ABSTRACT
T cells are considered to be critical drivers of intestinal inflammation in mice and people. The so called intra-epithelial lymphocyte (IEL) compartment largely consist of T cells. Interestingly, the specific regulation and contribution of IELs in the context of inflammatory bowel disease remains poorly understood, in part due to the lack of appropriate analysis tools. Powerful, label-free methods could ultimately provide access to this cell population and hence give valuable insight into IEL biology and even more to their disease-related functionalities. Raman spectroscopy has demonstrated over the last few years its potential for reliable cell characterization and differentiation, but its utility in regard to IEL exploration remains unknown. To address this question experimentally, we utilized a murine, T cell-driven experimental model system which is accepted to model human gut inflammation. Here, we repopulated the small intestinal IEL compartment (SI IELs) of Rag1-deficient mice endogenously lacking T cells by transferring naïve CD4+ T helper cells intraperitoneally. Using multivariate statistical analysis, high-throughput Raman spectroscopy managed to define a cell subpopulation ex vivo within the SI IEL pool of mice previously receiving T cells in vivo that displayed characteristic spectral features of lymphocytes. Raman data sets matched flow cytometry analyses with the latter identifying T cell receptor (TCR)αß+ CD4+ T cell population in SI IELs from T cell-transferred mice, but not from control mice, in an abundance comparable to the one detected by Raman spectroscopy. Hence, in this study, we provide experimental evidence for high-throughput Raman spectroscopy to be a novel, future tool to reliably identify and potentially further characterize the T cell pool of small intestinal IELs ex vivo.
Subject(s)
Receptors, Antigen, T-Cell, gamma-delta , Spectrum Analysis, Raman , Mice , Humans , Animals , Receptors, Antigen, T-Cell, gamma-delta/analysis , T-Lymphocytes , Intestine, Small/chemistry , Lymphocytes/chemistry , Receptors, Antigen, T-Cell, alpha-beta/analysis , Intestinal Mucosa/chemistryABSTRACT
The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.
Subject(s)
Betula , Spectrum Analysis, Raman , Allergens/chemistry , Germany , Pollen/chemistry , Spectrum Analysis, Raman/methodsABSTRACT
The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.
ABSTRACT
Multimodal optical imaging of tissue has significant potential to become an indispensable diagnostic tool in clinical pathology. Conventional bright-field microscopy provides contrast based on attenuation or reflectance of light, having no depth-related information and no molecular specificity. Recent developments in biomedical optics have introduced a variety of optical modalities, such as Raman spectroscopy (RS), fluorescence lifetime imaging microscopy (FLIM) of endogenous fluorophores, optical coherence tomography (OCT), and others, which provide a distinct characteristic, i.e., molecular, chemical, and morphological information, of the sample. To harvest the full analytical potential of those modalities, we have developed a novel multimodal imaging system, which allows the co-registered acquisition of OCT/FLIM/RS on a single device. The present implementation allows the investigation of biological tissues in the mesoscale range, 0.1-5 mm in a correlated manner. Due to the co-registered acquisition of the modalities, it is possible to directly compare and evaluate the corresponding information between the three modalities. Moreover, by additionally preparing and characterizing entire pathological hematoxylin and eosin (H&E) slides of head and neck biopsies, it is also possible to correlate the multimodal spectroscopic information to any location of the ground truth H&E information. To the best of our knowledge, this is the first development and implementation of a compact and clinically applicable multimodal scanning microscope, which combines OCT, FLIM, and RS together with the possibility for co-registering H&E information for a morpho-chemical tissue characterization and a correlation with the pathological ground truth (H&E) of the underlying signal origin directly in a clinical environment.
Subject(s)
Spectrum Analysis, Raman , Tomography, Optical Coherence , Diagnostic Tests, Routine , Microscopy, Fluorescence , Radionuclide ImagingABSTRACT
The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.
ABSTRACT
Current implementations of fiber-optic Raman spectroscopy probes are frequently based on non-contact probes with a fixed focus and thus and have to precisely maintain the probe-to-sample distance to ensure a sufficient signal collection. We propose and experimentally demonstrate a novel hand-held fiber-optic Raman probe design, which is based on a liquid lens autofocusing unit, combined with a distance sensor and an in-house developed algorithm to precisely determine the probe-to-sample distance. The reported probe significantly improves the signal stability even for hand-held operation, while reducing distance-dependent artifacts for the acquisition of Raman spectra and can improve the acquisition of Raman spectra in a variety of applications.
ABSTRACT
Neutrophils are important cells of the innate immune system and the major leukocyte subpopulation in blood. They are responsible for recognizing and neutralizing invading pathogens, such as bacteria or fungi. For this, neutrophils are well equipped with pathogen recognizing receptors, cytokines, effector molecules, and granules filled with reactive oxygen species (ROS)-producing enzymes. Depending on the pathogen type, different reactions are triggered, which result in specific activation states of the neutrophils. Here, we aim to establish a label-free method to indirectly detect infections and to identify the cause of infection by spectroscopic characterization of the neutrophils. For this, isolated neutrophils from human peripheral blood were stimulated in an in vitro infection model with heat-inactivated Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacterial pathogens as well as with heat-inactivated and viable fungi (Candida albicans). Label-free and nondestructive Raman spectroscopy was used to characterize neutrophils on a single cell level. Phagocytized fungi could be visualized in a few high-resolution false color images of individual neutrophils using label-free Raman spectroscopic imaging. Using a high-throughput screening Raman spectroscope (HTS-RS), Raman spectra of more than 2000 individual neutrophils from three different donors were collected in each treatment group, yielding a data set of almost 20â¯000 neutrophil spectra. Random forest classification models were trained to differentiate infected and noninfected cells with high accuracy (90%). Among the neutrophils challenged with pathogens, even the cause of infection, bacterial or fungal, was predicted correctly with 92% accuracy. Therefore, Raman spectroscopy enables reliable neutrophil phenotyping and infection diagnosis in a label-free manner. In contrast to the microbiological diagnostic standard, where the pathogen is isolated in time-consuming cultivation, this Raman-based method could potentially be blood-culture independent, thus saving precious time in bloodstream infection diagnostics.
Subject(s)
Candida albicans/isolation & purification , Escherichia coli/isolation & purification , Neutrophils/microbiology , Spectrum Analysis, Raman/methods , Staphylococcus aureus/isolation & purification , Animals , HumansABSTRACT
The design of nanoparticles for application in medical diagnostics and therapy requires a thorough understanding of various aspects of nanoparticle-cell interactions. In this work, two unconventional methods for the study of nanoparticle effects on cells, Raman spectroscopy and atomic force microscopy (AFM), were employed to track the molecular and morphological changes that are caused by the interaction between cervical carcinoma-derived HeLa cells and two types of cerium dioxide (CeO2) nanoparticles, ones with dextran coating and the others with no coating. Multivariate statistical analyses of Raman spectra, such as principal component analysis and partial least squares regression, were applied in order to extract the variations in the vibrational features of cell biomolecules and through them, the changes in biomolecular content and conformation. Both types of nanoparticles induced changes in DNA, lipid and protein contents of the cell and variations of the protein secondary structure, whereas dextran-coated CeO2 affected the cell-growth rate to a higher extent. Atomic force microscopy showed changes in cell roughness, cell height and nanoparticle effects on surface molecular layers. The method differentiated between the impact of dextran-coated and uncoated CeO2 nanoparticles with higher precision than performed viability tests. Due to the holistic approach provided by vibrational information on the overall cell content, accompanied by morphological modifications observed by high-resolution microscopy, this methodology offers a wider picture of nanoparticle-induced cell changes, in a label-free single-cell manner.
Subject(s)
Cell Membrane/drug effects , Metal Nanoparticles/chemistry , Pseudopodia/drug effects , Cell Membrane/chemistry , Cerium/chemistry , Dextrans/chemistry , HeLa Cells , Humans , Microscopy, Atomic Force , Principal Component Analysis , Pseudopodia/chemistry , Regression Analysis , Spectrum Analysis, Raman , Surface PropertiesABSTRACT
Non-muscle-invasive bladder cancer affects millions of people worldwide, resulting in significant discomfort to the patient and potential death. Today, cystoscopy is the gold standard for bladder cancer assessment, using white light endoscopy to detect tumor suspected lesion areas, followed by resection of these areas and subsequent histopathological evaluation. Not only does the pathological examination take days, but due to the invasive nature, the performed biopsy can result in significant harm to the patient. Nowadays, optical modalities, such as optical coherence tomography (OCT) and Raman spectroscopy (RS), have proven to detect cancer in real time and can provide more detailed clinical information of a lesion, e.g. its penetration depth (stage) and the differentiation of the cells (grade). In this paper, we present an ex vivo study performed with a combined piezoelectric tube-based OCT-probe and fiber optic RS-probe imaging system that allows large field-of-view imaging of bladder biopsies, using both modalities and co-registered visualization, detection and grading of cancerous bladder lesions. In the present study, 119 examined biopsies were characterized, showing that fiber-optic based OCT provides a sensitivity of 78% and a specificity of 69% for the detection of non-muscle-invasive bladder cancer, while RS, on the other hand, provides a sensitivity of 81% and a specificity of 61% for the grading of low- and high-grade tissues. Moreover, the study shows that a piezoelectric tube-based OCT probe can have significant endurance, suitable for future long-lasting in vivo applications. These results also indicate that combined OCT and RS fiber probe-based characterization offers an exciting possibility for label-free and morpho-chemical optical biopsies for bladder cancer diagnostics.
Subject(s)
Optical Fibers , Spectrum Analysis, Raman , Tomography, Optical Coherence/instrumentation , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Cell Line, Tumor , Collagen/metabolism , Humans , Neoplasm Grading , Neoplasm InvasivenessABSTRACT
Existing approaches for early-stage bladder tumor diagnosis largely depend on invasive and time-consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real-time tumor diagnosis can enable immediate laser-based removal of tumors using flexible cystoscopes in the outpatient clinic. Therefore, novel diagnostic modalities are required that can provide real-time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe-based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low- and high-grade tumor.
Subject(s)
Spectrum Analysis, Raman , Urinary Bladder Neoplasms , Humans , Multivariate Analysis , Neoplasm Grading , Urinary Bladder Neoplasms/diagnosisABSTRACT
Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.
ABSTRACT
Raman spectroscopy can provide the biomolecular fingerprint of a cell in a label-free manner. Although a variety of clinical and biomedical applications have been demonstrated, the method remains largely a niche technology. The two main problems are the complexity of data acquisition and the complexity of data analysis. Generally, Raman measurements are performed manually and require a substantial amount of time. This, on the other hand, frequently results in a low number of samples and hence with questionable statistical evaluation. Here, we propose an automated high content screening Raman spectroscopy (HCS-RS) platform, which can perform a series of experiments without human interaction, significantly increasing the number of measured samples and making the measurement more reliable. The automated image processing of bright field images in combination with automatic spectral acquisition of the molecular fingerprint of cells exposed to different physiological conditions enables label-free high content screening applications. The performance of the developed HCS-RS platform is demonstrated by investigating the effect of panitumumab on SW48 and SW480 colorectal cancer cells with wild-type and mutated K-RAS, respectively, in a series of concentrations. Our result indicates that the increased content of panitumumab prohibits the activation of the MAP kinase of the colorectal cancer cells with wild-type K-RAS strongly, whereas there is no significant effect on the K-RAS mutated cells. Moreover, the relative amount of the panitumumab content present in the cells is determined from the Raman spectral information, which could be beneficial for personalized patient treatment.
Subject(s)
Colonic Neoplasms/diagnostic imaging , Colonic Neoplasms/drug therapy , Colorectal Neoplasms/diagnostic imaging , Colorectal Neoplasms/drug therapy , High-Throughput Screening Assays/methods , Panitumumab/pharmacology , Single-Cell Analysis/methods , Spectrum Analysis, Raman/methods , Cell Line, Tumor , Colonic Neoplasms/diagnosis , Colorectal Neoplasms/diagnosis , Humans , Panitumumab/metabolismABSTRACT
Retinal diseases, such as age-related macular degeneration, are leading causes of vision impairment, increasing in incidence worldwide due to an aging society. If diagnosed early, most cases could be prevented. In contrast to standard ophthalmic diagnostic tools, Raman spectroscopy can provide a comprehensive overview of the biochemical composition of the retina in a label-free manner. A proof of concept study of the applicability of nonresonant Raman spectroscopy for retinal investigations is presented. Raman imaging provides valuable insights into the molecular composition of an isolated ex vivo human retina sample by probing the entire molecular fingerprint, i.e., the lipid, protein, carotenoid, and nucleic acid content. The results are compared to morphological information obtained by optical coherence tomography of the sample. The challenges of in vivo Raman studies due to laser safety limitations and predefined optical parameters given by the eye itself are explored. An in-house built setup simulating the optical pathway in the human eye was developed and used to demonstrate that even under laser safety regulations and the above-mentioned optical restrictions, Raman spectra of isolated ex vivo human retinas can be recorded. The results strongly support that in vivo studies using nonresonant Raman spectroscopy are feasible and that these studies provide comprehensive molecular information of the human retina.
ABSTRACT
Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.
Subject(s)
Spectrum Analysis, Raman , Cell Differentiation/drug effects , Cell Survival/drug effects , Doxorubicin/pharmacology , Humans , Principal Component Analysis , Support Vector Machine , THP-1 CellsABSTRACT
High-throughput screening Raman spectroscopy (HTS-RS) with automated localization algorithms offers unsurpassed speed and sensitivity to investigate the effect of dithiothreitol on the diatom Phaedactylum tricornutum. The HTS-RS capability that was demonstrated for this model system can be transferred to unmet analytical applications such as kinetic in vivo studies of microalgal assemblages.
Subject(s)
Diatoms/drug effects , Dithiothreitol/pharmacology , Algorithms , Diatoms/radiation effects , High-Throughput Screening Assays/methods , Light , Spectrum Analysis, Raman/methods , Xanthophylls/chemistry , Xanthophylls/metabolismABSTRACT
Raman spectroscopy using fiber optic probe combines non-contacted and label-free molecular fingerprinting with high mechanical flexibility for biomedical, clinical and industrial applications. Inherently, fiber optic Raman probes provide information from a single point only, and the acquisition of images is not straightforward. For many applications, it is highly crucial to determine the molecular distribution and provide imaging information of the sample. Here, we propose an approach for Raman imaging using a handheld fiber optic probe, which is built around computer vision-based assessment of positional information and simultaneous acquisition of spectroscopic information. By combining this implementation with real-time data processing and analysis, it is possible to create not only fiber-based Raman imaging but also an augmented chemical reality image of the molecular distribution of the sample surface in real-time. We experimentally demonstrated that using our approach, it is possible to determine and to distinguish borders of different bimolecular compounds in a short time. Because the method can be transferred to other optical probes and other spectroscopic techniques, it is expected that the implementation will have a large impact for clinical, biomedical and industrial applications.
Subject(s)
Augmented Reality , Optical Fibers , Spectrum Analysis, Raman/instrumentation , Data Analysis , Equipment Design , Image Processing, Computer-Assisted , Molecular ImagingABSTRACT
Caenorhabditis elegans is an animal model frequently used in research on the effects of metabolism on organismal aging. This comes with a requirement for methods to investigate metabolite content, turnover, and distribution. The aim of our study was to assess the use of a label-free approach to determine both content and distribution of glycogen, the storage form of glucose, in C. elegans. To this end, we grew C. elegans worms under three different dietary conditions for 24-48 h, representing starvation, regular diet and a high glucose diet, followed by analysis of glycogen content. Glycogen analysis was performed on fixed individual whole worms using Raman micro-spectroscopy (RMS). Results were confirmed by comparison with two conventional assays, i.e. iodine staining of worms and enzymatic determination of glycogen. RMS was further used to assess overall lipid and protein content and distribution in the same samples used for glycogen analysis. Expectedly, both glycogen and lipid content were highest in worms grown on a high glucose diet, lower in regularly fed, and lowest in starved nematodes. In summary, RMS is a method suitable for analysis of glycogen content in C. elegans that has the advantage over established methods that (i) individual worms (rather than hundreds per sample) can be analyzed, (ii) glycogen distribution can be assessed at subcellular resolution and (iii) the distribution patterns of other macromolecules can be assessed from the same worms. Thus, RMS has the potential to be used as a sensitive, accurate, cost-effective and high throughput method to evaluate glycogen stores in C. elegans.
Subject(s)
Caenorhabditis elegans/metabolism , Glycogen/metabolism , Spectrum Analysis, Raman , Animals , Caenorhabditis elegans Proteins/metabolism , Iodides/metabolism , Iodine/metabolism , Lipid MetabolismABSTRACT
A new approach is presented for cell lysate identification which uses SERS-active silver nanoparticles and a droplet-based microfluidic chip. Eighty-nanoliter droplets are generated by injecting silver nanoparticles, KCl as aggregation agent, and cell lysate containing cell constituents, such as nucleic acids, carbohydrates, metabolites, and proteins into a continuous flow of mineral oil. This platform enables accurate mixing of small volumes inside the meandering channels of the quartz chip and allows acquisition of thousands of SERS spectra with 785 nm excitation at an integration time of 1 s. Preparation of three batches of three leukemia cell lines demonstrated the experimental reproducibility. The main advantage of a high number of reproducible spectra is to apply statistics for large sample populations with robust classification results. A support vector machine with leave-one-batch-out cross-validation classified SERS spectra with sensitivities, specificities, and accuracies better than 99% to differentiate Jurkat, THP-1, and MONO-MAC-6 leukemia cell lysates. This approach is compared with previous published reports about Raman spectroscopy for leukemia detection, and an outlook is given for transfer to single cells. A quartz chip was designed for SERS at 785 nm excitation. Principal component analysis of SERS spectra clearly separates cell lysates using variations in band intensity ratios.
Subject(s)
Leukemia/diagnosis , Microfluidic Analytical Techniques/instrumentation , Spectrum Analysis, Raman/instrumentation , Cell Line, Tumor , Equipment Design , Humans , Metal Nanoparticles/chemistry , Microfluidic Analytical Techniques/methods , Silver/chemistry , Sonication , Spectrum Analysis, Raman/methodsABSTRACT
We present a high-throughput screening Raman spectroscopy (HTS-RS) platform for a rapid and label-free macromolecular fingerprinting of tens of thousands eukaryotic cells. The newly proposed label-free HTS-RS platform combines automated imaging microscopy with Raman spectroscopy to enable a rapid label-free screening of cells and can be applied to a large number of biomedical and clinical applications. The potential of the new approach is illustrated by two applications. (1) HTS-RS-based differential white blood cell count. A classification model was trained using Raman spectra of 52â¯218 lymphocytes, 48â¯220 neutrophils, and 7â¯294 monocytes from four volunteers. The model was applied to determine a WBC differential for two volunteers and three patients, producing comparable results between HTS-RS and machine counting. (2) HTS-RS-based identification of circulating tumor cells (CTCs) in 1:1, 1:9, and 1:99 mixtures of Panc1 cells and leukocytes yielded ratios of 55:45, 10:90, and 3:97, respectively. Because the newly developed HTS-RS platform can be transferred to many existing Raman devices in all laboratories, the proposed implementation will lead to a significant expansion of Raman spectroscopy as a standard tool in biomedical cell research and clinical diagnostics.
Subject(s)
Biochemistry/methods , Blood Cells/cytology , High-Throughput Screening Assays/methods , Leukocyte Count/methods , Neoplastic Cells, Circulating , Spectrum Analysis, Raman/methods , Cell Line, Tumor , HumansABSTRACT
Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.