Spectral discrimination of live prostate and bladder cancer cell lines using Raman optical tweezers

Classification of formalin-fixed bladder cancer cells with laser tweezer Raman spectroscopy

Bladder cancer is a common cancer that is relatively hard to detect at an early stage because of its non-obvious symptoms. It is known that bladder cells can be found in urine samples which potentially could be used for early detection of bladder cancer. Raman spectroscopy is a powerful non-invasive tool for accessing biochemical information of cells. Combined with laser tweezers, to allow isolation of single cells, Raman spectroscopy has been used to characterise a number of bladder cells that might be found in a urine sample. Using principal component-canonical variates analysis (PC-CVA) and k-fold validation, the results shows that the invasive bladder cancer cells can be identified with accuracy greater than 87%. This demonstrates the potential of developing an early detection method that identifies the invasive bladder cancer cells in urine samples.

Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy

Raman spectroscopy shows great potential for practical clinical applications. By analyzing the structure and composition of molecules through real-time, non-destructive measurements of the scattered light from living cells and tissues, it offers valuable insights. The Raman spectral data directly link to the molecular composition of the cells and tissues and provides a "molecular fingerprint" for various disease states. This review focuses on the practical and clinical applications of Raman spectroscopy, especially in the early detection of human diseases. Identifying predisease, which marks the transition from a healthy to a disease state, is crucial for effective interventions to prevent disease onset. Raman spectroscopy can reveal biological processes occurring during the transition states and may eventually detect the molecular dynamics in predisease conditions.

Rapid Identification of Pathogens Causing Bloodstream Infections by Raman Spectroscopy and Raman Tweezers

The search for the "Holy Grail" in clinical diagnostic microbiology-a reliable, accurate, low-cost, real-time, easy-to-use method-has brought up several methods with the potential to meet these criteria. One is Raman spectroscopy, an optical, nondestructive method based on the inelastic scattering of monochromatic light. The current study focuses on the possible use of Raman spectroscopy for identifying microbes causing severe, often life-threatening bloodstream infections. We included 305 microbial strains of 28 species acting as causative agents of bloodstream infections. Raman spectroscopy identified the strains from grown colonies, with 2.8% and 7% incorrectly identified strains using the support vector machine algorithm based on centered and uncentred principal-component analyses, respectively. We combined Raman spectroscopy with optical tweezers to speed up the process and captured and analyzed microbes directly from spiked human serum. The pilot study suggests that it is possible to capture individual microbial cells from human serum and characterize them by Raman spectroscopy with notable differences among different species. IMPORTANCE Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential. Therefore, our multidisciplinary team of microbiologists and physicists presents a method that reliably, rapidly, and inexpensively identifies pathogens causing bloodstream infections-Raman spectroscopy. We believe that it might become a valuable diagnostic tool in the future. Combined with optical trapping, it offers a new approach where the microorganisms are individually trapped in a noncontact way by optical tweezers and investigated by Raman spectroscopy directly in a liquid sample. Together with the automatic processing of measured Raman spectra and comparison with a database of microorganisms, it makes the whole identification process almost real time.

Raman Spectroscopy—A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings

Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful—quick, non-invasive, and non-destructive —tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.

Raman spectroscopy-a tool for rapid differentiation among microbes causing urinary tract infections

Urinary tract infections belong to the most common infections in the world. Besides community-acquired infections, nosocomial infections pose a high risk especially for patients having indwelling catheters, undergoing urological surgeries or staying at hospital for prolonged time. They can be often complicated by antimicrobial resistance and/or biofilm formation. Therefore, a rapid diagnostic tool enabling timely identification of a causative agent and its susceptibility to antimicrobials is a need. Raman spectroscopy appears to be a suitable method that allows rapid differentiation among microbes and provides a space for further analyses, such as determination of capability of biofilm formation or antimicrobial susceptibility/resistance in tested strains. Our work here presents a possibility to differ among most common microbes causing urinary tract infections (belonging to 20 species). We tested 254 strains directly from colonies grown on Mueller-Hinton agar plates. The results show that it is possible to distinguish among the tested species using Raman spectroscopy, which proves its great potential for future use in clinical diagnostics. Moreover, we present here a pilot study of a real-time analysis and identification (in less than 10 min) of single microbial cells directly in urine employing optical tweezers combined with Raman spectroscopy.

Raman tweezers as an alternative diagnostic tool for paroxysmal nocturnal hemoglobinuria

Paroxysmal nocturnal hemoglobinuria (PNH) is a rare disease characterized by hemolysis of red blood cells (RBC) and venous thrombosis. The gold standard method for the diagnosis of this disease is flow cytometry. Here, we propose a combined optical tweezers and Raman spectral (Raman tweezers) approach to analyze blood samples from volunteers with or without PNH conditions. Raman spectroscopy is a well-known method for investigating a material's chemical structure and is also used in molecular analysis of biological compounds. In this study, we trap individual RBCs found in whole blood samples drawn from PNH patients and the control group. Evaluation of the Raman spectra of these cells by band component analysis and machine learning shows a significant difference between the two groups. The specificity and the sensitivity of the training performed by support vector machine (SVM) analysis were found to be 81.8% and 78.3%, respectively. This study shows that an immediate and high accuracy test result is possible for PNH disease by employing Raman tweezers and machine learning.

Raman Spectrum-Based Diagnosis Strategy for Bladder Tumor

Raman spectroscopy is an optical technique that can potentially serve as a molecular diagnosis method. This approach is excellent in many aspects for diagnosing bladder tumors, and over the last 20 years, there has been a rapid increase in the number of related studies. However, no review article has covered the wide use of Raman spectroscopy in bladder tumors. A total of 26 original studies have suggested that Raman spectroscopy shows good performance in diagnosing bladder tumors from 4 aspects, including tissue sections, endoscopic methods, cell screening, and biomarkers. However, Raman spectroscopy needs to be modified by combining it with other techniques, and studies based on a large population are still urgently needed to expand its clinical value.

Optical design for laser tweezers Raman spectroscopy setups for increased sensitivity and flexible spatial detection

We demonstrate a method to double the collection efficiency in laser tweezers Raman spectroscopy (LTRS) by collecting both the forward-scattered and backscattered light in a single-shot multitrack measurement. Our method can collect signals at different sample volumes, granting both the pinpoint spatial selectivity of confocal Raman spectroscopy and the bulk sensitivity of non-confocal Raman spectroscopy simultaneously. Further, we display that our approach allows for reduced detector integration time and laser power. To show this, we measure the Raman spectra of both polystyrene beads and bacterial spores. For spores, we can trap them at 2.5 mW laser power and acquire a high signal-to-noise ratio power spectrum of the calcium-dipicolinic acid peaks using an integration time of ${2} \times {30}\;{\rm s}$. Thus, our method will enable the monitoring of biological samples sensitive to high intensities for longer times. Additionally, we demonstrate that by a simple modification, we can add polarization sensitivity and retrieve extra biochemical information.

The Impact of Preprocessing Methods for a Successful Prostate Cell Lines Discrimination Using Partial Least Squares Regression and Discriminant Analysis Based on Fourier Transform Infrared Imaging

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer research lies in its capability of monitoring the biochemical status of cells, which undergo malignant transformation and further examination of spectral features that differentiate normal and cancerous ones using proper mathematical approaches. Such examination can be performed with the use of chemometric tools, such as partial least squares discriminant analysis (PLS-DA) classification and partial least squares regression (PLSR), and proper application of preprocessing methods and their correct sequence is crucial for success. Here, we performed a comparison of several state-of-the-art methods commonly used in infrared biospectroscopy (denoising, baseline correction, and normalization) with the addition of methods not previously used in infrared biospectroscopy classification problems: Mie extinction extended multiplicative signal correction, Eiler’s smoothing, and probabilistic quotient normalization. We compared all of these approaches and their effect on the data structure, classification, and regression capability on experimental FT-IR spectra collected from five different prostate normal and cancerous cell lines. Additionally, we tested the influence of added spectral noise. Overall, we concluded that in the case of the data analyzed here, the biggest impact on data structure and performance of PLS-DA and PLSR was caused by the baseline correction; therefore, much attention should be given, especially to this step of data preprocessing.

In search of the correlation between nanomechanical and biomolecular properties of prostate cancer cells with different metastatic potential

Nanomechanical properties of living cells, as measured with atomic force microscopy (AFM), are increasingly recognized as criteria that differentiate normal and pathologically altered cells. Locally measured cell elastic properties, described by the parameter known as Young's modulus, are currently proposed as a new diagnostic parameter that can be used at the early stage of cancer detection. In this study, local mechanical properties of normal human prostate (RWPE-1) cells and a range of malignant (22Rv1) and metastatic prostate cells (LNCaP, Du145 and PC3) were investigated. It was found that non-malignant prostate cells are stiffer than cancer cells while the metastatic cells are much softer than malignant cells from the primary tumor site. Next, the biochemical properties of the cells were measured using confocal Raman (RS) and Fourier-transform infrared (FT-IR) spectroscopies to reveal these cells' biochemical composition as malignant transformation proceeds. Nanomechanical and biochemical profiles of five different prostate cell lines were subsequently analyzed using partial least squares regression (PLSR) in order to identify which spectral features of the RS and FT-IR spectra correlate with the cell's elastic properties. The PLSR-based model could predict Young's modulus values based on both RS and FT-IR spectral information. These outcomes show not only that AFM, RS and FT-IR techniques can be used for discrimination between normal and cancer cells, but also that a linear correlation between mechanical response and biomolecular composition of the cells that undergo malignant transformation can be found. This knowledge broadens our understanding of how prostate cancer cells evolve thorough the multistep process of tumor pathogenesis.

Snook R, Brown MD, Haines BA, Ridley A, Gardner P, Denbigh JL. Fatty-Acid Uptake in Prostate Cancer Cells Using Dynamic Microfluidic Raman Technology

It is known that intake of dietary fatty acid (FA) is strongly correlated with prostate cancer progression but is highly dependent on the type of FAs. High levels of palmitic acid (PA) or arachidonic acid (AA) can stimulate the progression of cancer. In this study, a unique experimental set-up consisting of a Raman microscope, coupled with a commercial shear-flow microfluidic system is used to monitor fatty acid uptake by prostate cancer (PC-3) cells in real-time at the single cell level. Uptake of deuterated PA, deuterated AA, and the omega-3 fatty acids docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) were monitored using this new system, while complementary flow cytometry experiments using Nile red staining, were also conducted for the validation of the cellular lipid uptake. Using this novel experimental system, we show that DHA and EPA have inhibitory effects on the uptake of PA and AA by PC-3 cells.

Raman spectral discrimination in human liquid biopsies of oesophageal transformation to adenocarcinoma

The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma [normal/squamous epithelium, inflammatory, Barrett's, low-grade dysplasia, high-grade dysplasia and oesophageal adenocarcinoma (OAC)]. The chemometric analysis of the spectral data was performed using principal component analysis, successive projections algorithm or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The genetic algorithm quadratic discriminant analysis (GA-QDA) model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA-QDA model achieved excellent accuracy in all oesophageal stages (>90%). The main GA-QDA features responsible for sample discrimination were: 1012 cm^-1 (C─O stretching of ribose), 1336 cm^-1 (Amide III and CH₂ wagging vibrations from glycine backbone), 1450 cm^-1 (methylene deformation) and 1660 cm^-1 (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy’s multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Nondestructive Identification and Accurate Isolation of Single Cells through a Chip with Raman Optical Tweezers

Raman optical tweezers (ROT) as a label-free technique plays an important role in single-cell study such as heterogeneity of tumor and microbial cells. Herein we designed a chip utilizing ROT to isolate a specific single cell. The chip was made from a polydimethylsiloxane (PDMS) slab and formed into a gourd-shaped reservoir with a connected channel on a cover glass. On the chip an individual cell could be isolated from a cell crowd and then extracted with ∼0.5 μL of phosphate-buffered saline (PBS) via pipet immediately after Raman spectral measurements of the same cell. As verification, we separated four different type of cells including BGC823 gastric cancer cells, erythrocytes, lymphocytes, and E. coli cells and quantifiably characterized the heterogeneity of the cancer cells, leukocyte subtype, and erythrocyte status, respectively. The average time of identifying and isolating a specific cell was 3 min. Cell morphology comparison and viability tests showed that the successful rate of single-cell isolation was about 90%. Thus, we believe our platform could further couple other single-cell techniques such as single-cell sequencing and become a multiperspective analytical approach at the level of a single cell.

Real-Time Profiling of Anti-(Epithelial Cell Adhesion Molecule)-Based Immune Capture from Molecules to Cells Using Multiparameter Surface Plasmon Resonance

Antibodies of epithelial cell-adhesion molecule (anti-EpCAM)-based interfaces have proven to be highly efficient at capturing circulating tumor cells (CTCs). To achieve the bonding of anti-EpCAM to the interface, biotin and streptavidin are used to modify the surface. These processes are critical to subsequent cell-capture efficiencies. However, quantitative research on the interactions between biotin, streptavidin, and biotinylated anti-EpCAM on the interface is lacking. In this work, the thermodynamics and kinetics of biomolecular interactions were determined by using surface plasmon resonance. The equilibrium binding affinities for biotinylated anti-EpCAM to streptavidin and streptavidin to biotin (illustrated by biotin-PEG400-thiol) were found to be 2.75 × 10⁶ and 8.82 × 10⁶ M^-1, respectively. Each streptavidin can bind up to 2.30 biotinylated anti-EpCAM under thermodynamic equilibrium. The findings provide useful information to optimize the modification of anti-EpCAM and improve the capture efficiency of CTCs.

Identification and characterization of bladder cancer by low-resolution fiber-optic Raman spectroscopy

Raman spectroscopy has been proved to be a promising diagnostic technique for various cancers detection. A major drawback for its clinical translation is the intrinsic weakness of Raman effects. Highly sensitive equipment and optimal measurement conditions are generally applied to overcome this drawback. However, these equipment are usually bulky, expensive and may also be easily influenced by surrounding environment. In this preliminary work, a low-resolution fiber-optic Raman sensing system is applied to evaluate the diagnostic potential of Raman spectroscopy to identify different bladder pathologies ex vivo. A total number of 262 spectra taken from 32 bladder specimens are included in this study. These spectra are categorized into 3 groups by histopathological analysis, namely normal bladder tissues, low-grade bladder tumors and high-grade bladder tumors. Principal component analysis fed artificial neural network are used to train a classification model for the spectral data with 10-fold cross-validation and an overall prediction accuracy of 93.1% is obtained. The sensitivities and specificities for normal bladder tissues, low-grade bladder tumors and high-grade bladder tumors are 88.5% and 95.1%, 90.3% and 98%, and 97.5% and 96.4%, respectively. These results demonstrate the potential of using a low-resolution fiber-optic Raman system for in vivo bladder cancer diagnosis.

Diagnostic Bacteriology: Raman Spectroscopy

Current clinical methodology for identification of bacterial infections relies predominantly on culturing microbes from patient material and performing biochemical tests. This can often be an inefficient and lengthy process, which has a significant detrimental effect upon patient care. Techniques used in other aspects of molecular research have the potential to revolutionize the way in which diagnostic tests are used and delivered in the clinical setting. The need for rapid, accurate, and cost-effective molecular techniques in the diagnostic laboratory is imperative to improving patient care, preventing the spread of drug resistance and decreasing the overall burden associated with nosocomial infections. Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are powerful vibrational spectroscopy techniques that are being developed for highly sensitive pathogen identification in complex clinical samples. Raman spectroscopy is a molecular technique that is capable of probing samples noninvasively and nondestructively. It has been used with high specificity to assess tissue and bacterial samples at the molecular level with diverse clinical and diagnostic applications. SERS has recently developed out of the advances in the Raman spectroscopy arena. This technique is designed to amplify Raman scattering and allows for better differentiation of bacterial isolates. Although the current parameters for the use of SERS require a pure culture and are relatively monoparametric, current breakthroughs and testing are pushing the technology to new levels and thus changing the face of modern bacterial diagnostics.

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.

Challenges in application of Raman spectroscopy to biology and materials

Raman spectroscopy has become an essential tool for chemists, physicists, biologists and materials scientists. In this article, we present the challenges in unravelling the molecule-specific Raman spectral signatures of different biomolecules like proteins, nucleic acids, lipids and carbohydrates based on the review of our work and the current trends in these areas. We also show how Raman spectroscopy can be used to probe the secondary and tertiary structural changes occurring during thermal denaturation of protein and lysozyme as well as more complex biological systems like bacteria. Complex biological systems like tissues, cells, blood serum etc. are also made up of such biomolecules. Using mice liver and blood serum, it is shown that different tissues yield their unique signature Raman spectra, owing to a difference in the relative composition of the biomolecules. Additionally, recent progress in Raman spectroscopy for diagnosing a multitude of diseases ranging from cancer to infection is also presented. The second part of this article focuses on applications of Raman spectroscopy to materials. As a first example, Raman spectroscopy of a melt cast explosives formulation was carried out to monitor the changes in the peaks which indicates the potential of this technique for remote process monitoring. The second example presents various modern methods of Raman spectroscopy such as spatially offset Raman spectroscopy (SORS), reflection, transmission and universal multiple angle Raman spectroscopy (UMARS) to study layered materials. Studies on chemicals/layered materials hidden in non-metallic containers using the above variants are presented. Using suitable examples, it is shown how a specific excitation or collection geometry can yield different information about the location of materials. Additionally, it is shown that UMARS imaging can also be used as an effective tool to obtain layer specific information of materials located at depths beyond a few centimeters.

This paper reviews various facets of Raman spectroscopy. This encompasses biomolecule fingerprinting and conformational analysis, discrimination of healthy vs. diseased states, depth-specific information of materials and 3D Raman imaging.

Automated analysis of single cells using Laser Tweezers Raman Spectroscopy

In recent years, significant progress has been made into the label-free detection and discrimination of individual cancer cells using Laser Tweezers Raman Spectroscopy (LTRS). However, the majority of examples reported have involved manual trapping of cells, which is time consuming and may lead to different cell lines being analysed in discrete batches. A simple, low-cost microfluidic flow chamber is introduced which allows single cells to be optically trapped and analysed in an automated fashion, greatly reducing the level of operator input required. Two implementations of the flow chamber are discussed here; a basic single-channel device in which the fluid velocity is controlled manually, and a dual-channel device which permits the automated capture and analysis of multiple cell lines with no operator input. Results are presented for the discrimination of live epithelial prostate cells and lymphocytes, together with a consideration of the consequences of traditional 'batch analysis' typically used for LTRS of live cells.

Fluorescence lifetime imaging of optically levitated aerosol: a technique to quantitatively map the viscosity of suspended aerosol particles

A technique to measure the viscosity of stably levitated single micron-sized aerosol particles.

Nuclear accumulation of anthracyclines in the endothelium studied by bimodal imaging: fluorescence and Raman microscopy

Anthracycline antibiotics display genotoxic activity towards cancer cells but their clinical utility is limited by their cardiac and vascular toxicity. The aim of this study was to develop a Raman-based methodology to study the nuclear accumulation of anthracyclines in the endothelium. For this purpose bimodal confocal Raman and fluorescence imaging was used to monitor cellular composition changes as a result of anthracycline exposure on endothelial cells (EA.hy926), and nuclear drug accumulation, respectively. Simultaneously effects of anthracyclines on endothelium viability were investigated by caspases-3 and -7 and MTT assays. We demonstrated that nuclear accumulation of DOX and EDOX was similar; however, EDNR accumulated in endothelial nuclei at concentrations 10 times higher than DNR. In turn, epimers of DOX or DNR were both consistently less toxic on the endothelium as compared to their congeners as evidenced by MTT and caspase assays. In summary, bimodal Raman and fluorescence-based nucleus profiling proves to be a valuable tool to study structure-activity relationship of nuclear accumulation and toxicity of anthracyclines in endothelium.

Raman spectroscopy for medical diagnostics--From in-vitro biofluid assays to in-vivo cancer detection

Raman spectroscopy is an optical technique based on inelastic scattering of light by vibrating molecules and can provide chemical fingerprints of cells, tissues or biofluids. The high chemical specificity, minimal or lack of sample preparation and the ability to use advanced optical technologies in the visible or near-infrared spectral range (lasers, microscopes, fibre-optics) have recently led to an increase in medical diagnostic applications of Raman spectroscopy. The key hypothesis underpinning this field is that molecular changes in cells, tissues or biofluids, that are either the cause or the effect of diseases, can be detected and quantified by Raman spectroscopy. Furthermore, multivariate calibration and classification models based on Raman spectra can be developed on large "training" datasets and used subsequently on samples from new patients to obtain quantitative and objective diagnosis. Historically, spontaneous Raman spectroscopy has been known as a low signal technique requiring relatively long acquisition times. Nevertheless, new strategies have been developed recently to overcome these issues: non-linear optical effects and metallic nanoparticles can be used to enhance the Raman signals, optimised fibre-optic Raman probes can be used for real-time in-vivo single-point measurements, while multimodal integration with other optical techniques can guide the Raman measurements to increase the acquisition speed and spatial accuracy of diagnosis. These recent efforts have advanced Raman spectroscopy to the point where the diagnostic accuracy and speed are compatible with clinical use. This paper reviews the main Raman spectroscopy techniques used in medical diagnostics and provides an overview of various applications.

Identifying the lineages of individual cells in cocultures by multivariate analysis of Raman spectra

The cellular and matrix cues that induce stem cell differentiation into distinct cell lineages must be identified to permit the ex vivo expansion of desired cell populations for clinical applications. Combinatorial biomaterials enable screening multiple different microenvironments while using small numbers of rare stem cells. New methods to identify the phenotypes of individual cells in cocultures with location specificity would increase the efficiency and throughput of these screening platforms. Here, we demonstrate that partial least-squares discriminant analysis (PLS-DA) models of calibration Raman spectra from cells in pure cultures can be used to identify the lineages of individual cells in more complex culture environments. The calibration Raman spectra were collected from individual cells of four different lineages, and a PLS-DA model that captured the Raman spectral profiles characteristic of each cell line was created. The application of these models to Raman spectra from test sets of cells indicated individual, fixed and living cells in separate monocultures, as well as those in more complex culture environments, such as cocultures, could be identified with low error. Cells from populations with very similar biochemistries could also be identified with high accuracy. We show that these identifications are based on reproducible cell-related spectral features, and not spectral contributions from the culture environment. This work demonstrates that PLS-DA of Raman spectra acquired from pure monocultures provides an objective, noninvasive, and label-free approach for accurately identifying the lineages of individual, living cells in more complex coculture environments.

Discrimination of bladder cancer cells from normal urothelial cells with high specificity and sensitivity: combined application of atomic force microscopy and modulated Raman spectroscopy

Atomic force microscopy (AFM) and modulated Raman spectroscopy (MRS) were used to discriminate between living normal human urothelial cells (SV-HUC-1) and bladder tumour cells (MGH-U1) with high specificity and sensitivity. MGH-U1 cells were 1.5-fold smaller, 1.7-fold thicker and 1.4-fold rougher than normal SV-HUC-1 cells. The adhesion energy was 2.6-fold higher in the MGH-U1 cells compared to normal SV-HUC-1 cells, which possibly indicates that bladder tumour cells are more deformable than normal cells. The elastic modulus of MGH-U1 cells was 12-fold lower than SV-HUC-1 cells, suggesting a higher elasticity of the bladder cancer cell membranes. The biochemical fingerprints of cancer cells displayed a higher DNA and lipid content, probably due to an increase in the nuclear to cytoplasm ratio. Normal cells were characterized by higher protein contents. AFM studies revealed a decrease in the lateral dimensions and an increase in thickness of cancer cells compared to normal cells; these studies authenticate the observations from MRS. Nanostructural, nanomechanical and biochemical profiles of bladder cells provide qualitative and quantitative markers to differentiate between normal and cancerous cells at the single cellular level. AFM and MRS allow discrimination between adhesion energy, elasticity and Raman spectra of SV-HUC-1 and MGH-U1 cells with high specificity (83, 98 and 95%) and sensitivity (97, 93 and 98%). Such single-cell-level studies could have a pivotal impact on the development of AFM-Raman combined methodologies for cancer profiling and screening with translational significance.

Highlighting a need to distinguish cell cycle signatures from cellular responses to chemotherapeutics in SR-FTIR spectroscopy

Previous research has seen difficulties in establishing clear discrimination by principal component analysis (PCA) between drug-treated cells analysed by single point SR-FTIR spectroscopy, relative to multisampling cell monolayers by conventional FTIR. It is suggested that the issue arises due to signal mixing between cellular-response signatures and cell cycle phase contributions in individual cells. Consequently, chemometric distinction of cell spectra treated with multiple drugs is difficult even with supervised methods. In an effort to separate cell cycle chemistry from cellular response chemistry in the spectra, renal carcinoma cells were stained with propidium iodide and fluorescent-activated cell sorted (FACS) after exposure to a number of chemotherapeutic compounds; 5-fluorouracil (5FU) and a set of novel gold-based experimental compounds. The cell spectra were analysed separately by PCA in G(1), S or G(2)/M phase. The mode of action of established drug 5FU, known to disrupt S phase, was confirmed by FACS analysis. The chemical signature of 5FU-treated cells discriminated against both the control and gold-compound (KF0101)-treated cell spectra, suggesting a different mode of action due to a difference in cellular response.

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.

Optimisation of wavelength modulated Raman spectroscopy: towards high throughput cell screening

In the field of biomedicine, Raman spectroscopy is a powerful technique to discriminate between normal and cancerous cells. However the strong background signal from the sample and the instrumentation affects the efficiency of this discrimination technique. Wavelength Modulated Raman spectroscopy (WMRS) may suppress the background from the Raman spectra. In this study we demonstrate a systematic approach for optimizing the various parameters of WMRS to achieve a reduction in the acquisition time for potential applications such as higher throughput cell screening. The Signal to Noise Ratio (SNR) of the Raman bands depends on the modulation amplitude, time constant and total acquisition time. It was observed that the sampling rate does not influence the signal to noise ratio of the Raman bands if three or more wavelengths are sampled. With these optimised WMRS parameters, we increased the throughput in the binary classification of normal human urothelial cells and bladder cancer cells by reducing the total acquisition time to 6 s which is significantly lower in comparison to previous acquisition times required for the discrimination between similar cell types.

FTIR microspectroscopy of selected rare diverse sub-variants of carcinoma of the urinary bladder

Urothelial carcinomas of the bladder are a heterogeneous group of tumours, although some histological sub-variants are rare and sparsely reported in the literature. Diagnosis of sub-variants from conventional urothelial carcinoma can be challenging, as they may mimic the morphology of other malignancies or benign tumours and therefore their distinction is important. For the first time, the spectral pathology of some of these sub-variants has been documented by infrared microspectroscopy and an attempt made to profile their biochemistry. It is important not only to identify and separate the cancer-associated epithelial tissue spectra from common tissue features such as stroma or blood, but also to detect the signatures of tumour sub-variants. As shown, their spectroscopic signals can change dramatically as a consequence of differentiation. Example cases are discussed and compared with histological evaluations.

Resonance micro-Raman investigations of the rat medial preoptic nucleus: effects of a low-iron diet on the neuroglobin content

The aim of this study was to investigate the medial preoptic nucleus (MPN) of the anterior hypothalamus by resonance Raman spectroscopy (514.5 nm) to determine if it is possible to enhance the Raman scattering of hemoproteins in fresh brain tissue slices. The resonance effect was compared with near-infrared Raman spectra. Two groups of male Sprague Dawley rats were studied, one control group on a normal diet and one group on a low-iron diet to evoke iron deficiency. Each group consisted of four rats, 38-41 days old. The diets lasted for 11, 12, and 15 days. The MPN regions of brain tissue slices were analyzed by monitoring raw and pre-processed mean data, by cluster analysis, and by deriving difference spectra from pre-processed mean spectra. Cluster analysis of the resonance Raman spectra could identify different hemoprotein groups, namely, hemoglobin (Hb) and neuroglobin (Ngb). Spectra from randomly distributed spots revealed high Hb content, whereas Ngb was evenly distributed in the MPN. The different spectra showed a decrease of the Ngb and lipid content for the animals on the low-iron diet. The Ngb decrease was approximately 20%. The data show that resonance Raman spectroscopy is well suited to study hemoproteins in fresh brain tissue.

Raman spectroscopy in biomedicine - non-invasive in vitro analysis of cells and extracellular matrix components in tissues

Raman spectroscopy is an established laser-based technology for the quality assurance of pharmaceutical products. Over the past few years, Raman spectroscopy has become a powerful diagnostic tool in the life sciences. Raman spectra allow assessment of the overall molecular constitution of biological samples, based on specific signals from proteins, nucleic acids, lipids, carbohydrates, and inorganic crystals. Measurements are non-invasive and do not require sample processing, making Raman spectroscopy a reliable and robust method with numerous applications in biomedicine. Moreover, Raman spectroscopy allows the highly sensitive discrimination of bacteria. Rama spectra retain information on continuous metabolic processes and kinetics such as lipid storage and recombinant protein production. Raman spectra are specific for each cell type and provide additional information on cell viability, differentiation status, and tumorigenicity. In tissues, Raman spectroscopy can detect major extracellular matrix components and their secondary structures. Furthermore, the non-invasive characterization of healthy and pathological tissues as well as quality control and process monitoring of in vitro-engineered matrix is possible. This review provides comprehensive insight to the current progress in expanding the applicability of Raman spectroscopy for the characterization of living cells and tissues, and serves as a good reference point for those starting in the field.

Micro-Raman spectroscopy of silver nanoparticle induced stress on optically-trapped stem cells

We report here results of a single-cell Raman spectroscopy study of stress effects induced by silver nanoparticles in human mesenchymal stem cells (hMSCs). A high-sensitivity, high-resolution Raman Tweezers set-up has been used to monitor nanoparticle-induced biochemical changes in optically-trapped single cells. Our micro-Raman spectroscopic study reveals that hMSCs treated with silver nanoparticles undergo oxidative stress at doping levels in excess of 2 µg/ml, with results of a statistical analysis of Raman spectra suggesting that the induced stress becomes more dominant at nanoparticle concentration levels above 3 µg/ml.

Mechanochemistry of single red blood cells monitored using Raman tweezers

Two microparticles were biochemically attached to a red blood cell at diametrically opposite parts and held by optical traps allowing to impose deformations. The cell deformation was monitored from the microscopy images. Raman spectra of the cell under tunable deformations were studied. Vibrational spectra analysis at different stretching states was supported with two statistical methods. Principal Component Analysis distinguishes the most prominent changes in spectra while 2D correlation technique monitors the evolution of Raman bands during stretching. The measurements show significant changes in the cell chemical structure with stretching however the changes saturate above 20% of cell deformation. Mechanical deformation of the cell mainly affects the bands corresponding to hemoglobin but contributions from spectrin and membrane proteins can not be excluded. The saturation of bands at higher deformations suggests some structural relaxation that RBC has to undergo to bear extra load. The results confirm widely accepted belief that spectrin released from membrane proteins allows for significant shape changes of the cells. We therefore tentatively suggest that interaction between membrane and cytoskeleton during deformation can be efficiently probed by confocal Raman spectroscopy, in particular via the peak around 1035 cm(-1).

Analysis of single eukaryotic cells using Raman Tweezers

Raman Tweezers is a technique that combines optical trapping with Raman spectroscopy and has enabled the spectroscopic analysis of single cells. Applications of this technique include the identification and discrimination of different types of cells, including healthy and non-healthy cells (e.g. cancer cells). In addition, the interaction of cells with stimuli, e.g. drugs, can also be studied on a single-cell basis. Herein, a generic protocol for the analysis of fixed and living single eukaryotic cells is described, including the considerations required to build a Raman Tweezers systems.

Quantitative ratiometric discrimination between noncancerous and cancerous prostate cells based on neuropilin-1 overexpression

A multiplexed, ratiometric method is described that can confidently distinguish between cancerous and noncancerous epithelial prostate cells in vitro. The technique is based on bright surface-enhanced resonance Raman scattering (SERRS) biotags (SBTs) infused with unique Raman reporter molecules, and carrying cell-specific peptides. Two sets of SBTs were used. One targets the neuropilin-1 (NRP-1) receptors of cancer cells through the RPARPAR peptide. The other functions as a positive control (PC) and binds to both noncancerous and cancer cells through the HIV-derived TAT peptide. Point-by-point 2D Raman maps of the spatial distribution of the two tags were constructed with subcellular resolution from cells simultaneously incubated with the two sets of SBTs. Averaging the SERRS signal over a given cell yielded an NRP/PC ratio from which a robust quantitative measure of the overexpression of the NRP-1 by the cancer cell line was extracted. The use of a local, on-cell reference produces quantitative, statistically robust measures of overexpression independent of such sources of uncertainty as variations in the location of the focal plane, the local cell concentration, and turbidity.

Variability in Raman spectra of single human tumor cells cultured in vitro: correlation with cell cycle and culture confluency

In this work we investigate the capability of Raman microscopy (RM) to detect inherent sources of biochemically based spectral variability between single cells of a human tumor cell line (DU145) cultured in vitro. Principal component analysis (PCA) is used to identify differences in single-cell Raman spectra. These spectral differences correlate with (1) cell cycle progression and (2) changing confluency of a cell culture during the first 3 to 4 days after sub-culturing. Cell cycle regulatory drugs are used to synchronize the cell cycle progression of cell cultures, and flow cytometry is used to determine the cell cycle distribution of cell cultures at the time of Raman analysis. Spectral variability arising from cell cycle progression is (1) expressed as varying intensities of protein and nucleic acid features relative to lipid features, (2) well correlated with known biochemical changes in cells as they progress through the cell cycle, and (3) shown to be the most significant source of inherent spectral variability between cells. Furthermore, the specific biomolecules responsible for the observed spectral variability due to both cell cycle progression and changes in cell culture confluency can be identified in the first and second components of principal component analysis (PCA). Our characterization of the inherent sources of variability in Raman spectra of single human cells will be useful for understanding subtle spectral differences in RM studies of single cells.

Monitoring the healing of combat wounds using Raman spectroscopic mapping

Soldiers wounded in modern warfare present with extensive and complicated acute wounds, confounded by an overwhelming inflammatory response. The pathophysiology of acute wounds is unknown and timing of wound closure remains subjective. Collagen gene expression profiles are presented for 24 patients. Impaired healing wounds showed a twofold decrease in the up-regulation of COL1A1 and COL3A1 genes in the beginning of the wound healing process, compared with normal healing wounds. By the final debridement, however, collagen gene expression profiles for normal and impaired healing wounds were similar for COL1A1 and COL3A1. In addition, Raman spectroscopic maps were collected of biopsy tissue sections, from the first and last debridements of 10 wounds collected from nine patients. Tissue components obtained for the debridement biopsies were compared to elucidate whether or not a wound healed normally. Raman spectroscopy showed a loss of collagen in five patients, indicated by a negative percent difference in the 1,665/1,445 cm(-1) band area ratios. Four healed patients showed an increased or unchanged collagen content. Here, we demonstrate the potential of Raman spectroscopic analysis of wound biopsies for classification of wounds as normal or impaired healing. Raman spectroscopy has the potential to noninvasively monitor collagen deposition in the wound bed, during surgical wound debridements, to help determine the optimal time for wound closure.

Raman tweezers spectroscopy of live, single red and white blood cells

An optical trap has been combined with a Raman spectrometer to make high-resolution measurements of Raman spectra of optically-immobilized, single, live red (RBC) and white blood cells (WBC) under physiological conditions. Tightly-focused, near infrared wavelength light (1064 nm) is utilized for trapping of single cells and 785 nm light is used for Raman excitation at low levels of incident power (few mW). Raman spectra of RBC recorded using this high-sensitivity, dual-wavelength apparatus has enabled identification of several additional lines; the hitherto-unreported lines originate purely from hemoglobin molecules. Raman spectra of single granulocytes and lymphocytes are interpreted on the basis of standard protein and nucleic acid vibrational spectroscopy data. The richness of the measured spectrum illustrates that Raman studies of live cells in suspension are more informative than conventional micro-Raman studies where the cells are chemically bound to a glass cover slip.

Optical manipulation for single-cell studies

In the last decade optical manipulation has evolved from a field of interest for physicists to a versatile tool widely used within life sciences. This has been made possible in particular due to the development of a large variety of imaging techniques that allow detailed information to be gained from investigations of single cells. The use of multiple optical traps has high potential within single-cell analysis since parallel measurements provide good statistics. Multifunctional optical tweezers are, for instance, used to study cell heterogeneity in an ensemble, and force measurements are used to investigate the mechanical properties of individual cells. Investigations of molecular motors and forces on the single-molecule level have led to discoveries that would have been difficult to make with other techniques. Optical manipulation has prospects within the field of cell signalling and tissue engineering. When combined with microfluidic systems the chemical environment of cells can be precisely controlled. Hence the influence of pH, salt concentration, drugs and temperature can be investigated in real time. Fast advancing technical developments of automated and user-friendly optical manipulation tools and cross-disciplinary collaboration will contribute to the routinely use of optical manipulation techniques within the life sciences.

Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy

In this study we obtained Fourier transform infrared (FTIR) spectra of fixed prostate cell lines of differing types as well as the primary epithelial cells from benign prostatic hyperplasia (BPH). Results showed that by using multivariate chemometric analysis it was possible to discriminate and classify these cell lines, which gave rise to sensitivity and specificity values of >94% and >98%, respectively. Following on from these results the possible influences of different factors on the discrimination and classification of the prostate cell lines were examined. Firstly, the effect of using different growth media during cell culturing was investigated, with results indicating that this did not influence chemometric discrimination. Secondly, differences in the nucleus-to-cytoplasm (N/C) ratio were examined, and it was concluded that this factor was not the main reason for the discrimination and classification of the prostate cancer (CaP) cell lines. In conclusion, given the fact that neither growth media nor N/C ratio could totally explain the classification it is likely that actual biochemical differences between the cell lines is the major contributing factor.

Construction of an integrated Raman- and angular-scattering microscope

We report on the construction of a multimodal microscope platform capable of gathering both elastically and inelastically scattered light from a 38 mum(2) region in both epi- and transillumination geometries. Simultaneous monitoring of elastic and inelastic scattering from a microscopic region allows noninvasive characterization of the chemistry and morphology of a living sample without the need for exogenous dyes or labels, thus allowing measurements to be made longitudinally in time on the same sample as it evolves naturally. A sample is illuminated either from above or below with a focused 785 nm TEM(00) mode laser beam, with elastic and inelastic scattering collected by two separate measurement arms. The measurements may be made either simultaneously, if identical illumination geometries are used, or sequentially, if the two modalities utilize opposing illumination paths. In the inelastic arm, Stokes-shifted light is dispersed by a spectrograph onto a charge-coupled device (CCD) array. In the elastic scattering collection arm, a relay system images the microscope's back aperture onto a CCD array. Postprocessing of the inelastic scattering to remove fluorescence signals yields high quality Raman spectra that report on the sample's chemical makeup. Comparison of the elastically scattered pupil images to generalized Lorenz-Mie theory yields estimated size distributions of scatterers within the sample.

Classification of fixed urological cells using Raman tweezers

In this paper we report on preliminary investigations into using Raman tweezers to classify urological cell lines. This builds on earlier work within the group, whereby Raman tweezer methodologies were developed, and the application of this technique to differentiate between live prostate cancer (CaP) and bladder cells lines (PC-3 and MGH-U1 respectively) was demonstrated.In this present study we analysed chemically fixed cells using two different fixative methods; SurePath (a commercial available liquid based cytology media) and 4% v/v formalin/PBS fixatives. The study has been expanded from our previous live cell study to include the androgen sensitive CaP cell line LNCaP, primary benign prostate hyperplasia (BPH) cells as well as primary urethral cells. Raman light from the cells was collected using a 514.5 nm Ar-ion laser excitation source in back-scattering configuration mode.Principal component-linear discriminate analysis (PC-LDA) models of resulting cell spectra were generated and these were validated using a blind comparison. Sensitivities and specificities of > 72% and 90% respectively, for SurePath fixed cells, and > 93% and 98% respectively for 4% v/v formalin/PBS fixed cells was achieved. The higher prediction results for the formalin fixed cells can be attributed to a better signal-to-noise ratio for spectra obtained from these cells.Following on from this work, urological cell lines were exposed to urine for up to 12 hours to determine the effect of urine on the ability to classify these cells. Results indicate that urine has no detrimental effect on prediction results.