Micro-Raman detection of nuclear membrane lipid fluctuations in senescent epithelial breast cancer cells

Raman Spectroscopy in Cellular and Tissue Aging Research

The establishment of various molecular, physiological, and genetic markers for cellular senescence and aging-associated conditions has progressed the aging study. To identify such markers, a combination of optical, proteomic-, and sequencing-based tools is primarily used, often accompanying extrinsic labels. Yet, the tools for clinical detection at the molecular, cellular, and tissue levels are still lacking which profoundly hinders advancements in the specific detection and timely prevention of aging-related diseases and pathologies. Raman spectroscopy, with its capability for rapid, label-free, and non-invasive analysis of molecular compositions and alterations in aging cells and tissues, holds considerable promise for in vivo applications. In this review, we present recent advancements in the application of Raman spectroscopy to the study of aging in cells and tissues. We explore the use of Raman spectroscopy and related techniques for detecting cellular aging and senescence, focusing on the molecular alterations that accompany these processes. Subsequently, we provide a review of the application of Raman spectroscopy in identifying aging-related changes in various molecules within tissues and organs.

Coherent Raman microscopy visualizes ongoing cellular senescence through amide I peak shifts originating from β sheets in disordered nucleolar proteins

Cellular senescence occurs through the accumulation of many kinds of stresses. Senescent cells in tissues also cause various age-related disorders. Therefore, detecting them without labeling is beneficial for medical research and developing diagnostic methods. However, existing biomarkers have limitations of requiring fixation and labeling, or their molecular backgrounds are uncertain. Coherent anti-Stokes Raman scattering (CARS) spectroscopic imaging is a novel option because it can assess and visualize molecular structures based on their molecular fingerprint. Here, we present a new label-free method to visualize cellular senescence using CARS imaging in nucleoli. We found the peak of the nucleolar amide I band shifted to a higher wavenumber in binuclear senescent cells, which reflects changes in the protein secondary structure from predominant α-helices to β-sheets originating from amyloid-like aggregates. Following this, we developed a procedure that can visualize the senescent cells by providing the ratios and subtractions of these two components. We also confirmed that the procedure can visualize nucleolar aggregates due to unfolded/misfolded proteins produced by proteasome inhibition. Finally, we found that this method can help visualize the nucleolar defects in naïve cells even before binucleation. Thus, our method is beneficial to evaluate ongoing cellular senescence through label-free imaging of nucleolar defects.

Noninvasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells

Anticancer therapy screening in vitro identifies additional treatments and improves clinical outcomes. Systematically, although most tested cells respond to cues with apoptosis, an appreciable portion enters a senescent state, a critical condition potentially driving tumor resistance and relapse. Conventional screening protocols would strongly benefit from prompt identification and monitoring of therapy-induced senescent (TIS) cells in their native form. We combined complementary all-optical, label-free, and quantitative microscopy techniques, based on coherent Raman scattering, multiphoton absorption, and interferometry, to explore the early onset and progression of this phenotype, which has been understudied in unperturbed conditions. We identified TIS manifestations as early as 24 hours following treatment, consisting of substantial mitochondrial rearrangement and increase of volume and dry mass, followed by accumulation of lipid vesicles starting at 72 hours. This work holds the potential to affect anticancer treatment research, by offering a label-free, rapid, and accurate method to identify initial TIS in tumor cells.

Deep ensemble learning and transfer learning methods for classification of senescent cells from nonlinear optical microscopy images

The success of chemotherapy and radiotherapy anti-cancer treatments can result in tumor suppression or senescence induction. Senescence was previously considered a favorable therapeutic outcome, until recent advancements in oncology research evidenced senescence as one of the culprits of cancer recurrence. Its detection requires multiple assays, and nonlinear optical (NLO) microscopy provides a solution for fast, non-invasive, and label-free detection of therapy-induced senescent cells. Here, we develop several deep learning architectures to perform binary classification between senescent and proliferating human cancer cells using NLO microscopy images and we compare their performances. As a result of our work, we demonstrate that the most performing approach is the one based on an ensemble classifier, that uses seven different pre-trained classification networks, taken from literature, with the addition of fully connected layers on top of their architectures. This approach achieves a classification accuracy of over 90%, showing the possibility of building an automatic, unbiased senescent cells image classifier starting from multimodal NLO microscopy data. Our results open the way to a deeper investigation of senescence classification via deep learning techniques with a potential application in clinical diagnosis.

Infra-red spectroscopy combined with machine learning algorithms enables early determination of Pseudomonas aeruginosa's susceptibility to antibiotics

Pseudomonas (P.) aeruginosa is a bacterium responsible for severe infections that have become a real concern in hospital environments. Nosocomial infections caused by P. aeruginosa are often hard to treat because of its intrinsic resistance and remarkable ability to acquire further resistance mechanisms to multiple groups of antimicrobial agents. Thus, rapid determination of the susceptibility of P. aeruginosa isolates to antibiotics is crucial for effective treatment. The current methods used for susceptibility determination are time-consuming; hence the importance of developing a new method. Fourier-transform infra-red (FTIR) spectroscopy is known as a rapid and sensitive diagnostic tool, with the ability to detect minor abnormal molecular changes including those associated with the development of antibiotic- resistant bacteria. The main goal of this study is to evaluate the potential of FTIR spectroscopy together with machine learning algorithms, to determine the susceptibility of P. aeruginosa to different antibiotics in a time span of ∼20 min after the first culture. For this goal, 590 isolates of P. aeruginosa, obtained from different infection sites of various patients, were measured by FTIR spectroscopy and analyzed by machine learning algorithms. We have successfully determined the susceptibility of P. aeruginosa to various antibiotics with an accuracy of 82-90%.

Unsaturated lipid isomeric imaging based on the Paternò-Büchi reaction in the solid phase in ambient conditions

In recent years, the development of unsaturated lipid isomeric imaging based on the Paternò-Büchi (PB) reaction has improved significantly. However, research on this imaging method in ambient conditions needs to expand. In this paper, a method of PB reaction in the solid phase in ambient conditions is developed, which is combined with air-flow-assisted desorption electrospray ionisation mass spectrometry (AFADESI-MS) to achieve in situ imaging of lipids at an isomeric level. Experiments showed that the efficiency of the PB reaction was much higher when spraying the reagent solution than when sprinkling the reactant powder directly, and it was not lower than that in the liquid phase. This method can simplify the reaction conditions in the imaging process and can be applied to tissue section samples with only 10 min of pre-processing. The study successfully demonstrated the spatial distribution of unsaturated lipid isomers, and the isomeric ratio corresponded to the lesion areas in mouse brain cancer tissues. Due to its simple operation and performance in ambient conditions, this method may be useful for future studies on lipid isomers in tissues.

Coherent anti-Stokes Raman scattering imaging of microcalcifications associated with breast cancer

Chemical imaging of calcifications was demonstrated in the depth of a tissue. Using long wavelength excitation, broadband coherent anti-Stokes Raman scattering and hierarchical cluster analysis, imaging and chemical analysis were performed 2 mm below the skin level in a model system. Applications to breast cancer diagnostics and imaging are discussed together with the methods to further extend the depth and improve the spatial resolution of chemical imaging.

Raman fingerprints as promising markers of cellular senescence and aging

Due to our aging population, understanding of the underlying molecular mechanisms constantly gains more and more importance. Senescent cells, defined by being irreversibly growth arrested and associated with a specific gene expression and secretory pattern, accumulate with age and thus contribute to several age-related diseases. However, their specific detection, especially in vivo, is still a major challenge. Raman microspectroscopy is able to record biochemical fingerprints of cells and tissues, allowing a distinction between different cellular states, or between healthy and cancer tissue. Similarly, Raman microspectroscopy was already successfully used to distinguish senescent from non-senescent cells, as well as to investigate other molecular changes that occur at cell and tissue level during aging. This review is intended to give an overview about various applications of Raman microspectroscopy to study aging, especially in the context of detecting senescent cells.

Potential of infrared microscopy to differentiate between dementia with Lewy bodies and Alzheimer's diseases using peripheral blood samples and machine learning algorithms

SIGNIFICANCE

Accurate and objective identification of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) is of major clinical importance due to the current lack of low-cost and noninvasive diagnostic tools to differentiate between the two. Developing an approach for such identification can have a great impact in the field of dementia diseases as it would offer physicians a routine objective test to support their diagnoses. The problem is especially acute because these two dementias have some common symptoms and characteristics, which can lead to misdiagnosis of DLB as AD and vice versa, mainly at their early stages.

AIM

The aim is to evaluate the potential of mid-infrared (IR) spectroscopy in tandem with machine learning algorithms as a sensitive method to detect minor changes in the biochemical structures that accompany the development of AD and DLB based on a simple peripheral blood test, thus improving the diagnostic accuracy of differentiation between DLB and AD.

APPROACH

IR microspectroscopy was used to examine white blood cells and plasma isolated from 56 individuals: 26 controls, 20 AD patients, and 10 DLB patients. The measured spectra were analyzed via machine learning.

RESULTS

Our encouraging results show that it is possible to differentiate between dementia (AD and DLB) and controls with an ∼86  %   success rate and between DLB and AD patients with a success rate of better than 93%.

CONCLUSIONS

The success of this method makes it possible to suggest a new, simple, and powerful tool for the mental health professional, with the potential to improve the reliability and objectivity of diagnoses of both AD and DLB.

Multiplex coherent anti-Stokes Raman scattering highlights state of chromatin condensation in CH region

Coherent Raman microscopy has become a powerful tool in label-free, non-destructive and fast cell imaging. Here we apply high spectral resolution multiplex coherent anti-Stokes Raman scattering (MCARS) microspectroscopy in the high wavenumber region to the study of the cell cycle. We show that heterochromatin - the condensed state of chromatin - can be visualised by means of the vibrational signature of proteins taking part in its condensation. Thus, we are able to identify chromosomes and their movement during mitosis, as well as structures like nucleoli and nuclear border in interphase. Furthermore, the specific organization of the endoplasmic reticulum during mitosis is highlighted. Finally, we stress that MCARS can reveal the biochemical impact of the fixative method at the cellular level. Beyond the study of the cell cycle, this work introduces a label-free imaging approach that enables the visualization of cellular processes where chromatin undergoes rearrangements.

Identification of senescent cells in multipotent mesenchymal stromal cell cultures: Current methods and future directions

Regardless of their tissue of origin, multipotent mesenchymal stromal cells (MSCs) are commonly expanded in vitro for several population doublings to achieve a sufficient number of cells for therapy. Prolonged MSC expansion has been shown to result in phenotypical, morphological and gene expression changes in MSCs, which ultimately lead to the state of senescence. The presence of senescent cells in therapeutic MSC batches is undesirable because it reduces their viability, differentiation potential and trophic capabilities. Additionally, senescent cells acquire senescence-activated secretory phenotype, which may not only induce apoptosis in the neighboring host cells following MSC transplantation, but also trigger local inflammatory reactions. This review outlines the current and promising new methodologies for the identification of senescent cells in MSC cultures, with a particular emphasis on non-destructive and label-free methodologies. Technologies allowing identification of individual senescent cells, based on new surface markers, offer potential advantage for targeted senescent cell removal using new-generation senolytic agents, and subsequent production of therapeutic MSC batches fully devoid of senescent cells. Methods or a combination of methods that are non-destructive and label-free, for example, involving cell size and spectroscopic measurements, could be the best way forward because they do not modify the cells of interest, thus maximizing the final output of therapeutic-grade MSC cultures. The further incorporation of machine learning methods has also recently shown promise in facilitating, automating and enhancing the analysis of these measured data.

Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network

Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the current Raman imaging methods to monitor the dynamic process of living cells. In this paper, we developed an artificial intelligence assisted fast Raman imaging method over the already fast line scan Raman imaging method. The reduced imaging time is realized by widening the slit and laser beam, and scanning the sample with a large scan step. The imaging quality is improved by a data-driven approach to train a deep convolutional neural network, which statistically learns to transform low-resolution images acquired at a high speed into high-resolution ones that previously were only possible with a low imaging speed. Accompanied with the improvement of the image resolution, the deteriorated spectral resolution as a consequence of a wide slit is also restored, thereby the fidelity of the spectral information is retained. The imaging time can be reduced to within 1 min, which is about five times faster than the state-of-the-art line scan Raman imaging techniques without sacrificing spectral and spatial resolution. We then demonstrated the reliability of the current method using fixed cells. We finally used the method to monitor the dynamic evolution process of living cells. Such an imaging speed opens a door to the label-free observation of cellular events with conventional Raman microscopy.

Early diagnosis of Alzheimer's disease using infrared spectroscopy of isolated blood samples followed by multivariate analyses

Alzheimer's disease (AD) is the most common cause of dementia, particularly in the elderly. The disease is characterized by cognitive decline that typically starts with insidious memory loss and progresses relentlessly to produce global impairment of all higher cortical functions. Due to better living conditions and health facilities in developed countries, which result in higher overall life spans, these countries report upward trends of AD among their populations. There are, however, no specific diagnostic tests for AD and clinical diagnosis is especially difficult in the earliest stages of the disease. Early diagnosis of AD is frequently subjective and is determined by physicians (generally neurologists, geriatricians, and psychiatrists) depending on their experience. Diagnosing AD requires both medical history and mental status testing. Having trouble with memory does not mean you have AD. AD has no current cure, but treatments for symptoms are available and research continues. In this study, we investigated the potential of infrared microscopy to differentiate between AD patients and controls, using Fourier transform infrared (FTIR) spectroscopy of isolated blood components. FTIR is known as a quick, safe, and minimally invasive method to investigate biological samples. For this goal, we measured infrared spectra from white blood cells (WBCs) and plasma taken from AD patients and controls, with the consent of the patients or their guardians. Applying multivariate analysis, principal component analysis (PCA) followed by linear discriminant analysis (LDA), it was possible to differentiate among the different types of mild, moderate, and severe AD, and the controls, with 85% accuracy when using the WBC spectra and about 77% when using the plasma spectra. When only the moderate and severe stages were included, an 83% accuracy was obtained using the WBC spectra and about 89% when using the plasma spectra.

Using Infrared Spectroscopy and Multivariate Analysis to Detect Antibiotics' Resistant Escherichia coli Bacteria

Bacterial pathogens are one of the primary causes of human morbidity worldwide. Historically, antibiotics have been highly effective against most bacterial pathogens; however, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Early and rapid determination of bacterial susceptibility to antibiotics has become essential in many clinical settings and, sometimes, can save lives. Currently classical procedures require at least 48 h for determining bacterial susceptibility, which can constitute a life-threatening delay for effective treatment. Infrared (IR) microscopy is a rapid and inexpensive technique, which has been used successfully for the detection and identification of various biological samples; nonetheless, its true potential in routine clinical diagnosis has not yet been established. In this study, we evaluated the potential of this technique for rapid identification of bacterial susceptibility to specific antibiotics based on the IR spectra of the bacteria. IR spectroscopy was conducted on bacterial colonies, obtained after 24 h culture from patients' samples. An IR microscope was utilized, and a computational classification method was developed to analyze the IR spectra by novel pattern-recognition and statistical tools, to determine E. coli susceptibility within a few minutes to different antibiotics, gentamicin, ceftazidime, nitrofurantoin, nalidixic acid, ofloxacin. Our results show that it was possible to classify the tested bacteria into sensitive and resistant types, with success rates as high as 85% for a number of examined antibiotics. These promising results open the potential of this technique for faster determination of bacterial susceptibility to certain antibiotics.

Raman technologies in cancer diagnostics

Despite significant effort, cancer still remains a leading cause of death worldwide. In order to reduce its burden, the development and improvement of noninvasive strategies for early detection and diagnosis of cancer are urgently needed. Raman spectroscopy, an optical technique that relies on inelastic light scattering arising from molecular vibrations, is one such strategy, as it can noninvasively probe cancerous markers using only endogenous contrast. In this review, spontaneous, coherent and surface enhanced Raman spectroscopies and imaging, as well as the fundamental principles governing the successful use of these techniques, are discussed. Methods for spectral data analysis are also highlighted. Utilization of the discussed Raman techniques for the detection and diagnosis of cancer in vitro, ex vivo and in vivo is described. The review concludes with a discussion of the future directions of Raman technologies, with particular emphasis on their clinical translation.

Detection of antibiotic resistant Escherichia Coli bacteria using infrared microscopy and advanced multivariate analysis

DeterminingE. colibacteria susceptibility by analyzing their FTIR spectra using multivariate analysis.

A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

Detection of Vero Cells Infected with Herpes Simplex Types 1 and 2 and Varicella Zoster Viruses Using Raman Spectroscopy and Advanced Statistical Methods

Of the eight members of the herpes family of viruses, HSV1, HSV2, and varicella zoster are the most common and are mainly involved in cutaneous disorders. These viruses usually are not life-threatening, but in some cases they might cause serious infections to the eyes and the brain that can lead to blindness and possibly death. An effective drug (acyclovir and its derivatives) is available against these viruses. Therefore, early detection and identification of these viral infections is highly important for an effective treatment. Raman spectroscopy, which has been widely used in the past years in medicine and biology, was used as a powerful spectroscopic tool for the detection and identification of these viral infections in cell culture, due to its sensitivity, rapidity and reliability. Our results showed that it was possible to differentiate, with a 97% identification success rate, the uninfected Vero cells that served as a control, from the Vero cells that were infected with HSV-1, HSV-2, and VZV. For that, linear discriminant analysis (LDA) was performed on the Raman spectra after principal component analysis (PCA) with a leave one out (LOO) approach. Raman spectroscopy in tandem with PCA and LDA enable to differentiate among the different herpes viral infections of Vero cells in time span of few minutes with high accuracy rate. Understanding cell molecular changes due to herpes viral infections using Raman spectroscopy may help in early detection and effective treatment.

Raman microscopy for cellular investigations--From single cell imaging to drug carrier uptake visualization

Progress in advanced therapeutic concepts requires the development of appropriate carrier systems for intracellular drug delivery. Consequently, analysis of interaction between carriers, drugs and cells as well as their uptake and intracellular fate is a current focus of research interest. In this context, Raman spectroscopy recently became an emerging analytical technique, due to its non-destructive, chemically selective and label-free working principle. In this review, we briefly present the state-of-the-art technologies for cell visualization and drug internalization. Against this background, Raman microscopy is introduced as a versatile analytical technique. An overview of various Raman spectroscopy investigations in this field is given including interactions of cells with drug molecules, carrier systems and other nanomaterials. Further, Raman instrumentations and sample preparation methods are discussed. Finally, as the analytical limit is not reached yet, a future perspective for Raman microscopy in pharmaceutical and biomedical research on the single cell level is given.

Raman spectroscopy enables noninvasive biochemical characterization and identification of the stage of healing of a wound

Accurate and rapid assessment of the healing status of a wound in a simple and noninvasive manner would enable clinicians to diagnose wounds in real time and promptly adjust treatments to hasten the resolution of nonhealing wounds. Histologic and biochemical characterization of biopsied wound tissue, which is currently the only reliable method for wound assessment, is invasive, complex to interpret, and slow. Here we demonstrate the use of Raman microspectroscopy coupled with multivariate spectral analysis as a simple, noninvasive method to biochemically characterize healing wounds in mice and to accurately identify different phases of healing of wounds at different time-points. Raman spectra were collected from "splinted" full thickness dermal wounds in mice at 4 time-points (0, 1, 5, and 7 days) corresponding to different phases of wound healing, as verified by histopathology. Spectra were deconvolved using multivariate factor analysis (MFA) into 3 "factor score spectra" (that act as spectral signatures for different stages of healing) that were successfully correlated with spectra of prominent pure wound bed constituents (i.e., collagen, lipids, fibrin, fibronectin, etc.) using non-negative least squares (NNLS) fitting. We show that the factor loadings (weights) of spectra that belonged to wounds at different time-points provide a quantitative measure of wound healing progress in terms of key parameters such as inflammation and granulation. Wounds at similar stages of healing were characterized by clusters of loading values and slowly healing wounds among them were successfully identified as "outliers". Overall, our results demonstrate that Raman spectroscopy can be used as a noninvasive technique to provide insight into the status of normally healing and slow-to-heal wounds and that it may find use as a complementary tool for real-time, in situ biochemical characterization in wound healing studies and clinical diagnosis.

Cell optical density and molecular composition revealed by simultaneous multimodal label-free imaging

We show how Raman imaging can be combined with independent but simultaneous phase measurements of unlabeled cells, with the resulting data providing information on how the light is retarded and/or scattered by molecules in the cell. We then show, for the first time to our knowledge, how the chemistry of the cell highlighted in the Raman information is related to the cell quantitative phase information revealed in digital holographic microscopy by quantifying how the two sets of spatial information are correlated. The results show that such a multimodal implementation is highly useful for the convenience of having video rate imaging of the cell during the entire Raman measurement time, allowing us to observe how the cell changes during Raman acquisition. More importantly, it also shows that the two sets of label-free data, which result from different scattering mechanisms, are complementary and can be used to interpret the composition and dynamics of the cell, where each mode supplies label-free information not available from the other mode.

Raman microspectroscopy: shining a new light on reproductive medicine

BACKGROUND The last 20 years have seen an enormous upsurge in the number of publications reporting findings obtained by Raman spectroscopy, a non-invasive, non-destructive method which uses the inelastic scattering of light to provide a 'fingerprint' of the sample's chemical composition and constituents. Long neglected because of practical difficulties, the technique has been transformed by recent technological advances into a powerful analytical tool capable of opening avenues of investigation that were previously out of the reach of biomedical scientists. Beyond introducing the approach and describing its relative merits and weaknesses, the aim of this review is to provide a spur for discussion of what may become an invaluable tool for biomedical investigations. METHODS A comprehensive review of the literature was conducted searching PubMed and Ovid databases using numerous MeSH terms associated with reproductive medicine. Furthermore, the reference lists of all reported literature were explored. The searches were restricted to English language articles published in the last 50 years. RESULTS Beginning with simple characterizations of biologically and medically important substances, aided by increasing technological sophistication, the use of Raman spectroscopy in biomedicine has quickly expanded to the investigation of complex biochemical interactions, the assessment of organelles and now the evaluation of living cells and tissue. The first Raman investigations of reproductive organs were primarily oncological in nature; however, the past few years have seen an increase in the application of the technique for the assessment and evaluation of both male and female gametes. In particular, progress has been made in the characterization, identification and localization of sperm nuclear DNA damage. CONCLUSIONS The use of Raman spectroscopy has already provided many tantalizing glimpses into the potential that the technique has to answer many of the unresolved issues in investigative and therapeutic reproductive medicine. However, without stringent assessment and the clear representation of the methods' findings, their true meaning cannot be revealed nor should any conclusions be hastily derived. For the potential of Raman microspectroscopy to be truly realized, the dependability and reliability of the technique and its results can only be ascertained by multidisciplinary collaborations that undertake carefully conducted, controlled and analysed studies.

Tip-enhanced Raman detection of antibody conjugated nanoparticles on cellular membranes

Tip enhanced Raman scattering (TERS) microscopy is used to image antibody conjugated nanoparticles on intact cellular membranes. The combination of plasmonic coupling and the resultant electric field obtained from intermediate focusing of a radially polarized source gives rise to Raman images with spatial resolution below 50 nm. Finite element method calculations are used to explain the origins of the observed image resolution and spectroscopic signals. The observed Raman scattering provides information about the biomolecules present near the nanoparticle probes. The results show that aggregates of nanoparticles produce spectroscopic results similar to those reported from other surface enhanced Raman spectroscopies, e.g., shell isolated nanoparticle enhanced Raman spectroscopy (SHINERS) and aggregated nanoparticles; however, TERS enables the detection of isolated nanoparticles on cell membranes where the observed spectra provide information about the interaction of the specific biomolecule conjugated to the nanoparticle probe. These measurements present a new technique for exploring biomolecular interactions on the surface of cells and tissue.

Diagnostic applications of Raman spectroscopy

Raman spectroscopy has been widely used in various fields of science. It has been successfully utilized to qualitatively and quantitatively determine the molecular compositions of solid, liquid, and gaseous samples. This review focuses on the diagnostic applications of Raman spectroscopy in the past 5 years, with specific emphasis on transplant allograft rejection and cancer detections. First we introduce the principle of Raman spectroscopy and associated surface enhancement techniques. Various recent biomedical and clinical applications of Raman spectroscopy are then reviewed in detail. Finally, we present the experimental and analytical techniques required to implement Raman spectroscopy in a laboratory.

FROM THE CLINICAL EDITOR

This review focuses on evolving diagnostic applications of Raman spectroscopy with special emphasis on transplant allograft rejection and cancer detection.

Raman Spectroscopic Imaging of Cholesterol and Docosahexaenoic Acid Distribution in the Retinal Rod Outer Segment

Raman vibrational spectroscopic imaging was performed on retinal rod cells isolated from bullfrogs (Rana catesbeiana). The Raman spectra enable determination of the lipid and protein rich rod outer segment (ROS) from the nucleus and inner segment of the cell. Peak fitting analysis of spectra obtained from individual rod photoreceptor cells show characteristic vibrational modes that can be associated with cholesterol and docosahexaenoic acid containing lipids. These results provide direct observations of biomolecular gradients in the rod photoreceptor cells, which, thus far, have been based on indirect detergent extracts and histochemical analysis with indicators such as filipin. The detected biomolecules are associated with regulation of the integral membrane protein rhodopsin, and methods capable direct observation of these biomolecules offer new routes to exploring their role in the regulation of cellular processes.