Cell surface charge has been recognized as an important cellular property. We developed a microfluidic sensor based on resistive pulse sensing to assess surface charge and sizes of single cells suspended in a continuous flow. The device consists of two consecutive resistive pulse sensors (RPSs) with identical dimensions. Opposite electric fields were applied on the two RPSs. A charged cell in the RPSs was accelerated or decelerated by the electric fields and thus exhibited different transit times passing through the two RPSs. The cell surface charge is measured with zeta potential that can be quantified with the transit time difference. The transit time of each cell can be accurately detected with the width of pulses generated by the RPS, while the cell size can be calculated with the pulse magnitude at the same time. This device has the ability to detect surface charges and sizes of individual cells with high tolerance in cell types and testing solutions compared with traditional electrophoretic light scattering methods. Three different types of cells including HeLa cancer cells, human dermal fibroblast cells, and human umbilical vein endothelial cells (HUVECs) were tested with the sensor. Results showed a significant difference of zeta potentials between HeLa cells and fibroblasts or HUVECs. In addition, when HeLa cells were treated with various concentrations of glutamine, the effects on cancer cell surface charge were detected. Our results demonstrated the great potential of using our sensor for cell type sorting, cancer cell detection, and cell status analysis.
Many bio-functions of cells can be regulated by their surface charge characteristics. Mapping surface charge density in a single cell’s surface is vital to advance the understanding of cell behaviors. This article demonstrates a method of cell surface charge mapping via electrostatic cell–nanoparticle (NP) interactions. Fluorescent nanoparticles (NPs) were used as the marker to investigate single cells’ surface charge distribution. The nanoparticles with opposite charges were electrostatically bonded to the cell surface; a stack of fluorescence distribution on a cell’s surface at a series of vertical distances was imaged and analyzed. By establishing a relationship between fluorescent light intensity and number of nanoparticles, cells’ surface charge distribution was quantified from the fluorescence distribution. Two types of cells, human umbilical vein endothelial cells (HUVECs) and HeLa cells, were tested. From the measured surface charge density of a group of single cells, the average zeta potentials of the two types of cells were obtained, which are in good agreement with the standard electrophoretic light scattering measurement. This method can be used for rapid surface charge mapping of single particles or cells, and can advance cell-surface-charge characterization applications in many biomedical fields.
The fast, accurate detection of biomolecules, ranging from nucleic acids and small molecules to proteins and cellular secretions, plays an essential role in various biomedical applications. These include disease diagnostics and prognostics, environmental monitoring, public health, and food safety. Aptamer recognition (DNA or RNA) has gained extensive attention for biomolecular detection due to its high selectivity, affinity, reproducibility, and robustness. Concurrently, biosensing with nanoparticles has been widely used for its high carrier capacity, stability and feasibility of incorporating optical and catalytic activity, and enhanced diffusivity. Biosensors based on aptamers and nanoparticles utilize the combination of their advantages and have become a promising technology for detecting of a wide variety of biomolecules with high sensitivity, reliability, specificity, and detection speed. Via various sensing mechanisms, target biomolecules have been quantified in terms of optical (e.g., colorimetric and fluorometric), magnetic, and electrical signals. In this review, we summarize the recent advances in and compare different aptamer–nanoparticle-based biosensors by nanoparticle types and detection mechanisms. We also share our views on the highlights and challenges of the different nanoparticle-aptamer-based biosensors.
Circular RNAs (circRNAs) are usually enriched in neural tissues, yet about 80% circRNAs have lower expression in gliomas relative to normal brains, highlighting the importance of circRNAs as tumor suppressors. However, the clinical impact as well as the pathways regulated by the tumor-suppressive circRNAs remain largely unknown in glioblastoma (GBM). Through bioinformatic analysis followed by experimental validation, we found that hsa_circ_0114014 (circLRRC7) was dramatically down-regulated in GBM when compared with normal brain tissues (p < 0.0001). GBM patients with a lower circLRRC7 expression had poorer progression-free survival (PFS, p < 0.05) and overall survival (OS, p < 0.05). Analyses of the predicted target miRNAs of circLRRC7 in CSCD and CRI databases, in combination with the miRNA expression data in GBMs and normal brains from GSE database, revealed miR-1281 as a potential downstream target of circLRRC7. Subsequently, the target genes of hsa-mir-1281 were predicted by TargetScan, miRDB and miRNATAR databases. Intersection analysis and correlation test indicated that PDXP was a potential target of miR-1281. In summary, circLRRC7 may be a tumor suppressor that associated with miR-1281 and PDXP expression in GBM, which may provide novel therapeutic targets for GBM treatment.
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