Substances, kits and applications thereof for detecting CAEBV and IM host differentially methylated genes

Abstract

The present invention relates to a substance for detecting differentially methylated genes of CAEBV and IM hosts, and belongs to the field of biotechnology. The present invention provides five differentially methylated sites located in the human genome, namely CYFIP1 chr15 22992841-22992940bp, PTPN6 chr12 7063598-7063888bp, LHPP chr15 126300842-126301818bp, E2F1 chr20 32267678-32267721bp and RAP1GAP2 chr17 2696550-2696769bp. Changes in the above five differentially methylated sites caused by EBV infection are related to CAEBV and IM, and early identification of CAEBV and IM can be performed by detecting changes in the above five differentially methylated sites.

Description

Technical Field

[0001] The present invention relates to a primer set and a kit for identifying methylation differences, in particular to a primer set, a kit and an application thereof for identifying differentially methylated genes of hosts infected with chronic active Epstein-Barr virus and infectious mononucleosis, belonging to the field of biotechnology. Background Art

[0002] Epstein-Barr virus (EBV) is a member of the γherpesvirus subfamily of the Herpesviridae family. It is a human lymphotropic virus that is widely distributed throughout the world. About 90% of healthy adults worldwide carry the virus. EBV proliferates in oropharyngeal epithelial cells and then infects B lymphocytes. These cells enter the blood circulation in large numbers, causing systemic infection, and can remain latent in human lymphoid tissues for a long time. EBV infection can manifest as proliferative infection and latent infection. Different infection states express different antigens. The antigens expressed in the proliferative infection period include EBV early antigens, EBV capsid proteins, and EBV membrane antigens, and the antigens expressed in the latent infection period include EBV nuclear antigens and latent membrane proteins. EBV is associated with the occurrence and development of a variety of human lymphocytic and epithelial tumors, such as Hodgkin's lymphoma, nasopharyngeal carcinoma, and EBV-related gastric cancer. It is a recognized DNA tumor virus.

[0003] EBV is the pathogen of infectious mononucleosis (IM) and chronic active EBV infection (CAEBV). IM is an acute lymphoproliferative disease that often occurs after the first EBV infection in adolescence. Its clinical manifestations include fever, pharyngitis, lymphadenitis, splenomegaly, abnormal liver function, and a large increase in monocytes and atypical lymphocytes in peripheral blood. CAEBV is a lymphoproliferative disease caused by EBV infection of B lymphocytes and T lymphocytes. CAEBV usually occurs secondary to primary EBV infection and is characterized by fever, lymphadenopathy and splenomegaly. Laboratory tests can reveal high copy numbers of EBV-DNA and / or abnormal EBV-related antibodies, and pathological examinations can detect EBV-encoded RNA and a variety of virus-related proteins in damaged tissues. Studies have found that early allogeneic hematopoietic stem cell transplantation is an effective way to cure the disease. Studies have found that epigenetic modifications, especially DNA methylation, play an important role in EBV infection-related diseases. After EBV infects host cells, EBV viral genes may regulate the DNA methylation level of host genes through methyltransferases, thereby participating in the EBV pathogenic process. The host genome methylation characteristics are different in different EBV-related diseases. Therefore, the corresponding diseases can be identified and diagnosed by detecting differential DNA methylation genes in the host. At present, the potential role of changes in host genome DNA methylation in the occurrence and development of chronic active EBV infection (CAEBV) and infectious mononucleosis (IM) has not been studied. Comparing the differentially methylated genes in the host genome between CAEBV and IM, thereby screening DNA methylation biomarkers that can be used for clinical diagnosis and prognosis, and through pathway analysis, the mechanism of methylation in the occurrence and development of the disease can be further revealed, which is of great significance as a basis for early detection and diagnosis of the disease. Summary of the invention

[0004] The primary technical problem to be solved by the present invention is to provide a new use of a substance for detecting the methylation level of relevant sites in the human genome of a sample to be tested in identifying or assisting in identifying chronic active EB virus infection and infectious mononucleosis.

[0005] Another technical problem to be solved by the present invention is to provide a detection primer set for the above detection site.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] Detection of the genome of the sample to be tested CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 Application of site methylation level substances in the preparation of products for identification or auxiliary identification of chronic active Epstein-Barr virus infection and infectious mononucleosis.

[0008] Preferably, the substance is a primer set.

[0009] Preferably, the primer set is selected from a primer pair consisting of SEQ ID No.1 and SEQ ID No.2, a primer pair of SEQ ID No.3 and SEQ ID No.4, a primer pair of SEQ ID No.5 and SEQ ID No.6, a primer pair of SEQ ID No.7 and SEQ ID No.8, and a primer pair of SEQ ID No.9 and SEQ ID No.10.

[0010] A primer set for detecting host differentially methylated genes in chronic active Epstein-Barr virus infection and infectious mononucleosis, wherein the primer set is used to detect methylation sites in human genome CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 The methylation level of the site.

[0011] Preferably, the primer set is selected from a primer pair consisting of SEQ ID No.1 and SEQ ID No.2, a primer pair of SEQ ID No.3 and SEQ ID No.4, a primer pair of SEQ ID No.5 and SEQ ID No.6, a primer pair of SEQ ID No.7 and SEQ ID No.8, and a primer pair of SEQ ID No.9 and SEQ ID No.10.

[0012] Use of the primer set in a detection reagent or detection kit for detecting or assisting in detecting host differential methylation levels of chronic active Epstein-Barr virus infection and infectious mononucleosis.

[0013] A kit for detecting host differentially methylated genes in chronic active Epstein-Barr virus infection and infectious mononucleosis, comprising the above primer set.

[0014] Compared with the prior art, the present invention has the following technical effects:

[0015] (1) The present invention optimizes and improves the screening method to screen out host differential methylation sites between CAEBV and IM with strong stability and significant specificity.

[0016] (2) The present invention provides five differentially methylated gene sites located on the human genome. Changes in the differentially methylated gene sites caused by EBV infection are associated with CAEBV. Early diagnosis of CAEBV can be performed by detecting changes in the differentially methylated gene sites in the human genome.

[0017] (3) The five differentially methylated sites between CAEBV and IM provided by the present invention have good specificity and excellent stability. CYFIP1 (chr15 22992841-22992940bp) PTPN6 (chr12 7063598-7063888bp) , LHPP (chr15 126300842-126301818bp) 、E2F1 (chr20 32267678-32267721bp) and RAP1GAP2( chr17 2696550-2696769bp), the changes of the above differential methylation sites can be further detected for early identification of CAEBV and IM.

[0018] (4) The present invention provides primers for detecting differentially methylated sites, which can be used to perform PCR amplification and pyrophosphate sequencing on their sequences to detect the methylation levels of the corresponding genes, thereby enabling early identification of CAEBV and IM. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1A Violin plots show the comparison of methylation levels of differentially hypermethylated regions of CAEBV relative to IM, HC, and uninfected groups;

[0020] Figure 1B Violin plots are shown, showing the comparison of the methylation levels of differentially hypomethylated CpG regions of CAEBV relative to IM, HC and uninfected groups;

[0021] Figure 2 To use a heat map to display the methylation status of the differentially methylated genes among the four groups screened according to the first screening method;

[0022] Figure 3 To improve the screening method, the methylation status of the differentially methylated genes among the four groups obtained by the second screening method was analyzed;

[0023] Figure 4A Five genes with significant methylation differences between CAEBV and IM selected according to the second screening criteria CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 methylation levels;

[0024] Figure 4B Five genes with significant methylation differences between CAEBV and IM selected according to the first screening criteria LDLR , IFITM1 , MCOLN2 , CCDC88C and SNORD93 methylation levels; Figure 5 The validation sample set included 5 children with CAEBV and 5 children with IM. CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 Gene methylation levels. DETAILED DESCRIPTION

[0025] The technical content of the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0026] Example 1 Screening and analysis of differentially methylated sites between CAEBV and IM

[0027] 1. Sample source

[0028] A total of 59 peripheral blood mononuclear cells (PBMC) samples were collected, including 24 from children with chronic active EBV infection (CAEBV), 17 from infectious mononucleosis (IM), 9 from healthy carriers with EBV (HC), and 9 from EBV-uninfected children.

[0029] 2. Methylation site detection and analysis

[0030] (1) Reduced representation bisulfite sequencing (RRBS) was used to detect methylation in the four groups of samples. Pairwise comparisons were performed and the methylation level of the CG base on each target sequence of each sample was calculated using the BSMAP built-in methylation calculation python program. The methylation level was calculated according to the following formula:

[0031] The methylation level of site C = the number of reads supporting methylation / (the number of reads supporting methylation + the number of reads supporting non-methylation).

[0032] (2) Count the methylation level of each site in each sample. If the depth is less than 30X, it will be represented as NA.

[0033] (3) Finally, according to the methylation levels calculated above, the R language was used for statistical and visual display, and the two-tailed t-test was used for inter-group difference analysis. When the p-value of the test result was less than 0.05 and the absolute value of the difference in the average methylation level between the groups was greater than 0.1, the difference was considered significant. In this way, the effective methylation information of the single site on the whole genome was obtained.

[0034] 3. Screening of significant differentially methylated sites

[0035] (1) Since RRBS can only compare differentially methylated sites between two groups, we compared the differentially methylated sites between the CAEBV and IM groups, the CAEBV and HC groups, and the CAEBV and uninfected groups, and found a total of 28,675 differential methylation regions (DMRs), as shown in Figure 1.

[0036] (2) To find specific differential methylation sites in CAEBV that were significantly different from those in IM, HC, and uninfected groups, we merged CAEBV with the DMRs obtained by pairwise comparisons between the three groups, removed duplicate DMRs, calculated the mean methylation values ​​of these DMRs in all samples, and marked the ID as the comparison group + DMR number. The mean, standard deviation, and p-value between groups were calculated for each DMR in each group.

[0037] (3) Based on the indicators calculated above, the p-value, standard deviation, and methylation difference value of each group were screened, with thresholds of 0.001, 0.15, and 0.1, respectively. The DMRs screened out in each group were merged, and 589 DMRs were obtained after screening, as shown in the figure. Figure 2 shown.

[0038] The above method initially detected 589 differentially methylated sites, but the stability and specificity were poor. In order to further screen out differentially methylated sites that can specifically distinguish CAEBV and IM, the inventors improved the screening scheme and further optimized the screening conditions. The optimization method is: first, select sites where the absolute value of the difference in the average methylation level between the two groups is greater than 0.25. Second, evaluate the stability within the differentially methylated site group, that is, calculate the coefficient of variation (CV), the formula is (S is the sample standard deviation, M is the sample mean), sites with CV less than 40% have better stability.

[0039] 4. Results of screening for differentially methylated sites between CAEBV and IM

[0040] (1) The number of differentially methylated regions (hypermethylated and hypomethylated) between CAEBV and IM, CAEBV and HC, and CAEBV and Normal groups, respectively. Figure 1A and Figure 1B shown. Figure 1A The violin plots show the comparison of methylation levels of differentially hypermethylated regions of CAEBV relative to IM, HC and uninfected groups; Figure 1B The violin plots show the methylation levels of differentially hypomethylated CpG regions in CAEBV relative to IM, HC and uninfected groups. In the figure, CAEBV: chronic active EBV infection; IM: infectious mononucleosis; HC: EBV healthy carriers; uninfected: healthy children not infected with EBV.

[0041] (2) The differentially methylated genes among the four groups were screened according to the first screening criteria, and the methylation status of each gene among the groups was displayed using a heat map. The results are as follows: Figure 2 shown. Figure 2 This is a heat map of cluster analysis of differentially methylated genes in the host genome in the four groups according to the first screening criteria. Each column represents a sample. Each row represents the average methylation level of each differentially methylated gene in the host genome in all samples. The methylation level corresponding to each region of all samples is represented by different colors. The color gradient from dark to light indicates the change from low to high gene methylation level. In the figure, CAEBV: chronic active EBV infection; IM: infectious mononucleosis; HC: EBV healthy carrier; uninfected: healthy children not infected with EBV.

[0042] (3) According to the above-mentioned adjusted and improved screening scheme, differentially methylated genes among the four groups were screened. According to the first point of the optimized scheme, a total of 192 differentially methylated sites were detected. The methylation status of each gene among the groups was displayed using a heat map. The results are as follows: Figure 3 shown. Figure 3 This is a heat map of cluster analysis of differentially methylated genes in the host genome in the four groups according to the second screening criteria. Each column represents a sample. Each row represents the average methylation level of each differentially methylated gene in the host genome of all samples. The methylation level corresponding to each region of all samples is represented by a different color. The color gradient from dark to light indicates the change from low to high gene methylation level. Among the 192 differentially methylated sites, the second point of the optimized scheme was used for screening, and a total of five genes with significant methylation differences between CAEBV and IM were screened. CYFIP1 (chr15 22992841-22992940bp), PTPN6(chr12 7063598-7063888bp), LHPP (chr15 126300842-126301818bp), E2F1 (chr20 32267678-32267721bp) and RAP1GAP2 (chr17 2696550-2696769bp).

[0043] The methylation levels and CV values ​​of the above genes are shown in Table 1 and Figure 4A and Figure 4B shown. Figure 4A Five genes with significant methylation differences between CAEBV and IM selected according to the second screening criteria CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 methylation level. Figure 4B for

[0044] Five genes with differential methylation between CAEBV and IM selected according to the first screening criteria LDLR , IFITM1 , MCOLN2 , CCDC88C and SNORD93 The methylation levels of the five sites screened in the second screening are more obvious. The methylation levels and CV values ​​of the five representative differentially methylated genes screened in the first screening were selected for comparison, as shown in Table 1. The Diff value can directly determine that the methylation levels of the five methylation sites screened in the second screening are significantly higher than those of the sites screened in the first screening, and the CV value can determine that their specificity is also higher than that of the sites screened in the first screening.

[0045] Table 1

[0046]

[0047] Example 2 Primers for detecting significantly differentially methylated gene levels in CAEBV and IM samples

[0048] 1. Primer Set

[0049] The inventors designed primers with high amplification efficiency and good specificity for the above-mentioned differentially methylated sites, which can detect the levels of the above-mentioned significantly differentially methylated genes in CAEBV and IM samples. The primer sequences are shown in the following table.

[0050] Table 2

[0051]

[0052] 2. Basic method for detecting the methylation level of target genes in CAEBV and IM samples using the above primer sets:

[0053] (1) DNA sample preparation: DNA was extracted using a universal genomic DNA extraction kit (Tiangen) using magnetic beads;

[0054] (2) NaHSO3 sample treatment: The DNA sample to be tested is treated with a commercial sodium bisulfite (NaHSO3) kit to cause the non-methylated cytosine (C) to undergo a deamination reaction and be converted into uracil (U), while the methylated cytosine cannot undergo a deamination reaction and remains as cytosine.

[0055] (3) PCR amplification reaction: The gene fragment to be detected is enriched and amplified through PCR reaction, and the product length is between 200-700bp.

[0056] a. After the sample is treated with NaHSO3, it is briefly centrifuged at low speed for later use.

[0057] b. Prepare the PCR reaction mixture as shown in the table below (the reaction system preparation process is completed under low temperature conditions to prevent inactivation due to long-term exposure to high temperature).

[0058] Table 3 PCR reaction components for methylation detection amplification

[0059]

[0060] c. Amplification PCR reaction procedure

[0061] The program was set according to the following temperature and time: 94°C, 4 min→(94°C, 20 s→56°C, 20 s→72°C, 1 min) 45 cycles→72°C, 3 min→4°C, ∞;

[0062] d. Use 3 μL of PCR product and 1 μL of Mix well, and detect by 1.5% agarose gel electrophoresis at 160V for 20 minutes. If the result is good, continue with the subsequent experiment. If the amplification effect is not good, adjust the amplification system and reaction conditions to optimize until the best PCR amplification result is obtained.

[0063] 3. SAP digestion reaction: The PCR product was treated with SAP (shrimp alkaline phosphatase) to remove free dNTPs in the system.

[0064] 4. Transcriptase reaction and methylation level detection:

[0065] The product was simultaneously reverse transcribed and digested with T7 RNA & DNA Polymerase and RNaseA to obtain small fragments containing CpG sites. The molecular weights of methylated and non-methylated fragments were different. Time-of-flight mass spectrometry was used to distinguish the fragments and calculate the methylation ratio.

[0066] Example 3 Using the above primer set of the present invention to detect the methylation level of the target gene in CAEBV and IM samples for verification

[0067] (1) Based on the above research, the present invention further validated the primer set in Table 2 in another sample set, which was from 5 children with CAEBV and 5 children with IM. CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 The methylation level of the gene is used to identify chronic active EB virus infection and infectious mononucleosis, thereby verifying the feasibility and effectiveness of the methylation site described in the present invention. The detection method and analysis method are the same as those described in Examples 1 and 2.

[0068] (2) Experimental results

[0069] The results are shown in Table 4 and Figure 5 As shown, in the PBMC samples of children in the CAEBV group, CYFIP1 , PTPN6 , LHPP , E2F1 and RAP1GAP2 The average methylation levels of the genes were higher than those of the IM group, and the differences were statistically significant. The experimental results show that early identification of CAEBV and IM can be performed by detecting changes in the differential methylation sites of the human genome described in the present invention. The verification experiment also shows that the five methylation sites provided by the present invention have high detection sensitivity, specificity and good repeatability.

[0070] Table 4

[0071]

Claims

1. Detection of the genome of the sample to be tested CYFIP1 chr15 22992841-22992940bp, PTPN6 chr127063598-7063888bp, LHPP chr15 126300842-126301818bp、 E2F1 chr20 32267678-32267721bp and RAP1GAP2 Use of a primer set for methylation level of chr17 2696550-2696769bp site in the preparation of a reagent or kit for distinguishing chronic active Epstein-Barr virus infection from infectious mononucleosis; The primer set consists of a primer pair as shown in SEQ ID No.1 and SEQ ID No.2, a primer pair as shown in SEQ ID No.3 and SEQ ID No.4, a primer pair as shown in SEQ ID No.5 and SEQ ID No.6, a primer pair as shown in SEQ ID No.7 and SEQ ID No.8, and a primer pair as shown in SEQ ID No.9 and SEQ ID No.

10.

2. A primer set for detecting host differential methylation levels in chronic active Epstein-Barr virus infection and infectious mononucleosis, characterized in that: The primer set is used to detect the methylation site of the human genome. CYFIP1 chr15 22992841-22992940bp, PTPN6 chr12 7063598-7063888bp, LHPP chr15 126300842-126301818bp、 E2F1 chr2032267678-32267721bp and RAP1GAP2 Methylation level of chr17 2696550-2696769bp site; The primer set consists of a primer pair as shown in SEQ ID No.1 and SEQ ID No.2, a primer pair as shown in SEQ ID No.3 and SEQ IDNo.4, a primer pair as shown in SEQ ID No.5 and SEQ ID No.6, a primer pair as shown in SEQ ID No.7 and SEQ IDNo.8, and a primer pair as shown in SEQ ID No.9 and SEQ ID No.

10.

3. Use of the primer set according to claim 2 in the preparation of a reagent or a kit for detecting host differential methylation levels of chronic active Epstein-Barr virus infection and infectious mononucleosis.

4. A kit for detecting host differential methylation levels in chronic active Epstein-Barr virus infection and infectious mononucleosis, characterized in that: The kit comprises the primer set according to claim 2.

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