Nanobiosensing Platforms for Real-Time and Non-Invasive Monitoring of Stem Cell Pluripotency and Differentiation

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.

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.

Phenotype Identification of HeLa Cells Knockout CDK6 Gene Based on Label-Free Raman Imaging

Identifying cell phenotypes is essential for understanding the function of biological macromolecules and molecular biology. We developed a noninvasive, label-free, single-cell Raman imaging analysis platform to distinguish between the cell phenotypes of the HeLa cell wild type (WT) and cyclin-dependent kinase 6 (CDK6) gene knockout (KO) type. Via large-scale Raman spectral and imaging analysis, two phenotypes of the HeLa cells were distinguished by their intrinsic biochemical profiles. A significant difference was found between the two cell lines: large lipid droplets formed in the knockout HeLa cells but were not observed in the WT cells, which was confirmed by Oil Red O staining. The band ratio of the Raman spectrum of saturated/unsaturated fatty acids was identified as the Raman spectral marker for HeLa cell WT or gene knockout type differentiation. The interaction between organelles involved in lipid metabolism was revealed by Raman imaging and Lorentz fitting, where the distribution intensity of the mitochondria and the endoplasmic reticulum membrane decreased. At the same time, lysosomes increased after the CDK6 gene knockout. The parameters obtained from Raman spectroscopy are based on hierarchical cluster analysis and one-way ANOVA, enabling highly accurate cell classification.

A Label-Free Electrical Impedance Spectroscopy for Detection of Clusters of Extracellular Vesicles Based on Their Unique Dielectric Properties

Extracellular vesicles (EVs) have gained considerable attention as vital circulating biomarkers since their structure and composition resemble the originating cells. The investigation of EVs' biochemical and biophysical properties is of great importance to map them to their parental cells and to better understand their functionalities. In this study, a novel frequency-dependent impedance measurement system has been developed to characterize EVs based on their unique dielectric properties. The system is composed of an insulator-based dielectrophoretic (iDEP) device to entrap and immobilize a cluster of vesicles followed by utilizing electrical impedance spectroscopy (EIS) to measure their impedance at a wide frequency spectrum, aiming to analyze both their membrane and cytosolic charge-dependent contents. The EIS was initially utilized to detect nano-size vesicles with different biochemical compositions, including liposomes synthesized with different lipid compositions, as well as EVs and lipoproteins with similar biophysical properties but dissimilar biochemical properties. Moreover, EVs derived from the same parental cells but treated with different culture conditions were characterized to investigate the correlation of impedance changes with biochemical properties and functionality in terms of pro-inflammatory responses. The system also showed the ability to discriminate between EVs derived from different cellular origins as well as among size-sorted EVs harbored from the same cellular origin. This proof-of-concept approach is the first step towards utilizing EIS as a label-free, non-invasive, and rapid sensor for detection and characterization of pathogenic EVs and other nanovesicles in the future.

Ultrasensitive two-dimensional material-based MCF-7 cancer cell sensor driven by perturbation processes

Changes in lipid composition and structure during cell development can be markers for cell apoptosis or various diseases such as cancer. Although traditional fluorescence techniques utilising molecular probes have been studied, these methods are limited in studying these micro-changes as they require complex probe preparation and cannot be reused, making cell monitoring and detection challenging. Here, we developed a direct current (DC) resistance sensor based on two-dimensional (2D) molybdenum disulfide (MoS₂) nanosheets to enable cancer cell-specific detection dependent on micro-changes in the cancer cell membrane. Atomistic molecular dynamics (MD) simulations were used to study the interaction between 2D MoS₂ and cancer lipid bilayer systems, and revealed that previously unconsidered perturbations in the lipid bilayer can cause an increase in resistance. Under an applied DC sweep, we observed an increase in resistance when cancer cells were incubated with the nanosheets. Furthermore, a correlation was observed between the resistance and breast cancer epithelial cell (MCF-7) population, illustrating a cell population-dependent sensitivity of our method. Our method has a detection limit of ∼3 × 10³ cells, below a baseline of ∼1 × 10⁴ cells for the current state-of-the-art electrical-based biosensors using an adherent monolayer with homogenous cells. This combination of a unique 2D material and electrical resistance framework represents a promising approach for the early detection of cancerous cells and to reduce the risk of post-surgery cancer recurrence.

Multimodal Label-Free Monitoring of Adipogenic Stem Cell Differentiation Using Endogenous Optical Biomarkers

Stem cell-based therapies carry significant promise for treating human diseases. However, clinical translation of stem cell transplants for effective treatment requires precise non-destructive evaluation of the purity of stem cells with high sensitivity (<0.001% of the number of cells). Here, a novel methodology using hyperspectral imaging (HSI) combined with spectral angle mapping-based machine learning analysis is reported to distinguish differentiating human adipose-derived stem cells (hASCs) from control stem cells. The spectral signature of adipogenesis generated by the HSI method enables identifying differentiated cells at single-cell resolution. The label-free HSI method is compared with the standard techniques such as Oil Red O staining, fluorescence microscopy, and qPCR that are routinely used to evaluate adipogenic differentiation of hASCs. HSI is successfully used to assess the abundance of adipocytes derived from transplanted cells in a transgenic mice model. Further, Raman microscopy and multiphoton-based metabolic imaging is performed to provide complementary information for the functional imaging of the hASCs. Finally, the HSI method is validated using matrix-assisted laser desorption/ionization-mass spectrometry imaging of the stem cells. The study presented here demonstrates that multimodal imaging methods enable label-free identification of stem cell differentiation with high spatial and chemical resolution.

A Spheroid-Forming Hybrid Gold Nanostructure Platform That Electrochemically Detects Anticancer Effects of Curcumin in a Multicellular Brain Cancer Model

In this study, a multifunctional platform that enables the highly efficient formation of 3D multicellular cancer spheroids and precise real-time assessments of the anticancer effects of curcumin in a brain tumor coculture model is reported. A highly conductive gold nanostructure (HCGN) is fabricated to facilitate cancer spheroid formation without using anti-cell adhesion molecules. A neuroblastoma (SH-SY5Y) and glioblastoma (U-87MG) coculture model is generated on HCGN with a specific cell-to-cell ratio (SH-SY5Y: U-87MG = 1:1), and their redox behaviors are successfully measured without destroying the distinct 3D structure of the multicellular spheroids. Using electrochemical signals as an indicator of spheroid viability, the effects of potential anticancer compounds on cocultured spheroids are further assessed. Remarkably, decreased cell viability in 3D spheroids caused by a low concentration of curcumin (30 µM) is detectable using the electrochemical method (29.4%) but not with a conventional colorimetric assay (CCK-8). The detection is repeated more than ten times for both short- (63 h) and long-term cultivation (144 h) without damaging the spheroids, enabling real-time, non-destructive pharmacokinetic analysis of various drug candidates. Therefore, it can be concluded that the hybrid platform is a highly promising, precise, and high-throughput drug screening tool based on 3D cell cultivation.

Recent Advances in Electrochemical Sensors for the Detection of Biomolecules and Whole Cells

Electrochemical sensors are considered an auspicious tool to detect biomolecules (e.g., DNA, proteins, and lipids), which are valuable sources for the early diagnosis of diseases and disorders. Advances in electrochemical sensing platforms have enabled the development of a new type of biosensor, enabling label-free, non-destructive detection of viability, function, and the genetic signature of whole cells. Numerous studies have attempted to enhance both the sensitivity and selectivity of electrochemical sensors, which are the most critical parameters for assessing sensor performance. Various nanomaterials, including metal nanoparticles, carbon nanotubes, graphene and its derivatives, and metal oxide nanoparticles, have been used to improve the electrical conductivity and electrocatalytic properties of working electrodes, increasing sensor sensitivity. Further modifications have been implemented to advance sensor platform selectivity and biocompatibility using biomaterials such as antibodies, aptamers, extracellular matrix (ECM) proteins, and peptide composites. This paper summarizes recent electrochemical sensors designed to detect target biomolecules and animal cells (cancer cells and stem cells). We hope that this review will inspire researchers to increase their efforts to accelerate biosensor progress-enabling a prosperous future in regenerative medicine and the biomedical industry.

Biosensors for Studies on Adhesion-Mediated Cellular Responses to Their Microenvironment

Cells interact with their microenvironment by constantly sensing mechanical and chemical cues converting them into biochemical signals. These processes allow cells to respond and adapt to changes in their environment, and are crucial for most cellular functions. Understanding the mechanism underlying this complex interplay at the cell-matrix interface is of fundamental value to decipher key biochemical and mechanical factors regulating cell fate. The combination of material science and surface chemistry aided in the creation of controllable environments to study cell mechanosensing and mechanotransduction. Biologically inspired materials tailored with specific bioactive molecules, desired physical properties and tunable topography have emerged as suitable tools to study cell behavior. Among these materials, synthetic cell interfaces with built-in sensing capabilities are highly advantageous to measure biophysical and biochemical interaction between cells and their environment. In this review, we discuss the design of micro and nanostructured biomaterials engineered not only to mimic the structure, properties, and function of the cellular microenvironment, but also to obtain quantitative information on how cells sense and probe specific adhesive cues from the extracellular domain. This type of responsive biointerfaces provides a readout of mechanics, biochemistry, and electrical activity in real time allowing observation of cellular processes with molecular specificity. Specifically designed sensors based on advanced optical and electrochemical readout are discussed. We further provide an insight into the emerging role of multifunctional micro and nanosensors to control and monitor cell functions by means of material design.

Guidelines for establishing a 3-D printing biofabrication laboratory

Advanced manufacturing and 3D printing are transformative technologies currently undergoing rapid adoption in healthcare, a traditionally non-manufacturing sector. Recent development in this field, largely enabled by merging different disciplines, has led to important clinical applications from anatomical models to regenerative bioscaffolding and devices. Although much research to-date has focussed on materials, designs, processes, and products, little attention has been given to the design and requirements of facilities for enabling clinically relevant biofabrication solutions. These facilities are critical to overcoming the major hurdles to clinical translation, including solving important issues such as reproducibility, quality control, regulations, and commercialization. To improve process uniformity and ensure consistent development and production, large-scale manufacturing of engineered tissues and organs will require standardized facilities, equipment, qualification processes, automation, and information systems. This review presents current and forward-thinking guidelines to help design biofabrication laboratories engaged in engineering model and tissue constructs for therapeutic and non-therapeutic applications.

Graphene Hybrid Materials for Controlling Cellular Microenvironments

Cellular microenvironments are known as key factors controlling various cell functions, including adhesion, growth, migration, differentiation, and apoptosis. Many materials, including proteins, polymers, and metal hybrid composites, are reportedly effective in regulating cellular microenvironments, mostly via reshaping and manipulating cell morphologies, which ultimately affect cytoskeletal dynamics and related genetic behaviors. Recently, graphene and its derivatives have emerged as promising materials in biomedical research owing to their biocompatible properties as well as unique physicochemical characteristics. In this review, we will highlight and discuss recent studies reporting the regulation of the cellular microenvironment, with particular focus on the use of graphene derivatives or graphene hybrid materials to effectively control stem cell differentiation and cancer cell functions and behaviors. We hope that this review will accelerate research on the use of graphene derivatives to regulate various cellular microenvironments, which will ultimately be useful for both cancer therapy and stem cell-based regenerative medicine.

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

We developed a label-free and noninvasive single-cell Raman microspectroscopy (SCRM)-based platform to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). Through large-scale Raman spectral analysis, we can distinguish hiPSCs and hiPSC-derived neural cells using their intrinsic biochemical profile. We identified glycogen as a Raman biomarker for neuronal differentiation and validated the results using conventional glycogen detection assays. The parameters obtained from SCRM were processed by a novel machine learning method based on t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, enabling highly accurate and robust cell classification. The platform and the proposed biomarker should also be applicable to other cell types and can shed light on developmental biology and glycogen metabolism disorders.

Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.

Enhancing Neurogenesis of Neural Stem Cells Using Homogeneous Nanohole Pattern-Modified Conductive Platform

Biocompatible platforms, wherein cells attach and grow, are important for controlling cytoskeletal dynamics and steering stem cell functions, including differentiation. Among various components, membrane integrins play a key role in focal adhesion of cells (18-20 nm in size) and are, thus, highly sensitive to the nanotopographical features of underlying substrates. Hence, it is necessary to develop a platform/technique that can provide high flexibility in controlling nanostructure sizes. We report a platform modified with homogeneous nanohole patterns, effective in guiding neurogenesis of mouse neural stem cells (mNSCs). Sizes of nanoholes were easily generated and varied using laser interference lithography (LIL), by changing the incident angles of light interference on substrates. Among three different nanohole patterns fabricated on conductive transparent electrodes, 500 nm-sized nanoholes showed the best performance for cell adhesion and spreading, based on F-actin and lamellipodia/filopodia expression. Enhanced biocompatibility and cell adhesion of these nanohole patterns ultimately resulted in the enhanced neurogenesis of mNSCs, based on the mRNAs expression level of the mNSCs marker and several neuronal markers. Therefore, platforms modified with homogeneous nanohole patterns fabricated by LIL are promising for the precise tuning of nanostructures in tissue culture platforms and useful for controlling various differentiation lineages of stem cells.

High density gold nanostructure composites for precise electrochemical detection of human embryonic stem cells in cell mixture

Precise detection of undifferentiated human pluripotent stem cells (hPSCs) and their entire subsequent elimination are incredibly important in preventing teratoma formations after transplantation. Recently, electrochemical sensing platforms have demonstrated immense potential as a new tool to detect remaining hPSCs in label-free and non-destructive manner. Nevertheless, one of the critical huddles of this electrochemical sensing approach is its low sensitivity since even low concentrations of remaining hPSCs were reported to form teratoma once transplanted. To address this issue, in this study, we report an engineering-based approach to improve the sensitivity of electrochemical sensing platform for hPSC detection. By optimizing the density of gold nanostructure and the matrigel concentration to improve both electro-catalytic property and biocompatibility, the sensitivity of the developed platform toward hESCs detection could reach 12,500 cells/chip, which is close to the known critical concentration of hPSCs (˜10,000 cells) that induce teratoma formation in vivo. Remarkably, the electrochemical signals were not detectable from other types of stem cell-derived endothelial cells (CB-EPCs) even at high concentrations of CB-EPCs (40,000 cells/chip), proving the high selectivity of the developed platform toward hPSC detection. Hence, the developed platform could be highly useful to solve the safety issues that are related with clinical application of hPSC-derived cells.