| Cells are the foundation of life.In order to uncover the basic laws of cellular activity,it is necessary to conduct in-depth research on the structure and function of cells.The protein expression and metabolic behaviors of tumor cells,which exhibit a high degree of heterogeneity,are different from normal cells.Systematic study of the heterogeneity of tumor cells in complex tissues could lead to a better understanding of the mechanisms by which cancer occurs and its developments.Traditional technology for tumor detection that based on fluorescent molecular markers could inevitably affect the composition of the cell and even interfere with gene expression.Besides,it is difficult to monitor the metabolic behavior of tumor cells in real-time with these methods.Therefore,to obtain accurate an d quantitative biological data,there is an urgent need to develop a non-invasive,label-free measurement to explore the physiological behavior of tumor cells.Scanning electrochemical microscopy(SECM)as a non-contact and label-free technique enables in-situ,real-time,and high-resolution characterization of multiple biological information by recording electrochemical reactions in microregions.In addition,with the development of microfluidic technology,Microfluidic devices have shown their unique advantages and influence in the field of biology due to their advantages of miniaturization,precise control,and high throughput.In this dissertation,we devoted to the combination of SECM label-free technology and microfluidics technology to characterize the heterogeneity of protein expression and the redox state of tumor cells and its difference with fibroblast with high throughput.The main researches of this dissertation are as follows:(1)On the basic of the combination of label-free SECM imaging with the detachable microfluidic chip,we proposed a new analytical method to systematically study the relationship between protein activity and gene expression in heterogeneous three-dimensional(3D)cell spheroids.The construction of 3D tumor models allows researchers to reproduce the complex in vivo scenes to more accurately analyze the morphological structure and membrane protein expression of tumor cells.Herein,we designed and fabricated a detachable microfluidic device that successfully cultured tumor cells(breast cancer,MCF-7)and stromal cells(fibroblast,NHDF)on the same chip。After the opening of the chip,we applied the dual-mediator voltage-switching mode SECM(VSM-SECM)to perform label-free imaging and quantitative analysis of the expression of alkaline phosphatase(ALP),a stem cell marker,of 3D cell spheroids in the chip.Subsequently,individual cell spheroids can be accurately selected for multi-gene expression analysis.The results of SECM showed that the effect of the morphology on the electrochemical signaling of the spheroids could be effectively decoupled by applying the VSM-SECM。The apparent heterogeneous rate constant kf(3.88×10-2 cm/s)extracted above the 3D breast cancer cells was 4.1 times that of the fibroblast spheroids(9.7×10-3 cm/s).It was demonstrated that tumor cells expressed more ALP than normal cells,thus having more potential to become tumor stem cells.Subsequent real-time PCR experiments with specific genes further confirmed that the mRNA level of ALP was upregulated in breast cancer cells and 8 times higher than that of fibroblast spheroids.Compared with fibroblasts,other genes such as pluripotency relevant transcriptional factor,SOX2,epithelial markers MUC1,EPCAM,etc.were remarkably enriched in 3D tumor,thus deeply revealing the potential stemness of breast cancer cells.This method breaks the limitation that only a few cells can be characterized in a single experiment in SECM studies,allowing us to obtain electrochemical information of 3D cell spheres and deep downstream molecular biology information in one study.This working system can provide us with more multidimensional cell biological information,helping us to have a more comprehensive and in-depth understanding of the physiological characteristics of tumor cells.(2)Combined with microfluidic single-cell capture array chips,a new fast label-free,high-throughput single-cell assay platform based on programmed SECM(P-SECM)was established.Traditional SECM imaging has always faced the challenge of taking too long to analyze a large number of active single cells simultaneously.Considering that critical electrochemical information such as enzyme activity of cells can also be collected when performing a simple line scan through cells,by trapping single cells in an addressable micro-pit array so that they are neatly arranged,we implemented a programmed SECM based on line scan mode,controlling probes to collect enzyme activity information of cells only through efficient pathways such as above the cell.As a proof of concept,we applied this programmed SECM to collect information on 900(30×30)micro-pits array(area size 1400×200 μm)occupied by polystyrene beads in 1.2 h,and the detection time was about 1/10 of that of traditional methods.Furthermore,combined with the VSM-SECM,we applied P-SECM to quantitatively detect the alkaline phosphatase(ALP)activity of 82 single cells,including 48 human cervical cancer cells(HeLa)and 34 normal fibroblasts(NHDF)in 20 min.We found that the apparent heterogeneous rate constant kf extracted on cells is not directly proportional to cell size,and this result can be used as direct evidence of cellular heterogeneity.The maximum kf(15.52×10-3 cm/s)in 48 HeLa cells was 3.1 times the maximum kf kf(5.52×10-3 cm/s)in 34 NHDF cells,and the kf distribution of HeLa cells was relatively dispersed compared with NHDF.These results revealed that HeLa cells showed higher ALP activity and its expression was in greater heterogeneity at single-cell level.The platform we have established by combining an addressable microfluidic device with a SECM that programmatically defines the scan path can provide a new reference for high-throughput label-free single-cell analysis.(3)Using the above-described combination of programmed SECM and the micro-pits array,we monitored redox state of tumor cells by detecting the dynamic changes of glutathione(GSH)efflux at the single-cell level under the stimulation of ferrocene methanol(FcMeOH).Thereafter,we carried out the cluster analysis of 702 single cells with the help of artificial intelligence deep learning.The growth and development of cells depends on the balance of fine systems in the body,and the redox state of cells is the most important part of this.Intracellular glutathione(GSH)expression is closely related to the redox status of tumor cells.Traditional fluorescent probe-based detection methods are unable to characterize the dynamic changes of GSH in real time with high throughput.Therefore,we applied VSMSECM to monitor the kinetics of GSH efflux from single human lung adenocarcinoma(A549)and normal human fibroblasts(NHDF)under FcMeOH stimulation to investigate their redox status.We found that GSH efflux of A549 cells of three different phenotypes(normal type,spread type,binuclear type)increased with the prolongation of the stimulation time.GSH efflux reaches stability when the cells were exposed to FcMeOH for 75 min.The extracted kf exhibited following relationship:binuclear type(9.8×10-3 cm/s)>spread type(7.6×103 cm/s)>normal type(4.5×10-3 cm/s).In contrast,little GSH efflux was detected from NHDF cells and the extracted maximum kf(0.8×10-3 cm/s)was only 1/6 to 1/12 of A549 cells.Besides,we examined the redox status of the captured 702 single cells with a micro-pit array,and the results showed that in 482 A549 cells,the largest kf was 9.83×10-3 cm/s and the minimum kf was 0.05×10-3 cm/s.In 220 single NHDF cells,the largest kr was 3.98 × 10-3 cm/s and the minimum kf is 0.04×10-3 cm/s.the kf of A549 cells changes more widely,indicating that the heterogeneity of the redox state of A549 cells is greater.Nearly 1/3 of the A549 cells showed a greater kf than NHDF,indicating that there was more reduced-GSH in A549 cells,which made it exhibited drug resistance.Finally,we clustered 702 single cells in combination with artificial intelligence deep learning.Although the information based on the two dimensions of cell size and cell redox state fails to accurately type the cells,the analytical method we propose undoubtedly provides a valuable reference for the analysis of single-cell heterogeneity. |
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