A probe library for targeted capture of ebv-encoded genes for single cell transcriptome sequencing

Abstract

The application provides a probe library for targeting capturing EBV coding genes for single cell transcriptome sequencing, relates to the technical field of genetic engineering, and the probe library covers EBV latent infection period related genes (EBNA1, EBNA2, LMP1, LMP2B), lytic replication period related genes (BARF0, LF2, BNL2A, BNL2B, BZLF1, BRLF1, BHRF1, RPMS1, BALF3, BALF5, BALF1) and specific non-coding RNA related genes (EBER1, EBER2), and the specific sequences of the probes are shown in SEQ ID NO. 1-84. The probe library has high sensitivity and specificity, can accurately distinguish infected cells from non-infected cells at the single cell level, and can finely group the infected cells, breaks through the limitation that traditional technologies cannot analyze EBV infection heterogeneity at the single cell level, and provides a powerful tool for basic research, biomarker discovery and drug target screening of EBV related diseases.

Description

Technical Field

[0001] This invention relates to the field of genetic engineering technology, and more specifically to a probe library for targeted capture of EBV-encoding genes for single-cell transcriptome sequencing. Background Technology

[0002] Epstein-Barr virus (EBV) is a widespread gamma-herpesvirus that infects more than 90% of the adult population worldwide. Following primary infection, EBV can establish a lifelong latent infection in human B lymphocytes and epithelial cells. EBV is closely associated with a variety of human diseases, including infectious mononucleosis, as well as various malignancies such as nasopharyngeal carcinoma (NPC), gastric cancer, Burkitt lymphoma (BL), Hodgkin lymphoma (HL), and post-transplant lymphoproliferative disorder (PTLD), chronic active EBV infection (CAEBV), and EBV-associated hemophagocytic lymphohistiocytosis (EBV-HLH).

[0003] The EBV infection life cycle exhibits significant phased characteristics, mainly including two core phases: the latency period and the lytic phase. The viral gene expression profiles differ markedly between these different phases.

[0004] Latent phase: The viral genome exists in the cell nucleus as an episome, with only a limited portion of viral genes expressed, evading recognition by the host's immune system. Based on the expressed viral gene profile, the latent phase can be divided into latent phases 0, I, II, and III. The core genes expressed in each phase include EBNA1 (maintaining viral genome replication), EBNA2 (major transcription activator), LMP1 (key oncogene), LMP2B, and various non-coding RNAs (such as EBER1 and EBER2).

[0005] Lysis phase: The virus enters the active replication phase, producing progeny viral particles. During this phase, almost all viral genes are sequentially activated and expressed, including core genes such as BZLF1 (Zta, the master switch of the lysis cycle) and BRLF1 (Rta), which are lysis initiation genes, and genes involved in viral DNA replication and nucleotide metabolism such as BALF5 (DNA polymerase) and BSMLF1.

[0006] In the research and clinical diagnosis of EBV-related diseases, understanding the interaction between EBV and host cells at the single-cell level is crucial. However, traditional EBV detection methods (such as serum PCR and antibody detection) and bulk sequencing technologies have significant limitations. Traditional detection methods struggle to achieve precise localization at the single-cell level, while bulk sequencing can only obtain the average signal of the cell population, failing to reveal key issues related to cellular heterogeneity, such as which specific cells in the same tumor tissue or whole blood sample are infected with EBV, whether infected cells are in the latent or lytic phase, and the characteristics of the host cell gene expression profiles under different infection states. Effective answers to these questions are a core prerequisite for elucidating the pathogenesis of EBV and discovering new therapeutic targets, and represent a critical technological bottleneck that urgently needs to be overcome in the current field of EBV-related research.

[0007] Existing technologies for comprehensive EBV detection at the single-cell level have the following main shortcomings and deficiencies: First, the expression levels of EBV-encoding genes in host cells are generally low, and traditional transcriptome sequencing technologies lack sufficient sensitivity to capture them at the single-cell level. Second, conventional single-cell sequencing (such as SMART-seq2) has low throughput, which cannot meet the needs of heterogeneous analysis of large-scale cell populations. Although the 10× Genomics platform supports high-throughput single-cell sequencing (500-10000 cells / sample), it can only capture the 3' end transcripts of host genes by default, lacking the ability to specifically enrich viral genes and thus failing to efficiently monitor low-expression EBV-encoding genes. Third, existing EBV targeted capture technologies suffer from low capture rates, high detection costs, and cumbersome experimental processes, making it difficult to achieve efficient and accurate large-scale detection.

[0008] It is worth noting that the Flex mode of the 10× Genomics platform allows users to enrich target transcripts using pre-designed gene-specific oligonucleotide probes (panels). These probes directly hybridize with RNA in cell lysates and are then introduced into the 10× GemCode chip for library construction and sequencing. The Flex mode perfectly combines the high sensitivity and specificity of targeted capture with the high throughput and high resolution of single-cell sequencing. However, there is currently no mature method for designing probe panels specifically for all EBV coding genes and integrating them with the 10× Genomics Flex single-cell sequencing platform for comprehensive and accurate analysis of EBV infection status. This invention aims to fill this gap. Summary of the Invention

[0009] (a) Technical problems to be solved

[0010] To address the shortcomings of existing technologies, this invention provides a probe library for targeted capture of EBV-encoding genes for single-cell transcriptome sequencing.

[0011] (II) Technical Solution

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] In a first aspect, the present invention provides an oligonucleotide probe library for targeted capture of EBV coding genes, the probe library including EBV latency-related genes (EBNA1, EBNA2, LMP1, LMP2B), cleavage-related genes (BARF0, LF2, BNL2A, BNL2B, BZLF1, BRLF1, BHRF1, RPMS1, BALF3, BALF5, BALF1), and non-coding RNA (EBER1, EBER2); the probe library includes all probes with nucleotide sequences as shown in SEQ ID NO. 1-84.

[0014] Secondly, the present invention provides a method for targeted capture of EBV-encoding genes based on 10×Genomics single-cell transcriptome sequencing, comprising the following steps:

[0015] S1. Sample preparation and fixation: Obtain the cell or tissue sample to be tested, prepare a single-cell suspension, add fixative and fix at 4℃ for 16-24 h;

[0016] S2. Probe hybridization: The probe library described in claim 1 is added to the hybridization mixture and mixed with the fixed sample. The mixture is then incubated in a PCR instrument at 42°C for 16-24 h to allow the probes to bind to viral RNA. After hybridization, unbound probes are removed with washing buffer.

[0017] S3. Single-cell isolation and labeling: The hybridized sample is encapsulated with gel beads bearing barcodes using microfluidic technology to form gel beads (GEMs), ensuring that each GEM contains one cell and one barcode-bearing gel bead, thereby achieving single-cell isolation and labeling; then, a reverse transcription reaction is performed within the GEM to generate cDNA carrying the cell barcode and unique molecular identifier (UMI);

[0018] S4. Library construction: The cDNA product in the GEM is recovered, pre-amplified and modified to construct a standardized DNA library suitable for sequencing;

[0019] S5. Sequencing: Perform high-throughput sequencing on the library constructed in step S5 to obtain nucleic acid sequence information;

[0020] S6. Data Analysis: The sequencing data obtained in step S6 were compared and analyzed using 10× Genomics Cell Ranger software.

[0021] Thirdly, the present invention provides the use of the probe library in the preparation of reagents or kits for targeted capture of EBV-encoding genes.

[0022] Specifically, the probe library can accurately distinguish between EBV-infected cells and non-infected cells at the single-cell level, and further refine the grouping of infected cells to identify cell subpopulations in different latent or lytic phases.

[0023] (III) Beneficial Effects

[0024] This invention provides a probe library for targeted capture of EBV coding genes for single-cell transcriptome sequencing. The probe library covers genes related to EBV latent infection (EBNA1, EBNA2, LMP1, LMP2B), genes related to lytic replication (BARF0, LF2, BNL2A, BNL2B, BZLF1, BRLF1, BHRF1, RPMS1, BALF3, BALF5, BALF1), and specific non-coding RNA-related genes (EBER1, EBER2). The probe library includes all probes with nucleotide sequences as shown in SEQ ID NO. 1-84. The probe library of this invention has the following advantages:

[0025] 1. High sensitivity and specificity: Through targeted probe design, this invention can directly enrich low-abundance EBV transcripts, effectively solving the problem of missed detection of non-polyA RNA and low-expression RNA in traditional 3'scRNA-seq technology. In particular, it can effectively detect key oncogenes such as LMP1 and LMP2, providing reliable technical support for early identification of EBV infection and accurate capture of oncogene-related genes.

[0026] 2. Possesses single-cell resolution and high-throughput analysis capabilities: The probe library of this invention can accurately distinguish infected and uninfected cells at the single-cell level, and can perform fine-grained grouping of infected cells, identifying cell subpopulations in different latent phases or lysis phases. This breaks through the limitations of traditional technologies that cannot analyze EBV infection heterogeneity at the single-cell level, and can reveal unprecedented cell heterogeneity.

[0027] 3. Panoramic Observation: The probe of this invention can simultaneously acquire the whole transcriptome information of host cells while accurately detecting EBV viral transcripts and clarifying the viral infection status. This allows for in-depth analysis of biological processes such as immune response, signaling pathway activation, and cell cycle of host cells under the precise knowledge of the viral status, directly establishing the causal relationship between the virus and the host. This provides an efficient research tool for elucidating core scientific questions such as the interaction mechanism between EBV and the host and the mechanism of viral carcinogenesis.

[0028] 4. High compatibility and flexibility: This invention is based on the mature and stable 10× Flex platform. The technology is mature and stable, and it can be used in combination with probe panels of other species or genes, with a wide range of applications.

[0029] 5. Powerful application value: It provides a powerful tool for basic research on EBV-related diseases, biomarker discovery, and drug target screening. Attached Figure Description

[0030] Figure 1 Figure 1 shows the results of flow cytometry in situ hybridization (FISH) for detecting the specificity and sensitivity of the probe library of this invention. Figure 2 shows the detection results of all EBV-encoded probes (including EBER1, EBER2, BHRF1, BARF0, EBNA-1, EBNA-2, BRLF1, BZLF1, LMP-1, LMP-2B, LF2, etc.) in the control group SUBP15 (uninfected cell line); Figure 3 shows the comparative detection results of EBER1 and EBER2 probes in the control group SUBP15 (uninfected cell line) and the experimental group EBV-LCL (EBV-infected cell line).

[0031] Figure 2 Figure 1 shows the results of verifying the specificity and sensitivity of the probe library of this invention based on single-cell transcriptome sequencing technology. Figure A is a UMAP clustering diagram of all samples; Figure B is a comparison of the UMAP distribution of cells in the control group (SUBP15) and the experimental group (EBV-LCL); Figure C is the UMAP distribution of EBV-infected and uninfected cells; Figure D is a bar chart showing the proportion of EBV infection in each sample; Figure E is the UMAP expression distribution of the EBV encoding genes covered by the probe library in cells.

[0032] Figure 3 To validate the performance of probe libraries based on single-cell transcriptome sequencing in disease models. Figure A is a schematic diagram illustrating the single-cell transcriptome data analysis workflow; Figure B is a UMAP visualization of all samples; Figure C shows the annotation of marker genes specifically expressed in different cell types; Figure D shows the proportional distribution of each cell subpopulation in different disease groups; Figure E is a UMAP visualization showing the distribution of EBV infection; Figure F is a UMAP visualization showing the EBV infection expression in all cells; Figure G is a UMAP visualization showing the EBV infection distribution in each disease type; and Figure H is a pie chart showing the proportion of EBV infection in each cell subpopulation across various diseases.

[0033] Figure 4This section presents a single-cell transcriptome analysis of NK cells in EBV infection. Figure A shows the UMAP plot of NK cell subsets; Figure B shows the expression of characteristic marker genes for each subset (violin plot); Figure C shows the enrichment level of subsets in different samples; Figures D and E show the differentially expressed gene analysis of the C0-GZMK-NK subset (volcano plot); Figure E shows the enrichment analysis of differentially expressed genes along the GO and KEGG pathways; Figure F shows the correlation between EBER2 and GZMK expression; Figure G is a heatmap of EBV gene expression in NK cells; and Figure H is a volcano plot illustrating EBV. + With EBV - Differentially expressed genes in NK cells; Figure I shows the enrichment analysis of the GO and KEGG pathways related to the differentially expressed genes; Figure J shows that GSEA analysis revealed that CD74 was significantly enriched as a core node in key pathways such as immune response and lymphocyte activation.

[0034] Figure 5 CD8 + Single-cell transcriptome analysis of T cells in EBV infection. Figure A shows CD8. + UMAP plot of T cell subsets; Figure B shows the expression of characteristic marker genes in each subset (violin plot); Figure C shows the enrichment degree of the subsets in different samples; Figure D shows the average expression heatmap of key genes in each subset; Figure E shows CD8... + Mapping of T cell functional status in UMAP space; Figure F shows EBV. + With EBV - Differentially expressed genes among CD8⁺ T cells (volcano plot); Figure G shows the GO functional enrichment analysis of differentially expressed genes; Figure H shows the KEGG pathway enrichment analysis of differentially expressed genes; Figure I shows that GSEA analysis reveals CD74 as a core node enriched in pathways such as immune response, lymphocyte activation, cytokine receptor action, and cellular ketone body metabolism.

[0035] Figure 6 Single-cell transcriptome analysis of NK / T cells in EBV infection. Figure A shows the UMAP of proliferating NK / T cell subsets; Figure B shows the UMAP of proliferating T cells and proliferating NK cells as two distinct lineages; Figure C shows the UMAP of EBV-infected cell populations (red represents EBV-positive cells, gray represents EBV-negative cells); Figure D compares the enrichment levels of each proliferating subset in different samples; Figure E is a heatmap visualization of EBV. + The main enrichment pathways in the C1, C3, and C4 populations of HLH; Figure F is a volcano plot showing EBV. + With EBV -Differentially expressed genes in proliferating NK / T cells; Figure G shows the pathways related to the above differentially expressed genes through GO functional enrichment analysis; Figure H shows the pathways related to the above differentially expressed genes through KEGG pathway enrichment analysis; Figure I shows that GSEA analysis reveals that CD74 is significantly enriched as a core node in key pathways such as immune response and lymphocyte activation.

[0036] Figure 7 This study presents a single-cell transcriptome analysis of monocytes in EBV-infected states. Figure A shows the UMAP plot representing monocyte subpopulations; Figure B shows a violin plot illustrating the average expression levels of characteristic marker genes in each subpopulation; Figure C shows UMAP cluster analysis dividing monocytes into 9 subclusters; Figure D shows the enrichment / deletion levels of samples from each monocyte subpopulation; Figure E shows KEGG pathway enrichment analysis of the main enriched pathways in the 9 monocyte subclusters (C1-C8); Figure F shows GO functional enrichment analysis of pathways related to differentially expressed genes in monocytes; and Figure G is a volcano plot illustrating EBV. + With EBV - Differentially expressed genes in monocytes; Figure H shows EBV. + Correlation analysis of EBER1 with host genes in monocytes; Figure I shows EBV. + Mononuclear cell functional enrichment analysis. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1

[0039] Preparation of a probe library for targeted capture of EBV-encoding genes for single-cell transcriptome sequencing

[0040] 1. Design principles of probe libraries

[0041] The oligonucleotide probe library constructed in this embodiment is based on the following design features to ensure specific targeting and full coverage of the EBV encoding gene:

[0042] (1) Full life cycle coverage: The probe library of this invention can effectively monitor the two core life cycles of EBV, namely latent infection and lytic replication, to achieve accurate capture of different infection stages of the virus;

[0043] (2) Functional gene cluster coverage: Key genes covering different functional categories (such as regulatory proteins, structural proteins, immune escape proteins, etc.) are covered in each life cycle of EBV.

[0044] (3) Clinical and research relevance: Prioritize genes that are closely related to the occurrence, development, diagnosis and treatment monitoring of EBV-related diseases (such as infectious mononucleosis, nasopharyngeal carcinoma, lymphoma, etc.).

[0045] (4) Molecular marker characteristics: containing genes, such as non-coding RNA, that serve as “molecular tags” for specific viral infection stages.

[0046] 2. Target gene selection

[0047] Based on the above design principles, the oligonucleotide probe library in this embodiment targets the following EBV-encoding genes, covering key genes during the latent infection period, key genes during the lytic replication period, and specific non-coding RNAs:

[0048] 2.1 Latent infection period

[0049] Latent infection is key to the persistent presence of EBV in the host and its role in tumorigenesis. This embodiment selects these genes to identify the types of latent infection (latency types I, II, and III), which are important molecular markers for distinguishing different EBV-related tumors. Specifically, these include:

[0050] EBNA1 (Epstein-Barr Nuclear Antigen 1): A "broad-spectrum" biomarker of latent infection, expressed in all forms of latent infection, it is essential for the stable replication and distribution of the viral genome (epidermis) during host cell division. EBNA1 is almost always expressed as long as the cell carries the viral genome and is in the latent phase. Detection of EBNA1 can confirm the presence of latent infection.

[0051] EBNA2 (Epstein-Barr Nuclear Antigen 2): A marker of latent type III infection and a major viral transcription activator, playing a central role in the initiation of B cell immortalization (transformation). It directly regulates the expression of other latent genes, such as LMP1. EBNA2 expression typically indicates active, highly tumorigenic latent type III infection (seen in immunosuppression-associated lymphoproliferative disorders).

[0052] LMP1 (Latent Membrane Protein 1): A core indicator of carcinogenicity and a marker of latent type II / III. It is commonly expressed in nasopharyngeal carcinoma, Hodgkin's lymphoma, and other diseases, and is key to assessing viral carcinogenic activity.

[0053] LMP2B (Latent Membrane Protein 2B): A co-marker for latent type II / III viruses, it mimics B cell receptor signaling to prevent infected B cells from undergoing apoptosis during the latent period, thereby maintaining the viral reservoir. It works synergistically with LMP1 and is an important tool for maintaining long-term viral latency.

[0054] 2.2 Fragmentation Replication Period

[0055] The lysis phase of replication is the stage in which the virus produces progeny and spreads, and it is also associated with the acute phase of disease and tissue damage. These genes were selected to confirm active viral replication and assess its replication level. Specifically, they include:

[0056] Immediate early genes: BZLF1 and BRLF1, which are the "master switch" for replication in the lysis cycle and the "start" markers for replication during lysis. The expression of BZLF1 (Zta) and BRLF1 (Rta) proteins is the first step in initiating the entire lysis-phase gene cascade reaction. Detecting the expression of these two genes is the most direct evidence for determining that the virus has entered the lysis phase.

[0057] Early genes: BALF5 and BHRF1, markers of the lysis phase. They represent key stages in viral genome replication and assembly preparation. BALF5: Encodes viral DNA polymerase, a core enzyme essential for viral genome replication. It is a clear indicator that the virus is actively replicating. BHRF1: Encodes a viral protein homologous to Bcl-2, whose main function is to inhibit apoptosis and create a favorable environment for viral replication; it is an important marker of the lysis phase.

[0058] Late-stage genes: BARF0 and BALF3, markers of the "late" lysis phase. They represent the assembly and maturation stages of viral particles. Covering these genes provides a more complete picture of the entire lysis and replication process. BARF0: Expressed during both the latent and lysis phases, its function may be related to immune regulation. BALF3: Involved in viral DNA processing and packaging.

[0059] Other lysis phase genes, including LF2, BNL2A, BNL2B, RPMS1, and BALF1, provide comprehensive coverage. These genes are typically involved in immune evasion (e.g., BNL2A / B can inhibit antigen presentation) and optimizing the replication environment. To ensure the probe library captures all possible viral activities, including those with complex or minor functions, and to avoid missed detections, further investigation is conducted.

[0060] 2.3 Non-coding RNA

[0061] Non-coding RNAs: Abundant "sentinel" EBER1 and EBER2 (Epstein-Barr Encoded RNAs): Highly sensitive markers of latent infection, these are EBV-encoded non-coding RNAs that are extremely abundant in latently infected cells (up to millions of copies per cell). Even in latent type I tumors (such as Burkitt lymphoma) where viral protein expression levels are very low or difficult to detect, EBERs are still highly expressed. In situ hybridization detection of EBERs is the "gold standard" for detecting EBV-infected cells in clinicopathological diagnosis. They are also included in probe libraries, allowing for sensitive detection of their expression using high-throughput sequencing technology.

[0062] 3. Design and Synthesis of Oligonucleotide Probe Libraries

[0063] For all the target genes mentioned above, oligonucleotide probes were designed using a unified probe backbone structure. The specific backbone sequences are as follows:

[0064] 5'-CCTTGGCACCCGAGAATTCCA-target-LHS-3' 5'Phos / -target-RHS-ACGCGGTTAGCACGTA-NN-ACTTTAGG-CGGTCCTAGCAA-3'

[0065] The left (LHS) probe contains a partial Read 2S (pRead 2S) and a complementary sequence to the EBV gene mRNA target site. The right (RHS) probe contains a phosphate ligation site at the 5' base, a target complementary sequence, a constant sequence, a probe barcode, and a partial capture sequence 1 (pCS1).

[0066] Based on the above backbone structure and the specific sequences of each target gene, corresponding oligonucleotide probes were designed and synthesized. The specific sequences of each probe are shown in SEQ ID NO.1-84. All synthesized oligonucleotide probes were mixed to obtain the oligonucleotide probe library specifically targeting all EBV-encoding genes in this embodiment.

[0067] Example 2

[0068] A method for targeted capture of EBV-encoding genes based on 10× Genomics single-cell transcriptome sequencing

[0069] 2.1 Sample preparation and fixation

[0070] Obtain cell or tissue samples potentially infected with EBV and prepare single-cell suspensions. Centrifuge at 400 g for 5 min at 4°C, remove the supernatant, add 1 mL of PBS buffer containing 1% BSA, mix well by pipetting, and use a cell counter to detect cell viability and concentration, calculating the total cell count. Centrifuge again at 4°C for 5 min at 400 g, remove the supernatant, collect the cells, add 1 mL of Fixation Buffer, mix well by pipetting, and fix at 4°C for 16-24 h. After fixation, centrifuge at 850 g for 5 min at room temperature, remove the supernatant, add 1 mL of pre-chilled Quenching Buffer, mix well by pipetting, and place on ice. Take 10 μL of sample to detect cell concentration and calculate the total cell count.

[0071] 2.2 Probe hybridization

[0072] The fixed cells were centrifuged at 850 rcf for 5 min at 4 °C and resuspended in Quenching Buffer. The supernatant was discarded, and the pellet was resuspended in 80 μL of Hyb mix and transferred to a PCR tube. The specific probe was added to the Hyb mix containing the fixed sample, and the mixture was pipetted and incubated in a PCR instrument at 42 °C for 16–24 h to allow the probe to bind to complementary viral RNA. After hybridization, the sample was washed with Post-Hyb Wash Buffer.

[0073] 2.3 Construction of the 10× Genomics Flex Library

[0074] 2.3.1 GEM (oil droplet) preparation

[0075] (1) Mixing reagents and samples

[0076] Prepare the GEM Master Mix (20.9 μL GEM Reagent Mix + 12.4 μL GEM Enzyme Mix), mix thoroughly by pipetting, briefly insulate, and store on ice for later use; dilute the sample to a viable cell concentration of 1-2 × 10⁻⁶. 3 / μL, take 2.4×10 4 For each cell, the sample volume is calculated using the formula: Sample volume = 24000 / viable cell concentration. Post-Hyb Resuspension is added to make the total volume 40 μL, followed by 35 μL of GEM Master Mix and thorough mixing (total volume 75 μL).

[0077] (2) Chromium chip loading

[0078] Add 50% glycerol to each unused well on the chip: 70 μL for well labeled 1, 50 μL for well labeled 2, and 45 μL for well labeled 3. Add the 75 μL of "Master Mix + Cell Suspension" to each row of wells labeled 1. Vortex the gel beads for 1 min, then briefly separate for 5 s, adding 50 μL to each row of wells labeled 2. Add 45 μL of separation oil to each row of wells labeled 3. Close the chip cap and immediately run on a Chromium Controller or X / iX. After the run, slowly aspirate 100 μL of GEM from the lowest point of the recovery well labeled 3 (avoid sealing the tip to the bottom of the well), and transfer it to an ice-cold PCR tube (close to the tube wall) within 20 s. The GEM should appear opaque and homogeneous to the naked eye.

[0079] 2.3.2 GEM incubation, probe and recovery of pre-amplification

[0080] (1) GEM incubation

[0081] Incubate GEM using the following PCR procedure: 25°C, 60 min → 60°C, 45 min → 80°C, 20 min. Store at 4°C after incubation.

[0082] (2) GEM recovery: Add 125 μL Recovery Agent to each sample at room temperature, mix well, let stand for 2 min, and then slowly remove the pink oil phase at the bottom of the tube after a short centrifugation.

[0083] (3) GEM recovery and pre-amplification

[0084] Prepare the pre-amplification mixture (Amp mix 25 + Pre-Amp Primers B) on ice, vortex and briefly centrifuge; add 35 μL to the above aqueous phase, mix well and briefly centrifuge, then incubate according to the following PCR procedure:

[0085] Table 1 Pre-amplification PCR program

[0086]

[0087] (3) Purification of pre-amplification products

[0088] Prepare the elution buffer (980 μL Buffer EB + 10 μL 10% Tween 20 + 10 μL Reducing Agent B), vortex and briefly centrifuge for later use; centrifuge the above PCR product for 30 s, transfer 70 μL of supernatant to a new tube; vortex to resuspend SPRIselect reagent, add 126 μL of SPRIselect reagent (1.8 times the supernatant volume) to each sample, mix well by pipetting, and incubate at room temperature for 5 min. Place the solution on a high magnetic rack until clear, discard the supernatant, add 200 μL of 80% ethanol to the precipitate for washing, let stand for 30 s, discard the ethanol, and repeat the washing twice. After a brief centrifugation, place on a low magnetic rack to remove residual ethanol (do not dry the sample). Remove from the magnetic rack, add 101 μL of elution buffer, let stand for 1 min, then mix by pipetting, incubate at room temperature for 2 min, then place on the magnetic rack at a high position until the solution is clear, transfer 100 μL of sample to a new 8-tube PCR tube, and store at 4°C for ≤72 hours or at -20°C for ≤4 weeks.

[0089] 2.3.3 Construction of Fixed RNA-Gene Expression Library

[0090] Select an appropriate sample index to ensure no index overlap during multiplex sequencing runs. Prepare the sample index PCR mixture (50 μL Amp Mix + 10 μL enzyme-free water) on ice; transfer 20 μL of SPRIselect purified sample to a new PCR tube, add 60 μL of the sample index PCR mixture, then add 20 μL of individual Dual Index TS Set A, mix thoroughly by pipetting, incubate briefly, and follow the PCR procedure below:

[0091] Table 2 Sample Index PCR Procedure

[0092]

[0093] 2.3.4 Document Size Sorting (SPRIselect)

[0094] Vortex resuspend the SPRIselect reagent, add 100 μL (1.0 concentration) to the sample, pipette to mix, and incubate at room temperature for 5 min; place the mixture on a magnetic rack until clear, and discard the supernatant; add 200 μL of 80% ethanol for washing, let stand for 30 seconds and discard the ethanol, repeat washing twice to complete library preparation.

[0095] 2.4 Sequencing

[0096] The constructed library was subjected to high-throughput sequencing to obtain nucleic acid sequence information.

[0097] 2.5 Data Analysis

[0098] The sequencing data obtained in section 2.4 were compared and analyzed using 10× Genomics Cell Ranger software.

[0099] Experimental Example 1

[0100] The specificity and sensitivity of the probe library of this invention were detected using flow cytometry in situ hybridization.

[0101] To verify the probe's specificity, we hybridized an EBV-encoded probe with a non-EBV-infected SUBP15 cell line and detected the specific binding of the probe using fish-flow fluorescence in situ hybridization. The results are as follows: Figure 1 As shown in Figure A, except for EBNA2-1 and EBNA2-2 which showed some non-specific signals, the other probes all exhibited good specificity.

[0102] Furthermore, we used the EBV-free cell line SUBP15 as the control group and the EBV-infected cell line EBV-LCL as the experimental group. We simultaneously verified the specificity and sensitivity of the EBV probes through hybridization experiments using the EBER1 and EBER2 probes. The results are as follows: Figure 1 As shown in Figure B, significant hybridization signals were detected in the experimental group of the two probe groups, while almost no signal was detected in the control group. This further confirms the reliability of the probe library in distinguishing the EBV infection status of cells.

[0103] Experimental Example 2

[0104] The specificity and sensitivity of the probe library of this invention were verified using single-cell transcriptome sequencing technology.

[0105] To evaluate the specificity and sensitivity of the probe library of this invention, we selected two cell lines for single-cell transcriptome sequencing: the control group consisted of uninfected SUBP15 cells, and the experimental group consisted of EBV-LCL cells infected with EBV. The results are as follows: Figure 2 As shown in AD, cluster analysis of the two groups of cells revealed that the experimental cells and the EBV probe group almost completely overlapped, with an infection rate approaching 100%. In contrast, the EBV infection detection rate of the control group cells was less than 1%, indicating that the cells in this group were almost uninfected by EBV. This preliminarily confirms the effectiveness of the probe library in distinguishing between EBV-infected and uninfected cells.

[0106] To further verify the specificity and sensitivity of the probe library of this invention against different EBV target genes, we systematically analyzed and presented the expression of 17 target genes (including EBER1, EBER2, BARF0, LMP-1, LMP-2B, EBNA-1, EBNA-2, BHRF1, BNLF2A, BNLF2B, BZLF1, BRLF1, RPMS1, BALF1, BALF3, LF2, and BALF5) in the probe library. The results are as follows: Figure 2 As shown in E, each gene probe exhibits strong specificity, accurately identifying and capturing the transcripts of the corresponding target genes, further confirming the precision and reliability of the probe design at the molecular level.

[0107] Experimental Example 3

[0108] The specificity and sensitivity of the probes of this invention in disease models were verified using single-cell transcriptome sequencing technology.

[0109] 1. Clinical Samples

[0110] To further verify the specificity and sensitivity of the probe library of this invention in EBV-related diseases, and to clarify the cell tropism, replication characteristics, and regulatory mechanisms of EBV on host immune cell function in different disease states, we conducted studies on multiple groups of clinical samples. For example... Figure 3 As shown in Figure A, we collected data from 2 healthy individuals, 2 individuals with EBV viremia, and 6 individuals with EBV-infected hemophagocytic lymphohistiocytosis. + HLH), 2 cases of tumor-associated hemophagocytosis (Tum-EBV) + HLH), 4 cases of chronic active EBV infection (CAEBV), and 6 cases of non-EBV-infected hemophagocytic lymphohistiocytosis (EBV). - Peripheral blood samples from patients with HLH were used for CD45 sorting using magnetic beads. + Cells were used for single-cell transcriptome sequencing, and transcriptome maps of each sample were successfully obtained.

[0111] 2 Overall CD45 + EBV infection feature analysis of cell subsets

[0112] CD45 based on cell type-specific marker genes + Cellular data were systematically annotated. Results are as follows: Figure 3As shown in B and C, a total of 11 major cell populations were identified, including NK cells (NK), T cells (T), proliferative NK / T cells, B cells (B), plasma cells, pre-neutrophil, neutrophils, monocytes, dendritic cells (DC), mast cells, and megakaryocytes.

[0113] Further comparison of the proportion differences of these 11 cell subsets among different disease groups ( Figure 3 D), the results show that: at EBV + In the HLH group, NK cells, plasma cells, and neutrophil precursors were significantly increased, while the proportion of dendritic cells decreased; in the CAEBV group, B cells and mast cells were significantly increased; and in the EBV-viremia group, proliferating NK / T cells and neutrophil precursors were increased.

[0114] To elucidate the cell tropism and replication activity of EBV under different disease states, the infection and expression of the virus in various cell subsets were analyzed. Figure 3 EH). The results showed that in EBV + In HLH, EBV primarily infects NK cells, T cells, proliferating NK / T cells, neutrophil precursors, and plasma cells, with an infection rate exceeding 40%. It exhibits active replication in NK cells, T cells, and proliferating NK / T cells. In CAEBV, infection is mainly concentrated in NK cells, T cells, B cells, monocytes, and dendritic cells, with T cells and proliferating NK / T cells showing particularly active viral replication. In EBV-viremia, EBV primarily infects B cells and plasma cells, exhibiting strong replication activity in these cell types. These results systematically reveal the differences in EBV-infected cell subsets and the heterogeneity of their replication characteristics under different clinical disease backgrounds, providing important cellular and molecular-level evidence for validating the specificity and sensitivity of probes.

[0115] 3. In-depth analysis of NK cell subsets

[0116] Given the high EBV infection rate in NK cells, we hypothesize that EBV infection of NK cells may be a key factor contributing to the severe clinical course of EBV-HLH. Therefore, it is particularly necessary to investigate the functional mechanisms of NK cell subsets in the context of EBV infection. We conducted in-depth single-cell transcriptome analysis of the NK cell population (excluding NKT cells), and re-clustered them using an unsupervised clustering algorithm (…). Figure 4(A, B) NK cells were divided into five different subsets, named C0-GZMK-NK, C1-PRSS23-NK, C2-AREG-NK, C3-PTGER3-NK and C4-TCF7-NK respectively.

[0117] Compare the differences in the proportion of NK cell subsets among different disease groups ( Figure 4 C) It was discovered that C0-GZMK-NK is EBV + The HLH group is a characteristic population, and EBV mainly infects GZMK. + NK cells; C2-AREG-NK is EBV + HLH, Tum-EBV + HLH and EBV - The three hemophagocytic disorders of HLH share a common subgroup; in addition, C3-PTGER3-NK is mainly composed of HLH12 samples, which is an independent outlier.

[0118] Subsequently, we performed differential gene expression (DGE) analysis on the C0-GZMK-NK population. Volcano plot results showed that C0-GZMK-NK exhibited coordinated upregulation of genes associated with antiviral and inflammatory responses (such as GZMK, EBER1, GBP1, CCR5, and CD74), while cytotoxicity-related genes (including PRF1, KLRK1, KLRF1, and FCGR3A) were downregulated. Figure 4 (D) This dual “activation-depletion” transcriptomic profile indicates a dysregulation of functional states, characterized by preserved antiviral signaling and suppressed cytotoxic potential, which may underlie impaired viral clearance in EBV+HLH disease. Pathway enrichment analysis further revealed significant enrichment of this subset in JAK-STAT signaling, NOD-like receptor pathways, antigen processing and presentation, and necroptosis. Notably, a strong positive correlation (r > 0.5) was observed between EBER2 and GZMK expression in EBV-infected NK cells, suggesting potential co-regulation or functional interaction (Figure 4E).

[0119] To further elucidate the impact of EBV infection on the functional status of NK cells, we performed differentially expressed genes (DEG) analysis between EBV⁺ and EBV⁻ NK cells. As shown in Figures G and H, EBV infection drives extensive functional reprogramming in NK cells, characterized by upregulation of antigen-presenting mechanisms (CD74), cell lysis mediators (GZMK, GZMH), exhaustion markers (RGS1, MAP4K1), apoptosis regulators (BAX, S100A9), JAK-STAT components (JAK3, JAK2, STAT1), and interferon-stimulated genes (NLRC5, GBP5, TRIM22), while downregulation of genes crucial for NK cell activation and cytotoxicity (KLRB1, KLRF1, KLRX1). Gene correlation analysis showed that in EBV-infected NK cells, EBER2 expression was significantly positively correlated with GZMK expression (correlation coefficient > 0.5). Figure 4 F) suggests that the two may be closely related in terms of function or regulation.

[0120] Analysis of EBV infection and expression patterns in NK cell subsets ( Figure 4 G) indicates that EBV mainly infects the CO-GZMK-NK subgroup, suggesting that this subgroup has a particular susceptibility to EBV.

[0121] For EBV positive (EBV) + ) and EBV negative (EBV) - DEG analysis was performed on NK cells, and the results were as follows: Figure 4 H) shows that in EBV + In NK cells, 295 genes were significantly upregulated, mainly including: antigen-presenting related genes (such as CD74, which is associated with MHC class II molecule assembly and inflammatory signaling); cytotoxic effector molecules (such as GZMK and GZMH); T / NK cell exhaustion markers (such as RGS1 and MAP4K1); apoptosis-related genes (such as BAX and S100A9); JAK-STAT signaling pathway members (such as JAK3, JAK2, and STAT1); and interferon-stimulated genes (such as NLRC5, GBP5, and TRIM22). Conversely, 413 genes were upregulated in EBV cells. + The expression of these genes was significantly downregulated in NK cells, mainly in genes related to NK cell activation recognition and cytotoxicity (KLRB1, KLRF1, KLRX1, etc.).

[0122] To systematically elucidate the functional significance of differentially expressed genes, GO functional annotation and KEGG pathway enrichment analysis were performed on the upregulated and downregulated genes, respectively. The results ( Figure 4(I) The results showed that upregulated genes were significantly enriched in interferon response, cytokine-mediated signaling pathways, EBV infection-related pathways, and NOD-like receptor signaling pathways, suggesting that EBV infection may drive NK cells into an antiviral response and inflammatory activation state; while downregulated genes were mainly enriched in molecular transduction activity and phagocytosis pathways, reflecting that some basic immune functions of NK cells may be suppressed after EBV infection. Further gene set enrichment analysis (GSEA) was performed... Figure 4 J) found that CD74 was significantly enriched in multiple key immune and inflammation-related pathways, suggesting that it may play an important role in the regulation of NK cell immunity associated with EBV infection.

[0123] 4 CD8 + In-depth analysis of T cell subsets

[0124] For CD8 + Single-cell transcriptome systematic analysis was performed on the T cell population (excluding NKT cells), and unsupervised cluster analysis was conducted. Figure 5 A, B), CD8 + T cells are divided into nine different subsets: C0-CCR7. + Tn-CD8, C1-GNLY + Teff-CD8, C2-NLRC5 + Tsen-CD8, C3-RGS1 + Tem-CD8, C4-CX3CR1 + Teff-CD8, C5-KLRB1 + MAIT-CD8, C6-KLRF1 + NKT-CD8, C7-MT2A + Tem-CD8 and C8-TCF7 + Tcm-CD8.

[0125] Comparing these 9 CD8 groups across different disease groups + Differences in the proportion of T cell subsets ( Figure 5 C) It was found that C2-NLRC5 + Tsen-CD8 is EBV + Characteristic subgroup of HLH group; C3-RGS1 + Tem-CD8 is EBV. - HLH and Tum-EBV + Common to the HLH disease group.

[0126] Figure 5 Systems D and E demonstrate CD8 +The high heterogeneity of T cells in healthy and disease states, based on differences in gene expression profiles, allows for the clear differentiation of T cell subsets with different differentiation states (e.g., naive, memory, effector) and functional characteristics (e.g., cytotoxic, exhausted, senescent). Compared to healthy controls, hemophagocytic patients showed a significant decrease in the proportion of effector T cells and NKT cells, while effector and memory T cells were significantly increased; the proportion of naive T cells showed no statistically significant difference among groups. Regarding functional status, the CD8.C2 subset exhibited active viral replication and showed senescent characteristics. EBV + The characteristic subset of HLH, CD8.C7, is in an activated inflammatory state; EBV - HLH and Tum-EBV + The CD8.C3 subset, a common feature of HLH, is mainly characterized by functional exhaustion and immune dysregulation.

[0127] EBV + With EBV - CD8 + DEG analysis between T cells ( Figure 5 F) shows that in EBV + CD8 + In T cells, the expression of 449 genes was significantly upregulated, mainly including plasma cell / immunoglobulin-related genes, cytotoxic effector molecules, and genes related to signal regulation and immune activation; conversely, the expression of 274 genes was significantly downregulated, involving cytokines and signaling pathway molecules, T cell receptor-related components, and immune checkpoint molecules. These differential expression patterns suggest that EBV infection may significantly affect CD8. + T cell functional differentiation and immune regulation status.

[0128] To further elucidate the functional significance of these differentially expressed genes, GO functional annotation and KEGG pathway enrichment analysis were performed on upregulated and downregulated genes, respectively. GO functional annotation ( Figure 5 G) showed that the upregulated genes were significantly enriched in biological processes such as immune response activity, leukocyte-mediated cytotoxicity, and cytokine receptor activity, suggesting that EBV infection may enhance CD8. + T cell immune effector function; while downregulated genes were mainly enriched in RNA metabolism, RNA splicing and other related pathways, reflecting that their basic cellular functions may be suppressed. KEGG pathway enrichment analysis ( Figure 5 H) showed that differentially expressed genes are mainly involved in signal transduction and immune regulation pathways such as NK cell-mediated cytotoxicity, JAK-STAT signaling pathway, and cytokine-cytokine receptor interaction.

[0129] Gene set enrichment analysis (GSEA) Figure 5I) It was found that CD74 was significantly enriched in multiple key immune and inflammation-related pathways, suggesting that it may play an important role in the regulation of T-cell immunity related to EBV infection.

[0130] 5. In-depth analysis of proliferating NK / T cell subsets

[0131] Previous studies have independently demonstrated the association between aberrant activation of proliferating NK / T cells and EBV⁺ HLH. Our current study shows that over 40% of proliferating NK / T cells exhibit direct EBV infection, indicating that this infection is a key pathogenic mechanism. Based on these findings, a single-cell transcriptome systematization of the proliferating NK / T cell population was performed, using unsupervised clustering analysis (…). Figure 6 A) This cell population was divided into five subpopulations with unique transcriptional characteristics, namely: C0-PLK1 + pro.T, C1-PNN + pro.T, C2-MXD4 + pro.T, C3-IGFBP7 + pro.NK and C4-MDM2 + The annotation of lineage-specific marker genes further confirmed that this population mainly originates from two major immune cell lineages: proliferating T cells and proliferating NK cells. Figure 6 B).

[0132] Spatial visualization analysis of cell infection state ( Figure 6 C) shows that EBV primarily infects C4-MDM2. + pro.T, C1-PNN + pro.T and C3-IGFBP7 + The three subgroups pro.NK suggest that these subgroups may have a higher susceptibility to EBV or provide a more active microenvironment for viral replication.

[0133] The composition and functional changes of various proliferative subsets were compared under different disease states, and the results are as follows: Figure 6 As shown in D and E, the proportions of C1, C3, and C4 cell subsets were significantly increased in EBV-HLH patients, suggesting they may play an important role in the pathogenesis of the disease. Functional enrichment analysis indicated that the C1 subset (PNN) was significantly elevated. + The KEGG pathway in pro.T cells is significantly enriched in the T cell receptor signaling pathway and the Th1 / Th2 cell differentiation pathway, suggesting that this population is in a critical stage of T cell activation and functional differentiation. The C3 subset (IGFBP7) is also highly enriched. +pro.NK cells were significantly enriched in natural killer cell-mediated cytotoxicity and cytoplasmic DNA sensing pathways, demonstrating their effector potential in antiviral innate immunity. The C4 subset (MDM2) was also significantly enriched. + The pro.T. subset was primarily enriched in the cell cycle and DNA replication pathways, suggesting its potential direct involvement in EBV-driven aberrant lymphocyte proliferation. In summary, these results outline a collaborative immunopathogenic network in EBV-HLH—the C4 subset promotes aberrant clonal expansion by disrupting cell cycle control; and the C1 and C3 subsets contribute to adaptive and innate immune dysregulation, respectively.

[0134] To gain a deeper understanding of the synergistic mechanism between EBV-infected and uninfected proliferating NK / T cells, we performed differential gene expression analysis on EBV-infected cells. + With EBV - DEG analysis of proliferating NK / T cells ( Figure 6 F) shows that in EBV + In cells, the expression of multiple function-related genes was significantly altered. Upregulated genes primarily included cytotoxic effector molecules (GNLY, GZMA, GZMB, PRF1), antigen-presenting related molecules (CD74), pro-apoptotic factors (BAX), and cell cycle regulatory proteins (MDM2). Downregulated genes primarily included core components of T cell receptors (TRAC, TRBC2). This expression pattern suggests that EBV infection may simultaneously induce enhanced cytotoxicity, activated antigen presentation, and initiated apoptosis signaling, indicating that infected cells are in a highly activated effector state. However, the downregulation of T cell receptor signaling-related genes may weaken antigen-specific immune recognition, leading to impaired T cell functional integrity. This "hyper-effects but weakened recognition signaling" immune phenotype may partially explain the coexistence of strong inflammatory responses and low viral clearance efficiency in EBV-related diseases. Furthermore, the upregulation of MDM2 further suggests that infection may promote cell survival and proliferation by inhibiting the p53 pathway, thereby maintaining persistent viral infection in the infection microenvironment.

[0135] Analysis of GO function annotations ( Figure 6 (G) showed that upregulated genes were significantly enriched in biological processes such as lectin response, NK cell-mediated cytotoxicity, and fatty acid metabolism; while downregulated genes were mainly involved in basic cellular functions such as RNA metabolism, chromatin remodeling, and RNA splicing. KEGG pathway analysis ( Figure 6 Further analysis revealed that differentially expressed genes were significantly enriched in key immune and proliferative regulatory pathways, including interferon-γ response, NK cell-mediated cytotoxicity, and cell cycle regulation. GSEA results ( Figure 6I) The results showed that CD74 was significantly enriched in multiple immune and inflammation-related pathways, suggesting that this molecule may play a key role in the immune regulatory network of proliferating NK / T cells infected with EBV, and may serve as an important functional hub connecting antigen presentation and inflammatory signal transduction.

[0136] 6. In-depth analysis of monocyte subsets

[0137] The overall distribution of monocytes was visualized and analyzed using UMAP dimensionality reduction. The results are as follows: Figure 7 As shown in Figure A, based on the expression profiles of classic surface marker genes, monocytes can be clearly annotated into three major subtypes: CD14, CD15, CD16, CD17, CD18, CD19 ... + Classical monocytes (CD14mono), CD14 + CD16 + Intermediate monocytes (CD14 / 16mono), and CD16 + Non-classical monocytes (CD16mono). Further, based on the average expression levels of characteristic genes in each subpopulation, monocytes were divided into nine subpopulations with distinct transcriptional functions. Figure 7 B and C) are CD14.C0 (GNAQ) + Mono), CD14.C1 (LYZ) + Mono), CD14.CD16.C2 (CALHM6 + Mono), CD14.C3 (ALOX5AP) + Mono), CD14.C4 (RGS2) + Mono), CD14.C5 (DDIT4) + Mono), CD14.C6 (STAB1) + Mono), CD14.C7 (CCL3) + Mono), CD16.C8 (NR4A1) + Mono).

[0138] Analysis of differences in the proportion of subgroups among different disease groups ( Figure 7 D) shows that CD14.C0 (GNAQ) + Mono (mono) is a characteristic group of the EBV-HLH group, and EBV mainly infects GNAQ. + Mono cells. CD14.C5 (DDIT4) + Mono is a characteristic population of EBV-HLH; CD14.CD16.C2 (CALHM6) + Mono), CD14.C7 (CCL3) + Mono), CD14.C3 (ALOX5AP)+ Mono is a population of mononuclear cells shared by the three groups of hemophagocytic cells.

[0139] Functional enrichment analysis ( Figure 7 E, F) show that the characteristic subgroup CD14.C0 (GNAQ) + The KEGG pathway of Mono was significantly enriched in the TNF signaling pathway, EBV infection pathway, JAK-STAT signaling pathway, NOD-like receptor signaling pathway, apoptosis signaling pathway, and NF-κB signaling pathway, suggesting that this subgroup may play a core role in EBV infection-related inflammation and immune regulation by regulating the above-mentioned core pathways.

[0140] For CD14.C0 (GNAQ) + EBV in the Mono subgroup + With EBV - DEG analysis of cells ( Figure 7 G) shows that in EBV + In cells, the expression of multiple function-related genes was significantly altered. Among them, the genes with upregulated expression mainly included EBER1, GNAQ, CXCL8, MRC1, and SLC44A1; the genes with downregulated expression mainly included ZFP36L1, HSPA6, AQP9, SERPINA1, PTAFR, and CSF3R.

[0141] Notably, in EBV-infected monocytes, EBER1 expression was significantly positively correlated with GNAQ expression (correlation coefficient > 0.3). Figure 7 H), suggesting that the two may have functional associations or joint regulatory mechanisms in virus-host interactions.

[0142] Further GO functional annotation analysis (Figure I) revealed that upregulated genes were significantly enriched in biological processes such as hematopoietic stem cell lineages, while downregulated genes were mainly involved in the Toll-like receptor signaling pathway, suggesting that EBV infection may affect the differentiation, maturation, and innate immune recognition functions of monocytes by regulating the above pathways.

[0143] In summary, the probe library of the present invention has the following beneficial effects:

[0144] 1. High sensitivity and specificity: Through targeted probe design, this invention can directly enrich low-abundance EBV transcripts, effectively solving the problem of missed detection of non-polyA RNA and low-expression RNA in traditional 3' scRNA-seq technology. In particular, it can effectively detect key oncogenes such as LMP1 and LMP2, providing reliable technical support for early identification of EBV infection and precise capture of oncogene-related genes.

[0145] 2. Possesses single-cell resolution and high-throughput analysis capabilities: The probe library of this invention can accurately distinguish infected and uninfected cells at the single-cell level, and can perform fine-grained grouping of infected cells, identifying cell subpopulations in different latent phases or lysis phases. This breaks through the limitations of traditional technologies that cannot analyze EBV infection heterogeneity at the single-cell level, and can reveal unprecedented cell heterogeneity.

[0146] 3. Panoramic Observation: The probe of this invention can simultaneously acquire the whole transcriptome information of host cells while accurately detecting EBV viral transcripts and clarifying the viral infection status. This allows for in-depth analysis of biological processes such as immune response, signaling pathway activation, and cell cycle of host cells under the precise knowledge of the viral status, directly establishing the causal relationship between the virus and the host. This provides an efficient research tool for elucidating core scientific questions such as the interaction mechanism between EBV and the host and the mechanism of viral carcinogenesis.

[0147] 4. High compatibility and flexibility: This invention is based on the mature and stable 10× Flex platform. The technology is mature and stable, and it can be used in combination with probe panels of other species or genes, with a wide range of applications.

[0148] 5. Powerful application value: It provides a powerful tool for basic research on EBV-related diseases, biomarker discovery, and drug target screening.

[0149] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An oligonucleotide probe library for targeted capture of EBV-encoding genes for single-cell transcriptome sequencing, characterized in that, The probe library includes EBV latency-related genes (EBNA1, EBNA2, LMP1, LMP2B), cleavage-related genes (BARF0, LF2, BNL2A, BNL2B, BZLF1, BRLF1, BHRF1, RPMS1, BALF3, BALF5, BALF1), and non-coding RNAs (EBER1, EBER2); the probe library includes all probes with nucleotide sequences as shown in SEQ ID NO. 1-84.

2. A method for targeted capture of EBV-encoding genes based on single-cell transcriptome sequencing, characterized in that, Includes the following steps: S1. Sample preparation and fixation: Obtain the cell or tissue sample to be tested, prepare a single-cell suspension, add fixative and fix at 4℃ for 16-24 h; S2. Probe hybridization: The probe library described in claim 1 is added to the hybridization mixture and mixed with the fixed sample. The mixture is then incubated in a PCR instrument at 42°C for 16-24 h to allow the probes to bind to viral RNA. After hybridization, unbound probes are removed with washing buffer. S3. Single-cell isolation and labeling: The hybridized sample is encapsulated with gel beads bearing barcodes using microfluidic technology to form gel beads (GEMs), ensuring that each GEM contains one cell and one barcode-bearing gel bead, thereby achieving single-cell isolation and labeling; then, a reverse transcription reaction is performed within the GEM to generate cDNA carrying the cell barcode and unique molecular identifier (UMI); S4. Library construction: The cDNA product in the GEM is recovered, pre-amplified and modified to construct a standardized DNA library suitable for sequencing; S5. Sequencing: Perform high-throughput sequencing on the library constructed in step S5 to obtain nucleic acid sequence information; S6. Data Analysis: The sequencing data obtained in step S6 were compared and analyzed using 10× Genomics Cell Ranger software.

3. The use of the probe library according to claim 1 in the preparation of reagents or kits for targeted capture of EBV encoding genes.

4. The application according to claim 3, characterized in that, The probe library can accurately distinguish between EBV-infected and non-infected cells at the single-cell level, and further refine the grouping of infected cells to identify cell subpopulations in different latent or lytic phases.

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