Cross-animal general skeleton-derived hematopoietic stem cell marker gene set and screening method thereof
By constructing a bone-derived hematopoietic stem cell marker gene set that is universal across animal classes, the problem of accurate identification of hematopoietic stem cells in marine invertebrates has been solved, the accurate identification and functional research of hematopoietic stem cells has been achieved, and the progress of disease-resistant breeding and clinical treatment of aquatic animals has been promoted.
Patent Information
- Application Number
- CN202510829759.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-20
- Publication Date
- 2025-09-12
AI Technical Summary
Existing technologies make it difficult to accurately define and sort hematopoietic stem cells in the shells of marine invertebrates, which limits the research on their stemness maintenance, regulatory mechanisms and physiological functions. In addition, there is a lack of functional targets for HSCs, making it difficult to develop targeted improvement strategies for the hematopoietic system.
A universal bone-derived hematopoietic stem cell marker gene set across animal phyla was constructed, including Cdc42, Cbx, Tfam, Denr, Mcts1, Ak2, Ruvbl, Ahcy, Nana and Vdac. Specific marker genes were screened through single-cell sequencing and bioinformatics analysis to achieve accurate identification of hematopoietic stem cells.
It has achieved precise identification of hematopoietic stem cells in marine invertebrates, provided molecular evidence to support the study of the evolutionary path of the hematopoietic system, and guided the disease-resistant breeding and clinical treatment of aquatic animals.
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Figure CN120624624A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of biomolecular markers, and specifically relates to a bone-derived hematopoietic stem cell marker gene set that is universal across animal classes and a screening method thereof. Background Art
[0002] Hematopoietic Stem Cells (HSCs), as adult stem cells with the potential for self-renewal and multidirectional differentiation, are the core cell population that maintains the homeostasis and regeneration and repair of the blood system. In vertebrates (such as humans and mice), HSCs mainly reside in the bone marrow microenvironment. Since the discovery of bone marrow hematopoietic stem cells in the 1950s, specific marker genes of vertebrate HSCs (such as CD34 、 CD133 、 c-Kit These marker genes play a key role in basic research, clinical hematopoietic stem cell transplantation, and immunotherapy. However, the origin, molecular characteristics, and regulatory mechanisms of hematopoietic stem cells in marine invertebrates have long been unknown, severely hindering research on hematopoietic stem cell evolution and breeding for disease resistance in aquaculture.
[0003] Our team's latest research has revealed for the first time the widespread presence of hematopoietic stem cell niches within the exoskeletons (shells) of marine invertebrates (molluscs, crustaceans, and echinoderms), with functions similar to those of vertebrate bone marrow. This discovery provides new insights into the origin and evolution of hematopoietic stem cells. However, research on HSCs in marine invertebrates still faces a technical bottleneck: the lack of a robust marker gene system. Therefore, the development of cell-specific molecular markers is crucial for cell identification and functional analysis. Cell-specific molecular markers can be used for precise cell definition, sorting and purification, lineage tracing, and functional analysis. Vertebrates (primarily humans and mice) have relatively well-defined cell-specific molecular markers. Reference databases such as Cellmarker and Panglaodb, as well as the CellTypist tool developed for immune cell subsets, allow for relatively accurate definition of cell types and / or subtypes. However, hematopoietic stem cell marker genes are not identical between humans and mice, and classic vertebrate HSC marker genes lack orthologs in invertebrates. Therefore, existing single-cell reference databases cannot be directly transferred to the identification of hematopoietic stem cells in marine invertebrates.
[0004] In addition to hematopoietic stem cells, the cell population within the shell also includes microenvironmental cells such as mesenchymal stem cells and macrophages. A single marker may also be expressed in other cell types, causing interference with cellular heterogeneity. Hematopoietic stem cells may also contain subpopulations at different stages of differentiation and functional states, necessitating the screening of combinations of multiple molecular marker genes for specific identification.
[0005] In summary, existing technologies make it difficult to accurately define and sort HSCs within the shells of marine invertebrates, limiting research on their stemness maintenance, regulatory mechanisms, and physiological functions. The lack of functional targets for HSCs in disease-resistant breeding of aquatic animals makes it difficult to develop targeted improvement strategies for the hematopoietic system. Therefore, the development of a universal cross-animal bone-derived hematopoietic stem cell marker gene set and screening methods has become a core technical requirement for accurately defining HSC cell populations, analyzing their hematopoietic mechanisms, and promoting cross-research between evolutionary biology, disease-resistant breeding, and clinical treatment. Summary of the Invention
[0006] The purpose of the present invention is to provide a bone-derived hematopoietic stem cell marker gene set that is universal across animal classes and a screening method thereof. The screening is convenient, simple and fast, and the obtained hematopoietic stem cell marker gene set can accurately realize the identification and screening of hematopoietic stem cells.
[0007] The present invention provides a hematopoietic stem cell marker gene set, which includes: Cdc42, Cbx, Tfam, Denr, Mcts1, Ak2, Ruvbl, Ahcy, Nana and Vdac At least five of them.
[0008] Preferably, the hematopoietic stem cell marker gene set is derived from: animal bones.
[0009] The present invention provides an application of the hematopoietic stem cell marker gene set described in the above technical solution, and the application includes: identifying and / or screening animal hematopoietic stem cells.
[0010] Preferably, the animals include: marine animals.
[0011] The present invention provides a method for screening a hematopoietic stem cell marker gene set as described in the above technical solution, characterized in that it comprises the following steps: (1) Sample processing: Prepare the sample into a single-cell suspension; (2) Single-cell sequencing: constructing a single-cell transcriptome library using the single-cell suspension described in step (1) and performing high-throughput sequencing; (3) Bioinformatics analysis: CellRanger software was used to perform quality control of raw data and quantify gene expression, optimize single-cell transcriptome sequencing data, and Seurat R package was used to perform cell clustering and screening of characteristic genes in each cell cluster; (4) Hematopoietic stem cell identification: Analyze the overlap significance of each cell population with vertebrate hematopoietic stem cell marker genes, and construct pseudo-temporal differentiation trajectories to verify the differentiation potential of potential hematopoietic stem cells; (5) Cross-species gene set screening: Cluster analysis is performed on the orthologous genes of the sample and mice to screen for characteristic genes that are conservatively expressed in the sample hematopoietic stem cells and closely related to hematopoietic function, thereby obtaining a hematopoietic stem cell marker gene set.
[0012] Preferably, the sample comprises: mollusks, ecdysozoa and deuterostomes.
[0013] Preferably, the indicators of the single cell suspension include: The cell viability was >85%, the cell concentration was 1000±200 cells / μL, and the proportion of cell aggregates was <1%.
[0014] Preferably, in step (3), the step of optimizing the single-cell transcriptome sequencing data is: (a) SoupX software was used to remove environmental RNA contamination. (b) predict and remove potential false positive cells formed by the fusion of two or more cells; (c) Zero-preserving imputation of missing values in the single-cell transcriptome expression matrix.
[0015] Preferably, in step (4), the step of identifying hematopoietic stem cells is: (α) The significance of overlap between each cell subset and mouse hematopoietic stem cell marker genes was assessed by two-sided Fisher's exact test. (β) Integrate the most significant cell subpopulations with the mature blood cell population for pseudo-time series analysis; (γ) Comprehensive judgment based on differentiation trajectory characteristics and stemness maintenance-related gene expression profiles.
[0016] The present invention provides a system for identifying hematopoietic stem cells, which includes: a product for detecting the hematopoietic stem cell marker gene set described in the above technical solution.
[0017] Beneficial effects: The present invention provides a hematopoietic stem cell marker gene set and a screening method thereof, wherein the hematopoietic stem cell marker gene set comprises: Cdc42, Cbx, Tfam, Denr, Mcts1, Ak2, Ruvbl, Ahcy, Nana and Vdac At least five of them.
[0018] Compared with the prior art, the advantages of the present invention are as follows: (1) This invention is the first to construct a universal cross-animal bone-derived hematopoietic stem cell marker gene set. This marker combination was obtained through cross-species homologous gene screening, overcoming the defect that traditional vertebrate markers (such as CD34) have no direct homologs in invertebrates, and realizing the accurate identification of HSCs in the shell.
[0019] (2) The above-mentioned hematopoietic stem cell marker gene set was screened based on evolutionary conservation, covering three major categories: mollusks, ecdysozoa, and deuterostomes, and has both species universality and cell specificity.
[0020] (3) By monitoring the expression dynamics of the above-mentioned hematopoietic stem cell marker genes, the immune status of aquatic animals can be evaluated (which can be directly converted into PCR primer sets for rapid on-site testing) and guide disease-resistant breeding; (4) The hematopoietic stem cell marker gene set provides molecular evidence for analyzing the evolutionary path of the hematopoietic system from invertebrates to vertebrates. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the embodiments are introduced below.
[0022] Figure 1 This is a hematopoietic stem cell identification diagram provided by the present invention, wherein A is the single cell population of the shell, and B is the characteristic genes and cell population definitions of each shell cell population; Figure 2 The significance of the overlap between the hematopoietic stem cells and mouse hematopoietic lineage cell marker genes provided by the present invention; Figure 3 The pseudo-time series analysis of hematopoietic stem cells and blood lymphocyte populations in the shell provided by the present invention; Figure 4 The present invention provides a universal cross-animal bone-derived hematopoietic stem cell marker gene set; Figure 5 This is an application example of using a specific marker gene set to define a model dwarf clam hematopoietic stem cell provided by the present invention; Figure 6 This is an application example of using a specific marker gene set provided by the present invention to define hematopoietic stem cells of fish (taking turbot as an example); DETAILED DESCRIPTION In the present invention, the Cdc42 For Cell Division Control Protein 42 Homolog; Cbx Chromobox protein homolog; Tfam is Transcription factor A, mitochondrial; Denr For Density-regulated protein; Mcts1 For Malignant T-cell-amplified sequence 1; Ak2 for Adenylate kinase 2, mitochondrial; Ruvbl for RuvB-like; Ahcy Adenosylhomocysteinase; NanaIt is Nascent polypeptide-associated complex subunitalpha; Vdac For Voltage-dependent anion-selective channel protein.
[0023] The present invention provides a system for identifying hematopoietic stem cells, comprising: a product for detecting the hematopoietic stem cell marker gene set described in the above technical solution; the product preferably comprises: a detection kit; the detection kit preferably comprises: a primer set or probe for detecting the hematopoietic stem cell marker gene set.
[0024] The system of the present invention also preferably includes a data analysis module and a result output module. The data analysis preferably utilizes one or more of the bioinformatics analysis methods, hematopoietic stem cell identification methods, and cross-species gene panel screening methods provided herein. The result output preferably generates an identification report comprising one or more of: a UMAP plot of cell subpopulations, stem cell percentages, pseudo-time-series trajectories, and a molecular marker expression heat map. These methods enable accurate identification of hematopoietic stem cells, particularly those of marine invertebrates.
[0025] In order to further illustrate the present invention, the solutions provided by the present invention are described in detail below in conjunction with the embodiments, but they should not be understood as limiting the scope of protection of the present invention.
[0026] Example 1 A screening method for a universal, cross-animal bone-derived hematopoietic stem cell marker gene set, which can be used to accurately identify hematopoietic stem cells in shellfish and fish, comprises the following steps: The samples were selected from the following species: the Japanese scallop, the swimming crab, and the purple sea urchin with good activity; Step 1: Sample processing, the steps are: Use sandpaper to remove any debris from the outer shell. Gently decalcify the sample with EDTA buffer. Gently pipette the sample with a sterile wide-bore pipette tip to release the cells. Let the sample rest on ice for 10 minutes, then remove the supernatant. Centrifuge the supernatant at 300g for 4-5 minutes at 4°C to collect the cell pellet A. Resuspend the cells in 3.5× PBS and centrifuge again at 650g for 4-5 minutes at 4°C. Remove the supernatant and resuspend the cells in 3.5× PBS buffer to prepare a single-cell suspension.
[0027] The cell suspension was filtered through a 40 μm cell sieve to obtain a filtered cell suspension; The filtered cell suspension was mixed with 0.4wt% trypan blue staining solution at a volume ratio of 9:1. Hemocytometer detection showed that the cell viability was >85%, the cell concentration was 1000±200 cells / μL, and the proportion of cell aggregates was <1%.
[0028] Step 2: Single-cell sequencing. After the single-cell suspension obtained in step 1 is subjected to activity detection, a single-cell transcriptome library is constructed and high-throughput sequencing is performed using the Illumina NovaSeq platform. Library construction mainly includes the following steps: 1) Single-cell capture: Set the number of cells loaded to 12,000. Add 75 μL of reverse transcription master mix and cell suspension to well 1 of Chip B, 40 μL of Gel Beads to well 2 of row 2, and 280 μL of Partitioning Oil to well 3 of row 3. Place the cells in the Chromium Controller instrument for cell capture to form GEMs (Gel Bead-in-Emulsion). 2) cDNA synthesis and amplification: Aspirate 100 μL of GEMs into a tube and place it in a PCR instrument for reverse transcription. The reverse transcription product is purified by GEM-RT and the cDNA is amplified and purified. 3) Single-cell library construction: Pipette 10 μL of purified cDNA into a new tube, add 25 μL of Buffer EB and 15 μL of prepared Fragmentation Master Mix for library fragmentation and end-addition reaction. After sorting the fragments of appropriate length using SPRIselect magnetic beads, perform adapter ligation reaction. After purification, perform 14 cycles of PCR reaction. 4) Take 1 μL of sample and use Agilent 2100 Bioanalyzer to detect the library fragment size. At the same time, take 1 μL of sample and use Qubit Fluorometer to determine the library concentration.
[0029] For detailed steps for single-cell library construction, please refer to the instructions provided on the 10X Genomics official website: Chromium Single Cell 3' Reagent Kits V3 User Guide.
[0030] Step 3: Bioinformatics analysis, the steps are: 1) Raw data quality control and gene expression quantification were performed using CellRanger (v4.0.0) software. Each cell must have more than 200 detectable UMIs (unique molecular identifiers) with mitochondrial UMIs not exceeding 5%, and each gene must be expressed in at least three cells. 2) Optimize single-cell transcriptome sequencing data, including the following steps: (a) Environmental RNA contamination was removed using SoupX (v1.5.2), and the contamination score was automatically calculated by the autoEstCont function; (b) DoubletFinder (v2.0.3) was used to predict and remove potential false positive cells formed by the fusion of two or more cells.
[0031] (c) Zero-preserving interpolation of missing values in the single-cell transcriptome expression matrix was performed using the RunALRA function in SeuratWrappers; 3) Cell clustering using the Seurat R package, including the following steps: (i) CreateSeuratObject function creates a Seurat object; (ii) NormalizeData function normalizes the data; (iii) FindVariableFeatures function identifies genes whose expression is highly variable between cells; (iv) The ScaleData function processes the data into a centralized distribution; (v) RunPCA function performs principal component dimensionality reduction analysis on the centered data, and ElbowPlot function checks the standard deviation of each principal component; (vi) FindNeighbors function searches for neighboring site data, and the dim dimension is set according to the standard deviation of the principal component; (vii) FindClusters function to divide data into similar groups; (viii) The FindAllMarkers function obtains the marker genes of each cell cluster. The threshold conditions for screening the characteristic genes of each cell subpopulation are min.pct = 0.25, logfc.threshold = 0.25, test.use = "wilcox", and the Benjamini-Hochberg correction is used. p Value < 0.05 ( Figure 1 ,exist Figure 1 UMAP stands for Uniform Manifold Approximation and Projection. The horizontal and vertical coordinates themselves have no predefined biological meaning. Instead, they represent the projection of high-dimensional data (typically the expression levels of thousands of genes) onto a two-dimensional plane after dimensionality reduction using the UMAP algorithm.
[0032] Based on the expression levels of each cell type of the mouse hematopoietic lineage obtained from the public database Expression Atlas (https: / / www.ebi.ac.uk / gxa / home), RNentropy (v1.2.2) was used to screen the characteristic genes of each cell type. The overlap of marker genes between cell groups at adjacent developmental stages was calculated using the overlapTable function in the R package WGCNA, and the statistical significance was evaluated using a two-sided Fisher's exact test ( Figure 2 ,exist Figure 2 In the text, Bone marrow refers to bone marrow; Myeloid lineage refers to myeloid lineage; Lymphoid lineage refers to lymphoid lineage).
[0033] The most significant cell subpopulations were integrated with mature blood cell populations for pseudo-time series analysis using the Monocle package. The differentiation pathways of the hematopoietic lineage were inferred based on the pseudo-time series values, and the differentiation potential of the potential hematopoietic stem cell population was verified. Figure 3 ); Through literature research, it was found that the above cell populations specifically expressed Xbp1, Klf1, Jun, Stat5a, Rbp4 And other classic hematopoietic stem cell marker genes; the above results were combined to identify the hematopoietic stem cell population.
[0034] OrthoFinder (v2.5.2) was used to perform cluster analysis of orthologous genes in the scallop, swimming crab, purple sea urchin, and mouse. Overlap analysis was performed on the hematopoietic stem cell population characteristic genes obtained by FindAllMarkers and the mouse hematopoietic stem cell characteristic genes obtained by RNentropy. Conserved characteristic genes in hematopoietic stem cells across species were screened. Further literature research was conducted to screen genes most closely related to hematopoiesis. Ultimately, a hematopoietic stem cell-specific molecular marker gene set was obtained; the molecular marker gene set consists of the following 10 genes: Cdc42, Cbx, Tfam, Denr, Mcts1, Ak2, Ruvbl, Ahcy, Nana and Vdac ( Figure 4 ).
[0035] To verify the universality of the above molecular marker gene set for cross-species identification of hematopoietic stem cells, single-cell transcriptomes of dwarf clam shells and turbot bones were constructed, and cell clustering was performed through bioinformatics analysis. The results are shown in Figure 5 and Figure 6 .
[0036] Combine Figure 5 and Figure 6 The results showed that the 10 genes in the above molecular marker gene set ( Cdc42, Cbx, Tfam, Denr, Mcts1, Ak2, Ruvbl, Ahcy, Nana and Vdac) are specifically expressed in hematopoietic stem cell populations, indicating that the molecular marker gene set provided by the present invention has species universality and cell specificity and can effectively identify hematopoietic stem cells.
Claims
1. A hematopoietic stem cell marker gene set, characterized in that: The hematopoietic stem cell marker gene set includes: Cdc42 、 Cbx、Tfam 、 Denr 、 Mcts1 、 Ak2 、 Ruvbl 、 Ahcy 、 Nana and Vdac At least five of them.
2. The hematopoietic stem cell marker gene set according to claim 1, characterized in that: The hematopoietic stem cell marker gene set is derived from: animal bones.
3. Use of the hematopoietic stem cell marker gene set according to claim 1 or 2, comprising: Identify and / or screen animal hematopoietic stem cells.
4. The use according to claim 3, characterized in that The animals include: marine animals.
5. The method for screening a hematopoietic stem cell marker gene set according to claim 1 or 2, characterized in that: The steps include: (1) Sample processing: Prepare the sample into a single-cell suspension; (2) Single-cell sequencing: constructing a single-cell transcriptome library using the single-cell suspension described in step (1) and performing high-throughput sequencing; (3) Bioinformatics analysis: CellRanger software was used to perform quality control of raw data and quantify gene expression, optimize single-cell transcriptome sequencing data, and Seurat R package was used to perform cell clustering and screening of characteristic genes in each cell cluster; (4) Hematopoietic stem cell identification: Analyze the overlap significance of each cell population with vertebrate hematopoietic stem cell marker genes, and construct pseudo-temporal differentiation trajectories to verify the differentiation potential of potential hematopoietic stem cells; (5) Cross-species gene set screening: Cluster analysis is performed on the orthologous genes of the sample and mice to screen for characteristic genes that are conservatively expressed in the sample hematopoietic stem cells and closely related to hematopoietic function, thereby obtaining a hematopoietic stem cell marker gene set.
6. The screening method according to claim 5, characterized in that The samples included: molluscs, ecdysozoa and deuterostomes.
7. The screening method according to claim 5, characterized in that The indicators of the single cell suspension include: The cell viability was >85%, the cell concentration was 1000±200 cells / μL, and the proportion of cell aggregates was <1%.
8. The screening method according to claim 5, characterized in that In step (3), the steps of optimizing single-cell transcriptome sequencing data are as follows: (a) Use SoupX software to remove environmental RNA contamination; (b) predict and remove potential false positive cells formed by the fusion of two or more cells; (c) Zero-preserving imputation of missing values in the single-cell transcriptome expression matrix.
9. The screening method according to claim 5, characterized in that In step (4), the step of identifying hematopoietic stem cells is: (α) The significance of overlap between each cell subset and mouse hematopoietic stem cell marker genes was assessed by two-sided Fisher's exact test. (β) Integrate the most significant cell subpopulations with the mature blood cell population for pseudo-time series analysis; (γ) Comprehensive judgment based on differentiation trajectory characteristics and stemness maintenance-related gene expression profiles.
10. A system for identifying hematopoietic stem cells, characterized in that: The system includes: a product for detecting the hematopoietic stem cell marker gene set according to claim 1 or 2.