Rapid and accurate identification of stem cell differentiation stages via SERS and convolutional neural networks.

Monitoring the transition of cell states during induced pluripotent stem cell (iPSC) differentiation is crucial for clinical medicine and basic research. However, both identification category and prediction accuracy need further improvement. Here, we propose a method combining surface-enhanced Raman spectroscopy (SERS) with convolutional neural networks (CNN) to precisely identify and distinguish cell states during stem cell differentiation. First, mitochondria-targeted probes were synthesized by combining AuNRs and mitochondrial localization signal (MLS) peptides to obtain effective and stable SERS spectra signals at various stages of cell differentiation. Then, the SERS spectra served as input datasets, and their distinctive features were learned and distinguished by CNN. As a result, rapid and accurate identification of six different cell states, including the embryoid body (EB) stage, was successfully achieved throughout the stem cell differentiation process with an impressive prediction accuracy of 98.5%. Furthermore, the impact of different spectral feature peaks on the identification results was investigated, which provides a valuable reference for selecting appropriate spectral bands to identify cell states. This is also beneficial for shortening the spectral acquisition region to enhance spectral acquisition speed. These results suggest the potential for SERS-CNN models in quality monitoring of stem cells, advancing the practical applications of stem cells.

SERS-based long-term mitochondrial pH monitoring during differentiation of human induced pluripotent stem cells to neural progenitor cells.

As one of the important organelles in the process of cell differentiation, mitochondria regulate the whole process of differentiation by participating in energy supply and information transmission. Mitochondrial pH value is a key indicator of mitochondrial function. Therefore, real-time monitoring of mitochondrial pH value during cell differentiation is of great significance for understanding cell biochemical processes and exploring differentiation mechanisms. In this study, Surface-enhanced Raman scattering (SERS) technology was used to achieve the real-time monitoring of mitochondrial pH during induced pluripotent stem cells (iPSCs) differentiation into neural progenitor cells (NPCs). The results showed that the variation trend of mitochondrial pH in normal and abnormal differentiated batches was different. The mitochondrial pH value of normal differentiated cells continued to decline from iPSCs to embryoid bodies (EB) day 4, and continued to rise from EB day 4 to the NPCs stage, and the mitochondrial microenvironment of iPSCs to NPCs differentiation became acidic. In contrast, the mitochondrial pH value of abnormally differentiated cells declined continuously during differentiation. This study improves the information on acid-base balance during cell differentiation and may provide a basis for further understanding of the changes and regulatory mechanisms of mitochondrial metabolism during cell differentiation. This also helps to improve more accurate and useful differentiation protocols based on the microenvironment within the mitochondria, improving the efficiency of cell differentiation.

DHM/SERS reveals cellular morphology and molecular changes during iPSCs-derived activation of astrocytes.

The activation of astrocytes derived from induced pluripotent stem cells (iPSCs) is of great significance in neuroscience research, and it is crucial to obtain both cellular morphology and biomolecular information non-destructively in situ, which is still complicated by the traditional optical microscopy and biochemical methods such as immunofluorescence and western blot. In this study, we combined digital holographic microscopy (DHM) and surface-enhanced Raman scattering (SERS) to investigate the activation characteristics of iPSCs-derived astrocytes. It was found that the projected area of activated astrocytes decreased by 67%, while the cell dry mass increased by 23%, and the cells changed from a flat polygonal shape to an elongated star-shaped morphology. SERS analysis further revealed an increase in the intensities of protein spectral peaks (phenylalanine 1001 cm-1, proline 1043 cm-1, etc.) and lipid-related peaks (phosphatidylserine 524 cm-1, triglycerides 1264 cm-1, etc.) decreased in intensity. Principal component analysis-linear discriminant analysis (PCA-LDA) modeling based on spectral data distinguished resting and reactive astrocytes with a high accuracy of 96.5%. The increase in dry mass correlated with the increase in protein content, while the decrease in projected area indicated the adjustment of lipid composition and cell membrane remodeling. Importantly, the results not only reveal the cellular morphology and molecular changes during iPSCs-derived astrocytes activation but also reflect their mapping relationship, thereby providing new insights into diagnosing and treating neurodegenerative diseases.

A SERS-Based Dual-Parameter Monitoring Nanoprobe of ROS and PI3K/Akt during Ginsenoside Rg3-Induced Cell Apoptosis.

Both the reactive oxygen species (ROS) level and Phosphatidylinositol 3 Kinase (PI3K) protein content are two crucial parameters for characterizing states of cell apoptosis. Current methods measure these parameters with two different techniques, respectively, which usually lead to evaluation contingency. Ginsenoside Rg3 exhibits an excellent anticancer effect, which is enacted by the Phosphatidylinositol 3 Kinase/Protein Kinase B (PI3K/Akt) pathway involving ROS; however, the precise mechanism that induces cell apoptosis remains unknown. This is due to the lack of information on quantitative intracellular ROS and PI3K. Here, we used a surface-enhanced Raman scattering (SERS)-based boric acid nanoprobe to monitor the intracellular ROS level and phosphatidylinositol-3,4,5-triphosphate (PI(3,4,5)P3) content, which reflects the regulatory effect of the PI3K/Akt pathway. After treatment with ginsenoside Rg3, the PI3K/Akt content first increased and then decreased as the ROS level increased. Moreover, when the ROS level significantly increased, the mitochondrial membrane potential reduced, thus indicating the dynamic regulation effect of intracellular ROS level on the PI3K/Akt pathway. Importantly, in addition to avoiding evaluation contingency, which is caused by measuring the aforementioned parameters with two different techniques, this SERS-based dual-parameter monitoring nanoprobe provides an effective solution for simultaneous ROS level and PI3K content measurements during cell apoptosis. Furthermore, the intracellular ROS level was also able to have a dynamic regulatory effect on the PI3K/Akt pathway, which is essential for studying ROS/PI3K/Akt-pathway-related cell apoptosis and its activation mechanism.

SERS-based error calibration of a TMB-H2O2 colorimetric system.

3,3',5,5'-tetramethylbenzidine (TMB)-H2O2 is widely used as an effective colorimetric system, in which the color reaction is implemented with peroxidase-catalyzed TMB oxidation by H2O2 that usually measured UV-vis absorption spectra or Raman spectra. However, its low accuracy significantly limits its application. Blue charge transfer complex (CTC), which is the product of TMB and H2O2 reaction and is used as the basis for partial colorimetric methods, usually causes colorimetric error owing to changes in the UV-vis absorption and Raman spectra during TMB oxidation under various environmental conditions (catalyst type, temperature, H2O2 concentration). Herein, we propose a surface-enhanced Raman spectrum (SERS)-based error calibration method to improve the accuracy of the TMB-H2O2 colorimetric system. It is found that under 633 nm laser excitation, TMB has three Raman peaks at 1189, 1335 and 1609 cm-1 in the single-electron oxidation phase, and these peaks disappear completely in the two-electron oxidation phase. By comparing these Raman peaks, we can conveniently obtain the actual process information during TMB oxidation. Using the proposed method, the accuracy of the TMB-H2O2 colorimetric system improved by more than 15%. Importantly, this SERS-based TMB-H2O2 error calibration method will open a new horizon for enzyme-linked immunosorbent assay (ELISA) and other biomedical applications.