BCAbox Algorithm Expands Capabilities of Raman Microscope for Single Organelles Assessment.
ABSTRACT: Raman microspectroscopy is a rapidly developing technique, which has an unparalleled potential for in situ proteomics, lipidomics, and metabolomics, due to its remarkable capability to analyze the molecular composition of live cells and single cellular organelles. However, the scope of Raman spectroscopy for bio-applications is limited by a lack of software tools for express-analysis of biomolecular composition based on Raman spectra. In this study, we have developed the first software toolbox for immediate analysis of intracellular Raman spectra using a powerful biomolecular component analysis (BCA) algorithm. Our software could be easily integrated with commercial Raman spectroscopy instrumentation, and serve for precise analysis of molecular content in major cellular organelles, including nucleoli, endoplasmic reticulum, Golgi apparatus, and mitochondria of either live or fixed cells. The proposed software may be applied in broad directions of cell science, and serve for further advancement and standardization of Raman spectroscopy.
Project description:Recent developments in Raman spectroscopy instrumentation and data processing algorithms have led to the emergence of Ramanomics - an independent discipline with unprecedented capabilities to map the distribution of distinct molecular groups in live cells. Here, we introduce a method for probing the absolute concentrations of proteins, RNA and lipids in single organelles of live cultured cells by biomolecular component analysis using microRaman data. We found significant cell-to-cell variations in the molecular profiles of organelles, thus providing a physiologically relevant set of markers of cellular heterogeneity. At the same cell the molecular profiles of different organelles can strongly correlate, reflecting tight coordination of their functions. This correlation was significant in WI-38 diploid fibroblasts and weak in HeLa cells, indicating profound differences in the regulation of biochemical processes in these cell lines.
Project description:To advance an understanding of cellular regulation and function it is crucial to identify molecular contents in cellular organelles, which accommodate specific biochemical processes. Toward achievement of this goal, we applied micro-Raman-Biomolecular Component Analysis assay for molecular profiling of major organelles in live cells. We used this assay for comparative analysis of proteins 3D conformation and quantification of proteins, RNA, and lipids concentrations in nucleoli, endoplasmic reticulum, and mitochondria of WI 38 diploid lung fibroblasts and HeLa cancer cells. Obtained data show substantial differences in the concentrations and conformations of proteins in the studied organelles. Moreover, differences in the intraorganellar concentrations of RNA and lipids between these cell lines were found. We report the biological significance of obtained macromolecular profiles and advocate for micro-Raman BCA assay as a valuable proteomics tool.
Project description:Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures.
Project description:Raman Microspectroscopy represents an innovative tool for the assessment of sperm biochemical features otherwise undetectable by routine semen analysis. Previously, it was shown that induced DNA damage can be detected in smeared sperm by this technique. This novel readout may be of value for clinical settings especially if it can be transferred to living cells. Yet, starting with living sperms this study was carried-out using a variety of conditions to disclose the Raman features of sperm nuclei under different hydration conditions and UV exposure. Human sperm were immobilized and Raman spectra were obtained from individual sperm as repeated measurements. To create conditions with controlled DNA damage, sperm samples were exposed to ultraviolet light. Several media were used to evaluate their effect on Raman spectra in aqueous conditions. To substantiate differences between the experimental conditions, the spectra were analyzed by Principal Component Analysis. We observed that spectra of sperm nuclei obtained in different solutions showed a qualitatively unchanged spectral pattern showing the principal signals related to DNA. Evaluating the effect of ultraviolet light generated the finding that spectra representing DNA damage were only observed in dry conditions but not in aqueous medium. Thus, Raman microspectroscopy was successfully applied for sperm analysis in different conditions, among them in live spermatozoa in aqueous solution during the initial measurement, revealing the principle use of this technique. However, implementation of Raman spectroscopy as a technique for clinical sperm analysis and selection may be especially relevant when DNA evaluation can be established using live sperm.
Project description:Breast cancer is the most prevalent cause of cancer-associated death in women the world over, but if detected early it can be treated successfully. Therefore, it is important to diagnose this disease at an early stage and to understand the biochemical changes associated with cellular transformation and cancer progression. Deregulated lipid metabolism has been shown to contribute to cell transformation as well as cancer progression. In this study, we monitored the biomolecular changes associated with the transformation of a normal cell into an invasive cell associated with breast cancer using Raman microspectroscopy. We have utilized primary normal breast cells, and immortalized, transformed, non-invasive, and invasive breast cancer cells. The Raman spectra were acquired from all these cell lines under physiological conditions. The higher wavenumber (2800-3000 cm-1) and lower wavenumber (700-1800 cm-1) range of the Raman spectrum were analyzed and we observed increased lipid levels for invasive cells. The Raman spectral data were analyzed by principal component-linear discriminant analysis (PC-LDA), which resulted in the formation of distinct clusters for different cell types with a high degree of sensitivity. The subsequent testing of the PC-LDA analysis via the leave-one-out cross validation approach (LOOCV) yielded relatively high identification sensitivity. Additionally, the Raman spectroscopic results were confirmed through fluorescence staining tests with BODIPY and Nile Red biochemical assays. Furthermore, Raman maps from the above mentioned cells under fixed conditions were also acquired to visualize the distribution of biomolecules throughout the cell. The present study shows the suitability of Raman spectroscopy as a non-invasive, label-free, microspectroscopic technique, having the potential of probing changes in the biomolecular composition of living cells as well as fixed cells.
Project description:Confocal Raman microspectroscopy was used to study the interaction between pulsed electric fields and live cells from a molecular point of view in a non-invasive and label-free manner. Raman signatures of live human adipose-derived mesenchymal stem cells exposed or not to pulsed electric fields (8 pulses, 1 000?V/cm, 100??s, 1?Hz) were acquired at two cellular locations (nucleus and cytoplasm) and two spectral bands (600-1 800?cm-1 and 2 800-3 100?cm-1). Vibrational modes of proteins (phenylalanine and amide I) and lipids were found to be modified by the electropermeabilization process with a statistically significant difference. The relative magnitude of four phenylalanine peaks decreased in the spectra of the pulsed group. On the contrary, the relative magnitude of the amide I band at 1658?cm-1 increased by 40% when comparing pulsed and control group. No difference was found between the control and the pulsed group in the high wavenumber spectral band. Our results reveal the modification of proteins in living cells exposed to pulsed electric fields by means of confocal Raman microspectroscopy.
Project description:Triacetylfusarinine C (TAFC) is a siderophore produced by certain fungal species and might serve as a highly useful biomarker for the fast diagnosis of invasive aspergillosis. Due to its renal elimination, the biomarker is found in urine samples of patients suffering from Aspergillus infections. Accordingly, non-invasive diagnosis from this easily obtainable body fluid is possible. Within our contribution, we demonstrate how Raman microspectroscopy enables a sensitive and specific detection of TAFC. We characterized the TAFC iron complex and its iron-free form using conventional and interference-enhanced Raman spectroscopy (IERS) and compared the spectra with the related compound ferrioxamine B, which is produced by bacterial species. Even though IERS only offers a moderate enhancement of the Raman signal, the employment of respective substrates allowed lowering the detection limit to reach the clinically relevant range. The achieved limit of detection using IERS was 0.5 ng of TAFC, which is already well within the clinically relevant range. By using an extraction protocol, we were able to detect 1.4 ?g/mL TAFC via IERS from urine within less than 3 h including sample preparation and data analysis. We could further show that TAFC and ferrioxamine B can be clearly distinguished by means of their Raman spectra even in very low concentrations.
Project description:<h4>Background</h4>Analysis of pollen grains reveals valuable information on biology, ecology, forensics, climate change, insect migration, food sources and aeroallergens. Vibrational (infrared and Raman) spectroscopies offer chemical characterization of pollen via identifiable spectral features without any sample pretreatment. We have compared the level of chemical information that can be obtained by different multiscale vibrational spectroscopic techniques.<h4>Methodology</h4>Pollen from 15 different species of Pinales (conifers) were measured by seven infrared and Raman methodologies. In order to obtain infrared spectra, both reflectance and transmission measurements were performed on ground and intact pollen grains (bulk measurements), in addition, infrared spectra were obtained by microspectroscopy of multigrain and single pollen grain measurements. For Raman microspectroscopy measurements, spectra were obtained from the same pollen grains by focusing two different substructures of pollen grain. The spectral data from the seven methodologies were integrated into one data model by the Consensus Principal Component Analysis, in order to obtain the relations between the molecular signatures traced by different techniques.<h4>Results</h4>The vibrational spectroscopy enabled biochemical characterization of pollen and detection of phylogenetic variation. The spectral differences were clearly connected to specific chemical constituents, such as lipids, carbohydrates, carotenoids and sporopollenins. The extensive differences between pollen of Cedrus and the rest of Pinaceae family were unambiguously connected with molecular composition of sporopollenins in pollen grain wall, while pollen of Picea has apparently higher concentration of carotenoids than the rest of the family. It is shown that vibrational methodologies have great potential for systematic collection of data on ecosystems and that the obtained phylogenetic variation can be well explained by the biochemical composition of pollen. Out of the seven tested methodologies, the best taxonomical differentiation of pollen was obtained by infrared measurements on bulk samples, as well as by Raman microspectroscopy measurements of the corpus region of the pollen grain. Raman microspectroscopy measurements indicate that measurement area, as well as the depth of focus, can have crucial influence on the obtained data.
Project description:Detailed studies of lipids in biological systems, including their role in cellular structure, metabolism, and disease development, comprise an increasingly prominent discipline called lipidomics. However, the conventional lipidomics tools, such as mass spectrometry, cannot investigate lipidomes until they are extracted, and thus they cannot be used for probing the lipid distribution nor for studying in live cells. Furthermore, conventional techniques rely on the lipid extraction from relatively large samples, which averages the data across the cellular populations and masks essential cell-to-cell variations. Further advancement of the discipline of lipidomics critically depends on the capability of high-resolution lipid profiling in live cells and, potentially, in single organelles. Here we report a micro-Raman assay designed for single-organelle lipidomics. We demonstrate how Raman microscopy can be used to measure the local intracellular biochemical composition and lipidome hallmarks-lipid concentration and unsaturation level, cis/trans isomer ratio, sphingolipids and cholesterol levels in live cells-with a sub-micrometer resolution, which is sufficient for profiling of subcellular structures. These lipidome data were generated by a newly developed biomolecular component analysis software, which provides a shared platform for data analysis among different research groups. We outline a robust, reliable, and user-friendly protocol for quantitative analysis of lipid profiles in subcellular structures. This method expands the capabilities of Raman-based lipidomics toward the analysis of single organelles within either live or fixed cells, thus allowing an unprecedented measure of organellar lipid heterogeneity and opening new quantitative ways to study the phenotypic variability in normal and diseased cells.
Project description:Coherent Raman microspectroscopy imaging is an emerging technique for noninvasive, chemically specific optical imaging, which can be potentially used to analyze the chemical composition and its distribution in biological tissues. In this report, a hierarchical cluster analysis was applied to hyperspectral coherent anti-Stokes Raman imaging of different chemical species through a turbid medium. It was demonstrated that by using readily available commercial software (Cytospec, Inc.) and cluster analysis, distinct chemical species can be imaged and identified through a rather thick layer of scattering medium. Once the clusters of different chemical composition were distinguished, a phase retrieval algorithm was used to convert coherent anti-Stokes Raman spectra to Raman spectra, which were used for chemical identification of hidden microscopic objects. In particular, applications to remote optical sensing of potential biological threats and to imaging through a layer of skin tissue were successfully demonstrated.