Evaluation of the potential of Raman microspectroscopy for prediction of chemotherapeutic response to cisplatin in lung adenocarcinoma

The study of the interaction of anticancer drugs with mammalian cells in vitro is important to elucidate the mechanisms of action of the drug on its biological targets. In this context, Raman spectroscopy is a potential candidate for high throughput, non-invasive analysis. To explore this potential, the interaction of cis-diamminedichloroplatinum(II) (cisplatin) with a human lung adenocarcinoma cell line (A549) was investigated using Raman microspectroscopy. The results were correlated with parallel measurements from the MTT cytotoxicity assay, which yielded an IC(50) value of 1.2 ± 0.2 μM. To further confirm the spectral results, Raman spectra were also acquired from DNA extracted from A549 cells exposed to cisplatin and from unexposed controls. Partial least squares (PLS) multivariate regression and PLS Jackknifing were employed to highlight spectral regions which varied in a statistically significant manner with exposure to cisplatin and with the resultant changes in cellular physiology measured by the MTT assay. The results demonstrate the potential of the cellular Raman spectrum to non-invasively elucidate spectral changes that have their origin either in the biochemical interaction of external agents with the cell or its physiological response, allowing the prediction of the cellular response and the identification of the origin of the chemotherapeutic response at a molecular level in the cell.     

Cisplatin-induced alteration on membrane composition of A549 cells revealed by ToF-SIMS

Cisplatin has been clinically used for treatment of solid tumors such as non–small-cell lung cancer for decades. However, tumor resistance may be acquired with losing the antitumor activity of cisplatin. As cellular membrane is the first barrier that cisplatin has to overcome before its further action inside the cells, the membrane composition must play a vital role in the cisplatin uptake and excretion, which further influences cisplatin sensitivity. In this work, we applied time-of-flight secondary ion mass spectrometry (ToF-SIMS) surface analysis combined with principle component analysis to distinguish the differences of cell membrane composition between non–small-cell lung cancer cells (A549) and its cisplatin resistant counterpart A549/DDP cells. The decreased phosphatidylcholine content and more abundant cholesterol were observed in the drug resistant cell surfaces, indicating the decreased membrane fluidity of A549/DDP cells. Moreover, we further compared membrane composition of A549 and A549/DDP cells after being treated with different concentrations of cisplatin. A higher composition level of proteins was discovered on all groups of A549/DDP cell membranes. The altered surface chemistry of cellular membranes induced by cisplatin indicates the significance of membrane structures in the drug resistance, which deserves further investigations to this regard.     

Finding relevant spectral regions between spectroscopic techniques by use of cross model validation and partial least squares regression

In this paper, we extend the concept of cross model validation (CMV) to multiple X and Y variables where different spectroscopic techniques serve as X and Y data in a regression context. For the first dataset on marzipan samples the main objective was to find significant regions in the spectral data, and to discuss the issue of false discovery, i.e. combinations of variables that erroneously are found to be significant. A permutation test within the framework of CMV showed that no regression coefficients in the partial least squares regression (PLSR) model between FT-IR and VIS/NIR spectra show significance at the 5% level. We believe the reason is that the CMV acts as strong filter towards spurious correlations. Corresponding CH- and OH-bands between FT-IR and NIR spectra gave significant regions. For the second dataset, the results from CMV are interpreted more in detail with chemical background knowledge in mind. Most of the significant regions found between the Raman and NIR spectra could be interpreted from the chemical composition of the oil mixtures. Some regions were more difficult to interpret, which could be due to systematic baseline effects in the NIR data.     

Imaging the cell wall of living single yeast cells using surface-enhanced Raman spectroscopy

The surface of a living yeast cell (Saccharomyces cerevisiae strain W303-1A) has been labeled with silver (Ag) nanoparticles that can form nanoaggregates which have been shown to have surface-enhanced Raman scattering (SERS) activity. The cell wall of a single living yeast cell has been imaged by use of a Raman microspectroscope. The SERS spectra measured from different Ag nanoaggregates were found to be different. This can be explained on the basis of detailed spectral interpretation. The SERS spectral response originates from mannoproteins which cover the outermost regions of the yeast cell wall. Analysis of SERS spectra from the cell wall and the extracted mannoproteins from the yeast has been performed for the clarification of variation in SERS spectra.     

Imaging live cells grown on a three dimensional collagen matrix using Raman microspectroscopy

Three dimensional collagen gels have been used as matrices for the imaging of live cells by Raman spectroscopy. The study is conducted on a human lung adenocarcinoma (A549) and a spontaneously immortalized human epithelial keratinocyte (HaCaT) cell line. The lateral resolution of the system has been estimated to be <1.5 μm making it possible to access the subcellular organization. Using K-means clustering analysis, it is shown that the different subcellular compartments of individual cells can be identified and differentiated. The biochemical specificity of the information contained in the Raman spectra allows the visualization of differences in the molecular signature of the different sub-cellular structures. Furthermore, to enhance the chemical information obtained from the spectra, principal component analysis has been employed, allowing the identification of spectral windows with a high variability. The comparison between the loadings calculated and spectra from pure biochemical compounds enables the correlation of the variations observed with the molecular content of the different cellular compartments.     

Label-free molecular imaging of immunological synapses between dendritic and T cells by Raman micro-spectroscopy

Confocal Raman micro-spectroscopy (CRMS) was used to measure spectral images of immunological synapse formation between dendritic and T cells without using molecular labels or other invasive procedures. The purpose-built inverted CRMS instrument integrated an environmental enclosure and a near-infrared laser to allow measurements on live cells maintained under physiological conditions. The integration of the wide-field fluorescence also enabled viability assays and direct comparison between Raman spectral images and gold-standard immuno-fluorescence images for specific molecules. Raman spectral images of nucleus and proteins were built by fuzzy c-mean clustering method. The Raman images were found to be in good correspondence with the immuno-fluorescence images of DNA and actin. These results indicate that actin is a main contributor to the Raman spectrum of the cytoplasm of dendritic and T cells. While for control cells the Raman spectral images of proteins indicated a more homogeneous distribution of proteins in the cytoplasm of dendritic cells, they indicated a higher accumulation of proteins at the immunological synapses when dendritic cells were pre-treated with laminin. These conclusions were also supported by confocal immuno-fluorescence imaging after cell fixation and labelling. This study demonstrates the potential of CRMS for label-free non-invasive imaging of junctions between live cells. Therefore, this technique may become a useful tool for studying cellular processes in live cells and where non-invasive molecular specific imaging is desirable, such as cell-cell interactions.     

The potential of Raman spectroscopy for characterisation of the fatty acid unsaturation of salmon

Raman spectroscopy has been evaluated for characterisation of the degree of fatty acid unsaturation (iodine value) of salmon (Salmo salar). The Norwegian Quality Cuts from 50 salmon samples were obtained, and the samples provided an iodine value range of 147.8-170.0 g I₂/100 g fat, reflecting a normal variation of farmed salmon. Raman measurements were performed both on different spots of the intact salmon muscle, on ground salmon samples as well as on oil extracts, and partial least squares regression (PLSR) was utilised for calibration. The oil spectra provided better iodine value predictions than the other data sets, and a correlation coefficient of 0.87 with a root mean square error of cross-validation of 2.5 g I₂/100 g fat was achieved using only one PLSR component. The ground samples provided comparable results, but at least two PLSR components were needed. Higher prediction errors were obtained from Raman spectra of intact salmon muscle, and this may partly be explained by sampling uncertainties in the relation between Raman measurements and reference analysis. All PLSR models obtained were based on chemically sound regression coefficients, and thus information regarding fatty acid unsaturation is readily available from Raman spectra even in systems with high contents of protein and water. The accuracy, the robustness and the low complexity of the PLSR models obtained suggest Raman spectroscopy as a promising method for rapid in-process control of the degree of unsaturation in salmon samples.     

Understanding the molecular information contained in principal component analysis of vibrational spectra of biological systems

K-means clustering followed by Principal Component Analysis (PCA) is employed to analyse Raman spectroscopic maps of single biological cells. K-means clustering successfully identifies regions of cellular cytoplasm, nucleus and nucleoli, but the mean spectra do not differentiate their biochemical composition. The loadings of the principal components identified by PCA shed further light on the spectral basis for differentiation but they are complex and, as the number of spectra per cluster is imbalanced, particularly in the case of the nucleoli, the loadings under-represent the basis for differentiation of some cellular regions. Analysis of pure bio-molecules, both structurally and spectrally distinct, in the case of histone, ceramide and RNA, and similarly in the case of the proteins albumin, collagen and histone, show the relative strong representation of spectrally sharp features in the spectral loadings, and the systematic variation of the loadings as one cluster becomes reduced in number. The more complex cellular environment is simulated by weighted sums of spectra, illustrating that although the loading becomes increasingly complex; their origin in a weighted sum of the constituent molecular components is still evident. Returning to the cellular analysis, the number of spectra per cluster is artificially balanced by increasing the weighting of the spectra of smaller number clusters. While it renders the PCA loading more complex for the three-way analysis, a pair wise analysis illustrates clear differences between the identified subcellular regions, and notably the molecular differences between nuclear and nucleoli regions are elucidated. Overall, the study demonstrates how appropriate consideration of the data available can improve the understanding of the information delivered by PCA.     

Quantitative multiplex CARS spectroscopy in congested spectral regions

A novel procedure is developed to describe and reproduce experimental coherent anti-Stokes Raman scattering (CARS) data, with particular emphasis on highly congested spectral regions. The approach, exemplified here with high-quality multiplex CARS data, makes use of spontaneous Raman scattering results. It is shown that the underlying vibrational Raman response can be retrieved from the multiplex CARS spectra, so that the Raman spectrum can be reconstituted, provided an adequate signal-to-noise ratio (SNR) is present in the experimental data and sufficient a priori knowledge of the vibrational resonances involved exists. The conversion of CARS to Raman data permits a quantitative interpretation of CARS spectra. This novel approach is demonstrated for highly congested multiplex CARS spectra of adenosine mono-, di-, and triphosphate (AMP, ADP, and ATP), nicotinamide adenine dinucleotide (NAD+), and small unilamellar vesicles (SUVs) of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). Quantitative determination of nucleotide concentrations and composition analysis in mixtures is demonstrated.     

Studying the Glycan Moiety of RNase B by Means of Raman and Raman Optical Activity

Raman and Raman optical activity (ROA) spectroscopy are used to study the solution‐phase structure of the glycan moiety of the protein ribonuclease B (RNase B). Spectral data of the intact glycan moiety of RNase B is obtained by subtracting high‐quality spectral data of RNase A, the non‐glycosylated form of the RNase, from the spectra of the glycoprotein. The remaining difference spectra are compared to spectra generated from Raman and ROA data of the constituent disaccharides of the RNase glycan, achieving convincing spectral overlap. The results show that ROA spectroscopy is able to extract detailed spectral data of the glycan moieties of proteins, provided that the non‐glycosylated isoform is available. Furthermore, good comparison between the full glycan spectrum and the regenerated spectra based on the disaccharide data lends great promise to ROA as a tool for the solution‐phase structural analysis of this structurally elusive class of biomolecules.     

Raman microscopy for the chemometric analysis of tumor cells

Raman spectroscopy is recognized as a tool for chemometric analysis of biological materials due to the high information content relating to specific physical and chemical qualities of the sample. Thirty cells belonging to two different prostatic cell lines, PNT1A (immortalized normal prostate cell line) and LNCaP (malignant cell line derived from prostate metastases), were mapped using Raman microscopy. A range of spectral preprocessing methods (partial least-squares discriminant analyses (PLSDAs), principal component analyses (PCAs), and adjacent band ratios (ABRs)) were compared for input into linear discriminant analysis to model and classify the two cell lines. PLSDA and ABR were able to correctly classify 100% of cells into benign and malignant groups, while PLSDA correctly classified a greater proportion of individual spectra. PCA was used to image the distribution of various biochemicals inside each cell and confirm differences in composition/distribution between benign and malignant cell lines. This study has demonstrated that PLSDAs and ABRs of Raman data can identify subtle differences between benign and malignant prostatic cells in vitro.     

Raman spectral imaging of single cancer cells: probing the impact of sample fixation methods

Raman spectroscopy has proven its potential for the analysis of cell constituents and processes. However, sample preparation methods compatible with clinical practice must be implemented for collection of accurate spectral information. This study aims at assessing, using micro-Raman imaging, the effects of some routinely used fixation methods such as formalin-fixation, formalin-fixation/air drying, cytocentrifugation, and air drying on intracellular spectral information. Data were compared with those acquired from single living cells. In parallel to these spectral information, cell morphological modifications that accompany sample preparation were compared. Spectral images of isolated cells were first analyzed in an unsupervised way using hierarchical cluster analysis (HCA), which allowed delimitation of the cellular compartments. The resulting nuclei cluster centers were compared and revealed at the molecular level that fixation induced changes in spectral information assigned to nucleic acids and proteins. In a second approach, a supervised fitting procedure using model spectra of DNA, RNA, and proteins, chemically extracted from living cells, revealed very small modifications at the level of the localization and quantification of these macromolecules. Finally, HCA and principal components analysis (PCA) performed on individual spectra randomly selected from the nuclear regions showed that formalin-fixation and cytocentrifugation are sample preparation methods that have little impact on the biochemical information as compared to living conditions. Any step involving cell air drying seems to accentuate the spectral deviations from the other preparation methods. It is therefore important in a future context of spectral cytology to take into account these variations.     

A decade of vibrational micro-spectroscopy of human cells and tissue (1994-2004)

Instrumentation used in infrared microspectroscopy (IR-MSP) permits the acquisition of spectra from samples as small as 100 pg (10(-10) g), and as small as 1 pg for Raman microspectroscopy (RA-MSP). This, in turn, allows the acquisition of spectral data from objects as small as fractions of human cells, and of small regions of microtome tissue sections. Since vibrational spectroscopy is exquisitely sensitive to the biochemical composition of the sample, and variations therein, it is possible to monitor metabolic processes in tissue and cells, and to construct spectral maps based on thousands of IR spectra collected from pixels of tissue. These images, in turn, reveal information on tissue structure, distribution of cellular components, metabolic activity and state of health of cells and tissue.     

PRIMARY PHOTOCHEMISTRY OF BACTERIORHODOPSIN: COMPARISON OF FOURIER TRANSFORM INFRARED DIFFERENCE SPECTRA WITH RESONANCE RAMAN SPECTRA

Abstract —Fourier transform infrared (FTIR) difference spectra of the BR→rK transition in bacteriorhodopsin at 77→K are compared with analogous resonance Raman difference spectra obtained using a spinning sample cell at 77→K. The vibrational frequencies observed in the FTIR spectra of native purple membrane and of purple membrane regenerated with 15-deuterioretinal are in good agreement with the frequencies observed in the Raman spectra, indicating that the lines in the FTIR difference spectra arise predominantly from retinal chromophore vibrations. This agreement confirms that the spinning cell method for obtaining resonance Raman spectra of K minimizes potential contributions from unwanted photoproducts. The unexpected similarity between the resonance Raman scattering intensities and the FTIR absorption intensities for BR and K is discussed in terms of the delocalized electronic structure of the chromophore. Finally, comparison of the Schiff base regions of the K Raman and FTIR spectra provide additional information on the assignment of its Schiff base vibration.     

A new series of titanocene dichloride derivatives bearing cyclic alkylammonium groups: Assessment of their cytotoxic properties

Ten new water soluble titanocene dichloride derivatives have been synthesized and characterized and their cytotoxicities against the human lung cancer cell line A549 have been assessed. The potencies of the compounds vary greatly, but dicationic 3-picolylium and 4-picolylium compounds exhibit IC₅₀ values that are unusually low for this class of compounds. In view of their potency against A549 cells, three of the new complexes were tested further on additional human cell lines including the small cell lung cancer cell line H69, the widely used cervical carcinoma cell line HeLa, the ovarian carcinoma cell line A2780 and its cisplatin resistant derivative A2780/CP. All three compounds exhibited potencies in all cell lines comparable to or better than those observed with the A549 cells, while one complex is actually more potent than cisplatin for HeLa cells.     

Aromatic amino acids providing characteristic motifs in the Raman and SERS spectroscopy of peptides

Raman and surface-enhanced Raman spectroscopies (SERS) are potentially important tools in the characterization of biomolecules such as proteins and DNA. In this work, SERS spectra of three cysteine-containing aromatic peptides: tryptophan-cysteine, tyrosine-cysteine, and phenylalanine-cysteine, bound to Au nanoshell substrates, were obtained, and compared to their respective normal Raman spectra. While the linewidths of the SERS peaks are significantly broadened (up to 70%), no significant spectral shifts (<6 cm (-1)) of the major Stokes modes were observed between the two modalities. We show that the Raman and SERS spectra of penetratin, a cell-penetrating peptide oligomer, can be comprised quite reliably from the spectra of its constituent aromatic amino acids except in the backbone regions where the spectral intensities are critically dependent on the length and conformations of the probed molecules. From this study we conclude that, together with protein backbone groups, aromatic amino acid residues provide the overwhelmingly dominant features in the Raman and SERS spectra of peptides and proteins when present. It follows that the Raman modes of these three small constructed peptides may likely apply to the assignment of Raman and SERS features in the spectra of other peptides and proteins.     

A near-infrared Fourier transform Raman spectroscopy of epidermal keratinocytes: changes in the protein-DNA structure following malignant transformation

We report here the use of near-infrared (NIR) Fourier transform (FT) Raman spectroscopy to analyze normal human epidermal keratinocytes prior to and following malignant transformation. Our analysis indicates specific Raman spectral differences between immortalized (HPK1A) and malignant ras transformed (HPK1A-ras) cells. In addition, striking spectral differences are seen in the DNA isolated from these cells and particularly in the 843/810 cm(-1) ratio with values of 1.6 +/- 0.13 in HPK1A cells and 0.68 +/- 0.09 in HPK1A-ras cells (mean +/- S.D., n = 12, P < 0.001) indicating specific alterations in the backbone conformation markers following malignant transformation. Subsequently, we analysed the effect of a strong inhibitor of keratinocyte growth, the Vitamin D analog EB1089, on the Raman spectra of intact cells and on the 843/810 cm(-1) ratio in the DNA isolated from both cell lines. Specific changes were observed in intact cells in the 1300-750 cm(-1) region. Furthermore, the 843/810 cm(-1) ratio of isolated DNA from HPK1A cells was not affected by EB1089 but significantly increased in DNA isolated from HPK1A-ras cells so much that it became closer to the value observed for HPK1A cells (1.07 +/- 0.10). Our data suggest that Raman analysis of DNA and in particular the 843/810 cm(-1) ratio can provide useful indices of malignant transformation and efficacy of anticancer agents.     

Blind image analysis for the compositional and structural characterization of plant cell walls

A new image analysis strategy is introduced to determine the composition and the structural characteristics of plant cell walls by combining Raman microspectroscopy and unsupervised data mining methods. The proposed method consists of three main steps: spectral preprocessing, spatial clustering of the image and finally estimation of spectral profiles of pure components and their weights. Point spectra of Raman maps of cell walls were preprocessed to remove noise and fluorescence contributions and compressed with PCA. Processed spectra were then subjected to k-means clustering to identify spatial segregations in the images. Cell wall images were reconstructed with cluster identities and each cluster was represented by the average spectrum of all the pixels in the cluster. Pure components spectra were estimated by spectral entropy minimization criteria with simulated annealing optimization. Two pure spectral estimates that represent lignin and carbohydrates were recovered and their spatial distributions were calculated. Our approach partitioned the cell walls into many sublayers, based on their composition, thus enabling composition analysis at subcellular levels. It also overcame the well known problem that native lignin spectra in lignocellulosics have high spectral overlap with contributions from cellulose and hemicelluloses, thus opening up new avenues for microanalyses of monolignol composition of native lignin and carbohydrates without chemical or mechanical extraction of the cell wall materials.     

Vibrational spectroscopy differentiates between multipotent and pluripotent stem cells

Over the last few years, there has been an increased interest in the study of stem cells in biomedicine for therapeutic use and as a source for healing diseased or injured organs/tissues. More recently, vibrational spectroscopy has been applied to study stem cell differentiation. In this study, we have used both synchrotron based FTIR and Raman microspectroscopies to assess possible differences between human pluripotent (embryonic) and multipotent (adult mesenchymal) stem cells, and how O(2) concentration in cell culture could affect the spectral signatures of these cells. Our work shows that infrared spectroscopy of embryonic (pluripotent) and adult mesenchymal (multipotent) stem cells have different spectral signatures based on the amount of lipids in their cytoplasm (confirmed with cytological staining). Furthermore, O(2) concentration in cell culture causes changes in both the FTIR and Raman spectra of embryonic stem cells. These results show that embryonic stem cells might be more sensitive to O(2) concentration when compared to mesenchymal stem cells. While vibrational spectroscopy could therefore be of potential use in identifying different populations of stem cells further work is required to better understand these differences.     

Investigation of the specificity of Raman spectroscopy in non-invasive blood glucose measurements

Although several in vivo blood glucose measurement studies have been performed by different research groups using near-infrared (NIR) absorption and Raman spectroscopic techniques, prospective prediction has proven to be a challenging problem. An important issue in this case is the demonstration of causality of glucose concentration to the spectral information, especially as the intrinsic glucose signal is smaller compared with that of the other analytes in the blood–tissue matrix. Furthermore, time-dependent physiological processes make the relation between glucose concentration and spectral data more complex. In this article, chance correlations in Raman spectroscopy-based calibration model for glucose measurements are investigated for both in vitro (physical tissue models) and in vivo (animal model and human subject) cases. Different spurious glucose concentration profiles are assigned to the Raman spectra acquired from physical tissue models, where the glucose concentration is intentionally held constant. Analogous concentration profiles, in addition to the true concentration profile, are also assigned to the datasets acquired from an animal model during a glucose clamping study as well as a human subject during an oral glucose tolerance test. We demonstrate that the spurious concentration profile-based calibration models are unable to provide prospective predictions, in contrast to those based on actual concentration profiles, especially for the physical tissue models. We also show that chance correlations incorporated by the calibration models are significantly less in Raman as compared to NIR absorption spectroscopy, even for the in vivo studies. Finally, our results suggest that the incorporation of chance correlations for in vivo cases can be largely attributed to the uncontrolled physiological sources of variations. Such uncontrolled physiological variations could either be intrinsic to the subject or stem from changes in the measurement conditions.