Autofluorescence-Raman Mapping Integration analysis for ultra-fast label-free monitoring of adipogenic differentiation of stem cells

Imaging of perivascular adipose tissue in cardiometabolic diseases by Raman spectroscopy: Towards single-cell analysis

Perivascular adipose tissue (PVAT) has emerged as a dynamic organ influencing vascular function and cardiovascular health. In this brief review, an overview of the recent research in the investigation of PVAT is presented, ranging from in vivo studies to single-cell methodologies, in particular those based on Raman spectroscopy. The strengths and limitations of each, emphasizing their contributions to the current understanding of PVAT biology were discussed. Ultimately, the integration of these diverse methodologies promises to uncover new therapeutic targets and diagnostic biomarkers, including those emerging from simple Raman spectroscopy-based measurements of alterations in lipid unsaturation degree, invariably associated with PVAT dysfunction.

Acceleration of high-quality Raman imaging via a locality enhanced transformer network

Raman imaging (RI) is an outstanding technique that enables molecular-level medical diagnostics and therapy assessment by providing characteristic fingerprint and morphological information about molecules. However, obtaining high-quality Raman images generally requires a long acquisition time, up to hours, which is prohibitive for RI applications of timely cytopathology and histopathology analyses. To address this issue, image super-resolution (SR) based on deep learning, including convolutional neural networks and transformers, has been widely recognized as an effective solution to reduce the time required for achieving high-quality RI. In this study, a locality enhanced transformer network (LETNet) is proposed to perform Raman image SR. Specifically, the general architecture of the transformer is adopted with the replacement of self-attention by convolution to generate high-fidelity and detailed SR images. Additionally, the convolution in the LETNet is further optimized by utilizing depth-wise convolution to improve the computational efficiency of the model. Experiments on hyperspectral Raman images of breast cancer cells and Raman images of a few channels of brain tumor tissues demonstrate that the LETNet achieves superior 2×, 4×, and 8× SR with fewer parameters compared with other SR methods. Consequently, high-quality Raman images can be obtained with a significant reduction in time, ranging from 4 to 64 times. Overall, the proposed method provides a novel, efficient, and reliable solution to expedite high-quality RI and promote its application in real-time diagnosis and therapy.

Raman spectroscopy to assess the differentiation of bone marrow mesenchymal stem cells into a glial phenotype

Background

Mesenchymal stem cells (MSCs) are multipotent precursor cells with the ability to self-renew and differentiate into multiple cell linage, including the Schwann-like fate that promotes regeneration after lesion. Raman spectroscopy provides a precise characterization of the osteogenic, adipogenic, hepatogenic and myogenic differentiation of MSCs. However, the differentiation of bone marrow mesenchymal stem cells (BMSCs) towards a glial phenotype (Schwann-like cells) has not been characterized before using Raman spectroscopy.

Method

We evaluated three conditions: 1) cell culture from rat bone marrow undifferentiated (uBMSCs), and two conditions of differentiation; 2) cells exposed to olfactory ensheathing cells-conditioned medium (dBMSCs) and 3) cells obtained from olfactory bulb (OECs). uBMSCs phenotyping was confirmed by morphology, immunocytochemistry and flow cytometry using antibodies of cell surface: CD90 and CD73. Glial phenotype of dBMSCs and OECs were verified by morphology and immunocytochemistry using markers of Schwann-like cells and OECs such as GFAP, p75 NTR and O4. Then, the Principal Component Analysis (PCA) of Raman spectroscopy was performed to discriminate components from the high wavenumber region between undifferentiated and glial-differentiated cells. Raman bands at the fingerprint region also were used to analyze the differentiation between conditions.

Results

Differences between Raman spectra from uBMSC and glial phenotype groups were noted at multiple Raman shift values. A significant decrease in the concentration of all major cellular components, including nucleic acids, proteins, and lipids were found in the glial phenotype groups. PCA analysis confirmed that the highest spectral variations between groups came from the high wavenumber region observed in undifferentiated cells and contributed with the discrimination between glial phenotype groups.

Conclusion

These findings support the use of Raman spectroscopy for the characterization of uBMSCs and its differentiation in the glial phenotype.

Optical diffraction tomography and Raman spectroscopy reveal distinct cellular phenotypes during white and brown adipocyte differentiation

White adipose tissue (WAT) and brown adipose tissue (BAT) are the primary types of fats in humans, and they play prominent roles in energy storage and thermogenesis, respectively. While the mechanisms of terminal adipogenesis are well understood, much remains unknown about the early stages of adipogenic differentiation. Label-free approaches, such as optical diffraction tomography (ODT) and Raman spectroscopy, offer the ability to retrieve morphological and molecular information at the single cell level without the negative effects of photobleaching and system perturbation due to introduction of fluorophores. In this study, we employed 3D ODT and Raman spectroscopy to gain deeper insights into the early stages of differentiation of human white preadipocytes (HWPs) and human brown preadipocytes (HBPs). We utilized ODT to retrieve morphological information, including cell dry mass and lipid mass, and Raman spectroscopy to obtain molecular information about lipids. Our findings reveal that HWPs and HBPs undergo dynamic and differential changes during the differentiation process. Notably, we found that HBPs accumulated lipids more rapidly and had a higher lipid mass than HWPs. Additionally, both cell types experienced an increase and subsequent decrease in cell dry mass during the first seven days, followed by an increase after day 7, which we attribute to the transformation of adipogenic precursors in the early stages. Finally, HBPs had higher lipid unsaturation levels than HWPs for the same differentiation timepoints. The insights gained from our study provide crucial contributions towards the advancement of new therapies for obesity and related diseases.

Progress in Nano-Biosensors for Non-Invasive Monitoring of Stem Cell Differentiation

Non-invasive, non-destructive, and label-free sensing techniques are required to monitor real-time stem cell differentiation. However, conventional analysis methods, such as immunocytochemistry, polymerase chain reaction, and Western blot, involve invasive processes and are complicated and time-consuming. Unlike traditional cellular sensing methods, electrochemical and optical sensing techniques allow non-invasive qualitative identification of cellular phenotypes and quantitative analysis of stem cell differentiation. In addition, various nano- and micromaterials with cell-friendly properties can greatly improve the performance of existing sensors. This review focuses on nano- and micromaterials that have been reported to improve sensing capabilities, including sensitivity and selectivity, of biosensors towards target analytes associated with specific stem cell differentiation. The information presented aims to motivate further research into nano-and micromaterials with advantageous properties for developing or improving existing nano-biosensors to achieve the practical evaluation of stem cell differentiation and efficient stem cell-based therapies.

Recent Advances in Electrochemical Biosensors for Monitoring Animal Cell Function and Viability

Redox reactions in live cells are generated by involving various redox biomolecules for maintaining cell viability and functions. These qualities have been exploited in the development of clinical monitoring, diagnostic approaches, and numerous types of biosensors. Particularly, electrochemical biosensor-based live-cell detection technologies, such as electric cell-substrate impedance (ECIS), field-effect transistors (FETs), and potentiometric-based biosensors, are used for the electrochemical-based sensing of extracellular changes, genetic alterations, and redox reactions. In addition to the electrochemical biosensors for live-cell detection, cancer and stem cells may be immobilized on an electrode surface and evaluated electrochemically. Various nanomaterials and cell-friendly ligands are used to enhance the sensitivity of electrochemical biosensors. Here, we discuss recent advances in the use of electrochemical sensors for determining cell viability and function, which are essential for the practical application of these sensors as tools for pharmaceutical analysis and toxicity testing. We believe that this review will motivate researchers to enhance their efforts devoted to accelerating the development of electrochemical biosensors for future applications in the pharmaceutical industry and stem cell therapeutics.

Recent Advances in Monitoring Stem Cell Status and Differentiation Using Nano-Biosensing Technologies

In regenerative medicine, cell therapies using various stem cells have received attention as an alternative to overcome the limitations of existing therapeutic methods. Clinical applications of stem cells require the identification of characteristics at the single-cell level and continuous monitoring during expansion and differentiation. In this review, we recapitulate the application of various stem cells used in regenerative medicine and the latest technological advances in monitoring the differentiation process of stem cells. Single-cell RNA sequencing capable of profiling the expression of many genes at the single-cell level provides a new opportunity to analyze stem cell heterogeneity and to specify molecular markers related to the branching of differentiation lineages. However, this method is destructive and distorted. In addition, the differentiation process of a particular cell cannot be continuously tracked. Therefore, several spectroscopic methods have been developed to overcome these limitations. In particular, the application of Raman spectroscopy to measure the intrinsic vibration spectrum of molecules has been proposed as a powerful method that enables continuous monitoring of biochemical changes in the process of the differentiation of stem cells. This review provides a comprehensive overview of current analytical methods employed for stem cell engineering and future perspectives of nano-biosensing technologies as a platform for the in situ monitoring of stem cell status and differentiation.

A polymer-based chemical tongue for the non-invasive monitoring of osteogenic stem-cell differentiation by pattern recognition of serum-supplemented spent media

The development of non-invasive techniques to characterize cultured cells is invaluable not only to ensure the reproducibility of cell research, but also for quality assurance of industrial cell products for...

Ternary Electrochemiluminescence Biosensor Based on DNA Walkers and AuPd Nanomaterials as a Coreaction Accelerator for the Detection of miRNA-141

In this study, a ternary electrochemiluminescence (ECL) sensing platform coupled with a multiple signal amplification strategy was proposed for ultrasensitive detection of miRNA-141. The initial signal amplification was achieved via three-dimensional reduced graphene oxide (3D-rGO)@Au nanoparticles (NPs) to form an excellent conductive layer. Then, AuPd NPs as a coreaction accelerator was introduced into the N-(4-aminobutyl)-N-(ethylisoluminol) (ABEI)-H₂O₂ system to facilitate the transformation from H₂O₂ to excess superoxide anion radicals (O₂^•-), which further amplified the ECL emission of ABEI, leading to a significant increase of the ECL signal. Meanwhile, in the presence of miRNA-141 and T7 Exonuclease (T7 Exo), the self-assembled DNA swing arm can be driven to walk autonomously. The DNA walker reaction could result in the release of numerous labeled luminophores, which could react to achieve an extremely weak ECL signal. Surprisingly, the established ECL sensor platform for the detection of miRNA-141 demonstrated excellent sensitivity with a low detection limit of 31.9 aM in the concentration range from 100 aM to 1 nM. Consequently, the designed strategy greatly improves the luminous efficiency of the ternary ECL system and provides a special approach for the detection of nucleic acids and biomarkers in clinical and biochemical analysis.