Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis

Infrared spectroscopic tissue imaging is a potentially powerful adjunct tool to current histopathology techniques. By coupling the biochemical signature obtained through infrared spectroscopy to the spatial information offered by microscopy, this technique can selectively analyze the chemical composition of different features of unlabeled, unstained tissue sections. In the past, the tissue features that have received the most interest were parenchymal and epithelial cells, chiefly due to their involvement in dysplasia and progression to carcinoma; however, the field has recently turned its focus toward stroma and areas of fibrotic change. These components of tissue present an untapped source of biochemical information that can shed light on many diverse disease processes, and potentially hold useful predictive markers for these same pathologies. Here we review the recent applications of infrared spectroscopic imaging to stromal and fibrotic regions of diseased tissue, and explore the potential of this technique to advance current capabilities for tissue analysis.     

Identification of B and T cells in human spleen sections by infrared microspectroscopic imaging.

BACKGROUND: Infrared spectroscopy probes the chemical composition and molecular structure of complex systems such as tissue and cells. Infrared spectroscopic imaging combines this spectral information with lateral resolution near the single-cell level. We analyzed whether this method is competitive with classic immunohistochemical methods for immunologic tissue and cells. METHODS: We recorded infrared microspectroscopic mapping datasets with a 90- x 90-microm2 aperture from a 3- x 3-mm2 unstained tissue area of human spleen. A secondary follicle containing a germinal center and a T zone were studied in more detail by infrared microspectroscopic imaging with lateral resolution near 5 mum. The results were compared with consecutive sections stained by immunoglobulin D antibodies. T and B lymphocytes were extracted from human blood and served as independent test samples. RESULTS: Cluster analysis of infrared datasets produced images that distinguished anatomical features such as primary and secondary follicles, T zones, arteries, and spleen red pulp. The assignments could be confirmed in consecutive sections by immunohistochemical staining. Main spectral variances between T and B lymphocytes in high-resolution measurements were attributed to specific spectral contributions of DNA and cytosol. CONCLUSIONS: Sensitivity and specificity of the infrared based methods are comparable to those of standard staining procedures for identification of B and T cells. However, infrared spectroscopic imaging can offer advantages in velocity, data throughput, and standardization because of minimal sample preparation. The results emphasize the potential of infrared spectroscopy as an innovative tool for the distinction of cell types, in particular in immunologic tissue.     

The use of optical spectroscopy in combinatorial chemistry.

Infrared and Raman spectroscopy allow direct spectral analysis of the solid-phase, thus avoiding the tedious cleavage of compounds from the solid support. With diagnostic bands in starting materials or products, infrared and Raman spectroscopy are efficient in monitoring each reaction step directly on the solid phase. Consequently, infrared and Raman spectroscopy have evolved as the premier analytical methodology for direct analysis on the solid support. While infrared transmission spectroscopy is a general analytical method for resin samples, internal reflection spectroscopy is especially suited for solid polymer substrates known as "pins" or "crowns." Single bead analysis is done best by infrared microspectroscopy, whereas photoacoustic spectroscopy allows totally nondestructive analysis of resin samples. With an automated accessory, diffuse reflection spectroscopy provides a method for high throughput on-bead monitoring of solid-phase reactions. Providing identification based on molecular structure, HPLC-FTIR is, therefore, complementary to LC-MS. Additionally, Raman spectroscopy as a complement to infrared spectroscopy can be applied to resin samples and-using a Raman microscope-to single beads. Fluorometry as an extremely sensitive spectroscopic detection method allows rapid quantification of organic reactions directly on the resin.     

The use of optical spectroscopy in combinatorial chemistry

Infrared and Raman spectroscopy allow direct spectral analysis of the solid‐phase, thus avoiding the tedious cleavage of compounds from the solid support. With diagnostic bands in starting materials or products, infrared and Raman spectroscopy are efficient in monitoring each reaction step directly on the solid phase. Consequently, infrared and Raman spectroscopy have evolved as the premier analytical methodology for direct analysis on the solid support. While infrared transmission spectroscopy is a general analytical method for resin samples, internal reflection spectroscopy is especially suited for solid polymer substrates known as “pins” or “crowns.” Single bead analysis is done best by infrared microspectroscopy, whereas photoacoustic spectroscopy allows totally nondestructive analysis of resin samples. With an automated accessory, diffuse reflection spectroscopy provides a method for high throughput on‐bead monitoring of solid‐phase reactions. Providing identification based on molecular structure, HPLC‐FTIR is, therefore, complementary to LC‐MS. Additionally, Raman spectroscopy as a complement to infrared spectroscopy can be applied to resin samples and—using a Raman microscope—to single beads. Fluorometry as an extremely sensitive spectroscopic detection method allows rapid quantification of organic reactions directly on the resin. © 1999 John Wiley & Sons, Inc. Biotechnol Bioeng (Comb Chem) 61:179–187, 1998/1999.     

Spectroscopic methods and their applicability for high‐throughput characterization of mammalian cell cultures in automated cell culture systems

The number and use of automated cell culture systems for mammalian cell culture are steadily increasing. Automated cell culture systems require miniaturized analytics with a high throughput to obtain as much information as possible from single experiments. Standard analytics commonly used for conventional bioreactor samples cannot handle the high throughput and the low sample volumes. Spectroscopic methods provide a means of meeting this analytical requirement and afford fast and direct access to process information. In the first part of this review, UV/VIS, fluorescence, Raman, near‐infrared, and mid‐infrared spectroscopy are presented. In the second part of the review, these spectroscopic methods are evaluated in terms of their applicability in the new field of mammalian cell culture processes in automated cell culture systems. Unlike standard bioreactors, these automated systems have special requirements that apply to the use of spectroscopic methods. Therefore, they are compared with regard to cell culture automation, throughput, and required sample volume.     

Infrared spectroscopy with multivariate analysis potentially facilitates the segregation of different types of prostate cell

The prostate gland is conventionally divided into zones or regions. This morphology is of clinical significance as prostate cancer (CaP) occurs mainly in the peripheral zone (PZ). We obtained tissue sets consisting of paraffin-embedded blocks of cancer-free transition zone (TZ) and PZ and adjacent CaP from patients (n = 6) who had undergone radical retropubic prostatectomy; a seventh tissue set of snap-frozen PZ and TZ was obtained from a CaP-free gland removed after radical cystoprostatectomy. Paraffin-embedded tissue slices were sectioned (10-mum thick) and mounted on suitable windows to facilitate infrared (IR) spectra acquisition before being dewaxed and air dried; cryosections were dessicated on BaF(2) windows. Spectra were collected employing synchrotron Fourier-transform infrared (FTIR) microspectroscopy in transmission mode or attenuated total reflection-FTIR (ATR) spectroscopy. Epithelial cell and stromal IR spectra were subjected to principal component analysis to determine whether wavenumber-absorbance relationships expressed as single points in "hyperspace" might on the basis of multivariate distance reveal biophysical differences between cells in situ in different tissue regions. After spectroscopic analysis, plotted clusters and their loadings curves highlighted marked variation in the spectral region containing DNA/RNA bands ( approximately 1490-1000 cm(-1)). By interrogating the intrinsic dimensionality of IR spectra in this small cohort sample, we found that TZ epithelial cells appeared to align more closely with those of CaP while exhibiting marked structural differences compared to PZ epithelium. IR spectra of PZ stroma also suggested that these cells are structurally more different to CaP than those located in the TZ. Because the PZ exhibits a higher occurrence of CaP, other factors (e.g., hormone exposure) may modulate the growth kinetics of initiated epithelial cells in this region. The results of this pilot study surprisingly indicate that TZ epithelial cells are more likely to exhibit what may be a susceptibility-to-adenocarcinoma spectral signature. Thus, IR spectroscopy on its own may not be sufficient to identify premalignant prostate epithelial cells most likely to progress to CaP.     

Early detection of ozone-induced hydroperoxides in epithelial cells by a novel infrared spectroscopic method

In the lower atmosphere ozone is a toxic and an unwanted oxidising pollutant causing injury to the airway epithelial cells by lipid peroxidation to yield products such as phospholipid hydroperoxides (PLHP). Measurements of PLHP, which are primary oxidation products, may reflect an early susceptibility of the target cell to oxidative stress. Biphasic cultures of bronchial epithelial cells (BEAS-2B) were exposed to ozone at environmentally relevant concentrations (0.1-1.0 ppm) for 4 and 12 h. Detection of PLHP was made using a novel technique based on fourier transform infrared spectroscopy (FTIR) in combination with high performance thin-layer chromatography (HPTLC). Six phospholipids were identified on the HPTLC plate; lysophosphatidylcholine (LPC), sphingomyelin (SM), phosphatidylcholine (PC), lysophosphatidylethanolamine (LPE), phosphatidylinositol (PI), and phosphatidylethanolamine (PE). From the FTIR spectra, O-O stretching of hydroperoxides was identified in the range 890-820 cm^-1. Multivariate data analysis revealed a positive correlation (r = 0.99 for 4 h exposure and r = 0.98 for 12 h exposure) between ozone exposure levels and the region of the FTIR-spectrum comprising the main wavelengths for hydroperoxides. These data support this alternative, versatile and novel spectroscopic approach for the early detection of ozone-mediated damage in human airway epithelial cells.     

Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging

Glandular tumors arising in epithelial cells comprise the majority of solid human cancers. Glands are supported by stroma, which is activated in the proximity of a tumor. Activated stroma is often characterized by the molecular expression of α-smooth muscle actin (α-SMA) within fibroblasts. However, the precise spatial and temporal evolution of chemical changes in fibroblasts upon epithelial tumor signaling is poorly understood. Here we report a label-free method to characterize fibroblast changes by using Fourier transform infrared spectroscopic imaging and comparing spectra with α-SMA expression in primary normal human fibroblasts. We recorded the fibroblast activation process by spectroscopic imaging using increasingly tissue-like conditions: 1), stimulation with the growth factor TGFβ1; 2), coculture with MCF-7 human breast cancerous epithelial cells in Transwell coculture; and 3), coculture with MCF-7 in three-dimensional cell culture. Finally, we compared the spectral signatures of stromal transformation with normal and malignant human breast tissue biopsies. The results indicate that this approach reveals temporally complex spectral changes and thus provides a richer assessment than simple molecular imaging based on α-SMA expression. Some changes are conserved across culture conditions and in human tissue, providing a label-free method to monitor stromal transformations.     

Vibrational spectroscopy-based quantification of liver steatosis

The liver plays a central role in lipid metabolism, and abnormal lipid accumulation in the liver is a key feature of Non-Alcoholic Fatty Liver Disease. In experimental studies, quantification of liver steatosis is commonly based on lipids staining or biochemical analysis. Here, we present a spectroscopic approach for quantitative analysis of the lipid content in the freeze-dried liver. The method is based on vibrational spectroscopy (Raman and infrared) measurements applied for Partial Least Squares (PLS) regression modeling. The obtained PLS models show a good correlation of the spectroscopic data with the reference histological evaluation of steatosis based on Oil Red O (ORO)-stained images of liver cross sections. Vibrational spectroscopy with PLS-based modeling described here represents a useful approach for the fast assessment of the liver steatosis in a small sample of freeze-dried liver tissue. In conclusion, our work demonstrates the easy-to-use method that can be applied in laboratory routine as a beneficial alternative to the established ORO staining.     

Focal plane array infrared imaging: a new way to analyse leaf tissue

* Here, a new approach to macromolecular imaging of leaf tissue using a multichannel focal plane array (FPA) infrared detector was compared with the proven method of infrared mapping with a synchrotron source, using transverse sections of leaves from a species of Eucalyptus. * A new histological method was developed, ideally suited to infrared spectroscopic analysis of leaf tissue. Spatial resolution and the signal-to-noise ratio of the FPA imaging and synchrotron mapping methods were compared. * An area of tissue 350 microm(2) required approx. 8 h to map using the synchrotron technique and approx. 2 min to image using the FPA. The two methods produced similar infrared images, which differentiated all tissue types in the leaves according to their macromolecular chemistry. * The synchrotron and FPA methods produced similar results, with the synchrotron method having superior signal-to-noise ratio and potentially better spatial resolution, whereas the FPA method had the advantage in terms of data acquisition time, expense and ease of use. FPA imaging offers a convenient, laboratory-based approach to microscopic chemical imaging of leaves.     

Infrared imaging microscopy of bone: Illustrations from a mouse model of Fabry disease

Bone is a complex tissue whose composition and properties vary with age, sex, diet, tissue type, health and disease. In this review, we demonstrate how infrared spectroscopy and infrared spectroscopic imaging can be applied to the study of these variations. A specific example of mice with Fabry disease (a lipid storage disease) is presented in which it is demonstrated that the bones of these young animals, while showing typical spatial variation in mineral content, mineral crystal size, and collagen maturity, do not differ from the bones of age- and sex-matched wild type animals.     

Infrared imaging microscopy of bone: illustrations from a mouse model of Fabry disease

Bone is a complex tissue whose composition and properties vary with age, sex, diet, tissue type, health and disease. In this review, we demonstrate how infrared spectroscopy and infrared spectroscopic imaging can be applied to the study of these variations. A specific example of mice with Fabry disease (a lipid storage disease) is presented in which it is demonstrated that the bones of these young animals, while showing typical spatial variation in mineral content, mineral crystal size, and collagen maturity, do not differ from the bones of age- and sex-matched wild type animals.     

Biologically inspired sensing: infrared spectroscopic analysis of cell responses to an inhalation health hazard

This work describes the development of a biologically based sensing technique to quantify chemical agents that pose inhalation health hazards. The approach utilizes cultured epithelial cells (A549 human type II pneumocytes) of the lung, exposed to potential toxins and monitored through the noninvasive means of infrared spectroscopy to quantify changes to cell physiology and function. Cell response to Streptolysin O, a cholesterol-binding cytolysin, is investigated here. Infrared spectra display changes in cell physiology indicative of membrane damage, altered proteins, and some nucleic acid damage. Methods to improve cell adhesion through modification of support surface properties are detailed. This spectroscopic approach not only provides a robust means to detect potential toxins but also provides information on modes of damage and mechanisms of cellular response.     

Spectroscopic characterization of microorganisms by Fourier transform infrared microspectroscopy

Spectroscopic fingerprints of bacteria were investigated by Fourier transform infrared (FTIR) microspectroscopy for the elucidation of chemical composition and structural information during growth. Good differentiation of six microorganisms was achieved down to the strain level. The inherent compositional and structural differences of cell envelopes and cytoplasm were investigated and utilized to obtain more detailed analysis of the spectroscopic features. Bands or regions of key functional groups were also identified in the original spectra. Microspectroscopic monitoring of bacterial growth demonstrated that FTIR spectroscopy cannot only provide molecular fingerprints of the cell envelope, but also compositional and metabolic information of the cytoplasm under different physiological conditions. This approach could be an effective alternative to traditional nutritional and biochemical methods to monitor and assess the effects of inhibitors and other environmental factors on microbial cell growth.     

Hierarchical band-target entropy minimization curve resolution and Pearson VII curve-fitting analysis of cellular protein infrared imaging spectra

A soft-modeling multivariate numerical approach that combines self-modeling curve resolution (SMCR) and mixed Lorentzian-Gaussian curve fitting was successfully implemented for the first time to elucidate spatially and spectroscopically resolved spectral information from infrared imaging data of oral mucosa cells. A novel variant form of the robust band-target entropy minimization (BTEM) SMCR technique, coined as hierarchical BTEM (hBTEM), was introduced to first cluster similar cellular infrared spectra using the unsupervised hierarchical leader-follower cluster analysis (LFCA) and subsequently apply BTEM to clustered subsets of data to reconstruct three protein secondary structure (PSS) pure component spectra—α-helix, β-sheet, and ambiguous structures—that associate with spatially differentiated regions of the cell infrared image. The Pearson VII curve-fitting procedure, which approximates a mixed Lorentzian-Gaussian model for spectral band shape, was used to optimally curve fit the resolved amide I and II bands of various hBTEM reconstructed PSS pure component spectra. The optimized Pearson VII band-shape parameters and peak center positions serve as means to characterize amide bands of PSS spectra found in various cell locations and for approximating their actual amide I/II intensity ratios. The new hBTEM methodology can also be potentially applied to vibrational spectroscopic datasets with dynamic or spatial variations arising from chemical reactions, physical perturbations, pathological states, and the like.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Quantitative,Architectural Analysis of Immune Cell Subsets in Tumor-Draining Lymph Nodes from Breast Cancer Patients and Healthy Lymph Nodes

Background

To date, pathological examination of specimens remains largely qualitative. Quantitative measures of tissue spatial features are generally not captured. To gain additional mechanistic and prognostic insights, a need for quantitative architectural analysis arises in studying immune cell-cancer interactions within the tumor microenvironment and tumor-draining lymph nodes (TDLNs).

Methodology/Principal Findings

We present a novel, quantitative image analysis approach incorporating 1) multi-color tissue staining, 2) high-resolution, automated whole-section imaging, 3) custom image analysis software that identifies cell types and locations, and 4) spatial statistical analysis. As a proof of concept, we applied this approach to study the architectural patterns of T and B cells within tumor-draining lymph nodes from breast cancer patients versus healthy lymph nodes. We found that the spatial grouping patterns of T and B cells differed between healthy and breast cancer lymph nodes, and this could be attributed to the lack of B cell localization in the extrafollicular region of the TDLNs.

Conclusions/Significance

Our integrative approach has made quantitative analysis of complex visual data possible. Our results highlight spatial alterations of immune cells within lymph nodes from breast cancer patients as an independent variable from numerical changes. This opens up new areas of investigations in research and medicine. Future application of this approach will lead to a better understanding of immune changes in the tumor microenvironment and TDLNs, and how they affect clinical outcomes.