Marker for sorting brain motor functional neural precursor cells and use thereof

Abstract

The application provides a marker for sorting brain motor functional neural precursor cells and application thereof, and belongs to the technical field of biological cells. The application provides application of KCNB2 and SEMA6D as protein markers in sorting brain motor functional neural precursor cells (BMFNPC). Cell sorting is performed by using the specific BMFNPC marker provided in the application, so that the cell purity of the BMFNPC can be significantly improved, batch difference can be reduced, and a high-purity and homogeneous BMFNPC cell population is obtained. The BMFNPC product prepared by using the sorting method provided in the application has high safety and effectiveness, and is conducive to transformation of the product to standardized and controllable clinical treatment.

Description

Technical Field

[0001] This invention belongs to the field of biological cell technology, specifically relating to a marker for sorting brain motor functional neural progenitor cells and its application. Background Technology

[0002] Existing methods for isolating tissue-derived neural stem cells have established a relatively standardized operational procedure. This procedure first involves obtaining the corresponding tissue fragments from the target tissue through precise micromanipulation. Then, the tissue is dissociated using enzymatic digestion (commonly collagenase, trypsin, etc.) combined with physical-mechanical methods (such as repeated pipetting and filtration) to obtain a mixed cell population. Next, the cells are cultured in serum-free medium supplemented with specific growth factors to selectively promote neural stem cell proliferation, and further purified and expanded through passage. Finally, the cells are identified using immunocytochemistry, typically using nestin as a characteristic marker of neural stem cells for confirmation. Further, after induction of differentiation, lineage-specific markers such as neurons and astrocytes are detected to assess their multi-lineage differentiation potential.

[0003] Current methods for obtaining tissue-derived neural stem cell populations using tissue block digestion and serum-free culture systems have fundamental limitations, namely, the high heterogeneity and insufficient controllability of cellular components. The obtained cells are not a homogeneous population, but rather a heterogeneous aggregate of target cells (neural progenitor cells) and various non-target cells (including astrocyte precursors, oligodendrocyte precursors, and fibroblasts). This inherent defect directly leads to two drawbacks: first, it is difficult to accurately enrich single cell subpopulations with specific functions, failing to meet the needs of targeted therapy for different disease types; second, the lack of effective sorting and quality control standards results in significant fluctuations in the proportion of different subpopulations in different batches of cell products, leading to poor batch-to-batch stability. Furthermore, different cell subpopulations have distinct secretory profiles: some highly express neurotrophic factors (such as BDNF and GDNF), while others tend to secrete inflammatory regulatory factors (such as IL-6 and TGF-β), and their exosome types and quantities also vary significantly. Therefore, when this mixed cell population is used for treatment, the observed overall effect (whether it is nerve regeneration, myelin repair, or immune regulation) is actually a combination of synergistic or antagonistic effects of multiple cells, and researchers cannot definitively attribute the therapeutic effect to a specific mechanism. This ambiguity in mechanistic research significantly reduces the reproducibility of experiments.

[0004] Furthermore, existing methods for isolating tissue-derived neural stem cells have yielded contradictory results in preclinical studies, with the same dosage and model showing different therapeutic effects. This makes it difficult to corroborate data and compromises reliability. In summary, the heterogeneity and non-reproducibility issues caused by inaccurate technology at the source (cell sorting methods) have become key obstacles hindering the standardization, evaluability, and safe and effective clinical translation of tissue-derived stem cell therapy. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide the application of KCNB2 and SEMA6D as protein markers in the sorting of brain motor functional neuroprogenitor cells (BMFNPC). Using the specific BMFNPC markers provided by this invention for cell sorting can significantly improve the cell purity of BMFNPC, reduce batch-to-batch variability, and obtain a high-purity, homogeneous BMFNPC cell population.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] This invention provides the application of KCNB2 and SEMA6D as protein markers in the sorting of neural progenitor cells for motor function in the brain.

[0008] The present invention also provides a brain motor functional neural progenitor cell, which is isolated from primary neural stem cells derived from brain tissue and expresses KCNB2 and SEMA6D.

[0009] The present invention also provides a method for sorting the above-mentioned brain motor functional neural progenitor cells, comprising the following steps: incubating primary neural stem cells derived from brain tissue with fluorescent antibodies KCNB2 and SEMA6D, adding DAPI for dead cell staining, and then performing live cell staining flow cytometry sorting.

[0010] Preferably, the purpose of the live cell staining flow cytometry sorting is to screen for live single cells that express KCNB2 and SEMA6D.

[0011] Preferably, the gating strategy for live cell staining flow cytometry sorting is: FSC-A vs SSC-A: live cell gate; FSC-H vs FSC-A: single cell gate; DAPI - Live cells; cells that are positive for both live and fluorescent antibodies.

[0012] Preferably, after sorting, the cells are cultured and passaged using serum-free complete neural stem cell culture medium, which consists of DMEM / F12, 2% B27 supplement, 1% N2 supplement, 20 ng / mL LFGF and 20 ng / mL EGF.

[0013] The present invention also provides the application of the above-mentioned brain motor functional neural progenitor cells or the above-mentioned method in any of the following: (1) preparing products for the prevention and / or treatment of Parkinson's disease; (2) preparing products for the repair of dopaminergic neuron damage.

[0014] The present invention also provides a kit for sorting brain motor functional neural progenitor cells, the kit comprising KCNB2 antibody and SEMA6D antibody.

[0015] This invention also provides the application of reagents for detecting KCNB2 and SEMA6D in the sorting of motor functional neural progenitor cells in the brain.

[0016] The beneficial effects of this invention are:

[0017] Using the specific BMFNPC markers provided by this invention for cell sorting can significantly improve the cell purity of BMFNPC, reduce batch-to-batch variability, and obtain a high-purity, homogeneous BMFNPC cell population.

[0018] The BMFNPC product prepared using the sorting method provided in this invention has high safety and efficacy, which is conducive to its transformation into standardized and controllable clinical treatment. Attached Figure Description

[0019] Figure 1 UMAP diagram of BMFNPC cells in single-cell transcriptional sequencing analysis;

[0020] Figure 2 ROC curves for gene markers in target cells (BMFNPC) and various non-target cells;

[0021] Figure 3 The identification results of BMFNPC cells obtained in Example 3;

[0022] Figure 4 The results of cell-specific gene detection in different groups are from Example 3. This indicates that p < 0.01;

[0023] Figure 5 The results of the differentiation ability test in Example 3;

[0024] Figure 6The identification results of BMFNPC cells obtained in Example 4;

[0025] Figure 7 The results of cell-specific gene detection in different groups are from Example 4. This indicates that p < 0.01. This indicates that p < 0.0001;

[0026] Figure 8 The results of differentiation ability testing are from Example 4;

[0027] Figure 9 The results are from the APO rotation test, where This indicates that p < 0.05;

[0028] Figure 10 The results of the step test are as follows, in which This indicates that compared to the sham control group, This indicates that p < 0.05. This indicates that p < 0.01. # indicates p < 0.001; # indicates p < 0.05 compared to the model control group;

[0029] Figure 11 The images show the results of detecting the levels of neurotransmitters and their metabolites in the striatum. The left image shows the detection results of the neurotransmitter dopamine (DA) in the striatum, and the right image shows the detection results of the metabolite dopamine, dopamine octopus (DOPAC). Compared with the sham control group, # indicates p < 0.001; # indicates p < 0.01 compared to the model control group, ## indicates p < 0.01, and ### indicates p < 0.001. Detailed Implementation

[0030] This invention provides the application of at least one of KCNB2, SEMA6D, GNAQ and GAP43 as a protein marker in the sorting of neural progenitor cells for motor function in the brain.

[0031] In this invention, a specific population of neural cells enriched in midbrain samples and highly expressing ROBO1 is defined as Brain Motor Functional Neuroprogenitor Cells (BMFNPCs). Existing methods for isolating and preparing BMFNPCs have significant drawbacks. The core problem with traditional methods lies in the lack of specific identification and precise separation techniques for BMFNPCs. Because their unique cell surface markers cannot be effectively used for sorting, the resulting population is typically a heterogeneous mix of BMFNPCs, other neural progenitor cells, and non-target cells. This ambiguity in cell composition directly leads to two serious consequences: first, low cell purity, making it difficult to obtain homogeneous cell populations with single functions; second, significant batch-to-batch variations in the composition and proportion of cell products. This uncertainty in starting materials poses a significant challenge to downstream basic research and clinical applications. In animal model experiments, the functional improvements (such as recovery of motor function) observed after transplantation of these heterogeneous cells are difficult to trace through their therapeutic mechanisms. The inability to determine whether BMFNPC itself plays a dominant role, or whether it is the result of synergistic or interfering effects from other confounding cells, means that therapeutic efficacy cannot be attributed to a single cell type, leading to ambiguous experimental conclusions and poor reproducibility. Ultimately, the safety and efficacy of cell products prepared using existing technologies cannot be consistently guaranteed, becoming a fundamental bottleneck restricting their transformation into standardized and controllable clinical treatments. The technical solution proposed in this invention can specifically identify and accurately sort BMFNPC, successfully solving the aforementioned technical problems currently existing in this field.

[0032] In this invention, KCNB2 (encoding the Kv2.2 channel) is highly expressed in midbrain dopaminergic neurons (such as the substantia nigra pars compacta) and midbrain motor-related nuclei (such as the red nucleus). It regulates neuronal excitability by delaying rectified potassium current, influencing motor initiation and coordination. During development, the Kv2.2 channel participates in setting the electrophysiological maturation time window of midbrain neurons and assists in guiding precise targeting of cortical-midbrain projections, supporting the formation of motor circuits. SEMA6D is enriched in midbrain dopaminergic neuron axons and midbrain tegmental neurons. Through its extracellular Ig-Plexin domain binding to receptors such as Plexin-A1, it transmits repulsive or attractive signals, regulating axonal guidance and branching. During the embryonic period, SEMA6D guides the path selection of midbrain projection axons by establishing local concentration gradients, preventing them from mistakenly entering adjacent sensory nuclei, thereby ensuring the independence and accuracy of motor-related circuits. GNAQ (encoding the Gαq subunit) is highly expressed in midbrain dopaminergic neurons, midbrain motor area glutamatergic neurons, and their dendrites, and activates PLCβ-IP3-Ca. 2+Signal cascades regulate intraneuronal calcium dynamics and synaptic plasticity. During development, the Gαq signaling pathway participates in the midbrain Lmx1a... + The proliferation, differentiation, and dopaminergic neuronal subtype specialization of precursor cells are crucial for the establishment of the midbrain motor regulatory system. GAP43 is persistently highly expressed in motor-related axons in midbrain dopaminergic pathways (such as the substantia nigra-striatal tract) and the rubra-spinal tract, promoting axonal elongation, pathway finding, and synapse formation by regulating F-actin dynamics and membrane curvature within the growth cone. During injury or development, upregulation of GAP43 expression can enhance midbrain axonal regeneration and presynaptic plasticity, supporting the functional repair and remodeling of motor circuits.

[0033] This invention also provides a biomarker for sorting brain motor functional neural progenitor cells, comprising at least one of KCNB2, SEMA6D, GNAQ, and GAP43. This invention does not specifically limit the source of KCNB2, SEMA6D, GNAQ, and GAP43; commercially available products conventional in the art can be used. In this invention, the biomarker preferably consists of at least two of these components, more preferably KCNB2 and SEMA6D, or GNAQ and GAP43.

[0034] This invention also provides a brain motor function neural progenitor cell, obtained by sorting from primary neural stem cells derived from brain tissue, and expressing the aforementioned markers. In this invention, the sorting method preferably includes live-cell staining flow cytometry sorting or magnetic bead sorting.

[0035] The present invention also provides a method for sorting the above-mentioned brain motor functional neural progenitor cells, comprising the following steps: incubating primary neural stem cells derived from brain tissue with fluorescent antibodies of the above-mentioned markers, adding DAPI for dead cell staining, and then performing live cell staining and flow cytometry sorting.

[0036] In this invention, the purpose of the live cell staining flow cytometry sorting is preferably to screen for live single cells that express the aforementioned markers. The preferred gating strategy for the live cell staining flow cytometry sorting is: FSC-A vs SSC-A: live cell gate; FSC-H vs FSC-A: single cell gate; DAPI -Live cells; cells positive for both fluorescent antibodies. After sorting, cells were cultured and passaged using serum-free neural stem cell complete culture medium, which consisted of DMEM / F12, 2% B27 supplement, 1% N2 supplement, 20 ng / mL FGF, and 20 ng / mL EGF. This invention does not specifically limit the source of each ingredient in the above culture medium; commercially available products commonly used in the field are acceptable. In this invention, the fluorescent markers on the biomarker antibodies preferably include FITC and PE.

[0037] In this invention, the preferred method for preparing primary neural stem cells derived from brain tissue includes the following steps: isolating midbrain tissue from brain tissue; digesting the midbrain tissue with a digestive solution, discarding the supernatant, adding DMEM / F12 culture medium, and agitating to separate the tissue; centrifuging and discarding the supernatant, adding tissue preservation solution, agitating to form a single-cell suspension, filtering through a 100μm sieve to obtain primary neural stem cells derived from brain tissue. In this invention, the digestive solution is preferably TryPLE (Gibco, 12604021); the tissue preservation solution is preferably MCE HY-K6010. This invention does not specifically limit the method for isolating midbrain tissue from brain tissue; conventional methods in the art can be used. In an embodiment of this invention, the digestion method for midbrain tissue is specifically as follows: centrifuging the isolated midbrain tissue at 300g at room temperature for 1 minute, discarding as much supernatant as possible, weighing, and subtracting the weight of the centrifuge tube to calculate the tissue weight (0.11g). Add 5 mL of digestion solution (TryPLE, Gibco, 12604021) to a centrifuge tube and gently shake. Place the centrifuge tube in a 35°C CO2 incubator for digestion, manually shaking every 5 minutes for 15 minutes. After digestion, centrifuge at 500g for 3 minutes at room temperature. Aspirate the supernatant to the 100μL mark using a sterile disposable pipette. Add 5 mL of DMEM / F12 culture medium and pipette up and down 3 times to separate the tissue. Centrifuge at 500g for 3 minutes at room temperature. Aspirate the supernatant to approximately 50μL using a sterile disposable pipette. Add 950μL of tissue preservation solution (MCE, HY-K6010) to the centrifuge tube using a 1ml pipette tip and gently pipette up and down 10-15 times to form a single-cell suspension. Filter through a 100μm sieve to obtain primary neural stem cells derived from brain tissue.

[0038] The present invention also provides the application of the above-mentioned brain motor functional neural progenitor cells or the above-mentioned method in any of the following: (1) preparing products for the prevention and / or treatment of Parkinson's disease; (2) preparing products for the repair of dopaminergic neuron damage.

[0039] This invention also provides a kit for sorting brain motor functional neural progenitor cells, the kit comprising at least one of KCNB2 antibody, SEMA6D antibody, GNAQ antibody, and GAP43 antibody. This invention does not specifically limit the source of the KCNB2 antibody, SEMA6D antibody, GNAQ antibody, and GAP43 antibody; commercially available products in the art can be used.

[0040] This invention also provides the application of detection reagents for the above-mentioned biomarkers in the sorting of functional motor progenitor cells of the brain. In this invention, the detection reagents for the above-mentioned biomarkers are preferably fluorescent antibodies or magnetic bead antibodies against the above-mentioned biomarkers.

[0041] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0042] Unless otherwise specified, the following embodiments are all conventional methods.

[0043] Unless otherwise specified, all materials and reagents used in the following examples are commercially available.

[0044] Example 1

[0045] The process of obtaining the marker of this invention

[0046] Single-cell transcriptome sequencing analysis

[0047] Single-cell sequencing experimental principle:

[0048] Single-cell transcriptome sequencing was commissioned to Xunyin Biotechnology Co., Ltd. Single-cell capture was performed using a microfluidic chip based on the 10×GenomicsChromium system within hydrogel beads (GEMs). Each bead carried a 10× barcode and a UMI (Unique Molecular Identifier) ​​Oligo(dT) probe, which could bind complementary to the polyA tail of mRNA. Simultaneously, each droplet contained only one cell, ensuring that the transcript was specifically barcode-tagged. Immediately after droplet formation, cells were lysed, and the released mRNA was captured by the Oligo(dT) probe on the bead and reverse transcribed within the same droplet, generating the first strand of cDNA with a 10× barcode, UMI, and TSO (Template Switch Oligo) sequence. The droplets were then broken, all cDNAs were collected, and library enrichment was performed by PCR amplification. The amplified products were concentrated in the 200–400 bp range. The amplified cDNA underwent fragmentation, end repair, A-tail ligation, adapter ligation, and secondary PCR before being introduced into the sample index, resulting in libraries from different samples carrying distinguishable sequencing tags. A qualified library has a main peak fragment size between 350 and 750 bp and contains no small fragments. If small fragments are present, a second purification process is performed until no small fragments are found (Agilent 4200 TapeStation); the library concentration is not less than 1 ng / μL (measured using Qubit 4.0). High-throughput sequencing of 150 bp paired ends (PE150) was performed using the Illumina sequencing platform, with ≥50,000 reads per cell to ensure the accuracy of single-cell sequencing data analysis.

[0049] Reference databases: NCBI, Ensembl, human cell atlas (HCA), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology Resource (GO), The human protein atlas (HPA).

[0050] Test procedure:

[0051] 1. Sample:

[0052] The test samples were human neural stem cells isolated from primary tissues, from three donor sources, with four tissue sites (cortex, hippocampus, midbrain, and spinal cord) isolated from each source, totaling 12 batches of cells.

[0053] 2. Sample processing:

[0054] The processed samples (human neural stem cells) were captured as single cells in oil-in-water gel beads (GEMs) using a 10×Genomics Chromium microfluidic chip. Each droplet contained only one cell. Immediately after droplet formation, the cells were lysed, and the released mRNA was captured by Oligo(dT) probes on the gel beads. Reverse transcription was then performed within the same droplet, generating a first-strand cDNA with 10×Barcode, UMI, and TSO (Template Switch Oligo) sequences. The droplets were then broken, and all cDNAs were collected and enriched by PCR amplification. The amplified products were concentrated in the 200–400 bp range. The amplified cDNA underwent fragmentation, end repair, A-tail ligation, adapter ligation, and a second PCR before being introduced into the sample index, giving the libraries from different samples distinguishable sequencing tags. Qualified libraries had a main peak fragment size between 350–750 bp and no small fragments. If small fragments are present, a second purification process is performed until no small fragments are found (Agilent 4200 TapeStation); the library concentration is not less than 1 ng / μL (measured using Qubit 4.0). High-throughput sequencing of 150 bp paired ends (PE150) is performed using the Illumina sequencing platform, with ≥50,000 reads per cell to ensure the accuracy of single-cell sequencing data analysis.

[0055] 3. Parameterized transcriptome analysis workflow:

[0056] The raw image files obtained from high-throughput sequencing were converted into sequencing reads by CASAVA base recognition and stored in FASTQ format. The sequencing adapters and low-quality fragments in the data were processed using fastp software (Chen S, Zhou Y, Chen Y, Gu J.fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018 Sep1;34(17):i884-i890. doi: 10.1093 / bioinformatics / bty560. PMID: 30423086;PMCID: PMC6129281.). (A sliding window method was used, with 4 bases per window. If the average base quality value of the window was less than 10, the reads were truncated from that point. Reads with a tail quality of less than 3 or containing N (N indicates that the base information cannot be determined) were truncated. Reads shorter than 60 bp and their paired reads were filtered out.) CellRanger was used to perform quality control on the filtered data. Each read obtained from sequencing was labeled with a barcode and a UMI. Reads with the same barcode came from the same cell; and among the data from the same cell, reads with the same UMI came from the same molecule.The STAR (Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, ​​Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013 Jan 1;29(1):15-21. doi: 10.1093 / bioinformatics / bts635. Epub 2012 Oct 25. PMID: 23104886; PMCID: PMC3530905.) software was used to align the sequencing data labeled with barcodes and UMIs to the GRCh38 version of the human reference genome provided by NCBI. Then, feature Counts (Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014 Apr) software was used to align the sequencing data labeled with barcodes and UMIs to the GRCh38 version of the human reference genome provided by NCBI. 1;30(7):923-30. doi: 10.1093 / bioinformatics / btt656.Epub 2013 Nov 13. PMID: 24227677.) The expression profile was statistically analyzed using software. Reads with the same barcode and the same UMI were repeated sequencing data of the same molecule. They were merged during the statistical analysis to obtain a preliminary cell-gene expression matrix.

[0057] The initial expression matrix contained data from both cells and non-cells (background). After further filtering, the expression matrix for cells was obtained. The initial expression matrix was filtered using the Cell Ranger and EmptyDrops (Lun ATL, Riesenfeld S, Andrews T, Dao TP, Gomes T; participants in the 1st Human Cell Atlas Jamboree; Marioni JC. EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data. Genome Biol. 2019 Mar 22;20(1):63. doi: 10.1186 / s13059-019-1662-y. PMID: 30902100; PMCID: PMC6431044.) analysis methods. First, a desired number of cells (N, default 3000) is specified. Then, the barcodes are sorted from highest to lowest based on their total number of UMIs. Filtering is performed using two methods: First, the 99th percentile of the top N UMI values ​​is taken as the maximum estimated total number of UMIs (m), and barcodes with UMIs exceeding m / 10 are considered the final captured cells. Second, RNA expression characteristics are used to distinguish cells from the background; this method can identify cells with low RNA expression levels. The cell expression data obtained from both methods are merged to obtain complete cell expression data for subsequent analysis.

[0058] The cell expression matrix was further filtered using the Seurat package (Butler, A., Hoffman, P., Smibert, P. et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol 36, 411–420 (2018). https: / / doi.org / 10.1038 / nbt.4096) to remove cells with excessively low UMI numbers and excessively high mitochondrial proportions. After filtering out low-quality cells, the CCA method was used to merge samples and remove batch effects. Clustering and result visualization were performed using Seurat (Butler, Hoffman et al. 2018): the LogNormalize command was used to normalize the gene expression data to remove differences in gene expression caused by varying data volumes during sequencing. Using FindVariableFeatures, 2000 highly variable genes were selected for subsequent data dimensionality reduction. Linear scaling was used to standardize the data. PCA was used for dimensionality reduction. Based on the principal component analysis results, the top 15 PCs were selected, and the data was clustered using a graph-based clustering algorithm. UMAP nonlinear dimensionality reduction was used to visualize the data, resulting in 35 cell subpopulations. Differential expression analysis was performed using the FindMarkers function to obtain a list of marker genes for each cell subpopulation. The cell subpopulations were manually annotated based on the SingleR and CellTypist databases and common neural cell gene annotation reference sets, ultimately identifying multiple cell types including microglia, radial glial cells, intermediate progenitor cells, oligodendrocytes, astrocytes, neurons, and neural progenitor cells.

[0059] Among these cell populations, a special group of neural cells highly expressing ROBO1 was found and enriched in midbrain samples. The gene expression matrix of this special neural cell population was extracted, and enrichment analysis was performed using ClusterProfiler software. The generated data is presented in an Excel spreadsheet. The enrichment results revealed that many genes were significantly enriched in pathways related to motor control, synapsis, and projection differentiation, totaling 105 key pathways and 195 related genes. This invention defines this cell group as Brain Motor Functional Neuroprogenitor Cells (BMFNPC).

[0060] The UMAP diagram of BMFNPC cells in single-cell transcription sequencing analysis is shown below. Figure 1 As shown, examples of pathway enrichment are presented in Table 1.

[0061] Table 1 Examples of Pathway Enrichment

[0062]

[0063] Human protein atlas data were obtained from the HPA (Human Protein Atlas) database. By comparing the 195 gene entries mentioned above, a list of membrane protein genes, totaling 47 genes, was obtained. Based on the list of marker genes, genes that were significantly differentially expressed in BMFNPC were selected. Finally, a combination of four protein genes with high expression levels that could be used for live cell flow cytometry sorting was selected, as shown in Table 2, which can be used to sort BMFNPC cells.

[0064] Table 2 shows four marker genes that can be used for live-cell flow cytometry sorting to obtain BMFNPC.

[0065]

[0066] Example 2

[0067] ROC curves of four gene markers from target cells (BMFNPC) and five non-target cell types.

[0068] Based on single-cell transcriptome data, KCNB2, SEMA6D, GNAQ, and GAP43 were validated to have high specificity and sensitivity in distinguishing target cells (BMFNPC) from various non-target cells, thus proving that each gene can independently serve as a specific molecular marker for identifying or detecting BMFNPC.

[0069] The data used in the analysis were derived from single-cell RNA sequencing of BMFNPC, endothelial cells, erythrocytes, mesenchymal stem cells, microglia, and unseparated primary cells. This dataset provides a complete transcriptome expression profile for each single cell. Normalized expression levels of the KCNB2, SEMA6D, GNAQ, and GAP43 genes were obtained from the single-cell sequencing data.

[0070] ROC curve analysis:

[0071] To independently quantify the ability of each gene to distinguish BMFNPC, the following steps were used for ROC analysis:

[0072] (1) BMFNPC cells were defined as “positive” samples, and each non-target cell type (endothelial cells, erythrocytes, mesenchymal stem cells, microglia, and unisolated primary cells) was defined as a “negative” sample, forming five independent control groups.

[0073] (2) For each gene to be evaluated, its expression level in "positive" and "negative" samples is used as a diagnostic indicator.

[0074] (3) Using statistical analysis software, for each gene in each comparison group, ROC curves were plotted independently with cell type as the state variable and the expression level of the gene as the test variable.

[0075] (4) Calculate the area under the curve (AUC) of each ROC curve. The AUC value directly measures the classification power of the gene in the specific comparison: AUC = 0.5 indicates no discrimination ability, and AUC = 1.0 indicates perfect discrimination (ROC curve is derived by comparing the expression levels of gene markers in the target cell and various non-target cells. The AUC value is the area under the ROC curve. The larger the AUC value, the greater the difference in the expression level of the gene in the two types of cells, and the easier it is to distinguish between the two types of cells).

[0076] Independent ROC analyses were performed on the four genes in five comparison groups, yielding a total of 20 quantitative results. Key data and conclusions are as follows:

[0077] The KCNB2, SEMA6D, GNAQ, and GAP43 genes all independently demonstrated good discriminative power in distinguishing BMFNPC from all five types of non-target cells. The AUC values ​​of all 20 ROC curves were greater than 0.75, with over 70% of the comparative AUC values ​​greater than 0.90 (see Table 3). This demonstrates that the biomarker genes possess the ability to distinguish BMFNPC from complex cellular backgrounds with high precision.

[0078] Table 3. AUC values ​​of 20 ROC curves

[0079]

[0080] ROC curves of gene markers of target cells (BMFNPC) and various non-target cells are shown below. Figure 2 As shown, a total of 20 curves are displayed, each corresponding to the performance of a gene in a specific comparison. All curves significantly deviate from the diagonal and tend towards the upper left corner, visually verifying the strong independent discriminative ability of each gene. The results indicate that using four specific gene markers (KCNB2, SEMA6D, GNAQ, and GAP43) can effectively distinguish target cells (BMFNPC) from other cells, and can serve as a high-performance strategy for BMFNPC purification.

[0081] Example 3

[0082] BMFNPC was prepared by sorting using KCNB2 and SEMA6D.

[0083] 1. Primary neural stem cells derived from human brain tissue (approved by the Medical Ethics Committee of Shanghai Oriental Hospital, ethics approval number

[2022] Research and Review No. (072)) were isolated, digested and prepared, and resuspended in DMEM / F12 medium to 3 mL for cell counting.

[0084] The counting results are shown in Table 4.

[0085] Table 4. Cell count results after tissue digestion

[0086]

[0087] 2. Live cell staining and flow cytometry sorting

[0088] 2.1 Antibody incubation: Add the antibody shown in Table 5 to each tube and use it according to the instructions. After incubation, wash twice (400g×5min, 4℃).

[0089] Table 5 Information on antibodies added during incubation

[0090]

[0091] 2.2 Staining of dead cells: Add DAPI (0.5 μg / mL) and incubate at 4℃ for 10 min.

[0092] 2.3 Sorting Settings:

[0093] Instrument: FACSAria III (Nozzle: 85 μm; Pressure: 45 psi; Temperature: 4 °C)

[0094] Gating strategy:

[0095] FSC-A vs SSC-A: Live Cell Phylum

[0096] FSC-H vs FSC-A: Single Cell

[0097] DAPI - Live cells

[0098] FITC + PE + Double-positive cells

[0099] Collection method: Single-cell mode, collected in DMEM / F12.

[0100] 3. Post-sorting cultivation

[0101] Immediately after sorting, the cells were centrifuged and resuspended in 2 mL of complete culture medium (the complete culture medium referred to here is a self-prepared serum-free neural stem cell complete culture medium, composed of DMEM / F12 + 2% B27 supplement + 1% N2 supplement + 20 ng / mL FGF + 20 ng / mL EGF). The counting results are shown in Table 6.

[0102] Table 6. Counting results after sorting

[0103]

[0104] Based on the counting results, the following preparation process was carried out: according to 1.0~1.5×10 5 Inoculation concentration of 1 inoculum per mL was used to inoculate the bottles, and the bottles were incubated in a carbon dioxide incubator at 35°C and 5% CO2 concentration. Harvesting time is determined based on the size of the neurospheres (generally, the diameter of the neurospheres should not exceed 400 μm). The addition of medium (the medium used for adding medium here and subsequent medium changes is a self-prepared serum-free complete neural stem cell culture medium, the specific composition of which is shown above) should be performed 2-3 days and 4-5 days after inoculation. Medium changes should be performed 7-8 days and 10-12 days after inoculation. When the diameter of the neurospheres reaches 200-400 μm, the neurospheres are collected and digested (add 5 mL of digestion solution (TryPLE, Gibco, 12604021) to a centrifuge tube, then gently shake. Place the centrifuge tube in a 35℃ CO2 incubator for digestion for 12-15 minutes, gently shaking every 3 minutes. Centrifuge at 300g for 1 minute. After centrifugation, resuspend the cells in an appropriate amount of DMEM / F12 medium, centrifuge again at 500g for 3 minutes, and repeat twice. The collected cells are recorded as generation P0.

[0105] P0 generation cells can be stably passaged by culturing and passaged according to the above preparation process.

[0106] 4. Cell (P9 generation) identification

[0107] The cell characteristics of the P9 generation cells obtained after sorting and culture were analyzed as follows.

[0108] 4.1 Cell viability assay:

[0109] 4.1.1 Instruments and Equipment: Cell Fluorescence Counter

[0110] 4.1.2 Operating Procedures:

[0111] Pre-dilute the cell suspension as needed, resuspend it, take an appropriate amount of cell suspension and mix it with the staining solution at a 1:1 ratio, add it to the counting chamber, read the value, repeat the counting twice, and take the average value.

[0112] 4.1.3 The test results are shown in Table 7.

[0113] Table 7 Results of cell viability assay

[0114]

[0115] 4.2 Cell Identification

[0116] 4.2.1 Cell Identification

[0117] 4.2.1.1 Instruments and Equipment: Carbon dioxide incubator, fluorescence inverted microscope

[0118] 4.2.1.2 Operating Procedures:

[0119] Cell culture: Seed the P9 generation cell suspension onto a pre-coated culture plate, change the culture medium every 2 days, culture for 3-5 days, and then terminate the culture.

[0120] Cell fixation: Remove the cell culture plate, wash with DPBS, fix each well with 1 mL of 4% paraformaldehyde fixative at room temperature for 10-20 min, wash with PBS 3 times, 5 min each time.

[0121] Cell blocking: Add 500 μL of 5% BSA / 0.25 PBST to each well and block at room temperature for 1 hour.

[0122] Add primary antibody working solution: Add 500 μL of primary antibody working solution to each well and react overnight at 4°C; wash 3 times with PBS for 5 min each time.

[0123] Add secondary antibody working solution: Add 500 μL of secondary antibody working solution to each well, incubate at room temperature in the dark for 1 hour, and wash 3 times with PBS for 5 min each time.

[0124] Nuclear staining: Add DAPI and react at room temperature for 15 min, then wash with PBS 3 times, 5 min each time.

[0125] Photographs: Transfer the sample to a fluorescence microscope for observation and photographs.

[0126] 4.2.1.3 Test results are as follows Figure 3 As shown, the BMFNPC marker (ROBO1) was positive, with a positive rate of ≥90%.

[0127] 4.2.2 Specific gene detection

[0128] 4.2.2.1 Instruments and equipment: Real-time quantitative PCR instrument, micro spectrophotometer, water bath.

[0129] 4.2.2.2 Reagents: HiScript® III ALL-in-one RT SuperMix Perfect for qPCR, AceQ qPCR SYBR Green I Master mix, Trizol, chloroform, isopropanol, 75% ethanol, RNase-free ddH2O.

[0130] 4.2.2.3 Operating Procedures:

[0131] Sample preparation: Experimental group: HN2302101M P9 single-cell suspension, cell count 2.5 × 10⁻⁶ 6 Control group: Unsorted HN2302101M P9 cell suspension after culture (preparation method as described in steps 1 and 2 above), cell count: 2.5 × 10⁻⁶. 6 ; Mesenchymal stem cell P9 generation (MSC-P9) suspension (umbilical cord blood-derived mesenchymal stem cells, Gibco, StemPro™ MSC SFM XenoFree medium, adherent culture, passage expansion), cell number: 2.5 × 10⁻⁶ 6 indivual.

[0132] RNA extraction: After centrifuging the cells and discarding the supernatant, add 1 mL of Trizol and mix well. Add 0.2 mL of chloroform (trichloromethane), vortex vigorously to mix, and let stand for 5 min before centrifuging (parameters: 12000g, 15 min, 4℃). Slowly aspirate approximately 400 μL of supernatant to a new EP tube, add an equal volume of 400 μL of pre-chilled isopropanol, invert to mix for 15 s, let stand for 10 min, and then centrifuge and discard the supernatant (parameters: 12000g, 15 min, 4℃). Add 1 mL of 75% ethanol to the precipitate, wash the precipitate, or directly aspirate the 75% ethanol, or centrifuge and discard the supernatant (parameters: 7500g, 5 min, 4℃), and let stand to dry.

[0133] RNA concentration determination: Dissolve RNA in 20-50 μL of nuclease-free water and determine the RNA concentration.

[0134] Reverse transcription of cDNA: Transfer 1 μg total RNA, 1 μL Enzyme Mix, and 4 μL 5×ALL-in-one qRT SuperMix to prepare a 20 μL reaction system. Make up the insufficient volume with RNase-free ddH2O for reverse transcription. Reaction program: 50℃, 15 min; 85℃, 5 sec.

[0135] qPCR preparation: Transfer 2 μL of cDNA, 4 μL of forward and reverse primers, and 10 μL of SYBR qPCR Master Mix to prepare a 20 μL reaction mixture. Make up the difference with RNase-free ddH2O if necessary. Perform qPCR according to the Mix instruction manual. The primer sequences used for qPCR are shown in Table 8, with GAPDH as an internal control. The reaction program is shown in Table 9.

[0136] Table 8 Primer sequences

[0137]

[0138] Table 9 Reaction Procedure

[0139]

[0140] Data processing: Summarize Ct values ​​and calculate 2. -△△Ct .

[0141] 4.2.2.4 Test Results:

[0142] Using unsorted human midbrain stem cells cultured to passage P9 as a baseline, we compared and detected sorted and cultured BMFNPC-P9 passage cells with mesenchymal stem cell passage P9 cells. The results are as follows: Figure 4 As shown, compared with pre-sorted cells and mesenchymal stem cells, the specific marker set genes (KCNB2, SEMA6D) are significantly highly expressed in sorted BMFNPC cells, which can specifically label BMFNPC cells.

[0143] 4.2.3 Differentiation capacity test

[0144] 4.2.3.1 Instruments and equipment: CO2 incubator, fluorescence inverted microscope.

[0145] 4.2.3.2 Operating Procedures:

[0146] Cell culture: Seed the P9 generation cell suspension onto pre-coated culture plates, change the differentiation medium every 2 days, culture for 10-14 days, and then terminate the culture.

[0147] Cell fixation: Remove the cell culture plate, wash with DPBS, fix each well with 1 mL of 4% paraformaldehyde fixative at room temperature for 10-20 min, wash with PBS 3 times, 5 min each time.

[0148] Cell blocking: Add 500 μL of 5% BSA / 0.25 PBST to each well and block at room temperature for 1 hour.

[0149] Add primary antibody working solution: Add 500 μL of primary antibody working solution to each well and react overnight at 4°C; wash 3 times with PBS for 5 min each time.

[0150] Add secondary antibody working solution: Add 500 μL of secondary antibody working solution to each well, incubate at room temperature in the dark for 1 hour, and wash 3 times with PBS for 5 min each time.

[0151] Nuclear staining: Add DAPI and react at room temperature for 15 min, then wash with PBS 3 times, 5 min each time.

[0152] Photographs: Transfer the sample to a fluorescence microscope for observation and photographs.

[0153] 4.2.3.3 Test Results:

[0154] like Figure 5 As shown, the positive rate of neuronal marker (beta3-Tubulin) is ≥90%, the positive rate of dopaminergic neuron marker (Tyrosine Hydroxylase) is ≥50%, and BMFNPC cells can differentiate into dopaminergic neurons.

[0155] Example 4

[0156] BMFNPC was prepared by sorting using GNAQ and GAP43.

[0157] 1. The difference from step 1 of Example 3 is that the final resuspending volume is 5 mL, while the rest is the same as step 1 of Example 3. The counting results are shown in Table 10.

[0158] Table 10 Cell count results after tissue digestion

[0159]

[0160] 2. Live cell staining and flow cytometry sorting

[0161] 2.1 Antibody incubation: Add the antibody shown in Table 11 to each tube and use it according to the instructions. After incubation, wash twice (400g×5min, 4℃).

[0162] Table 11 Information on antibodies added during incubation

[0163]

[0164] 2.2 Staining of dead cells: Same as step 2.2 in Example 3.

[0165] 2.3 Sorting settings: Same as step 2.3 in Example 3.

[0166] 3. Post-sorting cultivation: Same as step 3 in Example 3. The counting results are shown in Table 12.

[0167] Table 12 Counting Results After Sorting

[0168]

[0169] 4. Cell (P9 generation) identification

[0170] The cell characteristics of the P9 generation cells obtained after sorting and culture were analyzed as follows.

[0171] 4.1 Cell viability detection: Same as section 4.1 of Example 3, the detection results are shown in Table 13.

[0172] Table 13 Results of cell viability assay

[0173]

[0174] 4.2 Cell Identification

[0175] 4.2.1 Cell identification: Same as section 4.2.1 of Example 3.

[0176] The results of cell identification testing are as follows Figure 6 As shown, the BMFNPC marker (ROBO1) was positive, with a positive rate of ≥90%.

[0177] 4.2.2 Specific gene detection

[0178] The difference from section 4.2.2 in Example 3 is as follows:

[0179] Sample preparation: Experimental group: HN2408121M P9 single-cell suspension, cell count: 2.5 × 10⁻⁶ 6 Control group: Unsorted HN2408121MP9 cell suspension after culture, cell count: 2.5 × 10⁻⁶. 6 One; a suspension of mesenchymal stem cell P9 generation (MSC-P9) cells, with a cell count of 2.5 × 10⁶ cells. 6 indivual.

[0180] The primer sequences used for qPCR are shown in Table 14:

[0181] Table 14 Primer Sequences

[0182]

[0183] The remaining steps are the same as those in section 4.2.2 of Example 3.

[0184] Using unsorted human midbrain stem cells cultured to passage P9 as a baseline, we compared and detected sorted and cultured BMFNPC-P9 passage cells with mesenchymal stem cell passage P9 cells. The results are as follows: Figure 7As shown, compared with pre-sorted cells and mesenchymal stem cells, the specific marker set genes (GNAQ, GAP43) are significantly highly expressed in sorted BMFNPC cells, which can specifically label BMFNPC cells.

[0185] 4.2.3 Differentiation ability test:

[0186] Same as section 4.2.3 of Example 3, the results are as follows: Figure 8 As shown, the positive rate of neuronal marker (beta3-Tubulin) is ≥90%, the positive rate of dopaminergic neuron marker (Tyrosine Hydroxylase) is ≥50%, and BMFNPC cells can differentiate into dopaminergic neurons.

[0187] Example 5

[0188] Study on the therapeutic effect of BMFNPC cells on 6-OHDA Parkinson's disease rats

[0189] 1. Preparation of laboratory animals:

[0190] Thirty male Sprague-Dawley (SD) rats, weighing 200–220 g, were used. The animals were anesthetized with sodium pentobarbital (32 mg / kg; administered intraperitoneally). The anesthetized rats were fixed on a stereotaxic instrument. Based on the rat's stereotaxic atlas, with the anterior fontanelle as the zero point, the coordinates (two points) of the left medial forebrain fasciculus (MFB) were determined: aneroposterior (AP), -1.8 mm; mediolateral (ML), -2.5 mm; dorsoventral (DV), -7.5 mm and aneroposterior (AP), -1.8 mm; mediolateral (ML), -2.5 mm; dorsoventral (DV), -8.0 mm. The skull skin was incised, and the skull was drilled open. 16 μg of 6-OHDA (8 μg / 4 μL / point) or an equal volume of physiological saline was injected slowly at a rate of 0.5 μL / min, with the needle retained for 4 min. After the injection, the needle was slowly withdrawn, the incision was sutured, and erythromycin was applied to the incision to prevent infection. Postoperatively, the rats were observed to be awake and able to move freely.

[0191] Four weeks after the modeling surgery, an apomorphine-induced rotation test was performed to determine the success of the model. Rats with successful models were selected for further experiments. Apomorphine (APO) is a DA receptor agonist that induces rotation towards the contralateral side (healthy side) of the injury. A subcutaneous injection of 0.25 mg / kg was administered into the neck. After injection, the rats were placed in a circular basin, and the number of rotations towards the contralateral side (healthy side) was observed over 30 minutes. A model is considered successful if the number of rotations in 30 minutes is greater than or equal to 210 (References: (1) Huang YX, Luo WF, Li D, et al. CSC counteracts l-DOPA-induced overactivity of the corticostriatal synaptic ultrastructure and function in 6-OHDA-lesioned rats. Brain Res. 2011 Feb 28; 1376:113-21. (2) Kirik D, Rosenblad C, Björklund A. Characterization of behavioral and neurodegenerative changes following partial lesions of the nigrostriataldopamine system induced by intrastriatal 6-hydroxydopamine in the rat. ExpNeurol. 1998 Aug; 152(2):259-77.).

[0192] 2. Cell preparation:

[0193] The P8 generation cells corresponding to Example 3 were resuscitated at a rate of 1.0~1.5×10⁻⁶. 5 Inoculate cells at a concentration of 103 cells / mL and culture in a CO2 incubator at 35°C with 5% CO2. Harvest time is determined based on neurosphere size (generally, neurosphere diameter should not exceed 400 μm). Adding medium is typically done 2-3 days and 4-5 days after inoculation, while changing medium is done 7-8 days and 10-12 days after inoculation. When neurosphere diameter reaches 200-400 μm, collect the neurospheres and digest them for 12-15 minutes, gently shaking every 3 minutes. Centrifuge at 300g for 1 minute. After centrifugation, resuspend the cells in an appropriate amount of DMEM / F12 medium and centrifuge at 500g for 3 minutes, repeating twice. Discard the supernatant, resuspend the cells as single cells, wash twice with sodium chloride injection solution, and adjust the cell concentration to 5 × 103. 55 μL, for animal administration.

[0194] 3. Animal drug administration: After successful model establishment, animals were anesthetized and fixed in a stereotaxic apparatus to determine striatal coordinates (AP: 1.0 mm; ML: -3.5 mm; DV: -4.5 mm). After drilling a hole in the skull, BMFNPC suspension was injected directionally. The unilateral injection volume for rats was 5 × 10⁻⁶ mm. 5 The infusion rate was 1 μL / min, controlled by a microinfusion pump. After injection, the needle was left in place for 5 minutes, then slowly withdrawn, the surgical incision was sutured, and erythromycin ointment was applied to prevent infection. The administration details for different groups are shown in Table 15.

[0195] Table 15 Dosage in different groups

[0196]

[0197] 4. Detection indicators

[0198] 4.1 Behavioral Assessment

[0199] APO rotation test: Apomorphine (APO) is a DA receptor agonist that induces rotation towards the healthy side in animals. A subcutaneous injection of 0.25 mg / kg into the neck was administered. After injection, rats were placed in a circular basin, and the number of rotations towards the contralateral side (healthy side) within 30 minutes was observed. A successful 6-OHDA model was considered to have been established if the number of APO rotations within 30 minutes was greater than or equal to 210. Successful model animals were divided into a model control group and a model treatment group. The efficacy of cell therapy was evaluated every 2 weeks after administration of the test substance.

[0200] The results are as follows Figure 9 As shown, starting from week 4 of BMFNPC administration, the number of APO rotations in the model treatment group showed a decreasing trend compared to the model control group; at week 8 after administration, the decrease in the number of APO rotations in the model treatment group was more significant compared to the model control group. (p < 0.05). The above results indicate that striatal transplantation of BMFNPC can effectively reduce the number of rotations induced by APO and improve the loss of dopaminergic neurons in the brain.

[0201] Stepping test: This test evaluates forelimb function in rats. The experimenter uses one hand to stabilize the rat's hindquarters and hind limbs off the ground, while the other hand stabilizes the left forelimb, leaving the right forelimb on the ground. With the rat's head facing forward as the positive direction, the experimenter moves the rat diagonally to one side at a constant speed (90 cm within 5 seconds), recording the number of steps taken by the forelimb on the ground. Each rat is tested 5 times, and the mean is calculated. After administration of the test substance, the results are evaluated every 2 weeks to assess the improvement in forelimb function following cell therapy.

[0202] The results are as follows Figure 10 As shown, from week 0 to week 8 after drug administration, the number of steps in the model control group was significantly lower than that in the sham control group, while the number of steps in the model drug administration group showed an increasing trend compared to the model control group, and was significantly higher than that in the model control group at week 8. These results suggest that striatal transplantation of BMFNPC promotes the recovery of motor function in 6-OHDA rats.

[0203] 4.2 Detection of neurotransmitter and metabolite content in the striatum

[0204] Three months after administration of the test substance, following behavioral testing, three rats from each group were anesthetized with 4% chloral hydrate, and striatal tissue was harvested (from the surgical side (L) and contralateral side (R) separately) and stored at -80℃. For sample analysis, the tissue was removed, treated with 4% perchloric acid, sonicated to lyse the tissue, and centrifuged at 13200 rpm at 4℃ for 20 minutes. The supernatant was collected and filtered through a 0.22 μm syringe filter. The samples were then analyzed by HPLC for the neurotransmitter dopamine (DA) and its metabolite dopamine (DOPAC). The HPLC column used was an Antec C18 column (2.1 mm × 100 mm, 3 µm); the mobile phase was: 100 mM sodium dihydrogen phosphate, 0.74 mM sodium octyl sulfonate, 0.027 mM EDTA, 2 mM potassium chloride, 15% methanol, 1% acetonitrile, 0.05% acetic acid, pH 3.32 (adjusted with phosphoric acid or NaOH), the flow rate was 0.2 mL / min, and the column temperature was 30 °C.

[0205] The results are as follows Figure 11 As shown, compared with the sham control group, the levels of DA and DOPAC on the injured side were significantly reduced in both the model control group and the model drug-treated group. The levels of DA and DOPAC on the injured side were significantly upregulated in the model drug-treated group compared to the model control group. These results suggest that BMFNPC transplantation has a repairing effect on 6-OHDA-induced dopaminergic neuronal damage.

[0206] In summary, striatal transplantation of BMFNPC can improve motor dysfunction in 6-OHDA model rats to some extent and has a repairing effect on dopaminergic neuron damage.

[0207] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. The application of KCNB2 and SEMA6D as protein markers in the sorting of motor functional neural progenitor cells of the brain, characterized in that, The brain motor functional neural progenitor cells are a population of neural cells enriched in the midbrain sample and highly expressing ROBO1.

2. A method for sorting brain motor function neural progenitor cells, characterized in that, The brain motor functional neural progenitor cells are sorted from primary neural stem cells derived from brain tissue and express KCNB2 and SEMA6D; the brain motor functional neural progenitor cells are a population of neural cells enriched in midbrain samples and highly expressing ROBO1; the method includes the following steps: after incubating primary neural stem cells derived from brain tissue with fluorescent antibodies against KCNB2 and SEMA6D, DAPI is added for dead cell staining, followed by live cell staining and flow cytometry sorting.

3. The method according to claim 2, characterized in that, The purpose of the live cell staining flow cytometry sorting is to screen for live single cells that express KCNB2 and SEMA6D.

4. The method according to claim 3, characterized in that, The gating strategy for live cell staining flow cytometry sorting is as follows: FSC-A vs SSC-A: live cell gate; FSC-H vs FSC-A: single cell gate; DAPI - Live cells; cells that are positive for both live and fluorescent antibodies.

5. The method according to claim 2, characterized in that, After sorting, the cells were cultured and passaged using serum-free complete neural stem cell culture medium, which consisted of DMEM / F12, 2% B27 supplement, 1% N2 supplement, 20 ng / mL FGF and 20 ng / mL EGF.

6. The use of the method according to any one of claims 2 to 5 in the preparation of products that improve movement disorders in Parkinson's disease.

7. The application of reagents for detecting KCNB2 and SEMA6D in sorting brain motor functional neural progenitor cells, characterized in that... The brain motor functional neural progenitor cells are a population of neural cells enriched in the midbrain sample and highly expressing ROBO1.

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