quantity for characterizing molecular response during Raman scattering. Remarkably, stimulated Raman cross sections turn out to be not weak when compared to two-photon absorption, narrowing the conventional gap of cross sections between spontaneous Raman and UV-vis absorption by more than 1010 folds.

Strategies and Progress of Raman Technologies for Cellular Uptake Analysis of the Drug Delivery Systems

Nanoparticle (NP)-based drug delivery systems have the potential to significantly enhance the pharmacological and therapeutic properties of drugs. These systems enhance the bioavailability and biocompatibility of pharmaceutical agents via enabling targeted delivery to specific tissues or organs. However, the efficacy and safety of these systems are largely dependent on the cellular uptake and intracellular transport of NPs. Thus, it is crucial to monitor the intracellular behavior of NPs within a single cell. Yet, it is challenging due to the complexity and size of the cell. Recently, the development of the Raman instrumentation offers a versatile tool to allow noninvasive cellular measurements. The primary objective of this review is to highlight the most recent advancements in Raman techniques (spontaneous Raman scattering, bioorthogonal Raman scattering, coherence Raman scattering, and surface-enhanced Raman scattering) when it comes to assessing the internalization of NP-based drug delivery systems and their subsequent movement within cells.

Label-free detection and mapping of graphene oxide in single HeLa cells based on MCR-Raman spectroscopy

GO is a 2D nanomaterial that has attracted attention in many industries in recent years, such as the chemical industry, electronics or medicine. Due to its unique properties such as strength, hydrophilicity and large specific surface area with the possibility of functionalization, GO is a particularly attractive material in biomedicine as a candidate for use in targeted drug delivery. In such a case, we need information on whether graphene oxide penetrates into cells and whether we are able to detect and monitor GO in these cells during and also after the treatment to evaluate possible degradation process of GO and its interaction within the cell compartements. This work introduces the Raman spectroscopy as label-free detection method showing the advantages of combining Raman spectroscopy with MCR (Multivariate Curve Resolution) analysis for advanced detection of GO in cervical cancer (HeLa) cells. Our synthesized GO is characterized firstly by AFM, SEM and Raman spectroscopy and then MCR-Raman spectroscopy is used to detect internalized GO in individual HeLa cells. Moreover, by using our methodology, distribution of GO as well as its chemical stability inside the cell for up to six months is investigated without using any additional labeling or tracing the GO. Thus, MCR-Raman spectroscopy may become a new analytical tool in preclinical and clinical applications of graphene-based nanotheranostics.

Raman Spectroscopy Combined with Malaria Protein for Early Capture and Recognition of Broad-Spectrum Circulating Tumor Cells

Early identification of tumors can significantly reduce the mortality rate. Circulating tumor cells (CTCs) are a type of tumor cell that detaches from the primary tumor and circulates through the bloodstream. Monitoring CTCs may allow the early identification of tumor progression. However, due to their rarity and heterogeneity, the enrichment and identification of CTCs is still challenging. Studies have shown that Raman spectroscopy could distinguish CTCs from metastatic cancer patients. VAR2CSA, a class of malaria proteins, has a strong broad-spectrum binding effect on various tumor cells and is a promising candidate biomarker for cancer detection. Here, recombinant malaria VAR2CSA proteins were synthesized, expressed, and purified. After confirming that various types of tumor cells can be isolated from blood by recombinant malaria VAR2CSA proteins, we further proved that the VAR2CSA combined with Raman spectroscopy could be used efficiently for tumor capture and type recognition using A549 cell lines spiked into the blood. This would allow the early screening and detection of a broad spectrum of CTCs. Finally, we synthesized and purified the malaria protein fusion antibody and confirmed its in vitro tumor-killing activity. Herein, this paper exploits the theoretical basis of a novel strategy to capture, recognize, and kill broad-spectrum types of CTCs from the peripheral blood.

Raman Imaging Reveals Insights into Membrane Phase Biophysics in Cells

Cellular membranes are essential components of all living organisms. They are composed of a complex mixture of lipids with diverse chemical structures and crucial biological functions. The dynamic and heterogeneous nature of cellular membranes presents a challenge for studying their biophysical properties and organization in vivo. Raman imaging, particularly coherent Raman scattering techniques such as stimulated Raman scattering (SRS) microscopy, have emerged as powerful tools for studying cellular membranes with high spatial and temporal resolution and minimal perturbation. In this Review, we discuss the scientific importance and technical challenges of characterizing membrane composition in cellular contexts and how the advances of Raman imaging can provide unique insights into membrane phase behavior and organization. We also highlight recent applications of Raman imaging in studying cellular membranes and implications in diseases. In particular, the discovery of phase separation and a solid-phase intracellular membrane on endoplasmic reticulum is reviewed in detail, shedding light on the biology of lipotoxicity.

Identification of essential sites of lipid peroxidation in ferroptosis

Ferroptosis, an iron-dependent form of cell death driven by lipid peroxidation, provides a potential treatment avenue for drug-resistant cancers and may play a role in the pathology of some degenerative diseases. Identifying the subcellular membranes essential for ferroptosis and the sequence of their peroxidation will illuminate drug discovery strategies and ferroptosis-relevant disease mechanisms. In this study, we employed fluorescence and stimulated Raman scattering imaging to examine the structure-activity-distribution relationship of ferroptosis-modulating compounds. We found that, although lipid peroxidation in various subcellular membranes can induce ferroptosis, the endoplasmic reticulum (ER) membrane is a key site of lipid peroxidation. Our results suggest an ordered progression model of membrane peroxidation during ferroptosis that accumulates initially in the ER membrane and later in the plasma membrane. Thus, the design of ER-targeted inhibitors and inducers of ferroptosis may be used to optimally control the dynamics of lipid peroxidation in cells undergoing ferroptosis.

Seeing plants as never before

Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.

Harnessing the power of Raman spectroscopic imaging for ophthalmology

Eye diseases can cause great inconvenience to people's daily life; therefore, it is necessary to study the causes of ocular diseases and related physiological processes. Raman spectroscopic imaging (RSI) is a non-destructive, non-contact detection technique with the advantages of label-free, non-invasive and highly specific. Compared with other mature imaging technologies, RSI can provide real-time molecular information and high-resolution imaging at relatively low cost, making it very suitable for quantitative detection of biological molecules. RSI can reflect the overall situation of the sample, revealing the content distribution of the same substance in different areas of the sample. This review focuses on the recent advances in ophthalmology, with particular emphasis on the powerful use of RSI techniques, as well as its combination with other imaging techniques. Finally, we prospect the wider application and future potential of RSI approaches in ophthalmology.

Accurate and Rapid Detection of Peritoneal Metastasis from Gastric Cancer by AI-Assisted Stimulated Raman Molecular Cytology

Peritoneal metastasis (PM) is the mostcommon form of distant metastasis and one of the leading causes of death in gastriccancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here the authors established the stimulated Raman molecular cytology (SRMC), a chemical microscopy-based intelligent cytology. The authors firstly imaged 53 951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative). Then, the authors revealed 12 single cell features of morphology and composition that are significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, the authors developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix is crucial to identify the significant marker cell cluster, the divergence of which is finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, their SRMC method could reach 81.5% sensitivity, 84.9% specificity, and the AUC of 0.85, within 20 minutes for each patient. Together, their SRMC method shows great potential for accurate and rapid detection of PM from GC.

Toward the Next Frontiers of Vibrational Bioimaging

Chemical imaging based on vibrational contrasts can extract molecular information entangled in complex biological systems. To this end, nonlinear Raman scattering microscopy, mid-infrared photothermal (MIP) microscopy, and atomic force microscopy (AFM)-based force-detected photothermal microscopies are emerging with better chemical sensitivity, molecular specificity, and spatial resolution than conventional vibrational methods. Their utilization in bioimaging applications has provided biological knowledge in unprecedented detail. This Perspective outlines key methodological developments, bioimaging applications, and recent technical innovations of the three techniques. Representative biological demonstrations are also highlighted to exemplify the unique advantages of obtaining vibrational contrasts. With years of effort, these three methods compose an expanding vibrational bioimaging toolbox to tackle specific bioimaging needs, benefiting many biological investigations with rich information in both label-free and labeling manners. Each technique will be discussed and compared in the outlook, leading to possible future directions to accommodate growing needs in vibrational bioimaging.

Fundamentals and Applications of Raman-Based Techniques for the Design and Development of Active Biomedical Materials

Raman spectroscopy is an analytical method based on light-matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided.

Imaging the uptake of deuterated methionine in Drosophila with stimulated Raman scattering

Introduction: Visualizing small individual biomolecules at subcellular resolution in live cells and tissues can provide valuable insights into metabolic activity in heterogeneous cells, but is challenging.

Methods: Here, we used stimulated Raman scattering (SRS) microscopy to image deuterated methionine (d-Met) incorporated into Drosophila tissues in vivo.

Results: Our results demonstrate that SRS can detect a range of previously uncharacterized cell-to-cell differences in d-Met distribution within a tissue at the subcellular level.

Discussion: These results demonstrate the potential of SRS microscopy for metabolic imaging of less abundant but important amino acids such as methionine in tissue.

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.

Euclidean distance-based Raman spectroscopy (EDRS) for the prognosis analysis of gastric cancer: A solution to tumor heterogeneity

The prognosis analysis of gastric cancer is critical for selection of treatments and development of advanced therapeutic methods. A prognosis approach that is accurate, fast, convenient, and of low cost for gastric cancers is in high demand. Raman spectroscopy is a label-free and non-destructive technique to provide molecular fingerprints of biological samples, holding promises for cancer prognosis. However, the major challenge of gastric cancer prognosis lies in the widely existing tumor heterogeneity, which leads to unexpected spectral variations within one type of samples. In this work, we have developed the Euclidean distance (ED)-based Raman spectroscopy (EDRS) method for the prognosis analysis of gastric cancer to eliminate the influence of tumor heterogeneity. Raman spectra were first collected on the slices of paraffin-preserved tumor tissues from gastric cancer patients. A standard spectrum to represent the 'worst prognostic tumor cells' was then established. The similarity between each spectrum of tissues and the standard spectrum was assessed by ED, to provide a direct assessment on the prognosis status. We have successfully classified the patients into poor and favorable prognosis groups, either based on the averaged regional ED values (sensitivity of 75 %, specificity of 96.8 %), or based on the minimal ED values at the patient level (sensitivity of 90 %, specificity of 100 %). EDRS was also investigated for survival analysis (AUC = 0.955), much better than the commonly applied post-neoadjuvant therapy (ypTNM) category (AUC = 0.718). Our work highlights EDRS as a rapid, accurate, low-cost and robust tool for heterogeneous cancer-related prognosis assessment and survival prediction, providing new insights for spectroscopic tumor analysis.

The role of altered lipid composition and distribution in liver fibrosis revealed by multimodal nonlinear optical microscopy

Intracellular lipid accumulation is commonly seen in fibrotic livers, but its exact role in liver fibrosis remains elusive. Here, we established a multimodal nonlinear optical microscopy to quantitatively map distribution of biomolecules in fibrotic livers. Our data revealed that unsaturated triglycerides were predominantly accumulated in central vein area during liver fibrosis but not in portal vein area. Moreover, the lipid homeostasis was remarkably dysregulated in the late-stage compared to the early-stage fibrosis, including increased unsaturated triglycerides with decreased lipid unsaturation degree and decreased membrane fluidity. Such alterations were likely due to up-regulated lipogenesis, desaturation, and peroxidation, which consequently led to endoplasmic reticulum stress and cell death. Inspiringly, injured hepatocyte could be rescued by remodeling lipid homeostasis via either supply of unsaturated fatty acids or enhancement of membrane fluidity. Collectively, our study improves current understanding of the role of lipid homeostasis in fibrosis and open opportunities for treatment.

Analysis of urine Raman spectra differences from patients with diabetes mellitus and renal pathologies

Background

Chronic kidney disease (CKD) poses a major public health burden. Diabetes mellitus (DM) is one of the major causes of CKD. In patients with DM, it can be difficult to differentiate diabetic kidney disease (DKD) from other causes of glomerular damage; it should not be assumed that all DM patients with decreased eGFR and/or proteinuria have DKD. Renal biopsy is the standard for definitive diagnosis, but other less invasive methods may provide clinical benefit. As previously reported, Raman spectroscopy of CKD patient urine with statistical and chemometric modeling may provide a novel, non-invasive methodology for discriminating between renal pathologies.

Methods

Urine samples were collected from renal biopsied and non-biopsied patients presenting with CKD secondary to DM and non-diabetic kidney disease. Samples were analyzed by Raman spectroscopy, baselined with the ISREA algorithm, and subjected to chemometric modeling. Leave-one-out cross-validation was used to assess the predictive capabilities of the model.

Results

This proof-of-concept study consisted of 263 samples, including renal biopsied, non-biopsied diabetic and non-diabetic CKD patients, healthy volunteers, and the Surine™ urinalysis control. Urine samples of DKD patients and those with immune-mediated nephropathy (IMN) were distinguished from one another with 82% sensitivity, specificity, positive-predictive value (PPV), and negative-predictive value (NPV). Among urine samples from all biopsied CKD patients, renal neoplasia was identified in urine with 100% sensitivity, specificity, PPV, and NPV, and membranous nephropathy was identified with 66.7% sensitivity, 96.4% specificity, 80.0% PPV, and 93.1% NPV. Finally, DKD was identified among a population of 150 patient urine samples containing biopsy-confirmed DKD, other biopsy-confirmed glomerular pathologies, un-biopsied non-diabetic CKD patients (no DKD), healthy volunteers, and Surine™ with 36.4% sensitivity, 97.8% specificity, 57.1% PPV, and 95.1% NPV. The model was used to screen un-biopsied diabetic CKD patients and identified DKD in more than 8% of this population. IMN in diabetic patients was identified among a similarly sized and diverse population with 83.3% sensitivity, 97.7% specificity, 62.5% PPV, and 99.2% NPV. Finally, IMN in non-diabetic patients was identified with 50.0% sensitivity, 99.4% specificity, 75.0% PPV, and 98.3% NPV.

Conclusions

Raman spectroscopy of urine with chemometric analysis may be able to differentiate between DKD, IMN, and other glomerular diseases. Future work will further characterize CKD stages and glomerular pathology, while assessing and controlling for differences in factors such as comorbidities, disease severity, and other lab parameters.

Bond-selective intensity diffraction tomography

Recovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 s per volume, with a lateral and axial resolution of ~350 nm and ~1.1 µm, respectively. BS-IDT's application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 µm x 100 µm).

A User-Friendly Platform for Single-Cell Raman Spectroscopy Analysis

The optimization of Raman instruments greatly expands our understanding of single-cell Raman spectroscopy. The improvement in the speed and sensitivity of the instrument and the implementation of advanced data mining methods help to reveal the complex chemical and biological information within the Raman spectral data. Here we introduce a new Matlab Graphical User-Friendly Interface (GUI), named "CELL IMAGE" for the analysis of cellular Raman spectroscopy data. The three main steps of data analysis embedded in the GUI include spectral processing, pattern recognition and model validation. Various well-known methods are available to the user of the GUI at each step of the analysis. Herein, a new subsampling optimization method is integrated into the GUI to estimate the minimum number of spectral collection points. The introduction of the signal-to-noise ratio (SNR) of the analyte in the binomial statistical model means the new subsampling model is more sophisticated and suitable for complicated Raman cell data. These embedded methods allow "CELL IMAGE" to transform spectral information into biological information, including single-cell visualization, cell classification and biomolecular/ drug quantification.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Alterations in the molecular composition of COVID-19 patient urine, detected using Raman spectroscopic/computational analysis

We developed and tested a method to detect COVID-19 disease, using urine specimens. The technology is based on Raman spectroscopy and computational analysis. It does not detect SARS-CoV-2 virus or viral components, but rather a urine ‘molecular fingerprint’, representing systemic metabolic, inflammatory, and immunologic reactions to infection. We analyzed voided urine specimens from 46 symptomatic COVID-19 patients with positive real time-polymerase chain reaction (RT-PCR) tests for infection or household contact with test-positive patients. We compared their urine Raman spectra with urine Raman spectra from healthy individuals (n = 185), peritoneal dialysis patients (n = 20), and patients with active bladder cancer (n = 17), collected between 2016–2018 (i.e., pre-COVID-19). We also compared all urine Raman spectra with urine specimens collected from healthy, fully vaccinated volunteers (n = 19) from July to September 2021. Disease severity (primarily respiratory) ranged among mild (n = 25), moderate (n = 14), and severe (n = 7). Seventy percent of patients sought evaluation within 14 days of onset. One severely affected patient was hospitalized, the remainder being managed with home/ambulatory care. Twenty patients had clinical pathology profiling. Seven of 20 patients had mildly elevated serum creatinine values (>0.9 mg/dl; range 0.9–1.34 mg/dl) and 6/7 of these patients also had estimated glomerular filtration rates (eGFR) <90 mL/min/1.73m² (range 59–84 mL/min/1.73m²). We could not determine if any of these patients had antecedent clinical pathology abnormalities. Our technology (Raman Chemometric Urinalysis—Rametrix^®) had an overall prediction accuracy of 97.6% for detecting complex, multimolecular fingerprints in urine associated with COVID-19 disease. The sensitivity of this model for detecting COVID-19 was 90.9%. The specificity was 98.8%, the positive predictive value was 93.0%, and the negative predictive value was 98.4%. In assessing severity, the method showed to be accurate in identifying symptoms as mild, moderate, or severe (random chance = 33%) based on the urine multimolecular fingerprint. Finally, a fingerprint of ‘Long COVID-19’ symptoms (defined as lasting longer than 30 days) was located in urine. Our methods were able to locate the presence of this fingerprint with 70.0% sensitivity and 98.7% specificity in leave-one-out cross-validation analysis. Further validation testing will include sampling more patients, examining correlations of disease severity and/or duration, and employing metabolomic analysis (Gas Chromatography–Mass Spectrometry [GC-MS], High Performance Liquid Chromatography [HPLC]) to identify individual components contributing to COVID-19 molecular fingerprints.

Quantitative Stimulated Raman Scattering Microscopy: Promises and Pitfalls

Since its first demonstration, stimulated Raman scattering (SRS) microscopy has become a powerful chemical imaging tool that shows promise in numerous biological and biomedical applications. The spectroscopic capability of SRS enables identification and tracking of specific molecules or classes of molecules, often without labeling. SRS microscopy also has the hallmark advantage of signal strength that is directly proportional to molecular concentration, allowing for in situ quantitative analysis of chemical composition of heterogeneous samples with submicron spatial resolution and subminute temporal resolution. However, it is important to recognize that quantification through SRS microscopy requires assumptions regarding both system and sample. Such assumptions are often taken axiomatically, which may lead to erroneous conclusions without proper validation. In this review, we focus on the tacitly accepted, yet complex, quantitative aspect of SRS microscopy. We discuss the various approaches to quantitative analysis, examples of such approaches, challenges in different systems, and potential solutions. Through our examination of published literature, we conclude that a scrupulous approach to experimental design can further expand the powerful and incisive quantitative capabilities of SRS microscopy.

Alkyne-Tagged Raman Probes for Local Environmental Sensing by Hydrogen-Deuterium Exchange

Alkyne-tagged Raman probes have shown high promise for noninvasive and sensitive visualization of small biomolecules to understand their functional roles in live cells. However, the potential for alkynes to sense cellular environments that goes beyond imaging remains to be further explored. Here, we report a general strategy for Raman imaging-based local environment sensing by hydrogen-deuterium exchange (HDX) of terminal alkynes (termed alkyne-HDX). We first demonstrate, in multiple Raman probes, that deuterations of the alkynyl hydrogens lead to remarkable shifts of alkyne Raman peaks for about 130 cm^-1, providing resolvable signals suited for imaging-based analysis with high specificity. Both our analytical derivation and experimental characterizations subsequently establish that HDX kinetics are linearly proportional to both alkyne pK_as and environmental pDs. After validating the quantitative nature of this strategy, we apply alkyne-HDX to sensing local chemical and cellular environments. We establish that alkyne-HDX exhibits high sensitivity to various DNA structures and demonstrates the capacity to detect DNA structural changes in situ from UV-induced damage. We further show that this strategy is also applicable to resolve subtle pD variations in live cells. Altogether, our work lays the foundation for utilizing alkyne-HDX strategy to quantitatively sense the local environments for a broad spectrum of applications in complex biological systems.

A Dual-Modal Single-Antibody Plasmonic Spectro-Immunoassay for Detection of Small Molecules

Small molecules play a pivotal role in regulating physiological processes and serve as biomarkers to uncover pathological conditions and the effects of therapeutic treatments. However, it remains a significant challenge to detect small molecules given the size as compared to macromolecules. Recently, the newly emerging plasmonic immunoassays based on surface-enhanced Raman scattering (SERS) offer great promise to deliver extraordinary sensitivity. Nevertheless, they are limited by the intrinsic SERS intensity fluctuations associated with the SERS uncertainty principle. The single transducer that relies on the intensity change is also prone to false signals. Additionally, the prevailing sandwich immunoassay format proves less effective towards detecting small molecules. To circumvent these critical issues, a dual-modal single-antibody approach that synergizes both the intensity and shift of the peak-based immunoassay with Raman enhancement, coined as the INSPIRE assay, is developed for small molecules detection. With two independent transduction mechanisms, it allows better prediction of analyte concentration and attenuation of signal artifacts, providing a new and robust strategy for molecular analysis. With a proof-of-concept demonstration for detection of free T4 and testosterone in serum matrix, the authors envision that the INSPIRE assay could be expanded for a wide spectrum of applications in biomedical diagnosis, discovery of new biopharmaceuticals, food safety, and environmental monitoring.

Structure analysis and non-invasive detection of cadmium-phytochelatin2 complexes in plant by deep learning Raman spectrum

Plants synthesize phytochelatins to chelate in vivo toxic heavy metal ions and produce nontoxic complexes for tolerating the stress. Detection of the complexes would simplify the identification of high phytoremediation cultivars, as well as assessment of plant food for safe consumption. Thus, a confocal Raman spectroscopy combined with density functional theory and deep learning was used for characterizing phytochelatin2 (PC₂), and Cd-PC₂ mixtures. Results showed the PC₂ chelate Cd²⁺ in a 2:1 ratio to produce Cd(PC₂)₂; Cd-S bonds of the Cd(PC₂)₂ have signature Raman vibrations at 305 and 610 cm^-1 which are the most distinctive spectral signatures for varieties of Cd-PCs complexes. The PC₂ was used as a natural probe to stabilize the chemical status of Cd, and to enrich and magnify Raman signature of the trace Cd for deep learning models which enabled condition of the Cd(PC₂)₂ in pak choi leaf to be visualized, quantified, and classified by directly using raw spectra of the leaf. This study provides a general protocol by using Raman information for structure analysis and non-invasive detection of heavy metal-PCs complexes in plants and provides a novel idea for simplifying identification of high phytoremediation cultivars, as well as assessment of heavy metal related food safeties.

Super-multiplexed vibrational probes: Being colorful makes a difference

Biological systems with intrinsic complexity require multiplexing techniques to comprehensively describe the phenotype, interaction, and heterogeneity. Recent years have witnessed the development of super-multiplexed vibrational microscopy, overcoming the 'color barrier' of fluorescence-based optical techniques. Here, we will review the recent progress in the design and applications of super-multiplexed vibrational probes. We hope to illustrate how rainbow-like vibrational colors can be generated from systematic studies on structure-spectroscopy relationships and how being colorful makes a difference to various biomedical applications.

Super-resolution mid-infrared spectro-microscopy of biological applications through tapping mode and peak force tapping mode atomic force microscope

Small biomolecules at the subcellular level are building blocks for the manifestation of complex biological activities. However, non-intrusive in situ investigation of biological systems has been long daunted by the low spatial resolution and poor sensitivity of conventional light microscopies. Traditional infrared (IR) spectro-microscopy can enable label-free visualization of chemical bonds without extrinsic labeling but is still bound by Abbe's diffraction limit. This review article introduces a way to bypass the optical diffraction limit and improve the sensitivity for mid-IR methods - using tip-enhanced light nearfield in atomic force microscopy (AFM) operated in tapping and peak force tapping modes. Working principles of well-established scattering-type scanning near-field optical microscopy (s-SNOM) and two relatively new techniques, namely, photo-induced force microscopy (PiFM) and peak force infrared (PFIR) microscopy, will be briefly presented. With ∼ 10-20 nm spatial resolution and monolayer sensitivity, their recent applications in revealing nanoscale chemical heterogeneities in a wide range of biological systems, including biomolecules, cells, tissues, and biomaterials, will be reviewed and discussed. We also envision several future improvements of AFM-based tapping and peak force tapping mode nano-IR methods that permit them to better serve as a versatile platform for uncovering biological mechanisms at the fundamental level.

Multicolor Photoactivatable Raman Probes for Subcellular Imaging and Tracking by Cyclopropenone Caging

Photoactivatable probes, with high-precision spatial and temporal control, have largely advanced bioimaging applications, particularly for fluorescence microscopy. While emerging Raman probes have recently pushed the frontiers of Raman microscopy for noninvasive small-molecule imaging and supermultiplex optical imaging with superb sensitivity and specificity, photoactivatable Raman probes remain less explored. Here, we report the first general design of multicolor photoactivatable alkyne Raman probes based on cyclopropenone caging for live-cell imaging and tracking. The fast photochemically generated alkynes from cyclopropenones enable background-free Raman imaging with desired photocontrollable features. We first synthesized and spectroscopically characterized a series of model cyclopropenones and identified the suitable light-activating scaffold. We further engineered the scaffold for enhanced chemical stability in a live-cell environment and improved Raman sensitivity. Organelle-targeting probes were then generated to achieve targeted imaging of mitochondria, lipid droplets, endoplasmic reticulum, and lysosomes. Multiplexed photoactivated imaging and tracking at both subcellular and single-cell levels was next demonstrated to monitor the dynamic migration and interactions of the cellular contents. We envision that this general design of multicolor photoactivatable Raman probes would open up new ways for spatial-temporal controlled profiling and interrogations in complex biological systems with high information throughput.

Vibrational line shape effects in plasmon-enhanced stimulated Raman spectroscopies

A density matrix treatment of plasmon-enhanced (PE) stimulated Raman spectroscopies is developed. Specifically, PE stimulated Raman Gain/Loss (PE-SRG/L) and coherent anti-Stokes Raman scattering (PE-CARS) due to monochromatic excitation and PE femtosecond stimulated Raman spectroscopy (PE-FSRS) are considered. A Lorentz oscillator model is used to explicitly describe the time dependence of plasmon-enhanced optical fields. These temporal characteristics are required for a density matrix based description of all plasmon-enhanced nonlinear molecular spectroscopies. Dispersive vibrational line shapes in PE-SRG/L and PE-FSRS spectra are shown to result primarily from terms proportional to the square of the complex optical field enhancement factor. The dependence on the plasmon resonance, picosecond and femtosecond pulse characteristics, and molecular vibrational properties are evident in the density matrix derived PE-FSRS intensity expression. The difference in signal detection mechanisms accounts for the lack of dispersive line shapes in PE spontaneous Raman spectroscopy. This density matrix treatment of PE-FSRS line shapes is compared with prior coupled wave results.

Raman microscopy-based quantification of the physical properties of intracellular lipids

The physical properties of lipids, such as viscosity, are homeostatically maintained in cells and are intimately involved in physiological roles. Measurement of the physical properties of plasma membranes has been achieved primarily through chemical or genetically encoded fluorescent probes. However, since most probes target plasma membranes, physical properties of lipids in intracellular organelles, including lipid droplets (LDs) are yet to be analyzed. Here, we present a novel Raman microscopy-based approach for quantifying the physical properties of intracellular lipids under deuterium-labeled fatty acid treatment conditions. Focusing on the fact that Raman spectra of carbon-deuterium vibration are altered depending on the surrounding lipid species, we quantitatively represented the physical properties of lipids as the gauche/trans conformational ratio of the introduced labeled fatty acids, which can be used as an indicator of viscosity. Intracellular Raman imaging revealed that the gauche/trans ratio of cytosolic regions was robustly preserved against perturbations attempting to alter the lipid composition. This was likely due to LDs functioning as a buffer against excess gauche/trans ratio, beyond its traditional role as an energy storage organelle. Our novel approach enables the observation of the physical properties of organelle lipids, which is difficult to perform with conventional probes, and is useful for quantitative assessment of the subcellular lipid environment.

Multiwell Raman plate reader for high-throughput biochemical screening

Although Raman spectroscopy has been used for the quantitative analysis of samples in many fields, including material science, biomedical, and pharmaceutical research, its low sensitivity hindered the application of the analytical capability for high-throughput screening. Here, we developed a high-throughput Raman screening system that can analyze hundreds of specimens in a multiwell plate simultaneously. Multiple high numerical aperture (NA) lenses are assembled under each well in the multiwell plate to detect Raman scattering simultaneously with high sensitivity. The Raman spectrum of 192 samples loaded on a standard 384-well plate can be analyzed simultaneously. With the developed system, the throughput of Raman measurement was significantly improved (about 100 times) compared to conventional Raman instruments based on a single-point measurement. By using the developed system, we demonstrated high-throughput Raman screening to investigate drug polymorphism and identify a small-molecule binding site in a protein. Furthermore, the same system was used to demonstrate high-speed chemical mapping of a centimeter-sized pork slice.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.