Differential Expression And Interaction In MicroRNA And Protein Of Neural Stem Cells And Motor Neurons

Spinal cord injury (SCI) produces its debilitating effects by the degeneration of specific neurons with subsequent functional loss. Cell replacement is a potential strategy for the treatment of SCI. Neural stem cells (NSCs) derived from spinal cord have been proposed as candidates for transplantation therapy in SCI. A key problem in using stem cell transplant for the treatment of SCI is how to make more of the NSCs differentiate into spinal motor neurons (MNs).MicroRNAs (miRNAs) are endogenous, approximately 23 nucleotide RNAs, and play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their post-transcriptional repression. They are involved in numerous cellular processes including development, proliferation, and differentiation. Recent studies indicate that miRNAs have an important role in regulating stem cell self-renewal and differentiation by selectively repressing the translation of specific mRNAs. To study the regulatory pathway of miRNA-gene in the differention of NSCs into MNs, we should first detect the protein difference between NSCs and MNs.In the present study, using the TaqMan low density array (TLDA) technique, we systematically investigated their differential expression of miRNA. Further, we compared the differential protein expression profiles with proteomic technology and identified several featured proteins whose expression matched the biological feature and function of NSCs and MNs. Finally, we integated the microRNA and proteomic data with microRNA gene-target prediction algorithms and generated a potential "interactome" regulatory network. These findings suggest that specially expressed microRNAs may contribute to the directed differentiation of neural stem cells into motor neurons and are potential targets for therapeutic interventions following spinal cord injury. The main aspects of this study are as followings:1. To culture MNs and NSCs from embryonic rat spinal cord. We developed a method allowing for isolation of highly purified rat MNs using immunomagnetic technology. P75-NGFR negative cells were used for the isolation of NSCs through the classical-neurosphere formation procedure. We developed an optimized and improved method to concomitantly isolate highly purified MNs and NSCs from the same sample of embryonic rat spinal cords. 2. To compare the profiling of miRNA expression between NSCs and MNs in embryonic spinal cord in rat. Using the TaqMan low density array (TLDA) technique, based on the quantitative real-time polymerase chain reaction (qPCR), we systematically investigated their differential expression of miRNA.95 differentially expressed microRNAs were identified in motor neurons,60 up-regulated expressed and 35 down-regulated expressed microRNAs. Using bioinformatic methods, clustering and transcriptional regulation of differential microRNAs were analyzed. Our analysis reveals that five miRNA clusters were predicted in MNs and NSCs, respectively. With the Ingenuity pathways analysis, we established one macromolecular network containing three sub-networks representing key functional units existing in the differential microRNAs in MNs.3. To analysis and to compare the proteomic differences between NSCs and MNs in embryonic spinal cord in rat and to discover the key different proteins. With the 2-D DIGE and HPLC-ESI-MS/MS, of the 87 selected protein spots,22 highly-expressed spots and 45 lowly-expressed spots were differentially expressed in MNs compared to NSCs. Further analysis revealed that 19 highly-expressed and 24 lowly-expressed proteins were identified in MNs. The results for ALDOC,STMN1,YWHAG from the proteomic experiment were validated with real-time PCR. Using the GenBank and Gene Ontology database, we obtain the biological process of these differently expressed proteins. With the Ingenuity pathways analysis, we established one protein network containing three sub-networks representing key functional units existing in the differential proteins in MNs.4. To establish the molecular network of miRNAs regulate protein. Using a computer-assisted approach, we first predicted the potential target genes for significantly changed miRNAs. Most of these target genes were predicted to encode transcription factors and enzymes. We identified microRNA-gene target pairs implicated in MN development by matching microRNA and protein data. With the Ingenuity pathways analysis, we established a regulatory network containing three sub-networks representing key functional units between differential microRNAs-and proteins.In conclusions:1. With miRNA profile, differential proteomics and bioinformatics, we detected and acquired the differentially expressed miRNAs and protein profiles between MNs and NSCs. By integrating microRNA, proteomic data and predicted target gene, we constructed the interactome regulatory network.2. By gain of function and/or loss of function methods of some key miRNAs, the special regulatory network of miRNA-mRNA will be activated and play an important role in the direted differention of NSCs into MNs.