Application of Mov10 as a new target in the diagnosis and treatment of diabetic nephropathy

Abstract

The present invention discloses the use of a reagent for quantifying the expression level of Mov10 in the preparation of a diabetic nephropathy diagnostic preparation, and the use of an inhibitor of Mov10 in the preparation of a drug for treating diabetic nephropathy. The present invention uses RNA-seq for bioinformatics analysis, constructs a SF-AS regulatory network to screen out the key splicing factor Mov10 in DN, and verifies in three types of renal intrinsic cells that it is significantly highly expressed and this high expression state promotes the abnormal proliferation, inflammation and fibrosis of mesangial cells, providing a new idea for the study of diabetic nephropathy and a new target for its treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of new targets for disease treatment, and in particular to the application of Mov10 as a new target in diabetic nephropathy diagnosis and treatment drugs. Background Art

[0002] Diabetic nephropathy (DN) is one of the common complications of diabetes, accounting for 40% of the total number of diabetic patients. It is the main cause of end-stage renal disease. Glomerular mesangial lesions are one of the most prominent pathological changes in DN. The mesangial cells of the glomeruli proliferate abnormally, the mesangial area expands, and the basement membrane of the glomerular capillaries thickens. However, the specific formation mechanism of this high-proliferation state has not yet been determined. Alternative splicing (AS) exists in 90%-95% of human genes and is a key biological process for expanding gene expression patterns and generating protein diversity. Proteins that regulate AS are called splicing factors. Splicing factors (SF) selectively splice exons or introns by binding to specific sequences of target gene pre-mRNA to produce different mRNA isoforms, thereby playing an important regulatory role in many biological processes. A single SF can regulate multiple splicing events. Changes in the expression of SF may lead to changes in disease-specific AS, thereby affecting the occurrence and development of the disease. Therefore, it is crucial to study the potential mechanisms of the SF-AS regulatory network in disease. The protein encoded by the Srsf7 gene is a member of the serine / arginine-rich pre-mRNA splicing factor family, and plays an important role in constitutive and alternative splicing of pre-mRNA, mRNA nuclear export, stability, and translation. Studies have shown that knockdown of Srsf7 in the proximal tubules in vitro triggered differential expression of approximately 2,000 genes and induced a proinflammatory phenotype, suggesting that alternative splicing of the proximal tubules plays a role in driving DN progression. In the late stage of DN, when renal function declines, the expression of VEGF AxxxmRNA increases relative to VEGF Axxxb mRNA.

[0003] In the process of gene expression, alternative splicing is a critical regulatory step. mRNA alternative splicing greatly increases the complexity of gene expression in eukaryotic organisms and the diversity of protein functions, increasing the diversity and adaptability of organisms. Through alternative splicing, most genes will produce multiple splicing isoforms with different biological functions. In this biological process, splicing factors play an important role. Like a pair of "scissors", they accurately repair pre-mRNA, cut off redundant parts, form multiple mRNA sequences, and then translate them into protein isoforms with different biological functions, participating in the occurrence of various diseases. So far, there has been no report on the role of SF in the proliferation of DN mesangial cells. Summary of the invention

[0004] One of the purposes of the present invention is to address the above-mentioned problem and to provide a reagent for quantifying the expression level of Mov10 and its use in preparing a diagnostic preparation for diabetic nephropathy.

[0005] In the application technology scheme, the expression level includes mRNA level and protein level.

[0006] The reagent for quantifying the Mov10 mRNA level is selected from the group consisting of: primers, probes, and gene chips;

[0007] The reagent for quantifying the level of Mov10 protein is selected from the group consisting of: antibodies and protein chips.

[0008] In the application technology scheme, Mov10 is significantly highly expressed in patients with diabetic nephropathy.

[0009] Another object of the present invention is to provide use of a Mov10 inhibitor in the preparation of a drug for treating diabetic nephropathy.

[0010] The inhibitor of Mov10 is selected from: a substance that can completely or partially inhibit the expression of Mov10 gene, and a substance that can completely or partially inhibit the activity or expression of splicing factor Mov10.

[0011] The inhibitor of Mov10 includes small molecule organic matter, small molecule inorganic matter, anti-Mov10 antibody, nucleic acid fragment or polypeptide which can specifically bind to splicing factor Mov10 and inhibit its activity.

[0012] The Mov10 inhibitor is selected from artificially synthesized small interfering RNA (siRNA) or short hairpin RNA (shRNA).

[0013] Preferably, the siRNA sequence is: the sense strand is shown in SEQ ID NO.1, and the antisense strand is shown in SEQ ID NO.2.

[0014] The beneficial effects of the present invention are:

[0015] Through bioinformatics analysis of RNA-seq, the SF-AS regulatory network was constructed to screen out the key splicing factor Mov10 in DN, and it was verified in three types of renal intrinsic cells that it was significantly highly expressed and this high expression state promoted the abnormal proliferation, inflammation and fibrosis of mesangial cells, providing a new idea for the study of diabetic nephropathy and a new target for its treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1: Screening of DN-related AS events; (A) RNA-seq of mouse kidney tissue; (B) Pie chart showing the proportion of different gene types in 3 pairs of normal mouse kidney tissues and 3 pairs of DN mouse kidney tissues identified by RNA-seq (left); Pie chart showing the distribution of differentially expressed genes (DEGs) in DN compared with normal tissues (right) (FDR<0.05, |log2FC|>1); (C) Line graph showing the number of transcripts for each differentially expressed protein-coding gene in DN; (D) Upset graph showing all DN-related AS events; (E) Comparison of differential splicing events in seven types of alternative splicing (AS) events between DN and NC; (F, G) Functional and pathway enrichment analysis of 535 genes containing 585 differential alternative splicing events; P<0.05 was considered statistically significant.

[0017] Figure 2 : Construction and validation of DN-related SF-AS network; (A) Volcano plot of 533 splicing factors between NC and DN tissues, red indicates upregulation and green indicates downregulation; (B) SF-AS interaction network (P<0.05, |Person|>0.8), yellow circles represent SFs associated with DN, red triangles represent AS events positively correlated with SFs, and green diamonds represent AS events negatively correlated with SFs; (C) The number of alternative splicing events regulated by splicing factors; (D) Expression of candidate SFs in epithelial cells; (E) Expression of candidate SFs in mesangial cells; (F) Expression of candidate SFs in podocytes; *P<0.05, **P<0.01, ***P<0.001.

[0018] Figure 3 :Mov10 promotes the proliferation, inflammation and fibrosis of mesangial cells; (A) Overexpression and knockdown of Mov10 in mesangial cells were verified at the mRNA level and protein efficiency; (B) EdU experiment detected the effect of Mov10 on the proliferation ability of mesangial cells; (C) qRT-PCR detected the expression of proinflammatory and fibrotic factors after overexpression and knockdown of Mov10; (D) Western blot detected the expression of proinflammatory and fibrotic factors after overexpression and knockdown of Mov10. DETAILED DESCRIPTION

[0019] The present invention will be further described below in conjunction with embodiments, but the present invention is not limited thereto.

[0020] The experimental methods in the following examples are all conventional methods unless otherwise specified; the materials and reagents used are all conventional materials and reagents in the art and are commercially available unless otherwise specified.

[0021] Example 1

[0022] 1 Materials and methods

[0023] 1.1 Experimental animals and reagents

[0024] Four-week-old male type 2 diabetes model mice (db / db mice) were purchased from the Model Animal Research Institute of Nanjing University and used as the DN group (n=3). Normal control C57BL / 6J mice were provided by the Experimental Animal Center of Chongqing Medical University. They were homogeneous in age and gender with the DN group mice and used as the normal group (n=3). Mice were raised in the Experimental Animal Center of Chongqing Medical University and killed after blood glucose and urine albumin were tested at 12 weeks of age. The renal cortex was taken and stored in liquid nitrogen for subsequent experiments. All operations were approved by the Ethics Committee of Chongqing Medical University. Mouse MCs (SV40-MES14) were preserved by this laboratory.

[0025] Transfection reagents 2000 was purchased from Invitrogen, USA; HighGene plus Transfection reagent cell transfection reagent and 2X Universal SYBR Green Fast qPCR Mix were purchased from Wuhan Aibote Biotechnology Co., Ltd.; rapid RNA extraction kit was purchased from Hunan Aikerui Bioengineering Co., Ltd.; reverse transcription kit was purchased from Japan TaKaRa; DMEM low glucose medium was purchased from Gibco, USA; DMEM high glucose medium was purchased from Chongqing Semik Biotechnology Co., Ltd.; goat anti-rabbit Tnf-α, Col-I, Fn and secondary antibody goat anti-rabbit IgG were purchased from Wuhan Sanying Biotechnology Co., Ltd.; goat anti-rabbit Il-6 was purchased from Abcam, UK; EdU cell proliferation detection kit was purchased from Guangzhou Ruibo Biotechnology Co., Ltd.; SDS-PAGE related reagents and cell lysis buffer, protein quantification kit were purchased from China Bio-Technology Co., Ltd.; PVDF membrane was purchased from Millipore, USA.

[0026] 1.2 Next-generation sequencing (RNA-seq)

[0027] The kidney tissues of three normal mice and three DN mice were sent to Liebing Biotechnology for RNA-seq detection. Fastp software was used to filter low-quality sequences, undetected sequences, and adapter sequences, and the base quality, GC content, length distribution, adapter retention, and duplication ratio of the data before and after filtering were analyzed. The Tophat2 algorithm was used for genome alignment to obtain the bam file of genome alignment, and information statistics were performed based on the bam file to obtain the genome alignment rate and the distribution results of reads on gene structure and chromosomes. HTSeq and gff3 files of genome annotation were used to select the FPKM standardization method according to the single-end or double-end sequencing type to count the gene expression. Based on the statistical results, the correlation between samples, RPKM / FPKM density and abundance analysis results were obtained, reflecting the distribution and discreteness of gene expression levels in individual samples, as well as the differences in overall gene expression levels in different samples.

[0028] 1.3 RNA-seq data processing

[0029] AS events in DN were evaluated by using CASH to obtain splicing percentage (PSI) for AS analysis of RNA-seq data. Multiple interactive sets of seven types of AS events were visualized using R software (version 4.2.2) with the UpsetR package. In order to screen out AS events with significant differences, |ΔPSI|>0.1 and P<0.05 were set as the screening criteria to be considered statistically significant.

[0030] 1.4SF-AS regulatory network

[0031] To explore the mutual regulation mechanism of AS events and SF, we obtained the information of SF from the SpliceAid 2 database and the SpliceAid-F database to build a network. The correlation between SF and AS events was analyzed using Person correlation, and the criteria were: the absolute value of the correlation coefficient > 0.8, p < 0.05. The SF-AS correlation network was visualized by Cytoscape (version 3.9.0).

[0032] 1.5 Cell culture and transfection

[0033] Mesangial cells were cultured in a 5% CO2, 37°C environment using DMEM medium containing 15% fetal bovine serum. The cells were divided into two groups, the high-glucose group cells were cultured in DMEM medium containing 25mmol / L glucose, and the low-glucose group cells were cultured in DMEM medium containing 5mmol / L glucose. The high-glucose group cells were plated in a six-well plate and transfected when the cells grew to 50%-80%. Prepare siRNA-Lipofectamine 2000 mixture, take 6ul lipo2000 transfection reagent and dilute it with serum-free high-glucose medium, gently mix and incubate at room temperature for 5min, then take 8ul diluted siRNA (sequence as shown in Table 1) and dilute it with serum-free high-glucose medium, gently mix and incubate at room temperature for 5min, mix the above two reagents together and incubate at room temperature for 20min to form a siRNA-lipo2000 mixture, and finally add it to the six-well plate, replace the serum medium for 4-6 hours, and collect the cells for subsequent experiments at 48h-72h. The low-sugar group cells were plated in a six-well plate. When the cells grew to 50%-80%, 4ul of plasmid was added to 200ul of serum-free low-sugar culture medium and mixed by pipetting. Then 8ul of HighGene plus transfection reagent was added and mixed by pipetting. 200ul of plasmid-HighGene plus transfection reagent mixture was added dropwise to the six-well plate. The culture medium with serum was replaced after 6 hours. After 48h-72h, the cells were collected for subsequent experiments.

[0034] Table 1

[0035]

[0036] 1.6 RNA extraction and real-time quantitative PCR (qRT-PCR)

[0037] Mouse MCs RNA was extracted using an RNA extraction kit, and total RNA was reverse transcribed into cDNA using a reverse transcription kit. Amplification detection was performed using 2X Universal SYBR Green Fast qPCR Mix. The system was 10 μL, and 3 replicates were set up for each group. The reaction conditions were: 95°C pre-denaturation for 3 min, 95°C for 5 s, 55°C for 34 s, 72°C for 60 s, and 40 cycles. The experimental results were based on the internal reference gene β-actin, and 2 -ΔΔCt The formula was used to perform relative quantitative analysis of gene expression.

[0038] The detection primers are shown in Table 2:

[0039] Table 2

[0040]

[0041] 1.7 EdU cell proliferation detection experiment

[0042] The transfected MCs cells were inoculated into 24-well plates according to the above method. After 24 hours of culture, 200 μL of EdU solution was added to each well and incubated in the incubator for 2 hours. After being fixed with 4% paraformaldehyde for 30 minutes, 2 mg / mL of glycine solution was added for 5 minutes. The cells were permeabilized with 0.5% Triton X-100 and washed 3 times with PBS. Then 1× The staining solution was incubated at room temperature for 30 minutes, and finally 1×Hoechest33342 reaction solution was added to stain the cell nucleus for 30 minutes at room temperature, and the images were collected using a fluorescence microscope after sealing with glycerol. ImageJ software was used for counting and analysis.

[0043] 1.8 Western blot detection of protein expression

[0044] The transfected cells were washed twice with PBS, centrifuged on ice with RIPA lysis buffer and 1% PMSF at 4°C, 14400r / min for 30min, and the supernatant was taken. The protein absorbance was measured at 562nm using a BCA kit. 8% and 12% SDS-PAGE were used for electrophoresis and transfer. After blocking with 5% skim milk at room temperature for 2h, rabbit anti-Tnf-α (1:500), rabbit anti-Il-6 (1:1000), rabbit anti-Col-I (1:1000), rabbit anti-Fn (1:2000) and rabbit anti-β-actin (1:5000) antibodies were placed in 4°C for overnight incubation, and the secondary antibody was incubated at room temperature for 1h. The luminescent liquid was used for color development and imaging was performed on the Bio-Rad gel imaging system.

[0045] 1.9 Statistical analysis

[0046] Graphpad Prism 9.1.1 statistical software was used for statistical analysis. The t-test was used to compare the means of the two groups. When P < 0.05, the difference was statistically significant.

[0047] 2 Results

[0048] 2.1 RNA-seq analysis revealed differential AS events associated with DN

[0049] To investigate the potential function of AS events in DN, we performed RNA-seq on kidney tissues from three normal mice and three diabetic nephropathy mice. Figure 1 A total of 57,057 transcripts were detected to be expressed in the renal transcriptome, and these transcripts were divided into six types of genes. A total of 4,222 protein-coding genes with differential expression were found in DN compared with normal renal tissue ( Figure 1B) Among these differentially expressed protein-coding genes, 86.7% (3661 / 4222) of the genes were transcribed into two or more dominant expression isoforms ( Figure 1 C). Since AS can cause a mRNA precursor to produce different mRNA splicing isoforms through different splicing modes, we then analyzed the AS events in the DN transcriptome data. AS events include 7 types: exon skipping, mutually exclusive exons, variable 5' splicing sites, variable 3' splicing sites, variable first exon, variable terminal exon, and retained introns. Compared with normal tissues, a total of 56,929 AS events were analyzed in DN ( Figure 1 D). Protein-coding genes showed the most differential splicing events, with 585 AS events showing significant differences in splicing changes among these protein-coding genes, and exon skipping was the most common AS event ( Figure 1 F). Next, we performed GO and KEGG enrichment analysis on 535 genes containing 585 different AS events and found that they were enriched in RNA splicing, protein binding, spliceosome and metabolic pathways ( Figure 1 F, G).

[0050] 2.2Mov10 is a key splicing factor in DN and is closely related to the occurrence of DN

[0051] Splicing factors (SFs) regulate the occurrence of AS events, and their abnormal changes affect the process of splicing regulation, thereby affecting the occurrence and development of the disease. We found a total of 637 splicing factors from the splicing factor database SpliceAid 2, SpliceAid-F and other databases, of which 533 splicing factors were related to DN. We performed differential analysis and found that 31 genes were upregulated and 78 genes were downregulated (Table 3, Figure 2 A). The SF-AS regulatory network can reveal the expression of key SFs regulating AS events. We then constructed a correlation network between the SF expression levels of AS events and PSI. We found that Ssb, Rbm25, Fastk, Mov10, Dek, Nsrp1, and Cwc15 regulated the most AS events ( Figure 2 B, C). Next, we validated these seven candidate key splicing factors, and the results showed that the splicing factor Mov10 was significantly overexpressed under high glucose conditions. Therefore, we focused on studying the functional role of Mov10 in DN.

[0052] As a splicing factor, Mov10 protein consists of 1003 amino acids (as shown in SEQ ID NO.21), is about 115kDa in size, and is a member of RNA helicase SF-1. It splices in a constitutive or selective, co-transcriptional manner, and has a profound impact on post-transcriptional gene regulation, 3'-UTR maturation, lncRNA processing, etc. Mov10 protein is expressed in a variety of cells, including embryonic stem cells, neuronal synapses, and other cells, and can be expressed at high levels in different organs (such as testis and thymus) at different developmental stages, and expressed to varying degrees in embryos and liver. Mov10 has been identified as an important regulator of the nervous system, promoting angiogenesis in glioma cells by regulating cell activity, migration, and tube formation. The expression level of MOV10 mRNA and protein in tumor cells is 2-3 times that of normal cells. The nucleotide sequence of the Mov10 gene is found in: NC_000069.7:c104725935-104702144 Mus musculus strain C57BL / 6J chromosome 3, GRCm39.

[0053] Table 3. Up-regulated and down-regulated genes found by differential analysis

[0054]

[0055] 2.3Mov10 promotes mesangial cell proliferation, inflammation and fibrosis

[0056] To determine the function of Mov10 in DN, we transfected glomerular mesangial cells with overexpression plasmids and si interference plasmids. Mesangial cells can effectively overexpress or knock down the expression of Mov10 ( Figure 3 A). EdU experiments revealed that overexpression of Mov10 promoted the proliferation of mesangial cells, while silencing Mov10 significantly inhibited the proliferation of mesangial cells ( Figure 3 B).

[0057] The mRNA and protein expression levels of inflammation-related factors Tnf-α and Il-6 and fibrosis-related factors Fn and Col-I were detected by qRT-PCR and Western Blot. The results showed that after overexpression of Mov10, the expression of Tnf-α, Il-6, Fn and Col-I was significantly increased. Conversely, after inhibiting the expression of Mov10, the expression of Tnf-α, Il-6, Col-I and Fn was significantly decreased ( Figure 3 C, D).

[0058] 3 Analysis

[0059] We used RNA-seq and bioinformatics analysis to construct the SF-AS regulatory network to screen out the key splicing factor Mov10 in DN, and verified it in three types of renal intrinsic cells and found that it was significantly overexpressed and this high expression state promoted the abnormal proliferation, inflammation and fibrosis of mesangial cells, providing a new idea for the study of diabetic nephropathy and a new target for its treatment.

Claims

1. Use of a Mov10 inhibitor in the preparation of a drug for treating diabetic nephropathy, wherein the Mov10 inhibitor is an artificially synthesized siRNA, and the siRNA sequence is: the sense strand is shown in SEQ ID NO.1, and the antisense strand is shown in SEQ ID NO.2.

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