CN113106160B - Markers, dual-omics kits and construction methods for assessing hepatic lineage cell maturity - Google Patents

Abstract

The invention provides a marker, a dual-omics kit and a construction method for evaluating the maturity of liver lineage cells. For the first time, the present invention expounds the microRNA sets and gene sets with time-sequential characteristics and regulatory relationship in cell development from a new perspective, and establishes a "transcription factor-microRNA-target gene" regulatory network related to regulating the differentiation and maturation of hepatocytes, and Liver lineage-specific gene signatures and microRNA signatures were obtained, which, or their combination, could serve as potential new markers of liver lineage cells. The invention also provides a dual-omics kit for hepatic lineage cells, which provides a new solution for large-scale expansion of stable hepatic lineage cells and monitoring the in vitro culture state of hepatic lineage cells.

Description

Markers, dual-omics kits and construction methods for assessing the maturity of hepatic lineage cells

technical field

The present invention relates to the field of biomedicine; more specifically, the present invention relates to a marker for evaluating the maturity of hepatic lineage cells, a dual-omics kit and a construction method.

Background technique

Stem cells, as a cell type with self-renewal and multilineage differentiation potential, provide an effective new therapeutic strategy for the treatment of organ function loss caused by end-stage diseases. At present, more than ten kinds of stem cell therapy products have been approved for marketing in the world, but there is no product approved in China. With the gradual improvement of China's stem cell therapy product management standards, 51 stem cell clinical studies in China have been filed with the National Health and Medical Commission, and 3 stem cell drugs have been accepted by the Food and Drug Administration and approved by the IND to enter clinical trials. The liver is the most important organ of human metabolism, and end-stage liver disease characterized by loss of liver function is a major hazard to human health. China is a big country with liver diseases. At present, 8 stem cell clinical research projects related to liver diseases have passed the filing.

However, regardless of the stem cell products that have been marketed or are undergoing clinical trials and clinical research stages, the current production process of stem cell products is mostly based on the traditional two-dimensional culture system. Under the two-dimensional culture system, the proliferation ability of stem cells is limited, stem cells are easily lost, and the system has high labor costs, large production losses, and unstable cell batch quality, which is not suitable for the industrial preparation and production of stem cell products. Compared with the two-dimensional culture system, the three-dimensional culture simulates the natural state of cells in the body, which can not only effectively maintain the stemness of stem cells and the stemness during the expansion process, but also overcome the problems of consumables and preparation space loss in two-dimensional culture conditions. Therefore, in stem cell products It has great advantages in large-scale expansion.

At present, the three-dimensional culture and expansion of stem cells based on microcarriers has made very good progress by simulating the microenvironment in vivo. On the basis of microcarriers combined with bioreactors, it is now possible to achieve large-scale expansion of stem cells including umbilical cord mesenchymal stem cells, and realize the production process of obtaining millions of cells in a short period of time. However, there are still many issues to be clarified in the transition from "small test" to large-scale expansion. The monitoring of the stability of the stemness of stem cells in large-scale expansion, and the quality (safety and effectiveness) of stem cell products Safeguarding is a top priority in the process.

At present, the commonly used indicators that can be used to detect the stability of three-dimensional large-scale expansion of stem cells are mostly indicators used to identify the characteristics of stem cells under two-dimensional culture conditions. For example, umbilical cord mesenchymal stem cells, umbilical cord mesenchymal stem cells maintained under two-dimensional culture conditions need to meet the surface markers of stem cells, gene expression and the ability of adipogenic, osteogenic, and chondrogenic differentiation. These indicators are also used as gold standards and are widely used in the quality identification of three-dimensional large-scale expansion of 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 a sufficient number of hepatocytes for transplantation, the present inventors currently obtain hepatic precursor cells or hepatic stem cells that can proliferate in vitro, and establish a large-scale expansion system for hepatic precursor cells or hepatic stem cells. After obtaining a sufficient number of transplantable cells, the liver precursor cells or liver stem cells are induced to differentiate into hepatocytes before transplantation, so as to obtain sufficient functional liver cells for transplantation to treat end-stage liver disease.

Based on this treatment strategy, the expansion of liver precursor cells or liver stem cells and the functional differentiation and maturation of liver precursor cells or liver stem cells into liver cells are involved. How to realize the detection of the stability of liver precursor cells or liver stem cells in the large-scale expansion during the first stage, and how to realize the evaluation of the functional maturity of liver cells in the second stage, is to realize large-scale Expanded hepatic precursor cells or hepatic stem cells are key to the treatment of end-stage liver disease.

At present, the evaluation of the stemness of liver precursor cells and liver stem cells in the first stage needs to be evaluated based on the expression of stem cell genes and the low expression of maturation markers, and there is still a lack of highly sensitive evaluation markers. The stability detection and quality control of mature hepatocytes in the second stage need to be comprehensively evaluated with more complex functional identification indicators, including cell morphology, detection of hepatocyte-specific gene expression levels, and indocyanine green uptake. Detoxification, fat synthesis, albumin secretion, urea synthesis, drug metabolism, etc. Due to its complex evaluation criteria, it is difficult to promote in the process of large-scale expansion. Therefore, there is an urgent need for a marker that can evaluate the stemness or maturity of liver stem cells, liver precursor cells and hepatocytes at different stages.

Human biliary tree stem cells (hBTSCs) are stem cells located in the peribiliary glands within the biliary tract. Isolation of biliary tree stem cells and their in vitro and in vivo characterization suggest that they can differentiate into mature hepatocytes, cholangiocytes, and pancreatic endocrine cells. Biliary tree stem cells were found in the major ducts of the biliary tree in donors of all ages, potentially giving rise to functional cell types during organ injury. At the distal end of the bile ducts in the hepatic parenchyma, known as the canal of Hering, is thought to be the niche where human hepatic stem cells (hHpSCs) reside. Biliary tree stem cells have been successfully used to rescue animals with liver dysfunction diseases and patients with end-stage liver disease. However, as found in studies of hepatocyte generation from pluripotent stem cells, including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), the time required for hBTSCs or hHpSCs to mature into hepatocytes takes months, and Often less efficient hepatocytes are obtained. At the same time, when culturing biliary tree stem cells, hepatic stem cells and mature hepatocytes in vitro, it is often difficult to predict the developmental state and maturity of hepatic stem cells, and it is impossible to quickly diagnose the cells of mature hepatocytes or liver precursor cells on a large scale. state.

Therefore, there is an urgent need in this field to have a solution for rapid detection and prediction of the maturity of hepatocytes, which is a basic task for the successful implementation of stem cell-based treatment of liver diseases.

Contents of the invention

The purpose of the present invention is to provide a marker for evaluating the maturity of hepatic lineage cells, a dual-omics kit and a construction method.

In the first aspect of the present invention, there is provided a microRNA tag or a gene tag or a combination thereof in the preparation of a detection reagent, a kit or a detection device for assessing the maturity of liver lineage cells, the microRNA tag includes a group selected from 10-17 microRNAs (such as 12, 14, 16):

The gene signature includes 10 to 23 genes (such as 12, 14, 16, 18, 20, 22) selected from the following group:

In another preferred example, the gene includes its transcript (mRNA).

In another preferred example, the assessment of the maturity of the hepatic lineage cells includes evaluating the stemness or maturity of hepatic stem cells, hepatic precursor cells, hepatocytes or biliary tree stem cells (hBTSCs) at different stages.

In another preferred example, the 10-17 microRNAs include: hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7-5p and 1-5, preferably 2-5 (such as 3 or 4) of hsa-let-7f-2-3p.

In another preferred example, the 10-23 genes include 1 or 2 of PIK3R1 and PTEN gene signatures.

In another preferred example, the assessment of the maturity of the hepatic lineage cells is carried out by detecting the expression of the microRNA label or gene label or a combination thereof in the cell; a significantly higher expression level of the microRNA label indicates that the more mature the cell Low (more immature) or higher stemness, significantly lower expression levels indicate higher cell maturity (more mature) or lower stemness; significantly higher expression levels of the gene signature indicate higher cell maturity (more mature ) or lower stemness, a significantly lower expression level indicates lower cell maturity (more immature) or higher stemness.

In another preferred example, the detection reagents for assessing the maturity of hepatic lineage cells include (but not limited to): PCR detection reagents, in situ hybridization reagents or immunological detection reagents for the microRNA tag or the gene tag preferably, including (but not limited to): primers for specifically amplifying the microRNA tag or the gene tag, specific recognition of the microRNA tag or the gene tag probe or specific binding to the gene The antibody of the protein encoded by the label; more preferably, the detection reagent is a primer, and the nucleotide sequence of the primer for detecting the microRNA label is selected from those shown in SEQ ID NO: 18-34 (downstream primers are from Tiangen kit), and the detection The nucleotide sequences of the primers of the gene tags are selected from those shown in SEQ ID NO:35-80.

In another preferred example, the detection device includes (but not limited to): a chip, a probe set (module), a primer probe set (module), an electrophoresis device or a gene sequencing instrument.

In another preferred example, the evaluation of the maturity of the hepatic lineage cells includes: evaluating the process of cell differentiation or the state of cells after differentiation, and evaluating the process of cell reprogramming or the state of cells after reprogramming.

In another aspect of the present invention, a kit or detection device for assessing the maturity of hepatic lineage cells is provided, which includes detection reagents for assessing the maturity of hepatic lineage cells, including (but not limited to): targeting microRNA tags Or a gene tag or a combination detection reagent, the microRNA tag includes 10 to 17 microRNAs (such as 12, 14, 16) selected from the following group:

The gene signature includes 10 to 23 genes (such as 12, 14, 16, 18, 20, 22) selected from the following group:

In another aspect of the present invention, a system for assessing the maturity of hepatic lineage cells is provided, comprising a detection unit and a data analysis unit;

The detection unit includes: a detection reagent that can measure the expression level of a microRNA tag or a gene tag or a combination thereof, or a kit or a detection device containing the detection reagent; the detection reagent includes (but is not limited to): A detection reagent for a tag or a gene tag or a combination thereof, the microRNA tag includes 10 to 17 microRNAs (such as 12, 14, 16) selected from the following group:

The gene signature includes 10-23 microRNAs (such as 12, 14, 16, 18, 20, 22) selected from the following group:

The data analysis unit includes: a processing unit for analyzing and processing the detection results of the detection unit (measured expression levels of microRNA tags or gene tags or combinations thereof), to obtain evaluation results of the maturity of hepatic lineage cells.

In a preferred example, the detection reagents include (but not limited to): PCR detection reagents, in situ hybridization reagents or immunological detection reagents, more preferably, include (but not limited to): specific amplification of the microRNA tag or Primers for the gene tag, probes that specifically recognize the microRNA tag or the gene tag, or antibodies that specifically bind to the protein encoded by the gene tag; preferably, the detection reagent is a primer that detects the microRNA tag The nucleotide sequences of the primers are selected from those shown in SEQ ID NOs: 18-34 (the downstream primers are from Tiangen kit), and the nucleotide sequences of the primers for detecting gene tags are selected from those shown in SEQ ID NOs: 35-80.

In another preferred example, the detection device includes (but not limited to): a chip, a probe set (module), a primer probe set (module), an electrophoresis device or a gene sequencing instrument.

In another aspect of the present invention, there is provided a method for assessing the maturity of hepatic lineage cells, comprising: using the system assessment described in claim 8 or 9; comprising: using the detection unit to detect the microRNA label or gene label or The expression level of its combination, and use the data analysis unit to analyze and process the detection result of the detection unit to obtain the result of the maturity of the hepatic lineage cells; wherein, the significantly higher expression level of the microRNA tag indicates that the lower the cell maturity ( The more immature) or the higher the stemness, the significantly lower expression level indicates that the cell maturity is higher (more mature) or the stemness is lower; the significantly higher expression level of the gene signature indicates that the cell maturity is higher (more mature) or The lower the stemness, the significantly lower expression levels indicate less mature (naive) or higher stemness of the cells.

In another preferred example, the following steps are included:

(1) obtaining a nucleic acid sample of the cell to be tested;

(2) Detecting the expression level of microRNA tags or gene tags or a combination thereof of the cells;

(3) Perform the following significant difference analysis of expression:

Satisfying one or more of the following conditions (1-5, such as 1, 2, 3, 4, 5) indicates that the higher the cell maturity or the lower the stemness:

① More than 50% of the gene signatures (more than 50% of 10 to 23) are highly expressed,

② The expression of all gene signatures (10-23) has a statistically significant increase on the whole,

③Low expression of more than 50% microRNA tags (more than 50% of 10-17 microRNAs),

④The expressions of all microRNA tags (10-17) were statistically significantly reduced,

⑤ There is also a significant difference in the double-label integration differential analysis of gene tags and microRNA tags, that is, the overall high expression of gene tags in the experimental group is also significant compared with the overall low expression of microRNA tags;

Satisfying one or more of the following conditions (1-5, such as 1, 2, 3, 4, 5) indicates that the lower the cell maturity or the higher the stemness:

(a) More than 50% of gene signatures (more than 50% of 10 to 23) are underexpressed,

(b) The expression of all gene signatures (10-23) is statistically significantly lower overall,

(c) More than 50% of microRNA tags (more than 50% of 10 to 17 microRNAs) are highly expressed,

(d) The expression of all microRNA tags (10-17) has a statistically significant increase,

(e) There is also a significant difference in the double-label integration differential analysis of gene tags and microRNA tags, that is, the overall low expression of gene tags in the experimental group is also significant compared with the overall high expression of microRNA tags;

If the result of the significant difference analysis is not significant, it indicates that the cell state is stable, and there is no obvious change in stemness and maturity.

In another preferred example, the "overall statistically significant increase" or "overall statistically significant decrease" refers to performing an overall statistical analysis of the expression of the group of tags to obtain a statistically significant representative expression The value of the level, for example, can include but not limited to the following statistics: expression median statistics, expression mean statistics, GSVA analysis.

In another preferred example, the method is used to target liver lineage cells in various states collected in different databases (such as but not limited to including embryonic liver stem cells, endoderm stem cells, liver precursor cells, mature liver cells, Adult hepatocytes, mature hepatocytes induced to differentiate, etc.) for maturity analysis.

In another preferred embodiment, the method is used to quickly judge whether the maturity or stemness of cells changes during large-scale culture in vitro, continuous subculture or reprogramming.

In another preferred example, the method for assessing the maturity of hepatic lineage cells is a method that does not directly aim at diagnosing a disease, or is a non-diagnostic method.

In another aspect of the present invention, a method for establishing a cell lineage-related "transcription factor-microRNA-target gene" regulatory network is provided, including:

(1) Obtain cells at different stages of the cell lineage, perform microRNA sequencing and RNA-seq sequencing (for example, can be obtained by data integration and cleaning of public databases);

(2) Determine the temporal characteristics of cell development through principal component analysis (PCA analysis);

(3) Perform short time series expression analysis (STEM analysis) to obtain microRNA sets and mRNA sets that change over time;

(4) GO or KEGG enrichment analysis;

(5) Use the microRNA-related target gene prediction database to obtain the target gene of the microRNA whose expression level gradually changes over time; preferably, the database includes (but not limited to) miRDB, miRTarBase, TargetScan, miRWalk and DIANA-MicroT - CDS database;

(6) Intersect with the genes whose expression levels change with lineage development, and then obtain microRNA tags and target gene tags that not only change gradually with lineage development but also have mutual regulatory effects.

In another preferred example, after step (6), it also includes: further verifying the reliability of the microRNA tags and target gene tags 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 example, it further includes: downloading experimentally supported lineage-associated microRNAs and their interactions between regulatory transcription factors from the TransmiR v2.0 database to obtain transcription factors capable of regulating microRNA tags.

In another preferred embodiment, it further includes: mapping the regulatory network of "transcription factor-microRNA-target gene" by cytoscape.

In another preferred example, it further includes: multi-dimensional verification method 1: obtaining cell lineage sequencing results during normal embryonic development, and verifying the reliability of regulatory network results through GSEA or GSVA analysis.

In another preferred example, it further includes: multi-dimensional verification method 2: obtaining the sequencing results of cell reprogramming in the process of lineage reprogramming, and verifying the reliability of the regulatory network results through GSEA or GSVA analysis.

In another preferred example, it further includes: verifying the obtained microRNA and genes by qRT-PCR and other experimental means, and monitoring the maturity of reprogrammed cells after serial passage in vitro.

Other aspects of the invention will be apparent to those skilled in the art from the disclosure herein.

Description of drawings

Figure 1. The basic steps and process of constructing the cell lineage-related "transcription factor-microRNA-target gene" regulatory network.

Figure 2. The unique system constructed by the present invention obtains the regulatory network of "transcription factor-microRNA-target gene" related to liver lineage.

Figure 3A-F, most of the 17 microRNAs and 23 genes are negatively correlated, and verify the accuracy of the "17microRNA" label.

Figure 4A-H, the accuracy of the label "23 genes" verified by the database related to embryonic development.

Figure 5A-G, lineage reprogramming-related database verification of the accuracy of the "23 genes" label.

Figure 6. Application of microRNA tags in in vitro cell culture reprogramming.

Figure 7. Application of gene tags in in vitro cell culture reprogramming.

Detailed ways

After a lot of analysis, research and screening, the present inventors expounded for the first time from a new perspective that there are microRNAs and genes with timing characteristics and regulatory relationships in the development of liver lineage cells, and established a "regulatory mechanism" related to the regulation of liver cell differentiation and maturation. Transcription factor-microRNA-target gene” regulatory network, and obtained liver lineage-specific gene signatures and microRNA signatures, these signatures or their combination can be used as potential new markers of liver lineage cells. On this basis, the present invention also provides a hepatic lineage-related dual-omics kit, which provides a new solution for large-scale expansion of stable hepatic lineage cells and monitoring the in vitro culture status of hepatic lineage cells.

the term

As used in the present invention, the "assessment" includes "detection", "measurement", "analysis", "prediction" or "evaluation".

As used herein, the "kit" may refer to a system of materials or reagents used to practice the methods disclosed herein.

As used in the present invention, the terms "high expression" and "high expression level" are interchangeable with each other and shall mean 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 significant increase. For example, the Student's T-test can be used to repeatedly detect at least one gene whose expression intensity exceeds the threshold to determine significance.

As used in the present invention, the terms "low expression" and "low expression level" are interchangeable with each other and shall mean at least 2%, 3%, 4% compared with "control" or "threshold" in the applied meaning %, 5%, 6%, 7%, 8%, 9% or 10%, preferably at least 15% or 20%, more preferably 25%, 30%, 50%, 80%, 100% or more significant reduction . For example, the Student's T-test can be used to repeatedly detect at least one gene whose expression intensity is lower than the threshold to determine significance.

As used in the present invention, the setting of "control" or "threshold" of gene or microRNA expression can be easily set by those skilled in the art based on the gist of the present invention. Choosing an appropriate "control" or "threshold" is a routine part of the experimental design. For example, the expression level of the corresponding microRNA or gene can be analyzed for statistical significance based on the expression level of the corresponding microRNA or gene in the cells whose maturity has been determined, and the obtained expression Value as "control" or "threshold".

The definition of cell maturity can be carried out according to existing definition standards in this field (such as the field of cell differentiation or cell reprogramming).

"Transcription factor-microRNA-target gene" regulatory network

Through a lot of research and analysis, the present inventors revealed in the present invention a specific regulatory network of microRNA and mRNA, which is closely related to the maturation of hepatic lineage stem cells into functional hepatocytes.

microRNA (microRNAs) is a class of short RNAs about 22 nucleotides in length that can form mRNA-induced silencing by cleaving messenger mRNA molecules (mRNA) or by binding to the complementary regions of their 3' untranslated regions (UTRs) complex to inhibit its translation to regulate messenger mRNA. Using these negative regulatory mechanisms, microRNAs are involved in a variety of developmental and biological cellular processes, including stem cell differentiation and cell cycle regulation. At the same time, microRNAs exert their regulatory functions by targeting various genes related to one or more signaling pathways, including HIPPO, WNT/β-catenin, PI3K/AKT signaling pathways, etc. However, which microRNAs are relevant to the timing of hepatocyte development, the regulatory network that microRNAs participate in, and how microRNAs manipulate the lineage maturation of stem cells at early lineage stages, including the differentiation of hepatic stem cells to hepatocytes, have not been elucidated in the art.

The present inventors found in their studies that when hepatocytes were transplanted into an animal model of liver injury, hepatocytes underwent hepatic differentiation and produced functional hepatocytes to rescue liver injury; however, the exact triggers that promote and maintain biliary tree stem cell differentiation and regulatory factors are unknown, which prompted the inventors' search work. The inventors analyzed 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 (hHBs) and mature hepatocytes (hAHeps) . On this basis, after a lot of analysis work, a potential "transcription factor-microRNA-target gene" regulatory network that can regulate the differentiation and maturation of hepatocytes was revealed.

The present invention also provides a method of how to construct the regulatory network of "transcription factor-microRNA-target gene" in the process of cell development and maturation lineage, the preferred operation mode of this method given in Figure 1 of the present invention and the examples.

On the basis of providing a "transcription factor-microRNA-target gene" regulatory network, the inventors not only obtained potential new markers of liver lineage-related cells, but also obtained a variety of verification methods (microRNA sequencing, RNA-seq sequencing, single Cell sequencing, qRT-PCR) verified its validity and applicability. As a result, a hepatic lineage-related dual-omics kit was developed, which provides new ideas and solutions for large-scale expansion of stable hepatic lineage-related cells and monitoring the in vitro culture status of hepatic lineage-related cells.

The establishment scheme of the above-mentioned regulatory network of the present invention can also be applied to the analysis of other types of cells other than the hepatic lineage cells. Stem cells can be differentiated into various cell types. By means of the analysis method of the present invention, it is also possible to analyze the differentiation process of stem cells to other types of cells or vice versa. Differentiation or reprogramming towards (maturity) microRNAs and/or target genes.

The present invention provides a complete method for predicting the development of cell lineages and constructing a "transcription factor-microRNA-target gene" regulatory network, and provides a complete method for studying the regulatory relationship between coding genes and non-coding genes in the development of more cell lineages. prediction system.

The method of the present invention is universally applicable to hepatic lineage cells of various species, such as but not limited to primates (including humans), rodents (such as mice, rats) and the like.

microRNA tags and gene tags and their applications

Based on the inventors' novel findings, the present invention reveals two omics signatures specific to the liver lineage: the "23 gene" signature and the "17 microRNA" signature. The present invention also discloses markers, kits and methods for assessing the maturity of hepatic lineage cells. Preferably, by performing enrichment analysis and multi-angle analysis on the test set data, we also optimize molecules that can not only be used as one of the markers in the label, but also may play a role in affecting the differentiation and maturation of liver cells. These core genes are The PIK3R1 and PTEN genes of the PI3K/AKT signaling pathway, the preferred microRNA is hsa-let-7a-5p, hsa-let-7e-5p, hsa-let-7i-5p, hsa-mir-7 in the let-7 family -5p, hsa-let-7f-2-3p.

The above-mentioned microRNA signature and gene signature disclosed in the present invention can be used as judgment marks (markers) for assessing the maturity of hepatic lineage cells. Therefore, it can be used to understand the state of the cells of interest (cells to be tested). The states include, but are not limited to: stable (non-differentiated, non-reprogrammed) state, differentiated (towards maturation) state, naive (towards increased stemness) state, and the like. The assessment of the maturity of hepatic lineage cells includes but is not limited to: evaluating the stemness or maturity of hepatic stem cells, hepatic precursor cells, hepatocytes or biliary tree stem cells (hBTSCs) at different stages.

Using the above-mentioned microRNA tags and gene tags disclosed in the present invention, the evaluated cells can be cells isolated from the body, or cells cultured and passaged in vitro. The cells evaluated can be natural cells, mutagenized cells or genetically engineered cells.

The present invention also provides a system for evaluating the maturity of hepatic lineage cells, which includes a detection unit and a data analysis unit; the detection unit includes: a reagent or device for specifically detecting the microRNA tag or gene tag or a combination thereof The data analysis unit includes: a processing unit for analyzing and processing the detection results of the detection unit (measured expression levels of microRNA tags or gene tags or a combination thereof) to obtain evaluation results of the maturity of hepatic lineage cells. The reagents for specifically detecting microRNA tags or gene tags or combinations thereof may include, but are not limited to: PCR detection reagents, in situ hybridization reagents or immunological detection reagents. The device for specifically detecting microRNA tags or gene tags or combinations thereof may include, but is not limited to: a chip, a probe set (module), a primer probe set (module), an electrophoresis device or a gene sequencing instrument.

As a preferred manner, according to the sequences of the microRNA tags or gene tags or combinations thereof, primers for specifically amplifying them can be designed for detection. Polymerase chain reaction (PCR) technology is well known to those skilled in the art, and its basic principle is the method of enzymatically synthesizing specific DNA fragments in vitro. The method of the present invention can be carried out using conventional PCR techniques. The inventors optimized and designed primers suitable for detection, and provided an optimized method for obtaining amplification products of microRNA tags or gene tags or combinations thereof from nucleic acid samples, the method comprising: using the nucleic acid sample as a template, Use a primer pair selected from SEQ ID NOs: 18-34 for microRNA tags (downstream primers are from Tiangen kit) or SEQ ID NOs: 35-80 for gene tags to perform PCR amplification to obtain amplified products. Utilizing the primers, a relatively ideal amplification result can be obtained by using a conventional PCR amplification method.

As an implementable way, the method of combining primers with probes can be used, so that the qualitative and quantitative detection is more sensitive and faster. For example, Taqman real-time fluorescent PCR detection technology can be used: during PCR amplification, a specific Taqman probe labeled with fluorescein is added while a pair of primers are added, the probe is an oligonucleotide, and its two Each end is labeled with a reporter fluorophore and a quencher fluorophore. When the probe is intact, the fluorescent signal emitted by the reporter group is absorbed by the quencher group; during PCR amplification, the 5'→3' exonuclease activity of Taq enzyme will degrade the probe, so that the reporter fluorescent group and quencher The fluorescent group is separated, the fluorescein is free in the reaction system, and emits fluorescence under specific light excitation. With the increase of the number of cycles, the amplified target gene fragments grow exponentially. The intensity of the fluorescent signal was changed with the increase, and the Ct (cycle threshold, Ct) value was obtained. The Ct value, that is, the number of amplification cycles passed when the fluorescent signal of the amplified product reaches the set threshold during the PCR amplification process, has a linear relationship with the logarithm of the initial copy number of the template. The fewer cycles the fluorescence reaches the threshold value, that is, the smaller the Ct value, so as to realize the quantitative and qualitative analysis of the starting template.

As an implementable manner, according to the sequence of the microRNA tag or gene tag or their combination, suitable probes can be designed and immobilized on a microarray or gene chip (also called "DNA chip") . The gene chip generally includes a solid phase carrier and oligonucleotide probes fixed on the solid phase carrier in an orderly manner, and the oligonucleotide probes are composed of continuous nucleotides. In order to enhance the intensity of the detection signal and improve the accuracy of the detection results, the hybridization-related site is preferably located in the middle of the probe. The solid phase carrier can adopt various commonly used materials in the field of gene chips, such as but not limited to nylon membranes, glass slides or silicon wafers modified with active groups (such as aldehyde groups, amino groups, isothiocyanate groups, etc.), Modified glass slides, plastic sheets, etc. The probe may also contain a stretch of amino-modified 1-30 polydeoxythymidylic acid (poly-dT) at its 5' end. The gene chip contains probes for at least one microRNA tag or gene tag or a combination thereof of the present invention; more preferably, the gene chip contains probes for two or more probes for the microRNA Probes for tags or gene tags or combinations thereof; most preferably, probes for all microRNA tags or gene tags or combinations thereof described in the present invention are included on one or more gene chips.

There are many methods for preparing cellular DNA for PCR amplification. The method of using PCR to amplify a specific segment of a gene is well known in the art, and there is no particular limitation in the present invention. The amplified product can be amplified by using a primer with a labeling group at the 5' end, or by incorporating a single nucleotide with a labeling group during the amplification process, or by hybridizing When adding a detection probe that specifically binds to the amplification product, the labeling group includes but is not limited to: Digoxigenin molecule (DIG), biotin molecule (Bio), fluorescein and its derivative biomolecules ( FITC, etc.), other fluorescent molecules (such as Cy3, Cy5, etc.), alkaline phosphatase (AP), horseradish peroxidase (HRP), etc. These labels and their labeling methods are well-known conventional techniques in the art, and you can also refer to "Gene Diagnosis Technology-Non-Radioactive Operation Manual" edited by Wang Shenwu; J. Sambrook, edited by D.W. Russell, "Molecular Cloning Experiment Guide, etc.

As a preferred mode of the present invention, a method for evaluating the maturity degree of hepatic lineage cells using the "23 gene" signature or "17microRNA" signature or a part 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 through a kit; 3) preliminary comparison of different developmental degrees The expression levels of 23 genes and 17 microRNAs in the cells; 4) Analysis of the differential expression of the 23 genes and 17 microRNAs.

As a preferred mode of the present invention, the expression levels of gene tags and microRNA tags can be obtained by calculating the method of tag analysis such as mean value, median value or GSVA gene set variation analysis. Perform difference analysis, and if there is a significant difference, it indicates that the cell state has changed. Significantly high expression of gene signatures indicates the maturation and differentiation of hepatic lineage cells, significantly high expression of microRNA signatures indicates naive hepatic lineage cells, and no significant change indicates stable cell state.

As a preferred mode of the present invention, double-label joint analysis can be performed. If the expression of the microRNA label is lower and the gene label is higher, it means that the group of cells is more mature. If the expression of the microRNA label is higher and the gene label is lower, it means that the stemness of the cells in this group is enhanced. If there is no significant difference in the double label, it indicates that the cell state is stable.

Based on the above results, the relationship between the maturity of the cells in the experimental group and the cells in the control group was obtained. Through the easy-to-operate dual-omics kit scheme and a variety of statistical analysis methods, it provides a new dual-omics marker for long-term culture and expansion of liver lineage-related cells in vitro, and provides a fast and convenient way to predict maturity , providing a convenient monitoring method for stable passage.

The present invention also provides a kit for detection, which may include reaction reagents or devices (such as primers, probes, etc.) fluid, written instructions for performing the assessment, etc.) or a system for delivering it from one location to another. For example, a kit can include one or more enclosures (eg, boxes) containing relevant reagents and/or complexing materials. These contents may be delivered to the intended recipient simultaneously or separately.

In addition, the kit can also include various reagents required for DNA extraction, PCR, hybridization, color development, etc., including but not limited to: extraction solution, amplification solution, hybridization solution, enzyme, control solution , chromogenic solution, washing solution, antibody, etc.

In addition, the kit may also include instructions for use and/or chip image analysis software and the like.

The present invention first reveals the important role of the "23 gene" label and the "17microRNA" label in the development of the liver lineage, and reveals that these two different omics labels have a significant negative correlation with the development of the liver lineage, thereby Provides a new effective method, kit and marker for assessing the developmental maturity of hepatic lineage-related cells, which is useful for monitoring the in vitro state of hepatic lineage cells and rapid large-scale in vitro expansion for liver failure and other related hepatic precursor cells and Mature hepatocytes are of great importance.

Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. Experimental methods not indicating specific conditions in the following examples are usually according to conventional conditions such as edited by J. Sambrook et al., Molecular Cloning Experiment Guide, Third Edition, Science Press, 2002, or according to the conditions described in the manufacturer suggested conditions.

Materials and methods

1. Microarray and RNA-seq sequencing data preparation of cells at different time series stages in the same lineage

All 15 datasets, including the inventor's and other massive RNA-seq, scRNA-seq, micro-RNA-seq data, were collected from the Gene Expression Omnibus (GEO) database (http://www.NCBI.NLM .NIH.gov/geo).

Among them, including the use of 4 data sets published before the inventor:

GSE101133(Yan F et al.Human embryonic stem cell-derived hepatitis 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 humanhepatocyte-derived liver progenitor-like cells and their use for the study ofhepatotropic pathogens.Cell Res.(2019)29:8-22.doi:10.1038/s41422-018-0103- x); and

GSE116113(Fu GB et al.Expansion and differentiation of humanhepatocyte-derived liver progenitor-like cells and their use for the study ofhepatotropic pathogens.Cell Res.(2019)29:8-22.doi:10.1038/s41422-018-0103- x).

Among them, 11 datasets 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 AberrantEnhancer 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 hepatitis 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 forlineage 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 hepatitis screening. Theranostics. (2019) 9:6690-6705. doi:10.7150/thno.34520).

All data were subjected to routine sequencing data analysis procedures for quality control, alignment, counting, data cleaning and normalization, and were displayed in a heat map using the pheatmap R software package.

Details about these datasets are provided in Table 1.

Table 1. Fifteen bi-omics datasets used to construct the regulatory network of the liver lineage

2. Tumor Genome Atlas (TCGA) and Human Protein Atlas (HPA) (USA)

To explore the role of key microRNAs, the inventors downloaded the normalized microRNA sequence data and corresponding clinical information of HCC patients from TCGA. Differential expression analysis and survival analysis were performed. "P<0.05" was considered significant. At the same time, the expression patterns of 23 genes in normal liver tissue were also explored in the HPA database (https://www.proteinatlas.org), and the present invention only showed moderately or highly expressed genes.

3. Short time series expression analysis (STEM)

Both mRNAs and microRNAs are stratified into different profiles according to the different expression patterns calculated by STEM analysis (default parameters). Four stages of the hepatic lineage (biliary tree stem cells (hBTSCs), hepatic stem cells (hHpSCs), hepatic progenitors (hHBs) and mature hepatocytes (hAHeps)) are considered as distinct time points.

4. Analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)

To explore the biological functions of liver lineage-specific gene profiles, KEGG and GO enrichment analyzes were performed using the ClusterProfiler R package (Yu G et al. clusterProfiler: an R package for comparing biological themes among gene clusters.OMICS.( 2012) 16:284-287. doi:10.1089/omi.2011.0118). In order to understand the potential functions of microRNAs, the DIANA-miRPathv3.0 database, the microRNA pathway analysis web server (http://SNF-515788.VM.okeanos.grnet.gr), was also adopted in this work because it can quickly Predict potential targets of microRNAs and then efficiently run KEGG pathway analysis (Vlachos IS et al. DIANA-miRPath v3.0: deciphering microRNA function with experimental support. Nucleic Acids Res. (2015) 43:W460-466.doi:10.1093/nar /gkv403).

5. MicroRNA-related target gene database

In the inventor's current work, the inventor used 3 databases, including the microRNA target gene prediction database (miRDB) (Chen Y, Wang X. miRDB: an online database for prediction offfunctional microRNA targets. Nucleic Acids Res. ( 2020)48:D127-D131.doi:10.1093/nar/gkz757), experimentally validated microRNA-target gene interaction database (miRTarBase) (Chou CH etal.miRTarBase update 2018:a resource for experimentally validated microRNA-target interactions.Nucleic Acids Res.(2018)46:D296-D302.doi:10.1093/nar/gkx1067) and TargetScan(Lewis Bp et al.Prediction of mammalian microRNAtargets.Cell.(2003)115:787-798.doi:10.1016/s0092- 8674(03)01018-3), to predict 52 microRNA targets, and only those targets overlapped by them can be used for further research.

Subsequently, the prediction results were confirmed by 2 comprehensive and comprehensive functional microRNA databases, including miRWalk (Sticht C et al. journal.pone.0206239) and DIANA-MicroT-CDS (Paraskevopoulou et al., 2013Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M, et al. DIANA-microT web serverv5.0: service integration into microRNA functional analysis workflows. Nucleic Acids Res. (2013) 41:W169-173. doi:10.1093/nar/gkt393). P<0.05 was considered statistically significant.

6. Establish a "transcription factor-microRNA-target gene" regulatory network

Experimentally supported interactions between lineage-associated microRNAs and their regulatory transcription factors were downloaded from the TransmiR v2.0 database, which contains 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. TransmiRv2.0: an updated transcription factor-microRNA regulation database. Nucleic Acids Res. (2019) 47:D253-D258.doi:10.1093/nar/gky1023) ). The construction of the "transcription factor-microRNA-target gene" regulatory network of the liver lineage was carried out by cytoscape (Java 3.7.1) software (Shannon Pet al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. (2003 )13:2498-2504. doi:10.1101/gr.1239303).

7. Principal component analysis (PCA) and three-dimensional principal component analysis (3D_PCA)

3D_PCA analysis (default parameters) of common mRNA-seq, microRNA-seq of biliary tree stem cells (hBTSCs), hepatic stem cells (hHpSCs), hepatic progenitor cells (hHBs) and mature hepatocytes (hAHeps) to examine the performance.

Principal component analysis was also performed on single-cell RNA-seq data from 251 hepatic progenitors/hepatocytes to visualize time-course changes in hepatic lineages.

8. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA)

RNA-seq data of differentiation of hBTSCs and total RNA-seq of Dlk+ hepatic progenitors/hepatocytes were scored using GSVA, with each sample/cell receiving a GSVA score (Hanzelmann S, Castelo R, Guinney J. GSVA:geneset variation analysis for microarray and RNA-seq data. BMC Bioinformatics. (2013) 14:7. doi:10.1186/1471-2105-14-7). All datasets related to liver development and cellular reprogramming were used for GSVA scoring to validate the lineage-specific signature of the '23-gene' signature.

Furthermore, GSEA analysis was used to reveal the relationship between PTEN/PIK3R1 and the stemness of liver-associated single cells (Subramanian A et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad SciU S A. (2005) 102:15545-15550. doi:10.1073/pnas.0506580102). The number of random sample permutations parameter was set to 1000.

9. Correlation analysis

The correlation between 23 gene signals, stem cells and PI3K/AKT signaling pathway was calculated to determine the regulatory relationship among 23 targets, 17 microRNAs and 1 signaling pathway. In the present study by the inventors, P<0.05 was considered statistically significant. Due to different data set sources and sample sizes, the threshold of the correlation coefficient is not defined, and the specific data are shown in the figure.

Example 1. Construction of cell lineage-related "transcription factor-microRNA-target gene" regulatory network

The method for constructing the regulatory network of "transcription factor-microRNA-target gene" in the process of cell development and maturation lineage mainly includes the following steps (Figure 1):

1. Obtain cells at different stages of cell lineage; perform microRNA sequencing and RNA-seq sequencing (GSE73114 database in 15 public databases in the aforementioned "1. Preparation of chips and RNA-seq sequencing data of cells at different time series stages in the same lineage" and GSE114974 database after routine processing of sequencing data);

2. Through principal component analysis (PCA analysis), it is confirmed that the development of cells does have temporal characteristics;

3. Obtain different expression patterns in different cell states through short-time sequence expression analysis (STEM analysis), and obtain microRNA sets and mRNA sets that change over time;

4. Ensuring the reliability of sequencing results through enrichment analysis such as GO and KEGG;

5. Use 5 microRNA-related target gene prediction databases (aforesaid "5. microRNA-related databases") to analyze and obtain the target genes of microRNA whose expression levels gradually change over time. These databases include miRDB, miRTarBase, TargetScan, miRWalk and DIANA-MicroT-CDS database;

6. Intersect with genes whose expression level changes with lineage development, and then obtain microRNA tags and target gene tags that not only change gradually with lineage development but also interact;

7. Further verify the reliability of these dual-omics label results through GO and KEGG enrichment analysis, correlation analysis, and three-dimensional principal component analysis (PCA);

8. Download experimentally supported lineage-associated microRNAs and their interactions between regulatory transcription factors from the TransmiR v2.0 database, and obtain transcription factors that can regulate microRNA tags.

9. Draw the regulatory network of "transcription factor-microRNA-target gene" by cytoscape.

After the "transcription factor-microRNA-target gene" regulatory network is obtained using the above method (construction stage), it further enters the verification and application stage, including the following:

10. Multi-dimensional verification method 1: Obtain cell lineage sequencing results known in the art during normal embryonic development, and verify the reliability of the regulatory network results through GSEA or GSVA analysis (data in the aforementioned "1. Chip and RNA- seq sequencing data preparation" in the public database);

11. Multi-dimensional verification method 2: Obtain the sequencing results of cell reprogramming in the process of lineage reprogramming known in the field, and verify the reliability of the regulatory network results through GSEA or GSVA analysis (data in the aforementioned "1. Chip and RNA- seq sequencing data preparation" in the public database).

12. qRT-PCR experiments verify the reliability and applicability of gene tags and microRNA tags, and realize the monitoring of the maturity of in vitro reprogramming and continuous multiple passage cells;

Refer to the schematic flowchart shown in FIG. 1 for the above process.

Using the unique system constructed by the inventors to obtain the liver lineage-related "transcription factor-microRNA-target gene" regulatory network is 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, hsa-let-7f-2-3p.

The 23 genes are 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.

Example 2. Most of the 17 microRNAs and 23 genes are negatively correlated, and verify the accuracy of the "17microRNA" label

The inventors analyzed that most of the 17 microRNAs and 23 genes have negative correlations.

According to 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 (hHBs) and mature hepatocytes (hAHEPs)) have a very clear timing , so this data is suitable for the "transcription factor-microRNA-target gene" network construction method of the present invention.

After constructing a network on the public data, the inventors obtained 17 microRNAs and 23 genes, which not only have lineage timing, but also have mutual regulatory relationships. According to the results of 3D_PCA analysis, it can be seen that the differences in timing and maturity of these four cell types can be found only by gene tags or microRNA tags (Fig. 3B and Fig. 3C).

Using further correlation analysis, it can be clearly seen that there is a regulatory relationship between 17 microRNAs and 23 genes, mainly negative regulation (Fig. 3E and Fig. 3F).

At the same time, it can also be seen that these 17 microRNAs do show an overall high expression trend in embryonic developing liver stem cells (Fig. 3D).

Example 3. Embryo development-related database verification of the accuracy of the "23 genes" label

To analyze 23 gene signatures (PIK3R1, PTEN, ACSL1, ANKRD46, CPEB3, CRY2, CSF1R, HAND2, HECW2, MEGF9, NHLRC3, NTF3, PAIP2, PDE4D, PGRMC1, PNRC1, RORA, SLC10A7, SLC8A1, SPRYD4, TIMP3, TMEM135 , TMEM64), the inventors used the following disclosed embryonic development-related databases to obtain cells at different lineage developmental stages, and analyzed the expression of the 23 gene signatures.

GSE90047: Including cells developed from hepatoblast to hepatocytes during embryonic development, embryonic day 10.5 (E10.5) to embryonic day 18.5 (E18.5);

GSE132034: including mouse liver organs at various developmental stages, embryo E12.5 → eighth week after birth (W8);

GSE28892: includes three types of cells: adult hepatic progenitor LPCs (Adult LPCs), differentiated mature hepatocytes (Differentiated Heps), and primary hepatocytes (Primary Heps).

GSE56734: includes two kinds of cells, embryonic day 13 hepatic progenitor cells (Hepatoblast) and mature hepatocytes, E13→Adult.

GSE25048: Includes two types of cells, endoderm stem cells and mature hepatocytes; Endoderm_Progenitors_1→Mature_Hepatocytes_4.

GSE101133: Including four kinds of cells, hepatic stem cells HpSC, hepatic progenitor cells Hepatoblast, hepatic precursor cells pre-hepatocyte and mature hepatocytes Hepatocyte.

GSE57878: Including two kinds of cells, hepatic progenitor LPCs and mature hepatocyte mature_hepatocyte.

The results are shown in Fig. 4A-G, these genes can show a gradual increase in gene expression with the progress of cell development and maturity.

For each of the above-mentioned libraries, the expression data of 23 genes were subjected to GSVA gene set variation analysis to obtain the expression of the "23 gene" label. It can be seen that with the progress of cell development and maturity, the expression of gene labels is significantly up-regulated ( Figure 4H). Therefore, in the embryonic development-related database, whether through the trend analysis of 23 genes or single-label analysis, it can suggest which cell type is in a more mature or naive state.

Example 4. Verification of the accuracy of the "23 gene" label by the lineage reprogramming related database

To analyze the "23 genes" signature (PIK3R1, PTEN, ACSL1, ANKRD46, CPEB3, CRY2, CSF1R, HAND2, HECW2, MEGF9, NHLRC3, NTF3, PAIP2, PDE4D, PGRMC1, PNRC1, RORA, SLC10A7, SLC8A1, SPRYD4, TIMP3, TMEM135, TMEM64), the inventors used the following disclosed lineage reprogramming related databases to obtain cells at different lineage development stages, and analyzed the expression of the 23 genes.

GSE75141: includes three types of cells: reprogrammed expandable hepatocytes, mature hepatocytes differentiated by expandable hepatocytes and primary mature hepatocytes;

GSE105019: includes three types of cells: reprogrammed hepatic progenitor-like cells, mature hepatocytes differentiated by hepatic progenitor-like cells and primary hepatocytes;

GSE124528: includes two types of cells: reprogrammed hepatic progenitor-like cells and mature hepatocytes differentiated from hepatic progenitors;

GSE112330: includes two types of cells: reprogrammed hepatic progenitor-like cells and mature hepatocytes differentiated by hepatic progenitor-like cells;

GSE116113; GSEA analysis of single-cell sequencing of hepatic precursor cells;

GSE90047; GSEA analysis of single-cell sequencing of hepatic lineage cells;

The results are shown in Figure 5A-D, these genes can show a trend of gradually high expression as the cell development maturity progresses.

As shown in Figures 5E and 5F, through the analysis of single-cell sequencing data, it can be found that the preferred PTEN and PIK3R1 genes can inhibit stem cell-related pathways, suggesting that PTEN and PIK3R1 are negatively related to stemness, suggesting that preferred PTEN and PIK3R1 may not only be potential markers, and may have the function of regulating the maturation of hepatocytes.

For each of the above-mentioned libraries, GSVA gene set variation analysis was performed to obtain the expression of the "23 gene" label in each group. It can be seen that the expression of the gene label increases significantly with the progress of cell development and maturity (Figure 5G). Therefore, in the reprogramming-related database, whether through the trend analysis of 23 genes or single-label analysis, it can suggest which cell type is in a more mature or naive state.

Example 5. Application of microRNA tags in in vitro cell culture reprogramming

The applicant previously achieved the transformation and expansion of primary human hepatocytes into hepatic precursor-like cells in an improved small molecule reprogramming culture system, and this primary hepatocyte-derived hepatic progenitor without any foreign gene introduction Somatic-like cells (Hepatocyte-derived liver progenitor-like cells, HepLPCs) can rapidly differentiate into functional hepatocytes, achieving reversible transformation between "Hepatocyte-HepLPCs" (Cell Research 2019; 29(1):8-22).

In the present invention, primary hepatocytes (Primary Heps, which are known to have normal functions such as metabolism and secretion, and whose cell maturity is 100% by default) and hepatic precursor-like cells obtained from reprogramming of mature hepatocytes ( HepLPCs P4, HepLPCs passage 4th generation cells) are the detection objects. That is, HepLPCs P4 are more immature (more stem) cells than primary hepatocytes.

The expression of the 17 microRNAs obtained after extensive screening and analysis in cells at different stages was verified by qRT-PCR, so as to realize the prediction of cell maturity after multiple passages and the monitoring of cell status.

The miRcute enhanced microRNA fluorescence quantitative detection kit (SYBR Green) (EP411) (purchased from Tiangen Biochemical Technology (Beijing) Co., Ltd.) was used.

The specific primer sequences (constructed by tailing method) of 17 microRNAs are shown in Table 2.

Table 2

The downstream primers were from the detection kit of Tiangen Company.

The results are shown in Figure 6. It can be seen that 12 of the 17 microRNAs obtained were significantly highly expressed (70.59%) in the HepLPCs P4 liver precursor-like cells, among which multiple microRNAs were extremely significantly highly expressed. More than 10 microRNAs are highly expressed relative to mature hepatocytes, which verifies that mature hepatocytes have indeed been reprogrammed into hepatic precursor-like cells from the level of epigenetic regulation, and have successfully passed to the fourth generation.

The results of 17 microRNAs were subjected to label analysis, and the expression of the "17microRNA" label was obtained by median analysis, and the significance was ****P<0.0001. Label analysis also showed that HepLPCs P4 were more immature (stem) cells than primary hepatocytes.

Therefore, when the 17 microRNAs are jointly or partially used for the analysis of the maturity of hepatic lineage cells, they can be used as ideal markers of significance.

Example 6. Application of gene tags in in vitro cell culture reprogramming

Primary hepatocytes (Primary Heps, whose cell maturity is known to be 100%), HepLPCs_P3 (passage 3) and HepLPCs_P4 (passage 4) cells (it is known that the two generations of cells are regenerated from mature hepatocytes) Programmed, all in the stage of liver precursor cells) as the detection object, through qRT-PCR to verify the expression of the above-mentioned 23 genes obtained after a large number of screening analyzes in different stages of cells, to realize the monitoring of maturation in continuous cultured cells in vitro degree and predict the state of cells.

Premix Ex TaqTM II荧光定量qRT-PCR检测试剂盒(购自TAKARA)。Using PrimeScriptTM RT Master Mix (Perfect Real Time) reverse transcription kit and TB

Premix Ex TaqTM II fluorescence quantitative qRT-PCR detection kit (purchased from TAKARA).

The specific primer sequences (constructed by tailing method) of 23 genes are shown in Table 3.

table 3

The results are shown in Figure 7. It can be seen that 15 of the 23 genes obtained were significantly underexpressed (65.22%) in HepLPCs P3 liver precursor cells, and many of them were extremely significantly underexpressed. Among the 23 genes, 16 were significantly underexpressed (69.57%) in HepLPCs P4 hepatic precursor cells, and many of them were extremely significantly underexpressed. Therefore, more than 10 genes were significantly under-expressed in the two groups of hepatic precursor cells, which verified from the transcriptional level that mature hepatocytes had indeed been successfully reprogrammed into hepatic precursor cells.

The results of 23 genes were analyzed by median value analysis for gene signature analysis, showing significant low expression in both HepLPCs P3 cells and HepLPCs P4 cells. Thus, single-gene signature analysis also suggested that mature hepatocytes had been reprogrammed into hepatic precursors. Therefore, when the 23 genes or the overall gene signature are jointly or partially used for the analysis of the maturity of hepatic lineage cells, they can be used as ideal markers of significance.

Summarizing the above-mentioned expression results obtained about 17 microRNAs and performing double-label joint analysis, it can be seen that the significantly low expression of the "23 gene" label and the significantly high expression of "17microRNA" are highly significant.

Therefore, both single-omics signature analysis and dual-omics signature integration analysis have consistently confirmed that primary hepatic mature cells have been reprogrammed into hepatic precursor cells, and whether they are expanded in vitro for three or four generations, they can still maintain Due to its stemness, the rapid prediction and monitoring of the maturity of hepatic precursor cells cultured in vitro using this kit has been successfully realized.

All documents mentioned in this application are incorporated by reference in this application as if each were individually incorporated by reference. In addition, it should be understood that after reading the above teaching content of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

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<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

cttatggggct 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

gagtccagcg tatccgaagc 20

<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

ccagagttct tcaccgtgct 20

<210> 48

<211> 20

<212>DNA

<213> Primer

<400> 48

ttcaaagtgg tgggtgtccc 20

<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

aacgcgatgt aaggaagcca 20

<210> 54

<211> 20

<212>DNA

<213> Primer

<400> 54

agtgctcgga cgtaggtttg 20

<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

gccctgttta ctgctctccc 20

<210> 63

<211> 20

<212>DNA

<213> Primer

<400> 63

tggccagctt gttcatggta 20

<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

cttgccgtag ggatgtctcg 20

<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

gcttcactcc cttctgcctt 20

<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

caggtcgcgt ctatgatggc 20

<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)

1. 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. 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. 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. 4. The use of claim 1, wherein the 10 to 23 gene signatures comprise PIK3R1 or PTEN.
5. 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. 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. 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. 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. 9. The use of claim 1, wherein said detecting means comprises: a chip, an electrophoresis device or a gene sequencing instrument.
10. 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. 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. 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. 13. The system of claim 12, wherein the detection reagent comprises: PCR detection reagent, in situ hybridization reagent or immunity detection reagent.
14. 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. 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. 16. The system of claim 12, wherein said detecting means comprises: a chip, an electrophoresis device or a gene sequencing instrument.
17. 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. 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. 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. 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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