Multivariate analysis of Raman spectra for in vitro non-invasive studies of living cells

Establishing Monoclonal Gammopathy of Undetermined Significance as an Independent Pre-Disease State of Multiple Myeloma Using Raman Spectroscopy, Dynamical Network Biomarker Theory, and Energy Landscape Analysis

Multiple myeloma (MM) is a cancer of plasma cells. Normal (NL) cells are considered to pass through a precancerous state, such as monoclonal gammopathy of undetermined significance (MGUS), before transitioning to MM. In the present study, we acquired Raman spectra at three stages-834 NL, 711 MGUS, and 970 MM spectra-and applied the dynamical network biomarker (DNB) theory to these spectra. The DNB analysis identified MGUS as the unstable pre-disease state of MM and extracted Raman shifts at 1149 and 1527-1530 cm-1 as DNB variables. The distribution of DNB scores for each patient showed a significant difference between the mean values for MGUS and MM patients. Furthermore, an energy landscape (EL) analysis showed that the NL and MM stages were likely to become stable states. Raman spectroscopy, the DNB theory, and, complementarily, the EL analysis will be applicable to the identification of the pre-disease state in clinical samples.

Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy

Raman spectroscopy is a rapid analysis method of biological samples without labeling and destruction. At present, the commonly used Raman spectrum classification models include CNN, RNN, etc. The transformer has not been used for Raman spectrum identification. This paper introduces a new method of transformer combined with Raman spectroscopy to identify deep-sea cold seep microorganisms at the single-cell level. We collected the Raman spectra of eight cold seep bacteria, each of which has at least 500 spectra for the training of transformer model. We compare the transformer classification model with other deep learning classification models. The experimental results show that this method can improve the accuracy of microbial classification. Our average isolation level accuracy is more than 97%.

Granulocyte colony-stimulating factor promotes an aggressive phenotype of colon and breast cancer cells with biochemical changes investigated by single-cell Raman microspectroscopy and machine learning analysis

Granulocyte colony-stimulating factor (G-CSF) is produced at high levels in several cancers and is directly linked with metastasis in gastrointestinal (GI) cancers. In order to further understand the alteration of molecular compositions and biochemical features triggered by G-CSF treatment at molecular and cell levels, we sought to investigate the long term treatment of G-CSF on colon and breast cancer cells measured by label-free, non-invasive single-cell Raman microspectroscopy. Raman spectrum captures the molecule-specific spectral signatures ("fingerprints") of different biomolecules presented on cells. In this work, mouse breast cancer line 4T1 and mouse colon cancer line CT26 were treated with G-CSF for 7 weeks and subsequently analyzed by machine learning based Raman spectroscopy and gene/cytokine expression. The principal component analysis (PCA) identified the Raman bands that most significantly changed between the control and G-CSF treated cells. Notably, here we proposed the concept of aggressiveness score, which can be derived from the posterior probability of linear discriminant analysis (LDA), for quantitative spectral analysis of tumorigenic cells. The aggressiveness score was effectively applied to analyze and differentiate the overall cell biochemical changes of G-CSF-treated two model cancer cells. All these tumorigenic progressions suggested by Raman analysis were confirmed by pro-tumorigenic cytokine and gene analysis. A high correlation between gene expression data and Raman spectra highlights that the machine learning based non-invasive Raman spectroscopy offers emerging and powerful tools to better understand the regulation mechanism of cytokines in the tumor microenvironment that could lead to the discovery of new targets for cancer therapy.

Study on the biochemical mechanisms of the micro-wave ablation treatment of lung cancer by ex vivo confocal Raman microspectral imaging

As a highly invasive and the most prevalent malignancy, lung cancer remains the leading cause of cancer-associated mortality worldwide, especially in China. Microwave ablation (MWA) is an effective, safe, and the least invasive ablative treatment modality, which has been increasingly used for the management of unrespectable lung tumors. However, the underlying biochemical mechanisms of MWA treatment remain to be incompletely elucidated. Therefore, to illustrate the complex biochemical responses of lung squamous cell carcinoma (LSCC) to MWA treatment, confocal Raman micro-spectral imaging (CRMI) was applied in combination with multivariate analysis. A total of twelve LSCC tissues were acquired from patients undergoing clinical treatment, and their spectral characteristics were analyzed to determine significant spectral variations following cancer progression and MWA treatment in comparison with healthy lung tissues. Point-scanned Raman datasets were acquired from sectioned tissue samples in both pre-therapy (Pre-MWA group) and post-therapy groups (Post-MWA group) and further analyzed using K-means cluster analysis (KCA) and principal component analysis (PCA) to highlight the detailed compositional variations of the biochemical constituents. The spectral variations of essential amino acids (such as phenylalanine and tryptophan), collagen, and nucleic acids in the cancerous tissues of the Post-MWA group were significantly enhanced compared to those in the Pre-MWA group. The acquired information further confirmed a remarkable increase in the content of nucleic acid, protein, and lipid in the cancerous tissue following MWA treatment and, a comparative spectral imaging investigation indicated that MWA had no noticeable adverse effects on the paracancerous tissues. Thus, the findings not only illustrated the underlying biochemical variability in lung cancer during MWA treatment but also further confirmed the feasibility of a combined analytical procedure for assessing the biochemical responses during thermal ablation, which could be applied to prominently enhance the effectiveness of MWA in lung cancer treatment in clinical settings.

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.

Filter-Membrane-Based Ultrafiltration Coupled with Surface-Enhanced Raman Spectroscopy for Potential Differentiation of Benign and Malignant Thyroid Tumors from Blood Plasma

Objective

The objective of this study is to evaluate the performance and feasibility of surface-enhanced Raman spectroscopy coupled with a filter membrane and advanced multivariate data analysis on identifying and differentiating benign and malignant thyroid tumors from blood plasma.

Patients and Methods

We proposed a membrane filter SERS technology for the differentiation between benign thyroid tumor and thyroid cancer. That is to say, by using filter membranes with optimal pore size, the blood plasma samples from thyroid tumor patients were pretreated with the macromolecular proteins being filtered out prior to SERS measurement. The SERS spectra of blood plasma ultrafiltrate obtained using filter membranes from 102 patients with thyroid tumors (70 thyroid cancers and 32 benign thyroid tumors) were then analyzed and compared. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA), were performed on the SERS spectral data after background subtraction and normalization, as well as the first derivative processing, to analyze and compare the differential diagnosis of benign thyroid tumors and thyroid cancer.

Results

SERS measurements were performed in blood plasma acquired from a total of 102 thyroid tumor patients (benign thyroid tumor N=32; thyroid cancer N=70). By using filter membranes, the macromolecular proteins in blood plasma were effectively filtered out to yield high-quality SERS spectra. 84.3% discrimination accuracy between benign and malignant thyroid tumor was achieved using PCA-LDA method, while Lasso-PLS-DA yields a discrimination accuracy of 90.2%.

Conclusion

Our results demonstrate that SERS spectroscopy, coupled with ultrafiltration and multivariate analysis has the potential of providing a non-invasive, rapid, and objective detection and differentiation of benign and malignant thyroid tumors.

Label-free serum detection of Trichinella spiralis using surface-enhanced Raman spectroscopy combined with multivariate analysis

Based on blood serum surface-enhanced Raman spectroscopy (SERS) analysis, this paper proposed a simple and unlabeled non-invasive serum detection for T. spiralis infection. Serum samples were collected and analyzed from 40 rats at 0 days post infection (dpi) (normal rats), 19 uninfected rats, and 16 rats infected with T. spiralis at 28 dpi, using SERS measurements. Multivariate statistical techniques, such as linear discriminant analysis (LDA) and principal components analysis (PCA), were used to analyze and identify the obtained blood serum SERS spectra. The diagnosis algorithms, based on PCA-LDA, achieved a diagnostic sensitivity of 87.5%, a specificity of 94.7%, and an accuracy of 91.4% for separating the samples infected with T. spiralis from the control samples. This exploratory study demonstrated that colloidal Ag NPs-based SERS serum analysis technique combined with PCA-LDA has a great potential in improving the detection of T. spiralis infection and onsite screening.

Serum Raman spectroscopy as a diagnostic tool in patients with Huntington's disease

Huntington's disease is an inherited fatal progressive neurodegenerative disorder. A possible new Raman ‘spectral’ biomarker was identified that uses a tiny drop of patients' blood serum; thus can have immense diagnostic and therapeutic implications.

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an abnormal CAG expansion in exon 1 of the huntingtin (HTT) gene. Given its genetic basis it is possible to study patients both in the pre-manifest and manifest stages of the condition. While disease onset can be modelled using CAG repeat size, there are no easily accessible biomarkers that can objectively track disease progression. Here, we employed a holistic approach using spectral profiles generated using both surface-enhanced Raman spectroscopy (SERS) and Raman Spectroscopy (RS), on the serum of healthy participants and HD patients covering a wide spectrum of disease stages. We found that there was both genotype- and gender-specific segregation on using the full range in the fingerprint region with both SERS and RS. On a more detailed interrogation using specific spectral intervals, SERS revealed significant correlations with disease progression, in particular progression from pre-manifest through to advanced HD was associated with serum molecules related to protein misfolding and nucleotide catabolism. Thus, this study shows the potential of Raman spectroscopy-based techniques for stratification of patients and, of SERS, in particular, to track disease status through provision of ‘spectral’ biomarkers in HD, with clinical applications for other diseases and trials looking at disease modifying therapies.

Combined Raman and polarization sensitive holographic imaging for a multimodal label-free assessment of human sperm function

Raman microspectroscopy (RM) and polarization sensitive digital holographic imaging (PSDHI) are valuable analytical tools in biological and medical research, allowing the detection of both biochemical and morphological variations of the sample without labels or long sample preparation. Here, using this multi-modal approach we analyze in vitro human sperm capacitation and the acrosome reaction induced by heparin. The multimodal microscopy provides morphofunctional information that can assess the sperms ability to respond to capacitation stimuli (sperm function). More precisely, the birefringence analysis in sperm cells can be used as an indicator of its structural normality. Indeed, digital holography applied for polarization imaging allows for revelation of the polarization state of the sample, showing a total birefringence of the sperm head in non-reacted spermatozoa, and a birefringence localized in the post-acrosomal region in reacted spermatozoa. Additionally, RM allows the detection and spectroscopic characterization of protein/lipid delocalization in the plasma and acrosomal membranes that can be used as valuable Raman biomarkers of sperm function. Interestingly, these spectral variations can be correlated with different time phases of the cell capacitation response. Although further experimentation is required, the proposed multimodal approach could represent a potential label-free diagnostic tool for use in reproductive medicine and the diagnosis of infertility.

Raman Microscopy and Bone

Raman microscopy is a nondestructive technique requiring minimal sample preparation that can be used to measure the chemical properties of the mineral and collagen parts of bone simultaneously. Modern Raman instruments contain the necessary components and software to acquire the standard information required in most bone studies. The spatial resolution of the technique is about a micron. As it is nondestructive and small samples can be used, it forms a useful part of a bone characterization toolbox.

Microfluidic chip for non-invasive analysis of tumor cells interaction with anti-cancer drug doxorubicin by AFM and Raman spectroscopy

Raman spectroscopy has been playing an increasingly significant role for cell classification. Here, we introduce a novel microfluidic chip for non-invasive Raman cell natural fingerprint collection. Traditional Raman spectroscopy measurement of the cells grown in a Polydimethylsiloxane (PDMS) based microfluidic device suffers from the background noise from the substrate materials of PDMS when intended to apply as an in vitro cell assay. To overcome this disadvantage, the current device is designed with a middle layer of PDMS layer sandwiched by two MgF₂ slides which minimize the PDMS background signal in Raman measurement. Three cancer cell lines, including a human lung cancer cell A549, and human breast cancer cell lines MDA-MB-231 and MDA-MB-231/BRMS1, were cultured in this microdevice separately for a period of three days to evaluate the biocompatibility of the microfluidic system. In addition, atomic force microscopy (AFM) was used to measure the Young's modulus and adhesion force of cancer cells at single cell level. The AFM results indicated that our microchannel environment did not seem to alter the cell biomechanical properties. The biochemical responses of cancer cells exposed to anti-cancer drug doxorubicin (DOX) up to 24 h were assessed by Raman spectroscopy. Principal component analysis over the Raman spectra indicated that cancer cells untreated and treated with DOX can be distinguished. This PDMS microfluidic device offers a non-invasive and reusable tool for in vitro Raman measurement of living cells, and can be potentially applied for anti-cancer drug screening.

Raman spectroscopy and coherent anti-Stokes Raman scattering imaging: prospective tools for monitoring skeletal cells and skeletal regeneration

The use of skeletal stem cells (SSCs) for cell-based therapies is currently one of the most promising areas for skeletal disease treatment and skeletal tissue repair. The ability for controlled modification of SSCs could provide significant therapeutic potential in regenerative medicine, with the prospect to permanently repopulate a host with stem cells and their progeny. Currently, SSC differentiation into the stromal lineages of bone, fat and cartilage is assessed using different approaches that typically require cell fixation or lysis, which are invasive or even destructive. Raman spectroscopy and coherent anti-Stokes Raman scattering (CARS) microscopy present an exciting alternative for studying biological systems in their natural state, without any perturbation. Here we review the applications of Raman spectroscopy and CARS imaging in stem-cell research, and discuss the potential of these two techniques for evaluating SSCs, skeletal tissues and skeletal regeneration as an exemplar.

Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data

The spectral contaminants are inevitable during micro-Raman measurements. A key challenge is how to remove them from the original imaging data, since they can distort further results of data analysis. Here, we propose a method named “automatic pre-processing method for Raman imaging data set (APRI)”, which includes the adaptive iteratively reweighted penalized least-squares (airPLS) algorithm and the principal component analysis (PCA). It eliminates the baseline drifts and cosmic spikes by using the spectral features themselves. The utility of APRI is illustrated by removing the spectral contaminants from a Raman imaging data set of a wood sample. In addition, APRI is computationally efficient, conceptually simple and potential to be extended to other methods of spectroscopy, such as infrared (IR), nuclear magnetic resonance (NMR), X-Ray Diffraction (XRD). With the help of our approach, a typical spectral analysis can be performed by a non-specialist user to obtain useful information from a spectroscopic imaging data set.

Characterization of an evolved carotenoids hyper-producer of Saccharomyces cerevisiae through bioreactor parameter optimization and Raman spectroscopy

An evolutionary engineering approach for enhancing heterologous carotenoids production in an engineered Saccharomyces cerevisiae strain was used previously to isolate several carotenoids hyper-producers from the evolved populations. β-Carotene production was characterized in the parental and one of the evolved carotenoids hyper-producers (SM14) using bench-top bioreactors to assess the impact of pH, aeration, and media composition on β-carotene production levels. The results show that with maintaining a low pH and increasing the carbon-to-nitrogen ratio (C:N) from 8.8 to 50 in standard YNB medium, a higher β-carotene production level at 25.52 ± 2.15 mg β-carotene g−1 (dry cell weight) in the carotenoids hyper-producer was obtained. The increase in C:N ratio also significantly increased carotenoids production in the parental strain by 298 % [from 5.68 ± 1.24 to 22.58 ± 0.11 mg β-carotene g−1 (dcw)]. In this study, it was shown that Raman spectroscopy is capable of monitoring β-carotene production in these cultures. Raman spectroscopy is adaptable to large-scale fermentations and can give results in near real-time. Furthermore, we found that Raman spectroscopy was also able to measure the relative lipid compositions and protein content of the parental and SM14 strains at two different C:N ratios in the bioreactor. The Raman analysis showed a higher total fatty acid content in the SM14 compared with the parental strain and that an increased C:N ratio resulted in significant increase in total fatty acid content of both strains. The data suggest a positive correlation between the yield of β-carotene per biomass and total fatty acid content of the cell.

Characterization and Visualization of Vesicles in the Endo-Lysosomal Pathway with Surface-Enhanced Raman Spectroscopy and Chemometrics

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive vibrational fingerprinting technique widely used in analytical and biosensing applications. For intracellular sensing, typically gold nanoparticles (AuNPs) are employed as transducers to enhance the otherwise weak Raman spectroscopy signals. Thus, the signature patterns of the molecular nanoenvironment around intracellular unlabeled AuNPs can be monitored in a reporter-free manner by SERS. The challenge of selectively identifying molecular changes resulting from cellular processes in large and multidimensional data sets and the lack of simple tools for extracting this information has resulted in limited characterization of fundamental cellular processes by SERS. Here, this shortcoming in analysis of SERS data sets is tackled by developing a suitable methodology of reference-based PCA-LDA (principal component analysis-linear discriminant analysis). This method is validated and exemplarily used to extract spectral features characteristic of the endocytic compartment inside cells. The voluntary uptake through vesicular endocytosis is widely used for the internalization of AuNPs into cells, but the characterization of the individual stages of this pathway has not been carried out. Herein, we use reporter-free SERS to identify and visualize the stages of endocytosis of AuNPs in cells and map the molecular changes via the adaptation and advantageous use of chemometric methods in combination with tailored sample preparation. Thus, our study demonstrates the capabilities of reporter-free SERS for intracellular analysis and its ability to provide a way of characterizing intracellular composition. The developed analytical approach is generic and enables the application of reporter-free SERS to identify unknown components in different biological matrices and materials.

Identification and distinction of non-small-cell lung cancer cells by intracellular SERS nanoprobes

Combination of surface enhanced Raman scattering and multivariate statistical method allows to identify and distinguish three subtypes of non-small-cell lung cancer cells and leukocytes on the single-cell level.

In vitro biophysical, microspectroscopic and cytotoxic evaluation of metastatic and non-metastatic cancer cells in responses to anti-cancer drug

The Breast Cancer Metastasis Suppressor 1 (BRMS1) is a nucleo-cytoplasmic protein that suppresses cancer metastasis without affecting the growth of the primary tumor. Previous work has shown that it decreases the expression of protein mediators involved in chemoresistance. This study measured the biomechanical and biochemical changes in BRMS1 expression and the responses of BRMS1 to drug treatments on cancer cells in vitro. The results show that BRMS1 expression affects biomechanical properties by decreasing the Young's modulus and adhesion force of breast cancer cells after doxorubicin (DOX) exposure. Raman spectral bands corresponding to DNA/RNA, lipids and proteins were similar for all cells after DOX treatment. The expression of cytokines were similar for cancer cells after DOX exposure, although BRMS1 expression had different effects on the secretion of cytokines for breast cancer cells. The absence of significant changes on apoptosis, reactive oxygen species (ROS) expression and cell viability after BRMS1 expression shows that BRMS1 has little effect on cellular chemoresistance. Analyzing cancer protein expression is critical in evaluating therapeutics. Our study may provide evidence of the benefit of metastatic suppressor expression before chemotherapy.

Flexible Sheet-Type Sensor for Noninvasive Measurement of Cellular Oxygen Metabolism on a Culture Dish

A novel flexible sensor was developed for the noninvasive oxygen metabolism measurement of cultivated cells and tissues. This device is composed of a transparent double-layered polymer sheet of ethylene-vinyl alcohol (EVOH) and poly(dimethylsiloxane) (PDMS) having an array of microhole structures of 90 μm diameter and 50 μm depth on its surface. All the microhole structures were equipped with a 1-μm-thick optical chemical sensing layer of platinum porphyrin-fluoropolymer on their bottom. The three-dimensional microstructures of the sensor were fabricated by a newly developed simple and low-cost production method named self-aligned hot embossing. The device was designed to be attached slightly above the cells cultivated on a dish to form a temporarily closed microspace over the target cells during measurement. Since the change in oxygen concentration is relatively fast in the microcompartmentalized culture medium, a rapid evaluation of the oxygen consumption rate is possible by measuring the phosphorescence lifetime of the platinum porphyrin-fluoropolymer. The combined use of the device and an automated optical measurement system enabled the high-throughput sensing of cellular oxygen consumption (100 points/min). We monitored the oxygen metabolism of the human breast cancer cell line MCF7 on a Petri dish and evaluated the oxygen consumption rate to be 0.72 ± 0.12 fmol/min/cell. Furthermore, to demonstrate the utility of the developed sensing system, we demonstrated the mapping of the oxygen consumption rate of rat brain slices and succeeded in visualizing a clear difference among the layer structures of the hippocampus, i.e., the cornu ammonis (CA1 and CA3) and dentate gyrus (DG).

Enhanced interfacial adhesion and osteogenesis for rapid "bone-like" biomineralization by PECVD-based silicon oxynitride overlays

Structurally unstable fracture sites require metal fixative devices, which have long healing times due to their lack of osteoinductivity. Bioactive glass coatings lack in interfacial bonding, delaminate, and have reduced bioactivity due to the high temperatures used for their fabrication. Here, we test the hypothesis that low-temperature PECVD amorphous silica can enhance adhesion to the underlying metal surface and that N incorporation enhances osteogenesis and rapid biomineralization. A model Ti/TiO2-SiOx interface was formed by first depositing Ti onto Si wafers, followed by surface patterning, thermal annealing to form TiO2, and depositing SiOx/Si(ON)x overlays. TEM micrographs showed conformal SiOx layers on Ti/TiO2 overlays while XPS data revealed the formation of an elemental Ti-O-Si interface. Nanoscratch testing verified strong SiOx bonding with the underlying TiO2 layers. In vitro studies showed that the surface properties changed significantly to reveal the formation of hydroxycarbonate apatite within 6 h, and Si(ON)x surface chemistry induced osteogenic gene expression of human periosteal cells and led to a rapid "bone-like" biomineral formation within 4 weeks. XANES data revealed that the incorporation of N increased the surface HA bioactivity by increasing the carbonate to phosphate ratio. In conclusion, silicon oxynitride overlays on bone-implant systems enhance osteogenesis and biomineralization via surface nitrogen incorporation.

High resolution Raman spectroscopy mapping of stem cell micropatterns

We report on the use of high resolution Raman spectroscopy mapping combined with a micro-engineered stem cell platform. This technique obtains quantitative information about the concentration of individual intracellular molecules such as proteins, lipids, and other metabolites, while tightly controlling cell shape and adhesion. This new quantitative analysis will prove highly relevant for in vitro drug screening applications and regenerative medicine.

The future of bioactive ceramics

Two important worldwide needs must be satisfied in the future; (1) treatment of the deteriorating health of an aging population and, (2) decreasing healthcare costs to meet the needs of an increased population. The ethical and economic dilemma is how to achieve equality in quality of care while at the same time decreasing cost of care for an ever-expanding number of people. The limited lifetime of prosthetic devices made from first-generation nearly inert biomaterials requires new approaches to meet these two large needs. This paper advises an expanded emphasis on: (1) regeneration of tissues and (2) prevention of tissue deterioration to meet this growing need. Innovative use of bioactive ceramics with genetic control of in situ tissue responses offers the potential to achieve both tissue regeneration and prevention. Clinical success of use of bioactive glass for bone regeneration is evidence that this concept works. Likewise the use of micron sized bioactive glass powders in a dentifrice for re-mineralization of teeth provides evidence that prevention of tissue deterioration is also possible. This opinion paper outlines clinical needs that could be met by innovative use of bioactive glasses and ceramics in the near future; including: regeneration of skeletal tissues that is patient specific and genetic based, load-bearing bioactive glass-ceramics for skeletal and ligament and tendon repair, repair and regeneration of soft tissues, and rapid low-cost analysis of human cell-biomaterial interactions leading to patient specific diagnoses and treatments using molecularly tailored bioceramics.

Secondary ion mass spectrometry and Raman spectroscopy for tissue engineering applications

Identifying the matrix properties that permit directing stem cell fate is crucial for expanding desired cell lineages ex vivo for disease treatment. Such efforts require knowledge of matrix surface chemistry and the cell responses they elicit. Recent progress in analyzing biomaterial composition and identifying cell phenotype with two label-free chemical imaging techniques, TOF-SIMS and Raman spectroscopy are presented. TOF-SIMS is becoming indispensable for the surface characterization of biomaterial scaffolds. Developments in TOF-SIMS data analysis enable correlating surface chemistry with biological response. Advances in the interpretation of Raman spectra permit identifying the fate decisions of individual, living cells with location specificity. Here we highlight this progress and discuss further improvements that would facilitate efforts to develop artificial scaffolds for tissue regeneration.

Detection of methemoglobin in whole blood based on confocal micro-Raman spectroscopy and multivariate statistical techniques

Raman spectroscopy has been shown to have the potential for revealing oxygenated and spin ability of hemoglobin. In this study, confocal micro-Raman spectroscopy is developed to monitor the effect of sodium nitrite on oxyhemoglobin (HbO2 ) in whole blood. We observe that the band at 1,638 cm(-1) which is sensitive to the oxidation state decreases dramatically, while the 1,586 cm(-1) (low-spin state band) reduces both in methemoglobin (MetHb) and poisoning blood. Our results show that adding in sodium nitrite lead to the transition from HbO2 (Fe(2+) ) to MetHb (Fe(3+) ) in whole blood, and the iron atom converts from the low spin state to the high spin state with a delocalization from porphyrin plane. Moreover, multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) are employed to develop effective diagnostic algorithms for classification of spectra between pure blood and poisoning blood. The diagnostic algorithms based on PCA-LDA yield a diagnostic sensitivity of 100% and specificity of 100% for separating poisoning blood from normal blood. Receiver operating characteristic (ROC) curve further confirms the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this study demonstrate that Raman spectroscopy combined with PCA-LDA algorithms has tremendous potential for the non-invasive detection of nitrite poisoning blood.

Raman database of amino acids solutions: a critical study of extended multiplicative signal correction

The Raman spectra of biological materials always exhibit complex profiles, constituting several peaks and/or bands which arise due to the large variety of biomolecules. The extraction of quantitative information from these spectra is not a trivial task. While qualitative information can be retrieved from the changes in peaks frequencies or from the appearance/disappearance of some peaks, quantitative analysis requires an examination of peak intensities. Unfortunately in biological samples it is not easy to identify a reference peak for normalizing intensities, and this makes it very difficult to study the peak intensities. In the last decades a more refined mathematical tool, the extended multiplicative signal correction (EMSC), has been proposed for treating infrared spectra, which is also capable of providing quantitative information. From the mathematical and physical point of view, EMSC can also be applied to Raman spectra, as recently proposed. In this work the reliability of the EMSC procedure is tested by application to a well defined biological system: the 20 standard amino acids and their combination in peptides. The first step is the collection of a Raman database of these 20 amino acids, and subsequently EMSC processing is applied to retrieve quantitative information from amino acids mixtures and peptides. A critical review of the results is presented, showing that EMSC has to be carefully handled for complex biological systems.

Quantitative, label-free characterization of stem cell differentiation at the single-cell level by broadband coherent anti-Stokes Raman scattering microscopy

We use broadband coherent anti-Stokes Raman scattering (BCARS) microscopy to characterize lineage commitment of individual human mesenchymal stem cells cultured in adipogenic, osteogenic, and basal culture media. We treat hyperspectral images obtained by BCARS in two independent ways, obtaining robust metrics for differentiation. In one approach, pixel counts corresponding to functional markers, lipids, and minerals, are used to classify individual cells as belonging to one of the three lineage groups: adipocytes, osteoblasts, and undifferentiated stem cells. In the second approach, we use multivariate analysis of Raman spectra averaged exclusively over cytosol regions of individual cells to classify the cells into the same three groups, with consistent results. The exceptionally high speed of spectral imaging with BCARS allows us to chemically map a large number of cells with high spatial resolution, revealing not only the phenotype of individual cells, but also population heterogeneity in the degree of phenotype commitment.

Phenotypic profiling of antibiotic response signatures in Escherichia coli using Raman spectroscopy

Identifying the mechanism of action of new potential antibiotics is a necessary but time-consuming and costly process. Phenotypic profiling has been utilized effectively to facilitate the discovery of the mechanism of action and molecular targets of uncharacterized drugs. In this research, Raman spectroscopy was used to profile the phenotypic response of Escherichia coli to applied antibiotics. The use of Raman spectroscopy is advantageous because it is noninvasive, label free, and prone to automation, and its results can be obtained in real time. In this research, E. coli cultures were subjected to three times the MICs of 15 different antibiotics (representing five functional antibiotic classes) with known mechanisms of action for 30 min before being analyzed by Raman spectroscopy (using a 532-nm excitation wavelength). The resulting Raman spectra contained sufficient biochemical information to distinguish between profiles induced by individual antibiotics belonging to the same class. The collected spectral data were used to build a discriminant analysis model that identified the effects of unknown antibiotic compounds on the phenotype of E. coli cultures. Chemometric analysis showed the ability of Raman spectroscopy to predict the functional class of an unknown antibiotic and to identify individual antibiotics that elicit similar phenotypic responses. Results of this research demonstrate the power of Raman spectroscopy as a cellular phenotypic profiling methodology and its potential impact on antibiotic drug development research.

Methods and applications of Raman microspectroscopy to single-cell analysis

Raman spectroscopy is a powerful biochemical analysis technique that allows for the dynamic characterization and imaging of living biological cells in the absence of fluorescent stains. In this review, we summarize some of the most recent developments in the noninvasive biochemical characterization of single cells by spontaneous Raman scattering. Different instrumentation strategies utilizing confocal detection optics, multispot, and line illumination have been developed to improve the speed and sensitivity of the analysis of single cells by Raman spectroscopy. To analyze and visualize the large data sets obtained during such experiments, sophisticated multivariate statistical analysis tools are necessary to reduce the data and extract components of interest. We highlight the most recent applications of single cell analysis by Raman spectroscopy and their biomedical implications that have enabled the noninvasive characterization of specific metabolic states of eukaryotic cells, the identification and characterization of stem cells, and the rapid identification of bacterial cells. We conclude the article with a brief look into the future of this rapidly evolving research area.

Raman spectral analysis of nasopharyngeal carcinoma cell line CNE2 after microwave radiation

This study aimed to study the effects of microwave radiation on the nasopharyngeal carcinoma cell line CNE2 by Raman spectroscopy. The cells were separated into a control group and radiated groups with radiation times of 2, 5, 10, and 25 min, respectively. Both principal components analysis and support vector machine were employed for statistical analysis of Raman spectra. The results show that the relative content of C-H deformation and amide I begin to change when the radiation time is over 10 min, and principal components analysis further confirms there are significant differences after 10 min of radiation. Moreover, support vector machine is simultaneously used to classify radiated samples from control samples. The classification accuracy is low until the radiation time reaches over 10 min. In conclusion, this study reveals the Raman spectral characteristics of CNE2 under different microwave radiation exposure timesand demonstrates Raman spectroscopy can be a potential method to explore cellular characterization after radiation. The final results may help in elucidating the mechanism by which microwave radiation interacts with tumor cells.

Toxicity effects of short term diesel exhaust particles exposure to human small airway epithelial cells (SAECs) and human lung carcinoma epithelial cells (A549)

In this study, confocal Raman spectroscopy, atomic force microscope (AFM) and multiplex ELISA were applied to analyze the biophysical responses (biomechanics and biospectroscopy) of normal human primary small airway epithelial cells (SAECs) and human lung carcinoma epithelial A549 cells to in vitro short term DEP exposure (up to 2h). Raman spectra revealed the specific cellular biomolecular changes in cells induced by DEP compared to unexposed control cells. Principal component analysis was successfully applied to analyze spectral differences between control and treated groups from multiple individual cells, and indicated that cell nuclei are more sensitive than other cell locations. AFM measurements indicated that 2h of DEP exposure induced a significant decrease in cell elasticity and a dramatic change in membrane surface adhesion force. Cytokine and chemokine production measured by multiplex ELISA demonstrated DEP-induced inflammatory responses in both cell types.

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.

Raman microscopy of bone

Raman microscopy is a non-destructive technique requiring minimal sample preparation that can be used to measure the chemical properties of the mineral and collagen parts of bone simultaneously. Modern Raman instruments contain the necessary components and software to acquire the standard information required in most bone studies. The spatial resolution of the technique is about a micron. As it is non-destructive and small samples can be used, it forms a useful part of a bone characterisation toolbox.

Raman spectroscopy of primary bovine aortic endothelial cells: a comparison of single cell and cell cluster analysis

There are many techniques that allow in vitro interactions among cells and their environment to be monitored, including molecular, biochemical and immunochemical techniques. Traditional techniques for the analysis of cells often require fixation or lysis from substrates; however, use of such destructive methods is not feasible where the expanded cell cultures are required to be used for clinical implantation. Several studies have previously highlighted the potential of Raman spectroscopy to provide useful information on key biochemical markers within cells. As such, we highlight the capability of Raman spectroscopy with different laser spot sizes for use as a non-invasive, rapid, and specific method to perform in situ analysis of primary bovine aortic endothelial cells (BAECs). Raman spectra were collected from both individual live cells cultured on fused silica substrates and on clusters of live cells placed on fused silica substrates, measured at 532 and 785 nm. The results obtained show notable spectral differences in DNA/RNA region indicative of the relative cytoplasm and nucleus contributions. Raman spectra of cell clusters show slight variations in the intensity of the phenylalanine peak (1004 cm(-1)) indicating variations in protein contribution. These spectra also highlight contributions from other cellular components such as, proteins, lipids, nucleic acids and carbohydrates, respectively.

Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis

The capabilities of using gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) to obtain blood serum biochemical information for non-invasive colorectal cancer detection were presented in this paper. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Both empirical approach and multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and colorectal cancer serum. The empirical diagnostic algorithm based on the ratio of the SERS peak intensity at 725 cm(-1) for adenine to the peak intensity at 638 cm(-1) for tyrosine achieved a diagnostic sensitivity of 68.4% and specificity of 95.6%, whereas the diagnostic algorithms based on PCA-LDA yielded a diagnostic sensitivity of 97.4% and specificity of 100% for separating cancerous samples from normal samples. Receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

Needle stylet with integrated optical fibers for spectroscopic contrast during peripheral nerve blocks

The effectiveness of peripheral nerve blocks is highly dependent on the accuracy at which the needle tip is navigated to the target injection site. Even when electrical stimulation is utilized in combination with ultrasound guidance, determining the proximity of the needle tip to the target region close to the nerve can be challenging. Optical reflectance spectroscopy could provide additional information about tissues that is complementary to these navigation methods. We demonstrate a novel needle stylet for acquiring spectra from tissue at the tip of a commercial 20-gauge needle. The stylet has integrated optical fibers that deliver broadband light to tissue and receive scattered light. Two spectrometers resolve the light that is received from tissue across the wavelength range of 500-1600 nm. In our pilot study, measurements are acquired from a postmortem dissection of the brachial plexus of a swine. Clear differences are observed between spectra acquired from nerves and those acquired from adjacent tissue structures. We conclude that spectra acquired with the stylet have the potential to increase the accuracy with which peripheral nerve blocks are performed.

Raman spectroscopic monitoring of the osteogenic differentiation of human mesenchymal stem cells

The differentiation of stem cells into multi-lineages is essential to aid the development of tissue engineered materials that replicate the functionality of their tissue of origin. For this study, Raman spectroscopy was used to monitor the formation of a bone-like apatite mineral during the differentiation of human mesenchymal stem cells (hMSCs) towards an osteogenic lineage. Raman spectroscopy observed dramatic changes in the region dominated by the stretching of phosphate groups (950-970 cm(-1)) during the period of 7-28 days. Changes were also seen at 1030 cm(-1) and 1070 cm(-1), which are associated with the P-O symmetric stretch of PO(4)(3-) and the C-O vibration in the plane stretch of CO(3)(2-). Multivariate factor analysis revealed the presence of various mineral species throughout the 28 day culture period. Bone mineral formation was observed first at day 14 and was identified as a crystalline, non-substituted apatite. During the later stages of culture, different mineral species were observed, namely an amorphous apatite and a carbonate, substituted apatite, all of which are known to be Raman markers for a bone-like material. Band area ratios revealed that both the carbonate-to-phosphate and mineral-to-matrix ratios increased with age. When taken together, these findings suggest that the osteogenic differentiation of hMSCs at early stages resembles endochondral ossification. Due to the various mineral species observed, namely a disordered amorphous apatite, a B-type carbonate-substituted apatite and a crystalline non-substituted hydroxyapatite, it is suggested that the bone-like mineral observed here can be compared to native bone. This work demonstrates the successful application of Raman spectroscopy combined with biological and multivariate analyses for monitoring the various mineral species, degree of mineralisation and the crystallinity of hMSCs as they differentiate into osteoblasts.

Nonlinear optical imaging and Raman microspectrometry of the cell nucleus throughout the cell cycle

Fundamental understanding of cellular processes at molecular level is of considerable importance in cell biology as well as in biomedical disciplines for early diagnosis of infection and cancer diseases, and for developing new molecular medicine-based therapies. Modern biophotonics offers exclusive capabilities to obtain information on molecular composition, organization, and dynamics in a cell by utilizing a combination of optical spectroscopy and optical imaging. We introduce here a combination of Raman microspectrometry, together with coherent anti-Stokes Raman scattering (CARS) and two-photon excited fluorescence (TPEF) nonlinear optical microscopy, to study macromolecular organization of the nucleus throughout the cell cycle. Site-specific concentrations of proteins, DNA, RNA, and lipids were determined in nucleoli, nucleoplasmic transcription sites, nuclear speckles, constitutive heterochromatin domains, mitotic chromosomes, and extrachromosomal regions of mitotic cells by quantitative confocal Raman microspectrometry. A surprising finding, obtained in our study, is that the local concentration of proteins does not increase during DNA compaction. We also demonstrate that postmitotic DNA decondensation is a gradual process, continuing for several hours. The quantitative Raman spectroscopic analysis was corroborated with CARS/TPEF multimodal imaging to visualize the distribution of protein, DNA, RNA, and lipid macromolecules throughout the cell cycle.

Detection of doxorubicin-induced apoptosis of leukemic T-lymphocytes by laser tweezers Raman spectroscopy

Laser tweezers Raman spectroscopy (LTRS) was used to acquire the Raman spectra of leukemic T lymphocytes exposed to the chemotherapy drug doxorubicin at different time points over 72 hours. Changes observed in the Raman spectra were dependent on drug exposure time and concentration. The sequence of spectral changes includes an intensity increase in lipid Raman peaks, followed by an intensity increase in DNA Raman peaks, and finally changes in DNA and protein (phenylalanine) Raman vibrations. These Raman signatures are consistent with vesicle formation, cell membrane blebbing, chromatin condensation, and the cytoplasm of dead cells during the different stages of drug-induced apoptosis. These results suggest the potential of LTRS as a real-time single cell tool for monitoring apoptosis, evaluating the efficacy of chemotherapeutic treatments, or pharmaceutical testing.

Raman spectroscopy in head and neck cancer

In recent years there has been much interest in the use of optical diagnostics in cancer detection. Early diagnosis of cancer affords early intervention and greatest chance of cure. Raman spectroscopy is based on the interaction of photons with the target material producing a highly detailed biochemical 'fingerprint' of the sample. It can be appreciated that such a sensitive biochemical detection system could confer diagnostic benefit in a clinical setting. Raman has been used successfully in key health areas such as cardiovascular diseases, and dental care but there is a paucity of literature on Raman spectroscopy in Head and Neck cancer. Following the introduction of health care targets for cancer, and with an ever-aging population the need for rapid cancer detection has never been greater. Raman spectroscopy could confer great patient benefit with early, rapid and accurate diagnosis. This technique is almost labour free without the need for sample preparation. It could reduce the need for whole pathological specimen examination, in theatre it could help to determine margin status, and finally peripheral blood diagnosis may be an achievable target.

Identification and differentiation of single cells from peripheral blood by Raman spectroscopic imaging

Medical diagnosis can be improved significantly by fast, highly sensitive and quantitative cell identification from easily accessible body fluids. Prominent examples are disseminated tumor cells circulating in the peripheral blood of cancer patients. These cells are extremely rare and therefore difficult to detect. In this contribution we present the Raman spectroscopic characterization of different cells that can be found in peripheral blood such as leukocytes, leukemic cells and solid tumor cells. Leukocytes were isolated from the peripheral blood from healthy donors. Breast carcinoma derived tumor cells (MCF-7, BT-20) and myeloid leukaemia cells (OCI-AML3) were prepared from cell cultures. Raman images were collected from dried cells on calcium fluoride slides using 785 nm laser excitation. Unsupervised statistical methods (hierarchical cluster analysis and principal component analysis) were used to visualize spectral differences and cluster formation according to the cell type. With the help of supervised statistical methods (support vector machines) a classification model with 99.7% accuracy rates for the differentiation of the cells was built. The model was successfully applied to identify single cells from an independent mixture of cells based on their vibrational spectra. The classification was confirmed by fluorescence staining of the cells after the Raman measurement.