Tuberculosis antigen specific host biomarker and kit for detecting tuberculous pleural effusion

Abstract

The invention relates to a tuberculosis antigen-specific host biomarker for diagnosing tuberculous pleural effusion and a kit, and belongs to the technical field of biological medicines. The host biomarker provided by the invention comprises the following components: IFN (interferon) gamma, IL-2 (interleukin-2), IL-12RB2 (interleukin-12R < 2 >), GZMB (Growth Zehnder Microorganism Blanket), IL-3 (interleukin-3), CXCL10 (C X-ray cell line 10), IL-12B (interleukin-12B), IL-18RAP ( According to the present invention, the mycobacterium tuberculosis RD1 region antigen or peptide fragment and the mycobacterium tuberculosis RD2 region antigen or peptide fragment are jointly used as the antigen irritants to stimulate the pleural effusion sample to be detected, and then the expression change of the host biomarker is detected so as to effectively identify and diagnose the tuberculous pleural effusion. By combining tuberculosis specific antigen stimulation and local infection microenvironment transcriptome analysis, the non-specificity defect of an existing host biomarker is overcome, and the host biomarker has high sensitivity and specificity in diagnosis of tuberculous pleural effusion.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to a tuberculosis antigen-specific host biomarker and kit for diagnosing tuberculous pleural effusion. Background Technology

[0002] Tuberculous pleurisy (TP) is caused by Mycobacterium tuberculosis (Mycobacterium tuberculosis). Mycobacterium tuberculosis , M.tb Tuberculous pleural effusion (TPE) is an inflammatory disease of the pleura caused by infection, with the typical clinicopathological change being pleural effusion. In countries with a high tuberculosis burden, TPE is one of the most common extrapulmonary tuberculosis (EPTB). The clinical manifestations of TPE are often nonspecific, thus relying on laboratory tests for PE to confirm the diagnosis and to differentiate it from other bacterial infections or malignant PE. However, due to the lack of precise biomarkers, TPE is easily missed, misdiagnosed, or diagnosed late. Therefore, timely and accurate diagnosis of TPE in clinical practice remains a significant challenge.

[0003] PE is a commonly used sample for diagnosing TP. However, in TPE... M.tb The bacterial load is usually extremely low; therefore, direct detection of bacteria in the sample is not possible. M.tb Or its components and other pathogen detection methods have extremely low sensitivity, such as smear microscopy and M.tb Culture or rapid detection M.tb Different studies have reported diagnostic sensitivities of 5%-22% and 14%-50% for DNA Xpert MTB / RIF and Xpert Ultra, respectively. Pleural biopsy or medical thoracoscopy combined with histopathological examination can increase the etiological diagnostic accuracy to 39%-76%, but its invasiveness limits its widespread clinical application. Biochemical markers such as adenosine deaminase (ADA) detection have a sensitivity of 92%-95%, but specificity is reduced due to factors such as inflammation.

[0004] The World Health Organization (WHO) recommends the Interferon-gamma release assay (IGRA), and in particular, the commercially available Tuberculous Infection of T Cells Spot Test (T-SPOT.TB) kit is increasingly being used for the diagnosis of EPTB. Due to the homing effect of specific T lymphocytes produced after tuberculous infection, these T cells present in TPE can respond to EPTB in vitro. M.tb The recall response to specific antigens is significantly stronger than that of T cells in the systemic circulation; therefore, IGRA detection at the site of infection may have higher diagnostic value. However, a meta-analysis showed that IGRA still has a false negative rate of approximately 20% in diagnosing pulmonary tuberculosis. Multiple studies have reported that the sensitivity of T-SPOT.TB in diagnosing TPE fluctuates significantly, ranging from 39% to 95%. This insufficient sensitivity directly increases the risk of misdiagnosis and missed diagnosis. Undiagnosed patients, due to delayed treatment, not only face a higher risk of death but may also become sources of transmission. Therefore, there is an urgent need to develop new diagnostic technologies with higher sensitivity and specificity, especially establishing detection methods that can effectively reduce false negative results, which is crucial for improving the diagnostic rate of TPE and effectively controlling the spread of the disease. Given the uniqueness of TPE samples, integration... M.tb Detection methods for pathogen-specific and host-specific biomarkers hold promise for addressing the shortcomings in sensitivity and specificity of the aforementioned diagnostic techniques. While current IGRA technology meets these criteria, further refinement is needed to incorporate a broader range of biomarkers. M.tb Specific antigens and host biomarkers other than interferon-gamma (IFNγ) are used to improve diagnostic accuracy. The core stimulating antigen of T-SPOT.TB comes from... M.tb A mixed peptide pool of T cell epitopes, including the 6 kDa early secreted antigenic target (ESAT6) and culture filtrate protein 10 (CFP10). These antigens are composed of... M.tbThe RD2 region is encoded by a gene encoding the Region of Differences 1 (RD1), which is absent in the Bacillus Calmette-Guérin (BCG) genome. Therefore, stimulating the antigens ESAT6 or CFP10 minimizes non-specific interference from BCG vaccination. However, the diagnostic sensitivity of this detection technique is limited by the ability of T cells to recognize antigenic epitopes. The RD2 region is also absent in widely used BCG substrains such as the BCG Pasteur strain and the BCG Danish strain. Proteins encoded by the RD2 region include Culturefiltrate protein 21 (CFP21) and Major protein of tuberculosis 64. M.tb 64, MPT64), exhibiting strong immunogenicity in the host immune response. Previously, our team (Patent Application No.: 202310704861.7, Patent Title: A Highly Specific Diagnostic Reagent and Kit for Mycobacterium tuberculosis Infection) developed a novel composition and its preparation method for tuberculosis diagnosis, comprising a fusion protein rEC (Recombinant ESAT6-CFP10, rEC) composed of the RD1 region-encoded proteins ESAT6 and CFP10, and a fusion protein rCM (Recombinant CFP21-MPT64, rCM) composed of the RD2 region-encoded proteins CFP21 and MPT64, used as antigenic stimuli. The IGRA technology established by combining RD1 and RD2 antigens significantly improved the sensitivity for diagnosing tuberculosis infection compared to IGRA technology established solely by the RD1 antigen or the commercially available T-SPOT.TB. In particular, inconsistencies were found in the IGRA detection results of the RD2-region rCM fusion protein and the RD1-region-based rEC fusion protein, as well as the detection results of T-SPOT.TB. These studies strongly suggest the need for more complex fusion methods. M.tb Specific antigens or their epitopes can increase the chances of being infected. M.tb The increased likelihood of T cells recognizing infected individuals enhances the sensitivity of the diagnostic test without compromising its specificity. Nevertheless, IGRA diagnosis takes at least two days, requiring patients to revisit the laboratory, necessitating the exploration of more sensitive, specific, and rapid diagnostic techniques.

[0005] Currently, a large amount of research focuses on developing diagnostic methods for tuberculosis infection based on host biomarkers. M.tbComparing the transcriptome, proteome or metabolome of infected and uninfected host peripheral blood samples, for example, comparing the transcriptome to find that part of the gene expression profile of infected host has changed and exploring these transcriptome markers for distinguishing tuberculosis from other diseases. However, most of these transcriptome markers are inflammatory markers in response to external stimuli, rather than specific pathogen infection specific markers, so inflammation or other pathogen infection may also cause these host markers to be produced, resulting in false positives in diagnosis. The biomarkers discovered by different omics strategies and techniques based on such host models also have the same shortcomings. In addition, no study has explored tuberculosis-specific transcriptome markers in the local immune microenvironment of TPE. Therefore, in order to overcome the non-specificity of existing host markers and to explore host markers in the PE sample of TPE patients, which has more diagnostic potential in the local microenvironment, and to broaden the T cell antigen epitope spectrum and enhance the recognition ability of T cells in tuberculosis-infected populations, the project stimulates pleural fluid mononuclear cells (PFMCs) with RD1 (rEC) and RD2 (rCM) as antigen stimulators, and analyzes the whole transcriptome of PFMCs before and after stimulation, aiming to screen and identify host-specific transcriptome markers produced after specific antigen stimulation, which are different from host markers under non-stimulation or non-specific stimulation. On the basis of discovering these tuberculosis antigen-specific host biomarkers, a detection method based on reverse transcription quantitative polymerase chain reaction (RT-qPCR) is finally established to realize a more sensitive, specific, convenient and rapid new diagnostic technology for TPE. M.tb SUMMARY SUMMARY

[0006] The present application comprehensively applies the respective advantages of pathogen and host biomarkers, integrates M.tb specific multi-antigen and the immune memory response characteristics of host T cells in the local infection, and establishes a highly sensitive, specific and rapid diagnostic technology for tuberculous pleural effusion. RD1 region antigens or any peptide segment of RD1 region encoded antigens, and RD2 region encoded antigens or any peptide segment of RD2 region encoded antigens are used as antigen stimulators, and the whole transcriptome sequencing of PFMCs in the local infection site is combined to screen and identify tuberculosis antigen-specific host transcriptome markers, so as to improve the diagnostic sensitivity and at the same time meet the high specificity of host biomarkers.

[0007] According to a first aspect of the present application, there is provided a host biomarker specific to a tuberculosis antigen for detecting tuberculous pleural effusion, the biomarker being at least one of the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2; The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are shown in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 and SEQ ID NO: 10, respectively.

[0008] According to another aspect of the present application, there is provided a reverse transcription quantitative polymerase chain reaction detection kit for detecting tuberculous pleural effusion, comprising any antigen encoded by the RD1 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD1 region of Mycobacterium tuberculosis, and further comprising any antigen encoded by the RD2 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD2 region, the peptide segment being an effective T cell epitope of the antigen encoded by the corresponding region; Further comprising primers for detecting at least one of the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2; The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are shown in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 and SEQ ID NO: 10, respectively.

[0009] According to another aspect of the present application, there is provided an enzyme-linked immunospot detection kit for detecting tuberculous pleural effusion, comprising any antigen encoded by the RD1 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD1 region of Mycobacterium tuberculosis, and further comprising any antigen encoded by the RD2 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD2 region, the peptide segment being an effective T cell epitope of the antigen encoded by the corresponding region; Also included are solid phase carrier coated capture antibodies for specifically binding to the protein encoded by the gene, biotin-labeled detection antibodies capable of specifically binding to the protein encoded by the gene, streptavidin-enzyme complex, and enzyme substrate developing solution, wherein the gene is at least one of IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8, and HAVCR2. The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8, and HAVCR2 are shown in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, and SEQ ID NO: 10, respectively.

[0010] According to another aspect of the present application, the reverse transcription quantitative polymerase chain reaction detection kit is used for preparing a reagent for detecting tuberculous pleural effusion.

[0011] Preferably, the application is specifically: stimulating the pleural effusion or pleural effusion mononuclear cell PFMCs by an antigen stimulant, the antigen stimulant including RD1 region antigen or any peptide segment of the RD1 region encoded antigen, and also including RD2 region encoded antigen or any peptide segment of the RD2 region encoded antigen; extracting mRNA of the stimulated pleural effusion or extracting mRNA of the stimulated pleural effusion mononuclear cell PFMCs, and then using the primer to detect the mRNA of at least one of the genes produced after stimulation by the reverse transcription quantitative polymerase chain reaction detection kit, and determining that the sample is tuberculous pleural effusion.

[0012] According to another aspect of the present application, the enzyme-linked immunospot detection kit is used for preparing a reagent for detecting tuberculous pleural effusion.

[0013] Preferably, the application is specifically: stimulating the pleural effusion mononuclear cell PFMCs by an antigen stimulant, the antigen stimulant including RD1 region antigen or any peptide segment of the RD1 region encoded antigen, and also including RD2 region encoded antigen or any peptide segment of the RD2 region encoded antigen; and detecting the protein expressed by at least one of the genes produced by T cells in the stimulated PFMCs by the enzyme-linked immunospot detection kit, and determining that the sample is tuberculous pleural effusion.

[0014] Overall, compared with the prior art, the above technical solutions conceived by the present application mainly have the following technical advantages: (1) The present application first establishes M.tb The antigen-specific stimulation combines with the local microenvironment transcriptome mechanism to screen and identify host biomarkers specific to tuberculosis antigens. The prior art relies on unstimulated or non-specific inflammatory markers, which is difficult to distinguish between tuberculosis and other pathogen-induced inflammatory diseases. The present application stimulates pleural effusion mononuclear cells by using RD1 region antigens or any peptide segment of RD1 region encoded antigens, and RD2 region encoded antigens or any peptide segment of RD2 region encoded antigens as antigen stimulators, to reveal the host T cell immune memory characteristics induced by tuberculosis antigens; at the same time, focusing on the local immune microenvironment of tuberculosis infection, the high-specificity host biomarkers related to T cell homing recall response are screened by amplifying the signal through antigen stimulation, and the non-specific interference of host markers is reduced.

[0015] (2) Although the existing RD1 region antigens ESAT6 and CFP10 can avoid the interference of BCG, the epitope coverage is limited. The present application innovatively uses RD1 and RD2 region specific antigens, which can cover a wider range of tuberculosis specific T cell epitopes, stimulate the generation of transcriptome markers, completely avoid the cross reaction of BCG, maintain high specificity, and significantly improve the detection sensitivity. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is the flowchart of the screening and verification of the TPE diagnostic biomarkers in the present application; wherein: A is the research design process, the PFMCs of TPE and non-tuberculous pleural effusion (Non-tuberculous pleural effusion, Non-TPE) patients are stimulated by tuberculosis specific antigens, and then the transcriptome sequencing is performed; B is the core gene identification process, the core genes of TPE are identified by differential expression gene analysis combined with protein interaction network analysis; C is the diagnostic value verification process, the host biomarkers that can distinguish TPE and Non-TPE are identified by ROC curve analysis.

[0017] Figure 2 It is the differential expression gene of the present application under different tuberculosis infection states and antigen specificity; wherein: A is the number of differential expression genes of TPE group and Non-TPE group; B is the volcano plot of differential expression genes of RD1 and RD2 stimulated TPE group and Non-TPE group; C is the intersection of differential expression genes between TPE group and Non-TPE group, pink represents differential genes unique to TPE group, and blue represents differential genes overlapping with Non-TPE group.

[0018] Figure 3 It is the clustering analysis result of PFMCs differential expression genes stimulated by tuberculosis specific antigens in the present application.

[0019] Figure 4 This document presents the functional enrichment results of differentially expressed genes induced by RD1 and RD2 stimulation in this invention. Specifically: A represents the gene ontology (GO) functional enrichment analysis of the RD1-stimulated TPE group; B represents the Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of the RD1-stimulated TPE group; C represents the GO functional enrichment analysis of the RD2-stimulated TPE group; and D represents the KEGG pathway enrichment analysis of the RD2-stimulated TPE group. The bubble size represents the number of genes, the horizontal axis represents the gene ratio, and the color gradient represents the corrected gene ratio. p Value (Benjamini Hochberg method correction), functional pathway enrichment is based on |log2Fold Change|>1.5. p DEGs analysis using the <0.05 standard screening.

[0020] Figure 5 This invention presents the protein-protein interaction networks (PPI) analysis, functional enrichment of core genes, and heatmap analysis. Specifically: A represents the PPI network diagrams of the Top 25 hub genes in the TPE and Non-TPE groups, respectively stimulated by RD1 and RD2. The node size in the network diagram is positively correlated with the Maximum clique centrality (MCC) score. The color gradient represents the log2 Fold Change. The PPI network is based on |log2FoldChange|>1.5. p A) DEGs analysis using the <0.05 standard; B) GO and KEGG enrichment analysis results of DEGs-hub genes in the TPE and Non-TPE groups; C) Heatmap of DEGs-hub gene expression levels in the TPE and Non-TPE groups.

[0021] Figure 6This invention establishes the co-expression network for tuberculous pleural effusion and analyzes key modules; wherein: A is a heatmap showing the correlation between the co-expression modules of the TPE group and the Non-TPE group and the stimulation of tuberculosis-specific antigen; B is a scatter plot showing the correlation between module membership (MM) and gene significance (GS) of ME-4 module genes; C is the significant enrichment results of GO and KEGG of ME-4 module genes; D is a PPI network diagram of the Top 10 hub genes of the ME-4 module; E is a scatter plot showing the correlation between MM and GS values ​​of ME-8 module genes; F is the significant enrichment results of GO and KEGG of the ME-8 module; G is a PPI network diagram of the Top 15 hub genes of the ME-8 module.

[0022] Figure 7 This is a validation analysis of the diagnostic value of the core gene in tuberculous pleural effusion in this invention; wherein, A is a bar chart of the relative expression levels of the core gene in the TPE group stimulated by RD1 and RD2; B is a correlation analysis of the gene expression levels of the core gene in RNA-seq and RT-qPCR; C is a scatter plot and ROC curve of the relative expression levels of the core gene in the TPE group (n=10) and the Non-TPE group (n=7). Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] To improve the sensitivity and specificity of diagnosing tuberculous pleural effusion, this invention utilizes a highly specific diagnostic reagent from our team's previous research (patent application number: 202310704861.7, patent title: A Highly Specific Diagnostic Reagent and Kit for Mycobacterium tuberculosis Infection) as an antigenic stimulus. This reagent is a fusion protein rEC composed of ESAT6 and CFP10 encoded by the RD1 region, and a fusion protein rCM composed of CFP21 and MPT64 encoded by the RD2 region. The recombinant proteins RD1 (rEC) and RD2 (rCM) are used in combination as antigenic stimuli to stimulate PFMCs in patients with pleural effusion. Whole transcriptome sequencing is performed on PFMCs before and after tuberculosis-specific antigen stimulation. By combining the advantages of both pathogen and host biomarkers, characteristic host transcriptome biomarkers of patients with tuberculous pleural effusion are screened and identified.

[0025] Specifically, this application analyzes differentially expressed genes in clinically diagnosed tuberculous pleural effusion samples and non-tuberculous pleural effusion samples. For differentially expressed genes, functional enrichment analysis, weighted gene co-expression network analysis, and protein interaction network analysis are used to identify the host core gene set of TPE patients with RD1 (rEC) and RD2 (rCM) antigen heterogeneity. At the same time, it is compared with differentially expressed genes of Non-TPE patients to remove non-specific core genes and finally screen out a set of host transcriptome markers specific to tuberculosis antigen.

[0026] This invention provides a method for diagnosing pathogens M.tb The presence of these genes provides host biomarkers for tuberculosis. These biomarkers include the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8, and HAVCR2. The full names and base sequences of these 10 genes are provided by the NCBI (National Center for Biotechnology Information (nih.gov)) platform, as follows: IFNγ: Interferon gamma (SEQ ID NO. 1) (NCBI Registration No.: NM_000619.3) IL-2: Interleukin-2 (SEQ ID NO. 2) (NCBI Registration No.: NM_000586.4) IL-12RB2: Interleukin 12 receptor subunit beta 2 (SEQ ID NO. 3) (NCBI Registration No.: NM_001258214.1) GZMB: Granzyme B (SEQ ID NO. 4) (NCBI Registration No.: NM_001346011.2) IL-3: Interleukin-3 (SEQ ID NO. 5) (NCBI Registration No.: NM_000588.4) CXCL10: CXC motif chemokine ligand 10 (SEQ ID NO. 6) (NCBI Registration No.: NM_001565.4) IL-12B: Interleukin-12 subunit beta (SEQ ID NO. 7) (NCBI Registration No.: NM_002187.3) IL-18RAP: Interleukin 18 receptor accessory protein (SEQ ID NO. 8) (NCBI Registration No.: NM_001393486.1) TNFRSF8: TNF receptor superfamily member 8 (SEQ ID NO. 9) (NCBI Registry No.: NM_001243.5) HAVCR2: Hepatitis A virus cellular receptor 2 (SEQ ID NO. 10) (NCBI Registry No.: NM_032782.5) The biomarkers provided by this invention are a set of genes, including the aforementioned 10 genes. This gene set was obtained by stimulating clinically diagnosed tuberculous pleural effusion (PFMCs) in patients with tuberculous pleural effusion (TPE) with tuberculous-specific antigens RD1 (such as the fusion protein rEC composed of proteins ESAT-6 and CFP-10 encoded by the RD1 region) and RD2 (such as the fusion protein rCM composed of proteins CFP-21 and MPT-64 encoded by the RD2 region), followed by transcriptome sequencing, differentially expressed gene analysis, protein interaction network analysis, and weighted gene co-expression network analysis. These 10 genes can specifically distinguish between patients with tuberculous pleural effusion and those with non-tuberculous pleural effusion. Clinically, this facilitates faster and more accurate diagnosis of patients with tuberculous pleural effusion and holds promise for screening and diagnosing tuberculous pleural effusion and other tuberculosis diseases, providing strong technical support for tuberculosis epidemic control.

[0027] This invention provides a reagent for the preparation of diagnostic tuberculous pleural effusion using the above-mentioned biomarkers, and also for the preparation of... M.tb The application of products for other tuberculosis infections caused by infection, the biological samples to be tested undergo... M.tb After stimulation with specific antigen compositions RD1 (such as the fusion protein rEC composed of proteins ESAT-6 and CFP-10 encoded by the RD1 region) and RD2 (such as the fusion protein rCM composed of proteins CFP-21 and MPT-64 encoded by the RD2 region), detection was performed. M.tb Changes in the expression of the above-mentioned antigen-specific biomarkers.

[0028] The M.tb Specific antigen composition, comprising M.tb The antigens encoded by the RD1 region are Rv3871, Rv3872, Rv3873, CFP10 (Rv3874), ESAT6 (Rv3875), Rv3876, Rv3877, Rv3878, and Rv3879c. M.tbThe RD2 region encodes all antigens, namely Rv1978, Rv1979c, MPT64 (Rv1980c), Rv1981c, Rv1982c, Rv1982a, Rv1983, CFP21 (Rv1984c), Rv1985c, Rv1986, Rv1987, and Rv1988, as well as peptides of the antigens encoded by the aforementioned RD1 and RD2 regions. These peptides constitute the effective T-cell epitopes of the antigens encoded by these regions. The antigen composition can specifically induce changes in the expression of the host biomarkers, thereby recognizing... M.tb Infect.

[0029] Specifically, the reagent includes substances that detect one or more of the following (1) to (3): (1) IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 genes; (2) mRNA encoded by the genes of IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2; (3) Proteins encoded by the genes of IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2.

[0030] In some embodiments, the diagnostic product includes a diagnostic tool for tuberculous pleural effusion. Accordingly, the kit includes either an RT-qPCR assay or an ELISPOT assay.

[0031] In some embodiments, the Mycobacterium tuberculosis-specific antigen composition comprises any antigen encoded by the RD1 region of Mycobacterium tuberculosis or any peptide segment of an antigen encoded by the RD1 region, namely Rv3871, Rv3872, Rv3873, CFP10 (Rv3874), ESAT6 (Rv3875), Rv3876, Rv3877, Rv3878, and Rv3879c; and any antigen encoded by the RD2 region of Mycobacterium tuberculosis or any peptide segment of an antigen encoded by the RD2 region, namely Rv1978, Rv1979c, and MPT64. The peptides (Rv1980c), Rv1981c, Rv1982c, Rv1982a, Rv1983, CFP21 (Rv1984c), Rv1985c, Rv1986, Rv1987, and Rv1988 constitute effective T-cell epitopes encoding antigens in this region. The antigen composition can specifically induce changes in the expression of the host biomarkers to recognize Mycobacterium tuberculosis infection.

[0032] Example 1: Screening of tuberculosis antigen-specific host transcriptome biomarkers of the present invention 1.1 Case Collection This invention included transcriptome sequencing of 6 patients with pleural effusion, including 3 confirmed TPE patients (1 diagnosed according to the Microbiological Reference Standard (MRS) and 2 according to the Clinical Reference Standard (CRS); and 3 confirmed Non-TPE patients. Following the Chinese health industry standard "Diagnosis of Pulmonary Tuberculosis" (WS 288-2017), the inclusion criteria for volunteer cases involved in this invention were as follows, based on clinical and laboratory examination results: 1) Patients with tuberculous pleural effusion: (1) Etiological evidence: Acid-fast bacilli were detected or cultured in sputum, pleural effusion or pleural tissue specimens. M.tb Or a positive XpertMTB / RIF result; (2) Molecular pathological evidence: Mycobacterium tuberculosis-specific nucleic acid was detected in the biopsy tissue by molecular biological detection methods such as PCR, in situ hybridization or gene sequencing; (3) Clinical comprehensive diagnostic criteria: The imaging shows typical signs of pleural effusion and the pleural fluid is exudate, ADA is elevated, and the tuberculin skin test is moderate or strongly positive, the gamma-interferon release test, or any positive result of Mycobacterium tuberculosis antibody is positive.

[0033] (4) There is a positive response to anti-tuberculosis drug treatment, while other possible causes of pleural effusion are ruled out.

[0034] 2) Patients with non-tuberculous pleural effusion: (1) Inflammatory pleural effusion: Chest imaging shows foci of infection, and conventional antibiotic treatment is effective; (2) Malignant pleural effusion: cytological or histopathological evidence; (3) Transudative pleural effusion: meets the diagnostic criteria for congestive heart failure or cirrhosis.

[0035] Meeting any of the above criteria and possessing at least one of them M.tb Negative culture or negative Xpert MTB / RIF result.

[0036] 1.2 Preparation of sequencing samples 1.2.1 Separation of PFMCs: 1) Reagent preparation: RPMI l640 complete medium: Add FBS (inactivated at 56℃ for 30 min, filtered through a 0.22 μm filter, final concentration 10%) and penicillin-streptomycin solution (100×, final concentration 1%) to RPMI l640 medium and store at 4℃.

[0037] 2) Collection of pleural effusion specimens: Collect 20-30 mL of pleural effusion, transport at room temperature, store at 4℃ for a short period of time, and ensure aseptic conditions throughout the process.

[0038] 3) Density gradient centrifugation to separate PFMCs: After centrifuging pleural effusion at 800 g for 8 min at room temperature, discard the supernatant. Gently resuspend the precipitate in RPMI 1640 medium. Carefully add the cell suspension to the lymphocyte separation medium at a 1:1 ratio using a Pasteur pipette, being careful not to disrupt the liquid surface between the pleural effusion cell suspension and the separation medium. Mix the two and centrifuge at 800 g for 22 min at room temperature (increase speed 2, decrease speed 1). After centrifugation, three liquid layers are obtained. The cloud layer at the interface between RPMI 1640 medium and Ficoll separation medium contains the obtained PFMCs. Carefully aspirate the cells from the cloud layer and transfer them to a new centrifuge tube, being careful not to aspirate the Ficoll separation medium.

[0039] 4) Cell washing: Add 10-14 mL of RPMI l640 medium to a centrifuge tube to wash the cells. Invert the tube until the cell pellet is mixed. Centrifuge at 800 g for 10 min at room temperature (acceleration 6, deceleration 4). After centrifugation, discard the supernatant and resuspend the cells in 0.5-1 mL of RPMI l640 complete medium preheated at 37℃ to obtain PFMCs.

[0040] 5) Cell Counting: PFMC suspension was added to 0.08% trypan blue staining solution at a 1:1 ratio and thoroughly vortexed. Immediately, 10 μL of the mixture was added to a cell counter for counting. The viable cell rate and the number of cells per mL were calculated. PFMC working solutions were diluted to their final concentrations using RPMI 1640 complete medium according to cell viability for subsequent experiments.

[0041] 1.2.2 Antigen stimulation of PFMCs: Three culture wells were prepared for each sequencing sample: negative control wells (RPMI 1640 complete medium), RD1 (rEC) antigen stimulation wells, and RD2 (rCM) antigen stimulation wells. PFMCs were diluted to 2.5 × 10⁻⁶ in complete medium. 6 For each cell / mL cell suspension, 1 mL of the cell suspension is seeded into a 12-well culture plate pre-added with 500 μL of the corresponding stimulant. The stimulant is gently mixed with the cells, and the cell plate is incubated at 37°C in a 5% CO2 incubator for 18-22 h.

[0042] like Figure 1 As shown in A, in this embodiment of the invention, 3 TPEs and 3 Non-TPEs were selected. Each sequencing sample included a negative control, RD1 and RD2 antigen stimulation wells, for a total of 18 samples.

[0043] 1.2.3 Sample collection: On the second day, the cell culture medium was transferred to a 2 mL sterile enzyme-free EP tube and centrifuged at 1000 g for 5 min at room temperature. The supernatant was discarded. 1 mL of sterile PBS solution was added to the cell culture plate to wash the residual cells. The cells were then transferred to the EP tube again to wash the cells. The cells were centrifuged at 1000 g for 5 min at room temperature. The supernatant was discarded and the cell pellet was collected. 1 mL of Trizol lysis buffer was added to each tube and the cells were repeatedly pipetted to ensure complete lysis. The samples were sealed with sealing film and immediately transferred to a -80℃ freezer for storage. They were then transported to the sequencing company on dry ice for subsequent transcriptome sequencing experiments.

[0044] 1.3 cDNA library construction and transcriptome sequencing Eighteen samples that passed quality testing (using an Agilent 2100 Bioanalyzer) were used to construct cDNA libraries. After passing quality testing, the libraries were sequenced using Illumina NovaSeq 6000 paired-end sequencing (PE150 mode). The raw data were then subjected to Fastp quality control and compared with the human reference genome using HISAT2 (Hierarchical Indexing for Spliced ​​Alignment Transcript2).

[0045] 1.4 Screening of tuberculosis antigen-specific host transcriptome biomarkers 1.4.1 Differentially expressed gene analysis In this embodiment of the invention, the DESeq2 algorithm was used to screen differentially expressed genes (DEGs), with a significance threshold set as |log2Fold Change| ≥ 1.5 and p Value < 0.05. FoldChange is defined as the ratio of gene expression levels in the experimental group (RD1 / RD2) to the control group (Blank), reflecting the differences in gene expression between the groups before and after antigen stimulation. In this embodiment of the invention, volcano plots are drawn using the ggplot2 package to display the differentially expressed genes between the groups.

[0046] like Figure 2As shown in the embodiments of the present invention, RD1 stimulation of TPE patients induced 468 DEGs (199 upregulated, 269 downregulated), while RD2 stimulation produced 234 DEGs (125 upregulated, 109 downregulated). The volcano plot shows the distribution of these DEGs and marks differentially expressed genes in some high-fold expression regions. Meanwhile, Non-TPE patients also showed significant DEGs upon antigen stimulation (RD1: 181, RD2: 335). To further screen host biomarkers that can distinguish between TPE and Non-TPE patients, this study analyzed the overlap of DEGs between the TPE and Non-TPE groups. 298 DEGs in the RD1-stimulated TPE group and 120 DEGs in the RD2-stimulated group were TPE-specific genes. 72 differentially expressed genes were co-present in both antigen-stimulated TPE groups and did not show significant differences in the Non-TPE group, and can be considered as candidate biomarkers specific to tuberculosis.

[0047] 1.4.2 Cluster analysis of differentially expressed genes To systematically understand the effect of tuberculosis-specific antigen stimulation on the transcriptional regulation of PFMCs in patients with pleural effusion, this invention uses the K-means algorithm to analyze gene expression clustering among different groups, analyzes genes with similar expression patterns in different patient transcriptomes, visualizes gene expression profiles of each group using the R package ClusterGVis (v0.1.1), and displays changes in gene expression after Z-score normalization.

[0048] like Figure 3 As shown, RD1 and RD2 stimulation significantly altered the transcriptomic characteristics of PFMCs in the embodiments of the present invention. Notably, compared with Non-TPE, the antigen-specific expression genes of TPE patients were concentrated in the C7 module (n=198) (mean Z-score >1.0), which was significantly enriched in T cell activation regulation, JAK-STAT signaling pathway, and tuberculosis-related pathways.

[0049] 1.4.3 Functional and pathway enrichment analysis of differentially expressed genes To further analyze the host immune response characteristics induced by RD1 and RD2 stimulation, functional and pathway enrichment analyses were performed in this embodiment of the invention. GO is a database describing gene function, comprising three parts: biological process (BP); cell component (CC); and molecular function (MF). KEGG is a database integrating genomic, chemical, and systemic functional information. Functional and pathway enrichment of differentially expressed genes in the TPE group was performed using these two databases. Enrichment analyses of GO and KEGG were performed using clusterProfiler (3.8.1) software, and the results were corrected using the Benjamini Hochberg method. p Values ​​less than 0.05 are considered to be significantly enriched entries.

[0050] like Figure 4 As shown in Table 1, in the KEGG analysis of this embodiment of the invention, DEGs generated by RD1 stimulation in TPE patients were significantly enriched in biological processes such as immune response, leukocyte differentiation, T cell activation, and JAK-STAT cascade. Among them, IL-2, IFNγ, and IL-23A were the most frequently occurring genes in the enriched pathways. KEGG pathway analysis showed that RD1-induced DEGs mainly involve cytokine-receptor interactions, JAK-STAT signaling pathways, and Th17 / Th1 / Th2 cell differentiation pathways, with IL-2 and IFNγ being high-frequency enriched genes. Figure 4 As shown in Table 2, DEGs from TPE patients stimulated by RD2 were also enriched in T cell-related functions. In GO analysis, the main biological processes involved included signal receptor activity regulation, Th1 immune responses, and T cell proliferation regulation. Highly enriched genes included IL-23A, IL-2, and IFNγ. KEGG pathway enrichment mainly included cytokine-receptor interactions, the JAK-STAT signaling pathway, and Th17 / Th1 / Th2 cell differentiation. Highly enriched genes were IL-2, IFNγ, IL-23A, and IL-2RA, which is highly similar to the KEGG pathway enrichment results from RD1 stimulation. In summary, DEGs generated from TPE patients stimulated by both RD1 and RD2 were significantly enriched in T cell immune-related pathways, and the highly enriched genes IL-2, IFNγ, and IL-23A are key regulatory molecules for T cell effector functions. These pathway and gene characteristics are highly consistent with the known mechanisms of tuberculosis antigen-specific T cell memory responses, further confirming that the DEGs screened in this invention are T cell specific.

[0051] Table 1

[0052] Table 2

[0053] 1.4.4 Core gene screening based on protein-protein interaction networks PPIs, by constructing interactions between proteins, can further reveal the response mechanisms of proteins in diseases or different physiological states. A PPI network was constructed using the Search tool for thetrieval of interacting genes / proteins (STRING) to identify differentially expressed genes in the TPE and Non-TPE groups. For unannotated proteins, the target gene sequences were aligned with selected reference protein sequences using Diamond (0.9.14), and the interaction network was finally drawn using Cytoscape (3.10.3). The core genes of the TPE and Non-TPE groups were identified using the MCC algorithm of the CytoHubba plugin.

[0054] like Figure 1 B and Figure 5As shown, in this embodiment of the invention, the Top 25 core genes of each group were screened using the MCC algorithm, and 11 common core genes were found to be generated by RD1 and RD2 stimulation of the TPE group. To further determine whether the core genes of the TPE group represent a tuberculosis-specific response, this embodiment of the invention compared and analyzed the core gene set of the Non-TPE group. Six core genes in the Non-TPE group overlapped with those in the TPE group, indicating that these genes may be non-specific effects of antigen stimulation. Simultaneously, functional pathway enrichment was performed on the core genes of both groups. The TPE group was enriched with pathways such as STAT pathway regulation (GO: 0042509), lymphocyte clonal expansion (GO: 005067), and Th1 / Th17 cell differentiation (hsa04658, hsa04659), consistent with the characteristics of antigen-specific memory T cell responses. The Non-TPE group was enriched with pathways such as the regulation of innate immune responses (GO: 0045088) and lipopolysaccharide responses (GO: 0032496), consistent with the characteristics of primary immune responses dominated by innate immune pathways. By comparing the expression changes of core genes between the two groups, genes that showed significant changes after stimulation with tuberculosis-specific antigens in the Non-TPE group were removed. Finally, a set of tuberculosis-specific host biomarkers (DEGs-hub genes) was screened based on differential expression analysis. The hub genes shared by RD1 and RD2 were IFNγ, GZMB, IL-2RA, IL-12RB2, IL-10, CCL20, IL-2, SSTR2, and PTGER3. Hub genes in the RD1 group included TNF-α, CXCL10, IL-12B, IL-21, IL-3, CCL25, BDKRB1, and FOS. Hub genes in the RD2 group included IL-23A, IL-18RAP, EDN1, IL-20, TNFRSF8, PDGFA, COLEC12, and MARCO. Among these, BDKRB1, FOS, COLEC12, and MARCO were downregulated differentially expressed genes, while the rest were upregulated differentially expressed genes.

[0055] 1.4.5 Weighted Gene Co-expression Network Analysis To gain a more systematic understanding of the tuberculosis antigen-specific transcriptome characteristics of TPE patients, this study employed weighted gene co-expression network analysis (WGCNA). WGCNA is an analysis method that identifies the association between a disease or biological trait and gene expression. In this study, the WGCNA R package was used to construct and visualize co-expression networks based on Pearson analysis for samples from the TPE and Non-TPE groups. The screening criteria for key tuberculosis-specific modules were |correlation| ≥ 0.5 and... p<0.05. To identify core genes in key modules, Pearson was used to calculate the correlation between gene expression within a key module and the correlation between modules, i.e., module membership (MM), and the gene significance (GS) between gene expression levels and tuberculosis traits. Candidate core genes for key modules were selected based on |MM|>0.8 and |GS|>0.4. Further GO and KEGG functional annotations and PPI network construction were performed on the selected genes to accurately identify WGCNA-hub genes.

[0056] like Figure 6 As shown in the embodiment of the present invention, the module-phenotype association analysis showed that in TPE patients, the ME-4 module and the ME-8 module were strongly positively correlated with tuberculosis-specific antigen stimulation. These two modules were not positively correlated in Non-TPE patients, suggesting that these two modules are tuberculosis-specific.

[0057] The key module ME-4 contains 124 genes, with a high positive correlation between its MM and GS values. After screening for |MM|>0.8 and |GS|>0.4, 48 core genes were identified. This module is significantly enriched in amino acid metabolism-related pathways, including tRNA aminoacylation and cellular amino acid metabolism processes. KEGG pathway analysis showed that this module is significantly enriched in the aminoacyl-tRNA biosynthesis pathway. This suggests that TPE patients may support T cell expansion and effector function by enhancing amino acid metabolism. The Top 10 hub genes of the ME-4 PPI network are: AARS, MARS, IARS, CARS, SARS, NARS, TARS, EPRS, PSAT1, and CHAC1.

[0058] The ME-8 module (n=3103), which was significantly associated with the TPE trait, also showed a high correlation between its MM value and GS value. To ensure that genes simultaneously met the requirements of differential expression and network importance, this study also compared it with the previous differentially expressed gene set (|log2Fold Change|>1, ...). p Intersections of samples <0.05 yielded 36 core genes. GO functional enrichment analysis showed significant enrichment in the regulation of interferon-gamma production and CD4+. + This module is involved in immune response-related biological processes such as α-β T cell activation. KEGG pathway enrichment analysis revealed that this module is significantly associated with the JAK-STAT signaling pathway and the Th1 cell differentiation pathway. ME-8 module functional pathway enrichment results suggest that genes in this module are significantly associated with Th1-type immune responses and immune regulation. M.tbThe clearance is closely related. To identify the core genes of the ME-8 module, the Top 15 hub genes of the ME-8 PPI network are: TNF-α, IFNγ, GZMB, IL-2RA, IRF4, LAG3, LTA, TNFRSF8, TNFRSF9, HAVCR2, CCL4, FASLG, PRF1, IL-12RB2, and IL-18R1.

[0059] To further ensure the tuberculosis specificity of the core genes, the expression levels of the core genes of the ME-4 and ME-8 modules were compared between the TPE and Non-TPE groups. Genes that showed significant changes after stimulation with tuberculosis-specific antigens in the Non-TPE group were removed, resulting in the WGCNA-hub genes: TNF-α, IFNγ, GZMB, IL-2RA, TNFRSF8, IL-12RB2, PRF1, IRF4, IL-18R1, HAVCR2, CCL4, PSAT1, and CHAC1.

[0060] 1.4.6 Selection of Tuberculosis Antigen-Specific Host Biomarkers The tuberculosis antigen-specific host biomarkers in this embodiment of the invention include two core gene sets. The first is the core differentially expressed gene set (DEGs-hubgenes, n=25) generated by TPE patients stimulated by the previously analyzed tuberculosis-specific antigens RD1 and RD2. Among these, RD1 and RD2 stimulation of TPE patients yields a total of 9 DEGs-hub genes (as shown in Table 3); RD1 antigen stimulation yields 8 hub genes (as shown in Table 4); and RD2 antigen stimulation yields 8 hub genes (as shown in Table 5). The second is the core gene set (WGCNA-hub genes, n=13) of the ME-4 and ME-8 modules, which are significantly associated with the tuberculosis-specific antigen stimulation phenotype. The WGCNA-hub genes share 6 overlapping genes with the DEGs-hub genes: IFNγ, GZMB, IL-2RA, IL-12RB2, TNF-α, and TNFRSF8. Table 6 only shows the unique genes of the WGCNA-hub genes. The two core gene sets mentioned above not only meet the criteria of significant differential expression, but also play a key role in tuberculosis infection, and have the potential to become diagnostic biomarkers that can distinguish between TPE and Non-TPE patients.

[0061] Table 3

[0062] Table 4

[0063] Table 5

[0064] Table 6

[0065] Example 2: Validation of the tuberculosis antigen-specific host transcriptome biomarker of the present invention Through transcriptome analysis, this invention screens a set of host transcriptome genes that can differentiate between patients with tuberculous and non-tuberculous pleural effusion. Based on this, an RT-qPCR analysis system suitable for clinical detection is established, and the reliability of the transcriptome data and the diagnostic performance of the candidate host biomarkers are verified using clinically diagnosed samples.

[0066] 2.1 Case Collection In this embodiment of the invention, a total of 26 clinically diagnosed TPE patients and 15 Non-TPE patients were included for validation of host transcriptome biomarkers, with inclusion criteria the same as in 1.1.

[0067] 2.2 RT-qPCR detection 2.2.1 RNA Extraction (1) Cell lysis: The antigen stimulation and cell lysis procedures for PFMCs are the same as in 1.2.

[0068] (2) RNA extraction: Add 200 μL of RNA extraction aid (1-bromo-3-chloropropane) to each 1 mL of cell lysis sample, vortex thoroughly, let stand for 5 min, strictly follow the SteadyPure RNA extraction kit (AG21024) operation, and the final eluted RNA can be used directly or stored at -80℃.

[0069] (3) RNA concentration determination: Take 1-2 μL of RNA solution and use a NanoDrop spectrophotometer to determine its concentration. An OD260 / OD280 ratio of 1.8-2.1 indicates that the extracted RNA sample is qualified and can be used for subsequent experiments.

[0070] 2.2.2 Reverse Transcription: Genomic DNA removal and reverse transcription were performed using the Takara PrimeScript™ FAST RT Reverse Transcription Kit, strictly following the kit instructions. Specific procedures are as follows: (1) Removal of gDNA reaction: Prepare the following reaction system on ice, in which 2 μL of 8×gDNA Eraser Premix is ​​added to a 16 μL reaction system, a maximum of 1 μg of RNA sample can be used, and RNase Free H2O is added to a total of 16 μL. After preparing the reaction mixture, transfer it to 42℃ for 2 min or room temperature for 5 min.

[0071] (2) Reverse transcription reaction: Add 4 μL of 5× RT Premix to the reaction solution in (1) on ice, mix gently, and then perform reverse transcription reaction at 37℃ for 10 min. Then transfer to a metal bath at 85℃ for 5 s. The obtained cDNA can be stored at -20℃ or at low temperature.

[0072] 2.2.3 Primer Design and Synthesis: Primers for the target gene were designed using the NCBI Pick Primer tool, and primer specificity was verified using Primer-BLAST. The primer sequences were synthesized by Qingke Biotechnology Co., Ltd., and the specific sequences are shown in Table 7.

[0073] Table 7

[0074] 2.2.4 RT-qPCR reaction (1) Reaction system preparation: The RT-qPCR reaction solution was prepared using Takara's TB Green® Premix Ex Taq™ II kit. The reaction solution was prepared on ice. The total system was 25 μL, containing 12.5 μL of TBGreen Premix Ex Taq II (Tli RNaseH Plus) (2×), 1 μL of PCR Forward Primer (10 μM), 1 μL of PCR Reverse Primer (10 μM), 2 μL of DNA template (<100 ng), and 8.5 μL of EasyDilution II. To reduce errors in the reaction solution preparation process, the premix was prepared first, thoroughly mixed, and then aliquoted into PCR plates for subsequent experiments.

[0075] (2) RT-qPCR detection: Place the PCR plate into the real-time PCR instrument and use the two-step PCR amplification program. First, pre-denature at 95℃ for 30 s; perform 40 cycles of reaction at 95℃ for 5 s and 60℃ for 30 s. The melting curve is set to 95℃ for 10 s and 65℃ for 50 s. At the same time, the temperature is increased from 65℃ to 95℃, and the fluorescence signal is detected when the temperature increases by 0.5℃ each time.

[0076] 2.2.5 Results Analysis: Using 2 -ΔΔCt Relative quantification was used to analyze gene expression levels, with ACTB as an internal reference gene, and the relative expression level of the gene was calculated as ΔCt = Ct. （目的基因） -Ct （内参基因） ,ΔΔCt=ΔCt （抗原刺激组） -ΔCt （对照组）The Mann-Whitney U test was used for intergroup comparisons. Pearson correlation analysis was used to analyze the concordance between RNA-seq data and RT-qPCR results. Receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy and determine the optimal cutoff value and area under the ROC curve (AUC). Bootstrap analysis (1000 iterations, random seed = 978) was used to estimate confidence intervals to ensure the reproducibility of threshold selection and correct for bias caused by small samples. All analyses were performed using GraphPad Prism 10.1.2, MedCalc 23.1.5, and R 3.5.0 (ggplot2 package) for statistical analysis and visualization of the data.

[0077] 2.3 Validation of Transcriptome Data To verify the reliability of the transcriptome data, this embodiment of the invention randomly selected 12 genes from the tuberculosis-specific host gene set and performed relative quantitative verification of these genes in TPE group PFMCs. TPE patient PFMCs were stimulated with RD1 and RD2 fusion proteins for 18-22 h, with unstimulated samples as controls and ACTB as an internal reference gene for RT-qPCR detection. The fold change in gene expression between the stimulated and unstimulated groups was compared. In this embodiment of the invention, the expression trends of all candidate genes after antigen stimulation were completely consistent with the transcriptome sequencing results. Pearson correlation analysis confirmed a significant positive correlation between RT-qPCR and RNA-seq gene expression levels (r=0.8866). p <0.0001), confirming the accuracy and reliability of the transcriptome sequencing data (e.g., ...). Figure 7 (A and B in the text).

[0078] 2.4 Validation of the diagnostic performance of tuberculosis antigen-specific host biomarkers like Figure 1 As shown in C, to evaluate the diagnostic performance of candidate genes, the relative gene expression levels of TPE (n=10) and Non-TPE (n=7) patients under the same antigen stimulation were measured. Similarly, antigen-stimulated and unstimulated samples were set up separately, using 2... -ΔΔCt The algorithm calculated the relative gene expression levels in the TPE and Non-TPE groups, and the Mann-Whitney U test was used to analyze the differences between the groups. Of the 32 core genes initially screened, BDKRB1, CCL25, PTGER3, and SSTR2 were excluded due to FPKM < 1. After validation in 3 TPE and 3 Non-TPE patients, 10 genes were identified as having significant diagnostic value.Figure 7 As shown in C and Table 8, in this embodiment of the invention, under RD1 antigen stimulation, the relative expression levels of 10 host gene markers in the TPE group were significantly higher than those in the Non-TPE group. p The AUC values ​​were <0.05, demonstrating excellent diagnostic efficacy. IFNγ and IL-2 achieved perfect differentiation (AUC=1.00), while the AUCs of the other eight genes were ≥0.83. Notably, IL-3, CXCL10, HAVCR2, IL-12RB2, and IL-18RAP had a Youden index of 0.90, corresponding to AUCs >0.95; GZMB and TNFSF8 had AUCs >0.90. All genes exhibited 100% specificity at the optimal cutoff value, indicating a strong ability to exclude non-tuberculous pleural effusions. In the RD2 stimulation system, IFNγ and IL-12RB2 showed perfect diagnostic performance (AUC=1.00), while GZMB, HAVCR2, IL-18RAP, and IL-2 had AUCs >0.90. Notably, HAVCR2, IL-12B, IL-18RAP, and IL-3 maintained 100% specificity under RD2 stimulation, further validating the stability of the biomarkers. Through the above validations, this embodiment of the invention demonstrates the robust reliability of 10 tuberculosis antigen-specific host transcriptome biomarkers in differentiating between tuberculous and non-tuberculous pleural effusions.

[0079] Table 8

[0080] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A host biomarker specific to tuberculosis antigens for detecting tuberculous pleural effusion, characterized in that, The biomarker is at least one of the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2; The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are shown in SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9 and SEQ ID NO:10, respectively.

2. A reverse transcription quantitative polymerase chain reaction test kit for detecting tuberculous pleural effusion, characterized by, Any antigen encoded by the RD1 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD1 region of Mycobacterium tuberculosis, and any antigen encoded by the RD2 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD2 region of Mycobacterium tuberculosis, wherein the peptide segment is an effective T cell epitope of the antigen encoded by the corresponding region; The primers for detecting at least one of the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are also included. The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are shown in SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9 and SEQ ID NO:10, respectively.

3. An enzyme-linked immunospot assay kit for detecting tuberculous pleural effusion, characterized by, Any antigen encoded by the RD1 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD1 region of Mycobacterium tuberculosis, and any antigen encoded by the RD2 region of Mycobacterium tuberculosis or any peptide segment of the antigen encoded by the RD2 region of Mycobacterium tuberculosis, wherein the peptide segment is an effective T cell epitope of the antigen encoded by the corresponding region; The solid-phase carrier coated capture antibody for specifically binding to the protein encoded by the gene, the biotin-labeled detection antibody capable of specifically binding to the protein encoded by the gene, the streptavidin-enzyme complex and the enzyme substrate developing solution are also included, wherein the gene is at least one of the following genes: IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2. The base sequences of the IFNγ, IL-2, IL-12RB2, GZMB, IL-3, CXCL10, IL-12B, IL-18RAP, TNFRSF8 and HAVCR2 are shown in SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9 and SEQ ID NO:10, respectively.

4. The use of the reverse transcription quantitative polymerase chain reaction detection kit according to claim 2 in the preparation of a reagent for detecting tuberculous pleural effusion.

5. The use according to claim 4, wherein the compound is ###0002### The application specifically comprises stimulating the pleural effusion or pleural effusion mononuclear cell PFMCs with an antigen stimulant, the antigen stimulant comprising an RD1 region antigen or any peptide segment encoding an antigen in the RD1 region, and also comprising an RD2 region antigen or any peptide segment encoding an antigen in the RD2 region; extracting mRNA from the stimulated pleural effusion or extracting mRNA from the stimulated pleural effusion mononuclear cell PFMCs, and then using the primer to detect the high expression of mRNA of at least one of the genes produced after stimulation by the reverse transcription quantitative polymerase chain reaction detection kit, so as to determine that the sample is a tuberculous pleural effusion.

6. The use of the enzyme-linked immunospot detection kit according to claim 3 in the preparation of a reagent for detecting tuberculous pleural effusion.

7. Use according to claim 6, wherein The application specifically comprises stimulating the pleural effusion mononuclear cell PFMCs with an antigen stimulant, the antigen stimulant comprising an RD1 region antigen or any peptide segment encoding an antigen in the RD1 region, and also comprising an RD2 region antigen or any peptide segment encoding an antigen in the RD2 region; and using the enzyme-linked immunospot detection kit to detect the protein expressed by the T cells in the stimulated PFMCs, so as to determine that the sample is a tuberculous pleural effusion.

Images