Raman imaging-based phenotyping of murine primary endothelial cells to identify disease-associated biochemical alterations

Prediction of cardiac differentiation in human induced pluripotent stem cell-derived cardiomyocyte supernatant using surface-enhanced Raman spectroscopy and machine learning

The efficient manufacturing of cardiomyocytes from human-induced pluripotent stem cells (hiPSCs) is essential for advancing regenerative therapies for myocardial injuries. However, ensuring cell quality during production is challenging since traditional methods are invasive, destructive, and time-consuming. In this study, we monitored cardiomyocyte differentiation of WTC11 hiPSCs by analyzing conditioned media collected at various stages using Raman spectroscopy, multivariate analysis, and machine learning. Differentiation efficiency was confirmed via flow cytometry and immunostaining. Raman spectra were processed using standard normal variate and second derivative transformations before performing a principal component analysis (PCA) and machine learning (Random Forest, K-Nearest Neighbors, and Deep Neural Networks [DNN]). Results show that PCA was unable to distinguish cells based on differentiation stages, while machine learning could reliably predict cell differentiation early in the cardiac cell manufacturing process. DNN models achieved accuracies exceeding 82 % in predicting differentiation, highlighting their potential as quality control tools. These findings underscore the potential of Raman spectroscopy coupled with machine learning as a tool for real-time monitoring of cardiomyocyte production.

Heterogeneity of Endothelial Cells Impacts the Functionality of Human Pancreatic In Vitro Models

Endothelial cells (ECs) play a crucial role in maintaining tissue homeostasis and functionality. Depending on their tissue of origin, ECs can be highly heterogeneous regarding their morphology, gene and protein expression, functionality, and signaling pathways. Understanding the interaction between organ-specific ECs and their surrounding tissue is therefore critical when investigating tissue homeostasis, disease development, and progression. In vitro models often lack organ-specific ECs, potentially limiting the translatability and validity of the obtained results. The goal of this study was to assess the differences between commonly used EC sources in tissue engineering applications, including human umbilical vein ECs (HUVECs), human dermal microvascular ECs (hdmvECs), and human foreskin microvascular ECs (hfmvECs), and organ-specific human pancreatic microvascular ECs (hpmvECs), and test their impact on functionality within an in vitro pancreas test system used for diabetes research. Utilizing high-resolution Raman microspectroscopy and Raman imaging in combination with established protein and gene expression analyses and exposure to defined physical signals within microfluidic cultures, we identified that ECs exhibit significant differences in their biochemical composition, relevant protein expression, angiogenic potential, and response to the application of mechanical shear stress. Proof-of-concept results showed that the coculture of isolated human islets of Langerhans with hpmvECs significantly increased the functionality when compared with control islets and islets cocultured with HUVECs. Our study demonstrates that the choice of EC type significantly impacts the experimental results, which needs to be considered when implementing ECs into in vitro models.

Cardiac multiscale bioimaging: from nano- through micro- to mesoscales

Cardiac multiscale bioimaging is an emerging field that aims to provide a comprehensive understanding of the heart and its functions at various levels, from the molecular to the entire organ. It combines both physiologically and clinically relevant dimensions: from nano- and micrometer resolution imaging based on vibrational spectroscopy and high-resolution microscopy to assess molecular processes in cardiac cells and myocardial tissue, to mesoscale structural investigations to improve the understanding of cardiac (patho)physiology. Tailored super-resolution deep microscopy with advanced proteomic methods and hands-on experience are thus strategically combined to improve the quality of cardiovascular research and support future medical decision-making by gaining additional biomolecular information for translational and diagnostic applications.

Molecular tracking of interactions between progenitor and endothelial cells via Raman and FTIR spectroscopy imaging: a proof of concept of a new analytical strategy for in vitro research

Circulating endothelial cell progenitors originating from the bone marrow are considered to be a powerful tool in the repair of endothelium damage. Due to their unique properties, endothelial progenitors are now broadly investigated to assess their clinical significance in diseases e.g., associated with brain endothelial dysfunction. However, their distinction in terms of the expression of specific markers remains ambiguous. Additionally, endothelial progenitor cells may change their repertoire of markers depending on the microenvironment of the tissue in which they are currently located. Here, we applied the label-free Raman and FTIR imaging to discriminate mice brain endothelium and endothelial progenitors. Cells cultured separately showed distinctly different spectral signatures extracted from the whole cellular interior as well as the detected intracellular compartments (nucleus, cytoplasm, perinuclear area, and lipid droplets). Then, we used these spectroscopic signals to examine the cells co-cultured for 24 h. Principal cluster analysis showed their grouping with the progenitor cells and segregation from brain endothelium at a level of the entire cell machinery (in FTIR images) which resulted from biochemical alternations in the cytoplasm and lipid droplets (in Raman images). The models included in partial least square regression indicated that lipid droplets are the key element for the classification of endothelial progenitor-brain endothelial cells interactions.

Multispectral Raman Differentiation of Malignant Skin Neoplasms In Vitro: Search for Specific Biomarkers and Optimal Wavelengths

Confocal scanning Raman and photoluminescence (PL) microspectroscopy is a structure-sensitive optical method that allows the non-invasive analysis of biomarkers in the skin tissue. We used it to perform in vitro diagnostics of different malignant skin neoplasms at several excitation wavelengths (532, 785 and 1064 nm). Distinct spectral differences were noticed in the Raman spectra of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), compared with healthy skin. Our analysis of Raman/PL spectra at the different excitation wavelengths enabled us to propose two novel wavelength-independent spectral criteria (intensity ratios for 1302 cm-1 and 1445 cm-1 bands, 1745 cm-1 and 1445 cm-1 bands), related to the different vibrational "fingerprints" of cell membrane lipids as biomarkers, which was confirmed by the multivariate curve resolution (MCR) technique. These criteria allowed us to differentiate healthy skin from BCC and SCC with sensitivity and specificity higher than 95%, demonstrating high clinical importance in the differential diagnostics of skin tumors.

Analytical Techniques for Single-Cell Biochemical Assays of Lipids

Lipids are essential cellular components forming membranes, serving as energy reserves, and acting as chemical messengers. Dysfunction in lipid metabolism and signaling is associated with a wide range of diseases including cancer and autoimmunity. Heterogeneity in cell behavior including lipid signaling is increasingly recognized as a driver of disease and drug resistance. This diversity in cellular responses as well as the roles of lipids in health and disease drive the need to quantify lipids within single cells. Single-cell lipid assays are challenging due to the small size of cells (∼1 pL) and the large numbers of lipid species present at concentrations spanning orders of magnitude. A growing number of methodologies enable assay of large numbers of lipid analytes, perform high-resolution spatial measurements, or permit highly sensitive lipid assays in single cells. Covered in this review are mass spectrometry, Raman imaging, and fluorescence-based assays including microscopy and microseparations.

Early biomolecular changes in brain microvascular endothelial cells under Epstein-Barr virus influence: a Raman microspectroscopic investigation

The brain microvascular endothelial cells (ECs) play an important role in protecting the brain from hazardous pathogens. However, some viral pathogens can smartly modulate the endothelial pathways to gain entry inside the brain. Further, these viruses can cause endothelial dysfunction which could develop serious neurological ailments. Epstein-Barr virus (EBV), an oncogenic virus, has also been linked to various neurological disorders. The virus primarily infects epithelial and B cells, however, it also has a tendency to infect ECs and cause endothelial activation. However, the impact of EBV influence on ECs is still underexplored. Studying the early events of virus-mediated cellular modulation could help in understanding the virus' infection strategy or aftermath. Raman microspectroscopy has been widely utilized in biomedical sciences to decipher cellular changes. To understand the EBV-influenced EC modulation by studying intracellular biomolecular changes at early time points, we utilized the Raman microspectroscopy tool. We treated the ECs with EBV and acquired the Raman spectra at different time points (2, 4, 6, 12, 24 and 36 h) and different sites (nucleus and periphery) to check changes in Raman intensities associated with specific biomolecules. In the EBV-treated cells, the status of various biomolecules in terms of Raman intensities was observed to be altered compared with uninfected cells. Specifically, the cholesterol, polysaccharide, nucleotides, nucleic acid and proline moieties were altered at different time points. We also investigated the possible correlation between these molecules using molecular network analysis and observed various associated factors. These factors could be influenced by EBV to alter the associated biomolecular levels. Our study paves the pathway to study EBV infection in human brain microvascular ECs and highlights specific biomolecular alterations, which can be focused for further mechanistic investigations.