CN113106160B - Marker for evaluating liver lineage cell maturity, double chemistry kit and construction method - Google Patents
Marker for evaluating liver lineage cell maturity, double chemistry kit and construction method Download PDFInfo
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Abstract
The invention provides a marker for evaluating the maturity of a liver lineage cell, a double chemistry kit and a construction method. The invention firstly expounds a microRNA set and a gene set which have time sequence characteristics and have regulation relation in cell development with a new visual angle, establishes a 'transcription factor-microRNA-target gene' regulation network related to regulation of hepatocyte differentiation and maturation, and obtains a gene label and a microRNA label of liver lineage specificity, and the labels or the combination of the labels can be used as potential new markers of liver lineage cells. The invention also provides a double-chemistry kit of the hepatic lineage cells, and provides a novel scheme for large-scale expansion of stable hepatic lineage cells and monitoring in-vitro culture state of the hepatic lineage cells.
Description
Technical Field
The invention relates to the field of biomedicine; more particularly, the invention relates to a marker for evaluating the maturity of a liver lineage cell, a double chemistry kit and a construction method.
Background
The stem cells, as cell types with self-renewal and multidirectional differentiation potential, provide an effective new treatment strategy for the treatment of organ function loss caused by terminal diseases. At present, more than ten stem cell therapy products are approved to be marketed internationally, and no product is approved in China at present. With the gradual improvement of the management specifications of Chinese stem cell therapy products, at present, 51 stem cell clinical researches have been recorded by the national Weijian Commission in China, and in addition, 3 stem cell medicines are accepted by the drug administration and are approved by IND to enter clinical tests. The liver is the most important organ for human metabolism, and the end-stage liver disease characterized by liver functional deficiency is a great harm to human health. China is a big country with liver diseases, and currently 8 stem cell clinical research projects related to liver diseases pass through the records in China.
However, whether the stem cell products are on the market or in clinical trials and clinical research stages, the production process of the stem cell products is mostly based on the traditional two-dimensional culture system. Under a two-dimensional culture system, the proliferation capacity of stem cells is limited, the stem cells are easy to lose, and the system has high labor cost, large production loss and unstable quality of cell batches, and is not suitable for industrial preparation and production of stem cell products. Compared with a two-dimensional culture system, the three-dimensional culture system simulates the natural state of cells in vivo, not only can effectively maintain the dryness of stem cells and the dryness in the amplification process, but also overcomes the problems of material consumption and preparation space loss under the two-dimensional culture condition, so that the method has great advantages in the large-scale amplification of stem cell products.
Currently, microcarrier-based three-dimensional culture and amplification of stem cells has made a very good progress in a way that mimics the microenvironment in cells. The bioreactor is combined on the basis of microcarrier, so that the large-scale amplification of stem cells including umbilical cord mesenchymal stem cells can be realized, and a production process for obtaining million-level cells in a short time is realized. However, there are many problems to be clarified in the transition from "bench scale" to scale, and monitoring the stability of maintenance of the stem cells in scale-up expansion is important in the process for guaranteeing the quality (safety and effectiveness) of stem cell products.
At present, most of the indexes commonly used for detecting the three-dimensional large-scale amplification stability of stem cells are indexes for identifying the characteristics of the stem cells under two-dimensional culture conditions. For example, umbilical cord mesenchymal stem cells, which are maintained under two-dimensional culture conditions, need to satisfy the capacity of stem cell surface markers, gene expression and adipogenic, osteogenic, chondrogenic differentiation. The indexes are also used as gold standards and widely applied to the quality identification of the three-dimensional large-scale amplification cells of the umbilical cord mesenchymal stem cells.
Unlike umbilical cord mesenchymal stem cells, mature hepatocytes have limited ability to proliferate in vitro. Therefore, in order to obtain sufficient transplanted number of liver cells, the present inventors have obtained liver precursor cells or liver stem cells that can be proliferated in vitro, and have established a scale-up system for amplifying liver precursor cells or liver stem cells. After a sufficient number of transplantable cells are obtained, the hepatic precursor cells or the hepatic stem cells are induced to differentiate into the hepatic cells before transplantation, so that sufficient functional hepatic cells are obtained for transplantation treatment of the end-stage liver diseases.
The treatment strategy based on the traditional Chinese medicine preparation is related to two stages of amplification of hepatic precursor cells or hepatic stem cells and functional differentiation and maturation of the hepatic precursor cells or the hepatic stem cells to the hepatic cells. How to detect the stability of the liver precursor cells or the liver stem cells in scale expansion in the first stage and how to evaluate the functional maturity degree of the liver cells in the second stage are the key to realize the scale expansion of the liver precursor cells or the liver stem cells for treating the end-stage liver diseases.
Currently, evaluation of the sternness of hepatic precursor cells and hepatic stem cells in the first stage needs to be based on stem cell gene expression and low expression of maturation markers, and highly sensitive evaluation markers are lacked. The stability detection and quality control of the second-stage mature hepatocytes require comprehensive evaluation by more complex functional identification indexes, including cell morphology, detection of hepatocyte-specific gene expression level, uptake/excretion of indocyanine green, fat synthesis, albumin secretion, urea synthesis, drug metabolism, and the like. Because the evaluation standard is complex, the method is difficult to popularize in the large-scale amplification process. Therefore, there is a need for a marker that can evaluate the sternness or maturity of hepatic stem cells, hepatic precursor cells and hepatic cells in different stages.
Human biliary trunk cells (hBTSCs) are stem cells located in the biliary tract in the glands surrounding the biliary tract. The isolation of biliary tree stem cells and their in vitro and in vivo properties suggest that they can differentiate into mature hepatocytes, biliary cells and pancreatic endocrine cells. Biliary tree stem cells are found in the major ducts of the biliary tree in donors of all ages, with the potential for generation of functional cell types during organ injury. Distal to the hepatic parenchymal bile ducts, called Hering's ducts, are considered niches where human hepatic stem cells (hHpSCs) reside. Biliary tree stem cells have been successfully applied to rescue animals with liver dysfunction diseases and patients with end-stage liver disease. However, as found in studies of generation of hepatocytes from pluripotent stem cells including Embryonic Stem Cells (ESCs) and Induced Pluripotent Stem Cells (iPSCs), the time required for the hBTSCs or hHpSCs to mature into hepatocytes takes months, and functionally inefficient hepatocytes are generally obtained. Meanwhile, when bile duct stem cells, hepatic stem cells and mature hepatic cells are cultured in vitro, the problem that the developmental state and the maturity of the hepatic stem cells are difficult to predict is often faced, and the cell state of the hepatic stem cells cannot be rapidly diagnosed when the hepatic stem cells or hepatic precursor cells are matured in a large scale.
Therefore, there is an urgent need in the art to have a scheme for rapidly detecting and predicting the maturity of hepatocytes, which is a fundamental task for successfully performing the treatment of stem cell-based liver diseases.
Disclosure of Invention
The invention aims to provide a marker for evaluating the maturity of a liver lineage cell, a two-component chemical kit and a construction method.
In a first aspect of the present invention, there is provided a use of a microRNA signature or a gene signature or a combination thereof for preparing a detection reagent, a kit or a detection device for assessing the maturity of cells of the liver lineage, wherein the microRNA signature comprises 10 to 17 micrornas (such as 12, 14, 16) selected from the following group:
the gene tag comprises 10 to 23 genes (such as 12, 14, 16, 18, 20 and 22) selected from the following group:
in another preferred embodiment, the gene comprises a transcript (mRNA) thereof.
In another preferred embodiment, the assessing the maturity of the liver lineage cells comprises evaluating the sternness or maturity of liver stem cells, liver precursor cells, hepatocytes or biliary tree stem cells (hBTSCs) at different stages.
In another preferred example, the 10 to 17 micrornas include: 1 to 5, preferably 2 to 5 (e.g., 3 or 4) of hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7-5p, and hsa-let-7f-2-3p.
In another preferred example, the 10 to 23 genes include 1 or 2 of the PIK3R1 and PTEN gene tags.
In another preferred example, said assessing the maturity of cells of the liver lineage is performed by detecting the expression of said microRNA signature or gene signature or a combination thereof within the cells; the microRNA label has a remarkably high expression level, which indicates that the maturity of the cell is lower (more immature) or the dryness is higher, and the remarkably low expression level indicates that the maturity of the cell is higher (more mature) or the dryness is lower; the gene label expression level is obviously high to indicate that the maturity of the cell is higher (more mature) or the dryness is lower, and the expression level is obviously low to indicate that the maturity of the cell is lower (more immature) or the dryness is higher.
In another preferred embodiment, the detection reagent for assessing the maturity of cells of the liver lineage includes (but is not limited to): a PCR detection reagent, an in situ hybridization reagent or an immunodetection reagent aiming at the microRNA label or the gene label; preferably, including (but not limited to): specifically amplifying the microRNA label or the primer of the gene label, and specifically identifying the probe of the microRNA label or the gene label or the antibody specifically binding with the protein coded by the gene label; preferably, the detection reagent is a primer, the nucleotide sequence of the primer for detecting the microRNA label is selected from the group consisting of SEQ ID NO. 18-34 (the downstream primer is from the Tiangen kit), and the nucleotide sequence of the primer for detecting the gene label is selected from the group consisting of SEQ ID NO. 35-80.
In another preferred embodiment, the detecting device includes (but is not limited to): a chip, a probe set (module), a primer probe set (module), an electrophoresis apparatus or a gene sequencing instrument.
In another preferred embodiment, said assessing the maturity of cells of the hepatic lineage comprises: evaluating the cell differentiation process or the state of the cell after differentiation, and evaluating the cell reprogramming process or the state of the cell after reprogramming.
In another aspect of the present invention, there is provided a kit or a test device for assessing the maturity of cells of the liver lineage, which includes test reagents for assessing the maturity of cells of the liver lineage, including (but not limited to): the detection reagent aiming at the microRNA label or the gene label or the combination thereof, wherein the microRNA label comprises 10-17 microRNAs (such as 12, 14 and 16) selected from the following group:
the gene tag comprises 10 to 23 genes (such as 12, 14, 16, 18, 20 and 22) selected from the following group:
in another aspect of the present invention, there is provided a system for assessing the maturity of cells of the hepatic lineage, comprising a detection unit and a data analysis unit;
the detection unit includes: a detection reagent capable of measuring the expression level of the microRNA label or the gene label or the combination thereof, or a kit or a detection device containing the detection reagent; the detection reagents include (but are not limited to): the detection reagent aiming at the microRNA label or the gene label or the combination thereof, wherein the microRNA label comprises 10-17 microRNAs (such as 12, 14 and 16) selected from the following group:
the gene label comprises 10-23 microRNAs (such as 12, 14, 16, 18, 20 and 22) selected from the following group:
the data analysis unit includes: and the processing unit is used for analyzing and processing the detection result (the measured expression level of the microRNA label or the gene label or the combination thereof) of the detection unit to obtain the evaluation result of the maturity degree of the liver lineage cells.
In a preferred embodiment, the detection reagent includes (but is not limited to): PCR detection reagents, in situ hybridization reagents, or immunodetection reagents, more preferably, including (but not limited to): specifically amplifying a primer of the microRNA label or the gene label, a probe specifically recognizing the microRNA label or the gene label, or an antibody specifically binding to a protein coded by the gene label; preferably, the detection reagent is a primer, the nucleotide sequence of the primer for detecting the microRNA label is selected from the group consisting of SEQ ID NO. 18-34 (the downstream primer is from the Tiangen kit), and the nucleotide sequence of the primer for detecting the gene label is selected from the group consisting of SEQ ID NO. 35-80.
In another preferred embodiment, the detecting device includes (but is not limited to): a chip, a probe set (module), a primer probe set (module), an electrophoresis apparatus or a gene sequencing instrument.
In another aspect of the present invention, there is provided a method of assessing the maturity of cells of the hepatic lineage, comprising: evaluating using the system of claim 8 or 9; the method comprises the following steps: detecting the expression level of the microRNA label or the gene label or the combination thereof by using the detection unit, and analyzing and processing the detection result of the detection unit by using the data analysis unit to obtain a liver lineage cell maturity result; wherein, the significantly high expression level of the microRNA label indicates that the maturity of the cell is lower (more immature) or the dryness is higher, and the significantly low expression level indicates that the maturity of the cell is higher (more mature) or the dryness is lower; the gene label expression level is obviously high to indicate that the maturity of the cell is higher (more mature) or the dryness is lower, and the expression level is obviously low to indicate that the maturity of the cell is lower (more immature) or the dryness is higher.
In another preferred embodiment, the method comprises the following steps:
(1) Obtaining a nucleic acid sample of a cell to be detected;
(2) Detecting the expression level of a microRNA signature or a gene signature or a combination thereof of the cell;
(3) The following expression significance difference analysis was performed:
satisfying one or more of the following (1-5, e.g., 1, 2, 3, 4, 5) conditions, indicating that the higher the maturity or the lower the sternness of the cell:
(1) more than 50% of the gene tags (more than 50% of 10-23) are highly expressed,
(2) the expression of all gene labels (10-23) has statistical significance on the whole,
(3) more than 50 percent of microRNA labels (more than 50 percent of 10-17 microRNAs) are low-expressed,
(4) the expression of all microRNA labels (10-17) is reduced in statistical significance,
(5) the gene label and the microRNA label are subjected to double-label integration difference analysis and are also significantly different, namely the overall high expression of the gene label in an experimental group is significant compared with the overall low expression of the microRNA label;
one or more of the following (1-5, e.g., 1, 2, 3, 4, 5) conditions are satisfied, indicating that the lower the maturity or the higher the sternness of the cell:
(a) Over 50% of the gene tags (over 50% of 10-23) are low-expressed,
(b) The expression of all gene tags (10-23) is statistically reduced on the whole,
(c) More than 50 percent of microRNA labels (more than 50 percent of 10-17 microRNAs) are highly expressed,
(d) The expression of all microRNA labels (10-17) has statistical significance,
(e) The gene label and the microRNA label are subjected to double-label integration difference analysis and are also significantly different, namely the overall low expression of the gene label in an experimental group is significant compared with the overall high expression of the microRNA label;
if the result of the significance difference analysis is not significant, the cell state is stable, and no obvious dry change or maturity change exists.
In another preferred embodiment, the expression "statistically significant overall" or "statistically significant overall" is an overall statistical analysis of the expression of the set of tags to obtain statistically significant values representing the expression level, such as but not limited to the following statistics: expression median value statistics, expression mean value statistics and GSVA analysis.
In another preferred embodiment, the method is used to perform a maturity analysis on cells of the liver lineage (such as but not limited to including embryonic liver stem cells, endodermal stem cells, hepatic precursor cells, mature hepatocytes, adult hepatocytes, induced-differentiation mature hepatocytes, etc.) in various states collected in different databases.
In another preferred embodiment, the method is used for rapidly judging whether the maturity or the aridity changes in the process of in vitro scale culture, continuous subculture or reprogramming of the cells.
In another preferred embodiment, the method of assessing the maturity of cells of the hepatic lineage is a method that does not directly target the diagnosis of the disease, or is a non-diagnostic method.
In another aspect of the present invention, there is provided a method for establishing a cell lineage associated "transcription factor-microRNA-target gene" regulatory network, comprising:
(1) Obtaining cells of different stages of a cell lineage, performing microRNA sequencing and RNA-seq sequencing (e.g., obtainable by data integration and washing of public databases);
(2) Determining a temporal characteristic of cell development by principal component analysis (PCA analysis);
(3) Performing short-time sequence expression analysis (STEM analysis) to obtain a microRNA set and an mRNA set which change along with sequences;
(4) Performing GO or KEGG enrichment analysis;
(5) Obtaining a microRNA target gene of which the expression level gradually changes along with the development of time by using a microRNA related target gene prediction database; preferably, the databases include, but are not limited to, the miRDB, miRTarBase, targetScan, miRWalk, and diala-MicroT-CDS databases;
(6) And taking intersection with genes with the expression level changing along with the pedigree development, and further obtaining a microRNA label and a target gene label which not only gradually change along with the pedigree development but also have mutual regulation and control effects.
In another preferred example, after the step (6), the method further comprises: the reliability of the microRNA tag and the target gene tag is further verified by methods including (but not limited to) the following group: GO and KEGG enrichment analysis, correlation analysis, three-dimensional Principal Component Analysis (PCA).
In another preferred embodiment, the method further comprises the following steps: and downloading pedigree related microRNAs supported by an experiment and interaction between the pedigree related microRNAs and the regulatory transcription factors of the pedigree related microRNAs from a TransmiR v2.0 database to obtain the transcription factors capable of regulating and controlling the microRNA labels.
In another preferred embodiment, the method further comprises the following steps: the mapping of the regulation and control network of the transcription factor-microRNA-target gene is carried out through cytoscape.
In another preferred embodiment, the method further comprises the following steps: multidimensional verification method 1: and obtaining a cell lineage sequencing result in a normal embryonic development process, and verifying the reliability of a regulation network result through GSEA or GSVA analysis.
In another preferred embodiment, the method further comprises the following steps: multidimensional verification method 2: and obtaining a cell reprogramming sequencing result in a lineage reprogramming process, and verifying the reliability of a regulation and control network result through GSEA or GSVA analysis.
In another preferred embodiment, the method further comprises the following steps: and verifying the obtained microRNA and gene by using experimental means such as qRT-PCR and the like, and monitoring the maturation degree of the reprogrammed cell after in vitro continuous passage.
Other aspects of the invention will be apparent to those skilled in the art in view of the disclosure herein.
Drawings
FIG. 1 shows basic steps and a process for constructing a cell lineage-related 'transcription factor-microRNA-target gene' regulatory network.
FIG. 2 shows that the unique system constructed by the invention obtains a liver lineage-related 'transcription factor-microRNA-target gene' regulatory network.
FIGS. 3A-F, 17 microRNAs and most of the 23 genes have negative correlations and verify the accuracy of the "17microRNA" signature.
FIGS. 4A-H, the database associated with embryonic development, verify the accuracy of the "23 Gene" signature.
FIGS. 5A-G, the lineage reprogramming correlation database, verifies the accuracy of the "23 Gene" signature.
FIG. 6 shows the application of the microRNA label in vitro cell culture reprogramming.
FIG. 7, application of gene signature in vitro cell culture reprogramming.
Detailed Description
The invention explains the existence of microRNA and genes with time sequence characteristics and regulation relation in the liver lineage cell development process by a new visual angle for the first time through a large number of analyses, researches and screens, establishes a 'transcription factor-microRNA-target gene' regulation network related to regulation of liver cell differentiation and maturation, and obtains a liver lineage specific gene label and a microRNA label, and the labels or the combination of the labels can be used as potential new markers of the liver lineage cell. On the basis, the invention also provides a dual-chemistry kit related to the hepatic lineage, and provides a novel scheme for large-scale expansion of stable hepatic lineage cells and monitoring of the in vitro culture state of the hepatic lineage cells.
Term(s) for
As used herein, the term "assessing" includes "detecting", "determining", "analyzing", "predicting" or "assessing".
As used herein, the term "kit" may refer to a system of materials or reagents for performing the methods disclosed herein.
As used herein, the terms "high expression", "high expression level" are interchangeable and shall mean in the sense of the application at least a 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9% or 10%, preferably at least a 15% or 20%, more preferably 25%, 30%, 50%, 80%, 100% or more significant increase compared to a control or "threshold". For example, the presence of at least one gene whose expression intensity exceeds a threshold can be detected in a repeat Student's T-test to determine significance.
As used herein, the terms "low expression", "low expression level" are interchangeable and shall mean in the sense of application a reduction of at least 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9% or 10%, preferably at least 15% or 20%, more preferably 25%, 30%, 50%, 80%, 100% or more, compared to a "control" or "threshold". For example, the presence of at least one gene with an expression intensity below a threshold value can be detected by Student's T-test to determine significance.
As used herein, the setting of a "control" or "threshold" for gene or microRNA expression is readily set by one skilled in the art based on the teachings of the present invention. The selection of an appropriate "control" or "threshold" is a routine part of the experimental design, e.g. a statistically significant analysis may first be performed on the basis of the expression level of the corresponding microRNA or gene in cells with a well-defined degree of maturity, and the obtained expression value is used as "control" or "threshold".
The definition of the degree of cell maturation can be carried out according to the definition criteria already existing in the art, such as in the field of cell differentiation or cell reprogramming.
Transcription factor-microRNA-target gene regulation network
Through extensive research and analysis, the inventor discloses a specific regulatory network of microRNA and mRNA, which is closely related to the liver lineage stem cell maturation into functional liver cells.
microRNAs (microRNAs) are a class of short RNAs of about 22 nucleotides in length that can modulate messenger mRNA by cleaving it (mRNA) or by binding to its complementary region of the 3' untranslated regions (UTRs) to form mRNA-induced silencing complexes to inhibit its translation. By utilizing these negative regulatory mechanisms, microRNAs are involved in a variety of developmental and biological cellular processes, including stem cell differentiation and cell cycle regulation, among others. Meanwhile, microRNA exerts its regulatory function by targeting various genes associated with one or more signal pathways, including HIPPO, WNT/beta-catenin, PI3K/AKT signal pathways, etc. However, it has not been elucidated in the art which micrornas have a correlation with the time sequence of hepatocyte development, the regulatory network involved in micrornas, and how micrornas manipulate lineage maturation of stem cells at an early lineage stage, including differentiation of hepatic stem cells into hepatocytes.
The present inventors found in their studies that when hepatocytes were transplanted into an animal model of liver injury, hepatocytes were liver differentiated and functional hepatocytes were produced to rescue liver injury; however, the exact triggers and regulators to promote and maintain differentiation of biliary tree stem cells are unknown, which prompted the present inventors' exploration. The present inventors performed the analysis of microRNA-seq and RNA-seq sequencing data for four stages of the hepatic lineage (biliary tree stem cells (hBTSCs), hepatic stem cells (hHpSCs), hepatic progenitor cells (hbbs), and mature hepatocytes (hAHeps)). On the basis, a large amount of analysis work reveals a potential transcription factor-microRNA-target gene regulation network capable of regulating differentiation and maturation of hepatocytes.
The invention also provides a method for constructing a regulation network of 'transcription factor-microRNA-target gene' in the process of cell development and maturation lineage, and the preferred operation mode of the method is shown in figure 1 and the embodiment of the invention.
On the basis of providing a 'transcription factor-microRNA-target gene' regulation and control network, the inventor not only obtains a potential new marker of the liver lineage related cells, but also verifies the effectiveness and the applicability of the marker by various verification means (microRNA sequencing, RNA-seq sequencing, single cell sequencing and qRT-PCR). Therefore, a related two-component chemical kit of the liver lineage is developed, and a new thought and scheme are provided for large-scale expansion of stable liver lineage-related cells and monitoring of the in vitro culture state of the liver lineage-related cells.
The scheme for establishing the regulatory network can also be applied to analyzing other types of cells besides the liver lineage cells. The stem cell can be differentiated into various cell types, and the analysis method of the present invention can also analyze the differentiation process of the stem cell into other cell types or vice versa, so as to obtain microRNA and/or target genes which are closely related to the differentiation process or reprogramming process and can reflect the differentiation or reprogramming trend (maturity) of the stem cell.
The invention provides a method for constructing a 'transcription factor-microRNA-target gene' regulation network for completely predicting cell lineage development, and provides a complete prediction system for researching the regulation relationship between coding genes and non-coding genes in more cell lineage development.
The methods of the invention have general applicability to cells of the hepatic lineage of various species, such as, but not limited to, primates (including humans), rodents (e.g., mice, rats), and the like.
MicroRNA label, gene label and application thereof
Based on the new findings of the present inventors, the present invention reveals two omics signatures specific for liver lineage: the "23 gene" tag and the "17microRNA" tag. Markers, kits and methods for assessing the degree of maturation of cells of the hepatic lineage are also disclosed. Preferably, by performing enrichment analysis and multi-angle analysis on the test set data, we also preferably select molecules which can not only serve as one of the markers in the tag, but also can exert functions affecting differentiation and maturation of hepatocytes, and the core genes are PIK3R1 and PTEN genes of a PI3K/AKT signaling pathway, and the preferred microRNAs are hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7-5p and hsa-let-7f-2-3p in the let-7 family.
The microRNA label and the gene label disclosed by the invention can be used as judgment markers (markers) for evaluating the maturity of the liver lineage cells. Thus, it is possible to understand what state the cell of interest (test cell) is in. The states include, but are not limited to: stable (non-differentiated, non-reprogrammed) state, differentiated (toward mature) state, immature (toward dryness-enhanced) state, etc. Such assessment of liver lineage cell maturity includes, but is not limited to: and evaluating the dryness or maturity of hepatic stem cells, hepatic precursor cells, hepatic cells or bile duct stem cells (hBTSCs) at different stages.
By utilizing the microRNA label and the gene label disclosed by the invention, the evaluated cells can be cells separated from an organism, and can also be cells cultured in vitro and passaged. The cells evaluated may be natural cells, mutagenized cells, or genetically engineered cells.
The present invention also provides a system for assessing the maturity of cells of the hepatic lineage, comprising a detection unit and a data analysis unit; the detection unit includes: a reagent or device for specifically detecting the microRNA label or the gene label or the combination thereof; the data analysis unit includes: and the processing unit is used for analyzing and processing the detection result (the measured expression level of the microRNA label or the gene label or the combination thereof) of the detection unit to obtain an evaluation result of the maturity degree of the liver lineage cells. The reagent for specifically detecting the microRNA label or the gene label or the combination thereof can include, but is not limited to: PCR detection reagent, in situ hybridization reagent or immunity detection reagent. The means for specifically detecting microRNA tags or gene tags or combinations thereof may include, but are not limited to: a chip, a probe set (module), a primer probe set (module), an electrophoresis apparatus or a gene sequencing instrument.
In a preferred embodiment, primers for specifically amplifying the microRNA or gene tag or the combination thereof can be designed according to the sequence of the microRNA or gene tag for detection. The Polymerase Chain Reaction (PCR) technique is well known to those skilled in the art and its basic principle is the in vitro enzymatic synthesis of specific DNA fragments. The method of the present invention can be carried out using conventional PCR techniques. The invention provides an optimized method for obtaining an amplification product of a microRNA label or a gene label or a combination thereof from a nucleic acid sample, wherein the method comprises the following steps: taking a nucleic acid sample as a template, and carrying out PCR amplification by using a primer pair selected from SEQ ID NO 18-34 (downstream primer comes from Tiangen kit) aiming at a microRNA label or SEQ ID NO 35-80 aiming at a gene label to obtain an amplification product. By using the primer, a more ideal amplification result can be obtained by adopting a conventional PCR amplification method.
As an implementable mode, a method of combining a primer with a probe can be utilized, so that the qualitative and quantitative detection is more sensitive and faster. For example, taqman real-time fluorescent PCR detection techniques can be employed: during PCR amplification, a pair of primers is added, and simultaneously a specific Taqman probe marked with fluorescein is added, wherein the probe is an oligonucleotide, and two ends of the probe are respectively marked with a reporter fluorescent group and a quenching fluorescent group. When the probe is complete, the fluorescent signal emitted by the reporter group is absorbed by the quenching group; during PCR amplification, the probe is digested and degraded by 5'→ 3' exonuclease activity of Taq enzyme, so that a report fluorescent group and a quenching fluorescent group are separated, fluorescein is dissociated in a reaction system and emits fluorescence under specific light excitation, an amplified target gene fragment grows exponentially along with the increase of cycle times, and a Ct (cycle threshold, ct) value is obtained by detecting the intensity of a corresponding fluorescence signal which changes along with amplification in real time. The Ct value, namely the number of amplification cycles which pass when the fluorescence signal of the amplification product reaches a set threshold value in the PCR amplification process, has a linear relation with the logarithm of the initial copy number of the template, the more the DNA amount of the template is, the less the number of cycles when the fluorescence reaches the threshold value is, namely the smaller the Ct value is, thereby realizing the quantitative and qualitative analysis of the initial template.
As an implementable manner, according to the sequence of the microRNA tag or the genetic tag or the combination thereof, a suitable probe can be designed and fixed on a microarray (microarray) or a gene chip (also referred to as "DNA chip"). The gene chip generally comprises a solid phase carrier and oligonucleotide probes orderly fixed on the solid phase carrier, wherein the oligonucleotide probes consist of continuous nucleotides. In order to enhance the intensity of the detection signal and improve the accuracy of the detection result, the hybridization-related site is preferably located in the middle of the probe. The solid phase carrier can adopt various common materials in the field of gene chips, such as but not limited to nylon membranes, glass slides or silicon wafers modified by active groups (such as aldehyde groups, amino groups, isonicotinic acid groups and the like), unmodified glass slides, plastic sheets and the like. The probe may further comprise an amino-modified poly (1-30) poly (deoxythymidylate) (poly dT) at its 5' end. The gene chip comprises at least one probe aiming at the microRNA label or the gene label or the combination thereof; more preferably, the gene chip comprises two or more probes for the microRNA label or the gene label or the combination thereof; most preferably, probes against all microRNA tags or gene tags according to the present invention or a combination thereof are contained on one or more gene chips.
Methods for preparing cellular DNA for PCR amplification are numerous. The method for amplifying a specific fragment of a gene by PCR is well known in the art, and is not particularly limited in the present invention. The labeling of the amplification product can be achieved by using primers with a labeling group at the 5' end, by incorporating a single nucleotide with a labeling group during amplification, or by adding a detection probe that specifically binds to the amplification product during hybridization, including but not limited to: digoxin molecules (DIG), biotin molecules (Bio), fluorescein and its derivative biomolecules (FITC, etc.), other fluorescent molecules (e.g., cy3, cy5, etc.), alkaline Phosphatase (AP), horseradish peroxidase (HRP), etc. These markers and methods of labeling are well known in the art and can be found in the genetic diagnostic techniques-nonradioactive operating Manual, compiled by Wangsu fifth Proc; J. sambrook, d.w. rassel eds, molecular cloning guidelines, etc.
As a preferred mode of the invention, a method for evaluating the maturity degree of the liver lineage cells by using the 23 gene label or the 17microRNA label or parts thereof is provided. The method comprises the following steps: 1) Sampling from the expanding hepatic stem cells or hepatic precursor cells; 2) Detecting the expression levels of 23 genes and 17 microRNAs of the cells by using the kit; 3) Preliminarily comparing the expression levels of 23 genes and 17 microRNAs of cells with different development degrees; 4) Expression difference analysis was performed on 23 genes and 17 microRNAs.
In a preferred embodiment of the present invention, the expression levels of the gene tag and the microRNA tag can be obtained by calculating through a calculation tag analysis method such as mean value, median value or GSVA gene set mutation analysis, and at this time, single tag analysis is performed first, and the tag and the control group are subjected to difference analysis, and if the difference is significant, the change of the cell state is suggested. If the gene label is obviously highly expressed, the mature differentiation of the liver lineage cells is prompted, if the microRNA label is obviously highly expressed, the larval differentiation of the liver lineage cells is prompted, and if the microRNA label is not obviously changed, the stable state of the cells is prompted.
As a preferred embodiment of the present invention, a dual-tag combined analysis may be performed, wherein the lower the microRNA tag expression is, the higher the gene tag is, the more mature the group of cells is. If the expression of the microRNA label is higher and the gene label is lower, the dryness of the group of cells is enhanced, and if the double labels have no significant difference, the cell state is stable.
And (4) combining the results to obtain the relationship between the maturity of the cells in the experimental group and the cells in the control group. Through a double-chemistry kit scheme with simple and convenient operation and various statistical analysis means, a novel double-chemistry marker is provided for in-vitro long-term culture and amplification of liver lineage related cells, a rapid and convenient maturity prediction mode is provided, and a convenient monitoring mode is provided for stable passage.
The invention also provides a kit for detection that may include a system for storing, transporting or delivering reaction reagents or devices (e.g., primers, probes, etc. in appropriate containers) and/or conjugate materials (e.g., buffers, written instructions for performing an assessment, etc.) from one location to another. For example, a kit can include one or more housings (e.g., cassettes) containing the relevant reagents and/or complexing materials. These contents may be delivered to the intended recipient simultaneously or separately.
In addition, the kit may further include various reagents required for DNA extraction, PCR, hybridization, color development, and the like, including but not limited to: an extraction solution, an amplification solution, a hybridization solution, an enzyme, a control solution, a color development solution, a washing solution, an antibody, and the like.
In addition, the kit can also comprise an instruction book and/or chip image analysis software and the like.
The invention firstly discloses the important functions of a 23 gene label and a 17microRNA label in the development process of a liver lineage, and discloses that the labels of the two different omics have obvious negative correlation with the development of the liver lineage, so that a novel effective method, a kit and a marker for evaluating the development maturity of the cells related to the liver lineage are provided, and the method, the kit and the marker have important significance for monitoring the in-vitro state of the cells of the liver lineage and rapidly amplifying the cells of liver precursor cells and mature liver cells related to liver failure and the like in vitro in a large scale.
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. The experimental procedures, for which specific conditions are not noted in the following examples, are generally performed according to conventional conditions such as those described in J. SammBruk et al, molecular cloning protocols, third edition, scientific Press, 2002, or according to the manufacturer's recommendations.
Materials and methods
1. Preparation of chip and RNA-seq sequencing data for cells at different time-sequential stages in the same lineage
All 15 data sets, including the present inventors and other bulk RNA-seq, scRNA-seq, micro-RNA-seq data, were collected from the Gene Expression Omnibus (GEO) database (http:// www.NCBI.NLM.NIH.gov/GEO).
These included the use of 4 data sets that the inventors have previously published:
GSE101133(Yan F et al.Human embryonic stem cell-derived hepatoblasts are an optimal lineage stage for hepatitis C virus infection.Hepatology.(2017)66:717-735.doi:10.1002/hep.29134)；
GSE75141(Wu H et al.Reversible transition between hepatocytes and liver progenitors for in vitro hepatocyte expansion.Cell Res.(2017)27:709-712.doi:10.1038/cr.2017.47)；
GSE105019 (Fu GB et al. Expansion and differentiation of human hepatocyte-derived promoter-like cells and the hair use for the student of hepatopic pathogens. Cell Res. (2019) 29; and
GSE116113(Fu GB et al.Expansion and differentiation of human hepatocyte-derived liver progenitor-like cells and their use for the study of hepatotropic pathogens.Cell Res.(2019)29:8-22.doi:10.1038/s41422-018-0103-x)。
among these, 11 data sets from other sources are also included:
GSE73114(Oikawa T et al.Model of fibrolamellar hepatocellular carcinomas reveals striking enrichment in cancer stem cells.Nat Commun.(2015)6:8070.doi:10.1038/ncomms9070)；
GSE114974(Dinh TA et al.MicroRNA-375Suppresses the Growth and Invasion of Fibrolamellar Carcinoma.Cell Mol Gastroenterol Hepatol.(2019)7:803-817.doi:10.1016/j.jcmgh.2019.01.008；Dinh TA et al.Hotspots of Aberrant Enhancer Activity in Fibrolamellar Carcinoma Reveal Candidate Oncogenic Pathways and Therapeutic Vulnerabilities.Cell Rep.(2020)31:107509.doi:10.1016/j.celrep.2020.03.073)；
GSE57833(http://www.NCBI.NLM.NIH.gov/geo)；
GSE57878(http://www.NCBI.NLM.NIH.gov/geo)；
GSE90047(Yang et al.A single-cell transcriptomic analysis reveals precise pathways and regulatory mechanisms underlying hepatoblast differentiation.Hepatology.(2017)66:1387-1401.doi:10.1002/hep.29353)；
GSE132034(Gong T et al.A time-resolved multi-omic atlas of the developing mouse liver.Genome Res.(2020)30:263-275.doi:10.1101/gr.253328.119)；
GSE28892(Shin S et al.Foxl1-Cre-marked adult hepatic progenitors have clonogenic and bilineage differentiation potential.Genes Dev.(2011)25:1185-1192.doi:10.1101/gad.2027811)；
GSE56734(Ito K et al.Gene targeting study reveals unexpected expression of brain-expressed X-linked 2in endocrine and tissue stem/progenitor cells in mice.J Biol Chem.(2014)289:29892-29911.doi:10.1074/jbc.M114.580084)；
GSE25048(Kim et al.Identification of DNA methylation markers for lineage commitment of in vitro hepatogenesis.Hum Mol Genet.(2011)20:2722-2733.doi:10.1093/hmg/ddr171)；
GSE112330(Xie B et al.A two-step lineage reprogramming strategy to generate functionally competent human hepatocytes from fibroblasts.Cell Res.(2019)29:696-710.doi:10.1038/s41422-019-0196-x)；
GSE124528(Wang Z et al.Generation of hepatic spheroids using human hepatocyte-derived liver progenitor-like cells for hepatotoxicity screening.Theranostics.(2019)9:6690-6705.doi:10.7150/thno.34520)。
all data were subjected to a conventional sequencing data analysis procedure for quality control, alignment, counting, data washing and normalization, and displayed in a heatmap using the pheamap R software package.
Detailed information on these data sets is provided in table 1.
TABLE 115 two-component data sets for constructing hepatic lineage regulatory networks
2. Tumor genomic profiling database (TCGA) and human protein profiling database (HPA) (USA)
To explore the role of key micrornas, the inventors downloaded standardized microRNA sequence data and corresponding clinical information from TCGA for HCC patients. And performing differential expression analysis and survival analysis. "P <0.05" was considered significant. Meanwhile, the expression patterns of 23 genes in normal liver tissues are also explored in the HPA database (https:// www.proteinalas. Org), and the invention only shows genes with medium or high expression.
3. Short time sequence expression analysis (STEM)
Both mRNAs and microRNAs were layered into different profiles based on different expression patterns calculated by STEM analysis (default parameters). The four stages of the hepatic lineage (biliary tree stem cells (hBTSCs), hepatic stem cells (hHpSCs), hepatic progenitors (hbds) and mature hepatocytes (hAHeps)) are considered to be different time points.
4. Gene Ontology (GO) and Kyoto Gene and genome encyclopedia (KEGG) analysis
To explore the biological functions of the liver lineage specific gene profile, KEGG and GO enrichment analyses were performed using a cluster analysis (clusterprofile) R-package (Yu G et al: clusterprofile: an R package for formulating biological the animal environmental genes clusters conditioners (2012) 16. In order to understand the potential functions of microRNAs, the DIANA-MIRPath v3.0 database, microRNA pathway analysis web server (http:// SNF-515788.VM. Linkage. Grnet. Gr) was also used in this work because it can quickly predict the potential targets of microRNAs and then run KEGG pathway analysis efficiently (Vlachos IS et al. DIANA-MIRPath v3.0: purifying microRNA function with experimental support. Nucleic Acids Res. (2015) 43 W460-466.doi 10.1093/nar/gkv 403.
5. MicroRNA related target gene database
In the present work of the present inventors, the present inventors used 3 databases, including microRNA target gene prediction database (mirDB) (Chen Y, wang X. MirDB: an online database for prediction of functional microRNA targets. Nucleic Acids Res. (2020) 48, D127-D131.Doi:10.1093/nar/gkz 757), experimentally verified microRNA-target gene interaction database (RTmiARBase) (Chou CH et. RTARBase update 2018 a resource for experimental valid expressed microRNA-target interactions Res. (2018) 46D-D302. Doi:10.1093/nar/gkx 7) and TagetRNA for target genes. Nucleic Acids Res. (2018) 46D-D302. Doi:10.1093/nar/gkx 7) and TagetRNA (Beijing) for further target prediction of only those targets of microRNA (cell No. 2003-8618, no..
Subsequently, the prediction results were confirmed by 2 comprehensive and comprehensive functional microRNA databases, including miRWAlk (Sticht C et al. MiRWAlk: an online resource for prediction of microRNA binding sites. PLoS one. (2018) 13. P <0.05 was considered statistically significant.
6. Establishing a 'transcription factor-microRNA-target gene' regulation network
The interaction between experimentally supported lineage-associated microRNAs and their regulatory transcription factors was downloaded from the TransmiR v2.0 database containing 3730 experimentally supported transcription factor microRNAs regulation covering about 623 transcription factors, -785 microRNAs and 1349 publications (Tong Z, cui Q, wang J, zhou Y. TransmiR v2.0: an updated transcription factor-microRNA regulation database. Nucleic Acids Res. (2019) 47 D253-D258.Doi:10.1093/nar/gky 1023). Construction of the "transcription factor-microRNA-target gene" regulatory network of the hepatic lineage was performed by cytoscape (Java 3.7.1) software (Shannon P et al. Cytoscape: a software environment for integrated models of biomolecellular interaction networks. Genome Res. (2003) 13.
7. Principal Component Analysis (PCA) and three-dimensional principal component analysis (3D _PCA)
A3D _PCAanalysis (default parameters) was performed on common mRNA sequences, microRNA sequences, of biliary tree stem cells (hBTSCs), hepatic stem cells (hHpSCs), hepatic progenitors (hHBs), and mature hepatocytes (hHeps) to examine the performance of the "23 Gene" signature.
Principal component analysis also showed single cell RNA-seq data for 251 hepatic progenitors/hepatocytes to show the time course of the hepatic lineage.
8. Gene Set Enrichment Analysis (GSEA) and Gene set mutation analysis (GSVA)
RNA-seq data for hBTSCs differentiation and total RNA-seq for Dlk + hepatic progenitors/hepatocytes were scored using the GSVA method, with each sample/cell receiving one GSVA score (Hanzelmann S, castelo R, guinney J.GSVA: gene set variation analysis for microarray and RNA-seq data.BMC Bioinformatics. (2013) 14. All datasets associated with liver development and cell reprogramming were used to perform GSVA scoring to validate the lineage specific characteristics of the "23 gene" signature.
In addition, GSEA analysis was used to reveal the relationship between PTEN/PIK3R1 and stem cell nature of liver-associated single cells (Subramanian A et al Gene set expression analysis: a knowledgeable-based expression for interpretive genome-with expression profiles. Proc Natl Acad Sci U.S. (2005) 102, 15545-15550.Doi 10.1073/pnas.0506580102. The number parameter of random sample permutations was set to 1000.
9. Correlation analysis
And calculating the correlation among 23 gene signals, stem cells and a PI3K/AKT signal channel so as to determine the regulation and control relation among 23 targets, 17 microRNAs and 1 signal channel. In our current studies, P <0.05 is considered to be statistically significant. Due to the different data set sources and sample sizes, the threshold of the correlation coefficient is not defined, and the specific data are shown in the graph.
Example 1 construction of cell lineage-associated "transcription factor-microRNA-target Gene" regulatory network
The method for constructing the regulatory network of the transcription factor-microRNA-target gene in the process of cell developmental maturation lineage mainly comprises the following steps (figure 1):
1. obtaining cells at different stages of a cell lineage; carrying out microRNA sequencing and RNA-seq sequencing (obtained by carrying out conventional processing on sequencing data of a GSE73114 database and a GSE114974 database in 15 public databases in the step 1, preparation of chips of cells in different time sequence stages in the same pedigree and preparation of RNA-seq sequencing data);
2. by principal component analysis (PCA analysis), it was confirmed that the development of cells indeed has a temporal profile;
3. different expression modes in different cell states are obtained and calculated through short-time sequence expression analysis (STEM analysis), and a microRNA set and an mRNA set which change along with time sequence are obtained;
4. the reliability of a sequencing result is ensured through GO, KEGG and other enrichment analysis;
5. analyzing and obtaining the target genes of the microRNAs with gradually changed expression levels along with the development of time by using 5 microRNA related target gene prediction databases (the aforementioned 5 and microRNA related databases), wherein the databases comprise a mirDB, a mirtarBase, a TargetScan, a mirWalk and a DIANA-MicroT-CDS database;
6. taking intersection with genes which change along with the development expression level of the pedigree, and further obtaining a microRNA label and a target gene label which not only gradually change along with the development of the pedigree but also have interaction;
7. further verifying the reliability of the results of the two-chemistry tags through GO and KEGG enrichment analysis, correlation analysis and three-dimensional Principal Component Analysis (PCA);
8. downloading the interaction between the lineage-related microRNA supported by the experiment and the transcription factor regulated by the lineage-related microRNA from the TransmiR v2.0 database to obtain the transcription factor capable of regulating the microRNA label.
9. The mapping of the regulation and control network of the transcription factor-microRNA-target gene is carried out through cytoscape.
After the 'transcription factor-microRNA-target gene' regulation network is obtained by the method (construction stage), the verification and application stage is further carried out, which comprises the following steps:
10. multidimensional verification method 1: obtaining the cell lineage sequencing result in the normal embryo development process known in the art, and verifying the reliability of the regulation and control network result through GSEA or GSVA analysis (data information is in the public database in the aforementioned '1, chip and preparation of RNA-seq sequencing data');
11. multidimensional verification method 2: obtaining the cell reprogramming sequencing result in the lineage reprogramming process known in the field, and verifying the reliability of the regulation and control network result through GSEA or GSVA analysis (data information is in the public database in the step 1, preparation of chip and RNA-seq sequencing data).
12. The reliability and the applicability of the gene label and the microRNA label are verified through a qRT-PCR experiment, and the in-vitro reprogramming and the monitoring of the maturity of cells after continuous multiple passages are realized;
the above process is illustrated schematically in the flow chart of fig. 1.
The unique system constructed by the inventor is used for obtaining a liver lineage-related 'transcription factor-microRNA-target gene' regulation network as shown in figure 2.
The 17 microRNAs are as follows: hsa-mir-181d-5p, hsa-mir-25-3p, hsa-mir-200c-3p, hsa-let-7a-5p, hsa-mir-181c-5p, hsa-mir-181a-5p, hsa-let-7e-5p, hsa-mir-221-3p, hsa-let-7i-5p, hsa-mir-502-3p, hsa-mir-222-3p, hsa-mir-181b-5p, hsa-mir-590-3p, hsa-mir-7-5p, hsa-mir-34a-5p, hsa-mir-26a-5p, and hsa-let-7f-2-3p.
The 23 genes were as follows: PIK3R1, PTEN, ACSL1, ANKRD46, CPEB3, CRY2, CSF1R, HAND2, HECW2, MEGF9, NHLRC3, NTF3, PAIP2, PDE4D, PGRMC1, PNRC1, RORA, SLC10A7, SLC8A1, SPRYD4, TIMP3, TMEM135, TMEM64.
Examples 2, 17 microRNAs and most of 23 genes have negative correlation, and the accuracy of the '17 microRNA' label is verified
The inventors analyzed that most of 17 microRNAs and 23 genes have negative correlation.
From the results of PCA analysis in fig. 3A, it can be seen that the four cell types (biliary tree stem cells (hBTSCs), hepatic stem cells (hHPSCs), hepatic progenitor cells (hbbs), and mature hepatocytes (hheps)) have very distinct timing sequences, so this data is applicable to the "transcription factor-microRNA-target gene" network construction method of the present invention.
After a network is constructed on the public data, the inventor obtains 17 microRNAs and 23 genes which not only have pedigree time sequence, but also have a mutual regulation relationship. As can be seen from the results of the 3D _PCAanalysis, differences in the timing sequence and maturity of these four cell types were found by means of gene tagging or microRNA tagging alone (FIGS. 3B and 3C).
Further using correlation analysis, it is clear that there is a regulatory relationship between 17 micrornas and 23 genes, mainly negative regulation (fig. 3E and 3F).
Meanwhile, it can also be seen that these 17 micrornas indeed show an overall high expression trend in the liver stem cells in embryonic development (fig. 3D).
Example 3 validation of the accuracy of the "23 Gene" signature in the database relating to embryonic development
To analyze the accuracy of 23 gene signatures (PIK 3R1, PTEN, ACSL1, ANKRD46, CPEB3, CRY2, CSF1R, HAND2, HECW2, MEGF9, NHLRC3, NTF3, PAIP2, PDE4D, PGRMC1, PNRC1, RORA, SLC10A7, SLC8A1, SPRYD4, TIMP3, TMEM135, TMEM 64), the present inventors obtained cells at different lineage development stages from the following published database related to embryonic development, respectively, and analyzed the expression of the 23 gene signatures.
GSE90047: including cells that develop during embryonic development from hepatic progenitors (hepatoblasts) to hepatocytes, 10.5 days of embryo (E10.5) to 18.5 days of embryo (E18.5);
GSE132034: including the liver organs of mice at various stages of development, embryo E12.5 → eighth week after birth (W8);
GSE28892: three cells were included: adult hepatic progenitor cells LPCs (Adult LPCs), differentiated mature hepatocytes (Differentiated Heps), primary hepatocytes (Primary Heps).
GSE56734: two cells were included, hepatic progenitors (hepatoblasts) and mature hepatocytes from embryonic day 13, E13 → Adult.
GSE25048: including two types of cells, endoderm stem cells and mature hepatocytes; endoderm _ Progenitors _1 → Mature _ Hepatocysts _4.
GSE101133: comprises four cells, liver stem cell HpSC, liver progenitor cell Hepatoblast, liver precursor cell pre-Hepatocyte and mature liver cell Hepatocyte.
GSE57878: comprises two cells, liver Progenitor Cells (LPCs) and mature liver cell mass _ hepatocyte.
The results are shown in FIGS. 4A-G, and these genes are capable of expressing genes with a generally increasing trend as the maturity of cell development progresses.
For each library, GSVA gene set mutation analysis was performed on the expression data of 23 genes to obtain the expression of the "23 gene" signature, and it was found that the expression of the gene signature was significantly up-regulated as the developmental maturity of the cell progressed (fig. 4H). Thus, in the database relating to embryo development, either trend analysis through 23 genes or single-tag analysis can suggest which cell type is in a more mature or more immature state.
Example 4 pedigree reprogramming related database verification of accuracy of "23 Gene" signature
To analyze the accuracy of the "23 gene" signature (PIK 3R1, PTEN, ACSL1, ANKRD46, CPEB3, CRY2, CSF1R, HAND2, HECW2, MEGF9, NHLRC3, NTF3, PAIP2, PDE4D, PGRMC1, PNRC1, RORA, SLC10A7, SLC8A1, SPRYD4, TIMP3, TMEM135, TMEM 64), the present inventors obtained cells at different lineage development stages from which the expression of the 23 genes was analyzed using the following already disclosed lineage reprogramming-relevant databases, respectively.
GSE75141: three cells were included: reprogrammed amplifiable hepatocytes, by which the amplifiable hepatocytes differentiate mature hepatocytes from primary mature hepatocytes;
GSE105019: three cells were included: reprogrammed hepatic progenitor-like cells, mature hepatocytes and primary hepatocytes differentiated by hepatic progenitor-like cells;
GSE124528: two types of cells are included: reprogrammed hepatic progenitor-like cells and hepatic progenitor cells differentiate into mature hepatocytes;
GSE112330: two types of cells are included: reprogrammed hepatic progenitor-like cells and hepatocytes matured by differentiation of the hepatic progenitor-like cells;
GSE116113; GSEA analysis for single cell sequencing of hepatocyte;
GSE90047; GSEA analysis for single cell sequencing of liver lineage cells;
as a result, as shown in FIGS. 5A-D, these genes showed a tendency of gradually increasing expression as the developmental maturity of the cells progressed.
As shown in fig. 5E and 5F, through analysis of single cell sequencing data, it can be found that the preferred PTEN and PIK3R1 genes can inhibit stem cell-associated pathways, suggesting that PTEN and PIK3R1 are negatively associated with sternness, suggesting that the preferred PTEN and PIK3R1 may not be merely potential markers, and may have a function of regulating hepatocyte maturation.
The GSVA gene set mutation analysis was performed on each of the above libraries to obtain the expression of the "23 gene" signature in each group, and it was found that the expression of the gene signature was significantly improved as the developmental maturity of the cells progressed (fig. 5G). Thus, in the reprogramming-associated database, either trend analysis through 23 genes or single-tag analysis can suggest which cell type is in a more mature or more immature state.
Example 5 application of microRNA tag in vitro cell culture reprogramming
The applicant realizes the transformation and amplification of human primary hepatocytes into liver precursor-like cells in an improved small molecule reprogramming culture system in the earlier stage, and the primary Hepatocyte-derived liver precursor-like cells (HepLPCs) without any exogenous gene introduction can be rapidly differentiated into functional hepatocytes to realize the reversible transformation between the "Hepate-HepLPCs" (Cell Research 2019 (1): 8-22.
The invention takes Primary hepatocytes (Primary hepatocytes, known that the metabolism and secretion of Primary hepatocytes are normal, and the cell maturity is 100% by default) and liver precursor-like cells (HepLPCs P4, hepLPCs passage 4 generation cells) obtained by reprogramming the mature hepatocytes as detection objects. That is, hepLPCs P4 is a more naive (more dry) cell than primary hepatocytes.
The expression conditions of the 17 microRNAs obtained after a large amount of screening analysis in cells at different stages are verified through qRT-PCR, so that the prediction of cell maturity and the monitoring of cell states after multiple passages are realized.
A miRcute enhanced microRNA fluorescent quantitative detection kit (SYBR Green) (EP 411) (available from Tiangen Biochemical technology, beijing) Inc.) was used.
Specific primer sequences (constructed by the tailing method) of 17 microRNAs are shown in Table 2.
TABLE 2
The downstream primer is from a detection kit of Tiangen corporation.
As a result, as shown in fig. 6, it can be seen that 12 of the obtained 17 micrornas are significantly highly expressed (70.59%) in HepLPCs P4 liver precursor-like cells, wherein a plurality of micrornas are very significantly highly expressed. Over 10 micrornas were highly expressed relative to mature hepatocytes, which verified from an apparent regulatory level that mature hepatocytes had indeed been reprogrammed to liver precursor-like cells and successfully passed to the fourth generation.
The results of 17 microRNAs were subjected to tag analysis, and the expression of the "17microRNA" tag was obtained by median analysis, with significance of P <0.0001. The label analysis also shows that HepLPCs P4 is a more immature (more dry) cell than the primary hepatocyte.
Therefore, when 17 microRNAs are used together or partially for analyzing the maturity degree of the liver lineage cells, the microRNAs can be used as the markers with ideal significance.
Example 6 application of Gene signature in vitro cell culture reprogramming
The method is characterized in that Primary hepatocytes (Primary Heps, the known cell maturity of which is 100%), hepLPCs _ P3 (passage 3 generation) and HepLPCs _ P4 (passage 4 generation) cells (the known two generations of cells are obtained by reprogramming from mature hepatocytes and are both in the stage of hepatic precursor cells) are used as detection objects, and qRT-PCR is used for verifying the expression conditions of the 23 genes obtained after the mass screening analysis in the cells at different stages, so that the monitoring of the maturity and the state of the cells to be predicted in-vitro continuous culture cells is realized.
Reverse transcription kit and TB by PrimeScript RT Master Mix (Perfect Real Time)
Premix Ex TaqTM II fluorescent quantitation qRT-PCR detection kit (purchased from TAKARA).
The primer sequences specific to the 23 genes (constructed by the tailing method) are shown in Table 3.
TABLE 3
As a result, as shown in fig. 7, it can be seen that 15 of the 23 genes obtained were significantly low expressed (65.22%) in HepLPCs P3 liver precursor cells, with many of the genes being very significantly low expressed. 16 of the 23 genes were significantly underexpressed (69.57%) in HepLPCs P4 liver precursor cells, with many of the genes being very significantly underexpressed. Thus, over 10 genes were significantly underexpressed in both sets of hepatocyte groups, which flanked the transcriptional level that indeed the successful reprogramming of mature hepatocytes into hepatocyte precursors was achieved.
The results of 23 genes were subjected to gene signature analysis using median analysis, and showed significantly low expression in both HepLPCs P3 cells and HepLPCs P4 cells. Thus, single gene signature analysis also suggests that mature hepatocytes have been reprogrammed to be liver precursor cells. Therefore, the 23 genes or the whole gene label can be used as a significant ideal marker when the gene or the whole gene label is used together or partially for the analysis of the maturity degree of the liver lineage cells.
Summarizing the expression results obtained by the 17 microRNAs, and performing double-label combined analysis, the significant low expression of the 23 gene label and the significant high expression of the 17microRNA are highly significant.
Therefore, both single-chemistry label analysis and dual-omic label integration analysis consistently prove that the primary liver mature cells are reprogrammed to be liver precursor cells, and the dryness of the primary liver mature cells can still be maintained no matter the primary liver mature cells are amplified for three generations or four generations in vitro, so that the rapid prediction and monitoring of the maturity of the liver precursor cells cultured in vitro by using the kit are successfully realized.
All documents referred to herein are incorporated by reference into this application as if each were individually incorporated by reference. Furthermore, it should be understood that various changes and modifications of the present invention can be made by those skilled in the art after reading the above teachings of the present invention, and these equivalents also fall within the scope of the present invention as defined by the appended claims.
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<212> RNA
<213> Homo sapiens
<400> 5
aacauucaac cugucgguga gu 22
<210> 6
<211> 23
<212> RNA
<213> Homo sapiens
<400> 6
aacauucaac gcugucggug agu 23
<210> 7
<211> 22
<212> RNA
<213> Homo sapiens
<400> 7
ugagguagga gguuguauag uu 22
<210> 8
<211> 23
<212> RNA
<213> Homo sapiens
<400> 8
agcuacauug ucugcugggu uuc 23
<210> 9
<211> 22
<212> RNA
<213> Homo sapiens
<400> 9
ugagguagua guuugugcug uu 22
<210> 10
<211> 22
<212> RNA
<213> Homo sapiens
<400> 10
aaugcaccug ggcaaggauu ca 22
<210> 11
<211> 21
<212> RNA
<213> Homo sapiens
<400> 11
agcuacaucu ggcuacuggg u 21
<210> 12
<211> 23
<212> RNA
<213> Homo sapiens
<400> 12
aacauucauu gcugucggug ggu 23
<210> 13
<211> 21
<212> RNA
<213> Homo sapiens
<400> 13
uaauuuuaug uauaagcuag u 21
<210> 14
<211> 24
<212> RNA
<213> Homo sapiens
<400> 14
uggaagacua gugauuuugu uguu 24
<210> 15
<211> 22
<212> RNA
<213> Homo sapiens
<400> 15
uggcaguguc uuagcugguu gu 22
<210> 16
<211> 22
<212> RNA
<213> Homo sapiens
<400> 16
uucaaguaau ccaggauagg cu 22
<210> 17
<211> 22
<212> RNA
<213> Homo sapiens
<400> 17
cuauacaguc uacugucuuu cc 22
<210> 18
<211> 24
<212> DNA
<213> Primer
<400> 18
caacattcat tgttgtcggt gggt 24
<210> 19
<211> 22
<212> DNA
<213> Primer
<400> 19
ccattgcact tgtctcggtc tg 22
<210> 20
<211> 25
<212> DNA
<213> Primer
<400> 20
cctaatactg ccgggtaatg atgga 25
<210> 21
<211> 26
<212> DNA
<213> Primer
<400> 21
cgcgtgaggt agtaggttgt atagtt 26
<210> 22
<211> 23
<212> DNA
<213> Primer
<400> 22
caacattcaa cctgtcggtg agt 23
<210> 23
<211> 21
<212> DNA
<213> Primer
<400> 23
aacattcaac gctgtcggtg a 21
<210> 24
<211> 25
<212> DNA
<213> Primer
<400> 24
cgctgaggta ggaggttgta tagtt 25
<210> 25
<211> 23
<212> DNA
<213> Primer
<400> 25
agctacattg tctgctgggt ttc 23
<210> 26
<211> 25
<212> DNA
<213> Primer
<400> 26
ccgtgaggta gtagtttgtg ctgtt 25
<210> 27
<211> 20
<212> DNA
<213> Primer
<400> 27
<210> 28
<211> 21
<212> DNA
<213> Primer
<400> 28
agctacatct ggctactggg t 21
<210> 29
<211> 22
<212> DNA
<213> Primer
<400> 29
aacattcatt gctgtcggtg gg 22
<210> 30
<211> 26
<212> DNA
<213> Primer
<400> 30
ccgcgcgcgt aattttatgt ataagc 26
<210> 31
<211> 27
<212> DNA
<213> Primer
<400> 31
cgctggaaga ctagtgattt tgttgtt 27
<210> 32
<211> 21
<212> DNA
<213> Primer
<400> 32
tggcagtgtc ttagctggtt g 21
<210> 33
<211> 25
<212> DNA
<213> Primer
<400> 33
ccgttcaagt aatccaggat aggct 25
<210> 34
<211> 26
<212> DNA
<213> Primer
<400> 34
gccgctatac agtctactgt ctttcc 26
<210> 35
<211> 21
<212> DNA
<213> Primer
<400> 35
cttatgggct tcggagcttt t 21
<210> 36
<211> 21
<212> DNA
<213> Primer
<400> 36
caagtagtgc ggatcttcgt g 21
<210> 37
<211> 22
<212> DNA
<213> Primer
<400> 37
taaattcggt gccgatcttc tg 22
<210> 38
<211> 23
<212> DNA
<213> Primer
<400> 38
gagtgggttc ctctgttaaa tcc 23
<210> 39
<211> 20
<212> DNA
<213> Primer
<400> 39
<210> 40
<211> 21
<212> DNA
<213> Primer
<400> 40
gagcggtgat tccatctgca t 21
<210> 41
<211> 21
<212> DNA
<213> Primer
<400> 41
ggtgtggaag tagtgacgga g 21
<210> 42
<211> 21
<212> DNA
<213> Primer
<400> 42
gtaggtctcg tcgtggttct c 21
<210> 43
<211> 21
<212> DNA
<213> Primer
<400> 43
gctactgctg ttgctgctct t 21
<210> 44
<211> 21
<212> DNA
<213> Primer
<400> 44
ttgccttcgt atctctcgat g 21
<210> 45
<211> 19
<212> DNA
<213> Primer
<400> 45
cgccgacacc aaactctcc 19
<210> 46
<211> 19
<212> DNA
<213> Primer
<400> 46
tcgccattct ggtcgtcct 19
<210> 47
<211> 20
<212> DNA
<213> Primer
<400> 47
<210> 48
<211> 20
<212> DNA
<213> Primer
<400> 48
<210> 49
<211> 21
<212> DNA
<213> Primer
<400> 49
gtgagtgtcg gccaggttat c 21
<210> 50
<211> 21
<212> DNA
<213> Primer
<400> 50
tgttgcacgg tatgctgaga g 21
<210> 51
<211> 21
<212> DNA
<213> Primer
<400> 51
ggttttgcat tcgcgttttt g 21
<210> 52
<211> 23
<212> DNA
<213> Primer
<400> 52
acatccagcc ggtaaagaat ttt 23
<210> 53
<211> 20
<212> DNA
<213> Primer
<400> 53
<210> 54
<211> 20
<212> DNA
<213> Primer
<400> 54
<210> 55
<211> 21
<212> DNA
<213> Primer
<400> 55
tctcccacaa actatggacc a 21
<210> 56
<211> 23
<212> DNA
<213> Primer
<400> 56
tgcatttgga ttcagattgc tct 23
<210> 57
<211> 21
<212> DNA
<213> Primer
<400> 57
ccacgatagc tgctcaaaca a 21
<210> 58
<211> 21
<212> DNA
<213> Primer
<400> 58
gtgccattgt ccacatcaaa a 21
<210> 59
<211> 21
<212> DNA
<213> Primer
<400> 59
gggctgctgc atgagatttt c 21
<210> 60
<211> 19
<212> DNA
<213> Primer
<400> 60
ccgcgcacga tcttgtaga 19
<210> 61
<211> 22
<212> DNA
<213> Primer
<400> 61
aagaagttga acgagtggtt gg 22
<210> 62
<211> 20
<212> DNA
<213> Primer
<400> 62
<210> 63
<211> 20
<212> DNA
<213> Primer
<400> 63
<210> 64
<211> 22
<212> DNA
<213> Primer
<400> 64
gaggtgatct tggttagtgg ca 22
<210> 65
<211> 23
<212> DNA
<213> Primer
<400> 65
tggattcgac ttagacttga cct 23
<210> 66
<211> 23
<212> DNA
<213> Primer
<400> 66
ggtgggttat ggtcttcaaa agg 23
<210> 67
<211> 20
<212> DNA
<213> Primer
<400> 67
<210> 68
<211> 19
<212> DNA
<213> Primer
<400> 68
gaagttccgt cagcccgtt 19
<210> 69
<211> 20
<212> DNA
<213> Primer
<400> 69
gctcatctac cacccagctc 20
<210> 70
<211> 20
<212> DNA
<213> Primer
<400> 70
<210> 71
<211> 21
<212> DNA
<213> Primer
<400> 71
acaacatgcg gcgattaagt c 21
<210> 72
<211> 21
<212> DNA
<213> Primer
<400> 72
gctctagcaa ttttgtcccc a 21
<210> 73
<211> 21
<212> DNA
<213> Primer
<400> 73
tgatgatcgt tcctgggtgt t 21
<210> 74
<211> 19
<212> DNA
<213> Primer
<400> 74
tggctgccca ataccctca 19
<210> 75
<211> 20
<212> DNA
<213> Primer
<400> 75
<210> 76
<211> 22
<212> DNA
<213> Primer
<400> 76
aggtgatacc gatagttcag cc 22
<210> 77
<211> 22
<212> DNA
<213> Primer
<400> 77
caagtccatc cctcataact gc 22
<210> 78
<211> 22
<212> DNA
<213> Primer
<400> 78
gcaatcaagt acagaggagc at 22
<210> 79
<211> 19
<212> DNA
<213> Primer
<400> 79
tgggtggaga gccttgact 19
<210> 80
<211> 19
<212> DNA
<213> Primer
<400> 80
gaaggtgccg atgaggacg 19
Claims (20)
- Use of a detection reagent of a microRNA signature or a gene signature or a combination thereof in the preparation of a kit or a detection device for assessing the maturity of cells of the hepatic lineage for distinguishing hepatic progenitor cells from mature hepatic cells, the microRNA signature comprising 10 to 17 microRNAs selected from the group consisting of:hsa-let-7a-5p，hsa-let-7e-5p，hsa-let-7i-5p，hsa-mir-7-5p，hsa-let-7f-2-3p，hsa-mir-181d-5p，hsa-mir-25-3p，hsa-mir-200c-3p，hsa-mir-181c-5p，hsa-mir-181a-5p，hsa-mir-221-3p，hsa-mir-502-3p，hsa-mir-222-3p，hsa-mir-181b-5p，hsa-mir-590-3p，hsa-mir-34a-5p，hsa-mir-26a-5p；the gene tag comprises 10 to 23 genes selected from the following group:PIK3R1，PTEN，ACSL1，ANKRD46，CPEB3，CRY2，CSF1R，HAND2，HECW2，MEGF9，NHLRC3，NTF3，PAIP2，PDE4D，PGRMC1，PNRC1，RORA，SLC10A7，SLC8A1，SPRYD4，TIMP3，TMEM135，TMEM64。
- 2. the use according to claim 1, wherein the 10 to 17microRNA tags comprise: 1-5 of hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7-5p and hsa-let-7f-2-3p.
- 3. The use according to claim 2, wherein the 10 to 17microRNA tags comprise: 2-5 of hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7-5p and hsa-let-7f-2-3p.
- 4. The use of claim 1, wherein the 10 to 23 gene signatures comprise PIK3R1 or PTEN.
- 5. The use according to any one of claims 1 to 4, wherein said assessing the maturity of cells of the hepatic lineage is carried out by detecting the expression of said microRNA signature or gene signature or a combination thereof within the cells; the obvious high expression level of the microRNA label indicates that the cell is a hepatic progenitor cell, and the obvious low expression level indicates that the cell is a mature hepatic cell; the significant high expression level of the gene label indicates that the cell is a mature hepatocyte, and the significant low expression level indicates that the cell is a hepatic progenitor cell.
- 6. The use of claim 1, wherein the detection reagent comprises: a PCR detection reagent, an in situ hybridization reagent or an immunodetection reagent aiming at the microRNA label or the gene label.
- 7. The use of claim 6, wherein the detection reagent comprises: specifically amplifying the microRNA label or the primer of the gene label, and specifically identifying the probe of the microRNA label or the gene label or the antibody specifically binding with the protein coded by the gene label.
- 8. The application of claim 7, wherein the detection reagent is a primer, the nucleotide sequence of the upstream primer for detecting the microRNA label is selected from the group consisting of SEQ ID NO 18-34, and the nucleotide sequence of the primer for detecting the gene label is selected from the group consisting of SEQ ID NO 35-80.
- 9. The use of claim 1, wherein said detecting means comprises: a chip, an electrophoresis device or a gene sequencing instrument.
- 10. A kit or test device for assessing the maturity of cells of the hepatic lineage that distinguish between hepatic progenitors and mature hepatocytes, comprising: the detection reagent aims at microRNA labels or gene labels or the combination thereof, wherein the microRNA labels comprise 10-17 microRNAs selected from the following group:hsa-let-7a-5p，hsa-let-7e-5p，hsa-let-7i-5p，hsa-mir-7-5p，hsa-let-7f-2-3p，hsa-mir-181d-5p，hsa-mir-25-3p，hsa-mir-200c-3p，hsa-mir-181c-5p，hsa-mir-181a-5p，hsa-mir-221-3p，hsa-mir-502-3p，hsa-mir-222-3p，hsa-mir-181b-5p，hsa-mir-590-3p，hsa-mir-34a-5p，hsa-mir-26a-5p；the gene tag comprises 10 to 23 genes selected from the following group:PIK3R1，PTEN，ACSL1，ANKRD46，CPEB3，CRY2，CSF1R，HAND2，HECW2，MEGF9，NHLRC3，NTF3，PAIP2，PDE4D，PGRMC1，PNRC1，RORA，SLC10A7，SLC8A1，SPRYD4，TIMP3，TMEM135，TMEM64。
- 11. the kit or test device of claim 10, wherein the test reagents comprise: PCR detection reagent, in situ hybridization reagent or immunity detection reagent.
- 12. A system for assessing the maturity of cells of the hepatic lineage that differentiate between hepatic progenitors and mature hepatocytes, comprising a detection unit and a data analysis unit;the detection unit includes: a detection reagent capable of measuring the expression level of the microRNA label or the gene label or the combination thereof, or a kit or a detection device containing the detection reagent; the detection reagent comprises: the detection reagent aims at microRNA labels or gene labels or the combination thereof, wherein the microRNA labels comprise 10-17 microRNAs selected from the following group:hsa-let-7a-5p，hsa-let-7e-5p，hsa-let-7i-5p，hsa-mir-7-5p，hsa-let-7f-2-3p，hsa-mir-181d-5p，hsa-mir-25-3p，hsa-mir-200c-3p，hsa-mir-181c-5p，hsa-mir-181a-5p，hsa-mir-221-3p，hsa-mir-502-3p，hsa-mir-222-3p，hsa-mir-181b-5p，hsa-mir-590-3p，hsa-mir-34a-5p，hsa-mir-26a-5p；the gene tag comprises 10 to 23 genes selected from the following group:PIK3R1，PTEN，ACSL1，ANKRD46，CPEB3，CRY2，CSF1R，HAND2，HECW2，MEGF9，NHLRC3，NTF3，PAIP2，PDE4D，PGRMC1，PNRC1，RORA，SLC10A7，SLC8A1，SPRYD4，TIMP3，TMEM135，TMEM64；the data analysis unit includes: and the processing unit is used for analyzing and processing the detection result of the detection unit, obtaining the evaluation result of the maturity of the liver lineage cells and distinguishing the liver progenitor cells from the mature liver cells.
- 13. The system of claim 12, wherein the detection reagent comprises: PCR detection reagent, in situ hybridization reagent or immunity detection reagent.
- 14. The system of claim 13, wherein the detection reagent comprises: specifically amplifying the microRNA label or the primer of the gene label, a probe specifically recognizing the microRNA label or the gene label, or an antibody specifically binding with the protein coded by the gene label.
- 15. The system of claim 14, wherein the detection reagent is a primer, the nucleotide sequence of the upstream primer for detecting the microRNA tag is selected from the group consisting of SEQ ID NO 18-34, and the nucleotide sequence of the primer for detecting the gene tag is selected from the group consisting of SEQ ID NO 35-80.
- 16. The system of claim 12, wherein said detecting means comprises: a chip, an electrophoresis device or a gene sequencing instrument.
- 17. A method of assessing the maturity of a cell of the hepatic lineage that distinguishes between hepatic progenitors and mature hepatocytes comprising: evaluating using the system of any one of claims 12-16; the method comprises the following steps: detecting the expression level of the microRNA label or the gene label or the combination thereof by using the detection unit, and analyzing and processing the detection result of the detection unit by using the data analysis unit to obtain a liver lineage cell maturity result; wherein,the obvious high expression level of the microRNA label indicates that the cell is a hepatic progenitor cell, and the obvious low expression level indicates that the cell is a mature hepatic cell;when the expression level of the gene label is obviously high, the cell is a mature liver cell, and when the expression level is obviously low, the cell is a liver progenitor cell.
- 18. The method of claim 17, comprising the steps of:(1) Obtaining a nucleic acid sample of a cell to be detected;(2) Detecting the expression level of a microRNA signature or a gene signature or a combination thereof of the cell;(3) The following expression significance difference analysis was performed:satisfying one or more of the following conditions, indicating that the cell is a mature hepatocyte:(1) the expression of all gene tags is statistically significant on the whole,(2) the expression of all microRNA labels has statistical significance to be reduced,(3) the gene label and the microRNA label are subjected to double-label integration difference analysis, namely the whole high expression of the gene label in an experimental group and the whole low expression of the microRNA label are also obviously different;satisfying one or more of the following conditions, indicating that the cell is a hepatic progenitor:(a) The expression of all gene signatures was statistically reduced as a whole,(b) The expression of all microRNA labels is statistically significant,(c) The gene label and the microRNA label are subjected to double-label integration difference analysis, namely the overall low expression of the gene label in an experimental group and the overall high expression of the microRNA label are obviously different.
- 19. The method of claim 17, wherein the method is used to rapidly determine whether there is a change in maturity or sternness during in vitro scale culture or reprogramming of cells to distinguish between hepatic progenitors and mature hepatocytes.
- 20. The method of claim 17, wherein the method is used to perform a maturity analysis of liver lineage cells at various states collected in different databases to distinguish between hepatic progenitors and mature hepatocytes.
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