Application of Spp1 in auxiliary diagnosis, treatment or prognosis of bone and soft tissue infection caused by staphylococcus aureus

Abstract

The invention discloses application of Spp1 in auxiliary diagnosis, treatment or prognosis of bone and soft tissue infection caused by staphylococcus aureus. The Spp1 comprises an Spp1 gene, mRNA expressed by the Spp1 gene or an Spp1 protein expressed by the Spp1 gene, can be used for preparing a reagent / kit for auxiliary diagnosis, treatment or prognosis of the bone and soft tissue infection caused by the staphylococcus aureus and can also be used for preparing and screening drugs for treating the bone and soft tissue infection caused by the staphylococcus aureus, and the nucleotide sequence of the Spp1 gene is shown as NCBI Reference Sequence: NC000071.7. Based on a multi-omics database and a gene editing technology, the bone and soft tissue infection molecule subtype and the key target Spp1 are found, theoretical support is provided for development of diagnostic markers and therapeutic drugs, and the method has definite clinical transformation and industrialization prospects.

Description

Technical Field

[0001] The present invention belongs to the field of biomedical technology, and particularly relates to the application of Spp1 in the auxiliary diagnosis, treatment or prognosis of bone and soft tissue infections caused by Staphylococcus aureus. Background Art

[0002] Bone and soft tissue infections, such as osteomyelitis, septic arthritis, muscle and soft tissue infections, implant infections, and infected nonunions and bone defects, are catastrophic diseases in orthopedics. Approximately one million new cases of bone and soft tissue infections occur globally each year, with approximately 200,000 new cases of nonunions and bone defects caused by infection. The incidence rate has been rapidly increasing in recent years, and diagnosis and treatment of these infections have long been plagued by a clinical dilemma characterized by high failure rates, high recurrence rates, and high disability rates. The high cost of treating bone and soft tissue infections places a heavy burden on patients, their families, and society, making them a global challenge that remains unresolved.

[0003] Numerous studies have shown that the main reasons for the difficulty in treating bone and soft tissue infections include bacterial biofilm formation, bacterial resistance, and the persistence of intracellular bacteria. The current gold standard for the treatment of bone and soft tissue infections is debridement combined with antibiotics. While increasingly sophisticated infection treatment options over the past few decades have effectively addressed the issues of bacterial biofilm and drug resistance, the large number of "intracellular bacteria" that invade and remain dormant within normal cells remain a key cause of treatment failure and recurrence, as surgical removal of these infected cells is difficult and antibiotics that can penetrate and kill them are few and far between. This urgent issue demands resolution.

[0004] Bone and soft tissue infections involve multiple cell types. Identifying the cell types invaded by intracellular bacteria and their targets for intervention is crucial for disease treatment and prognosis. Among host cells invaded by bacteria, macrophages are the first to be attacked, the most vulnerable to bacterial invasion, and the most serious consequences. This study integrates single-cell omics from clinical and animal samples to identify infected macrophages and potential intervention targets, aiming to gain a deeper and more comprehensive understanding of bone and soft tissue infections and provide a theoretical basis for the search for potential infection-targeting drugs. Summary of the Invention

[0005] Based on the shortcomings of the aforementioned prior art, the present invention aims to address the lack of effective therapeutic targets for infected macrophages in bone and soft tissue infections. The present invention provides the application of Spp1 in the auxiliary diagnosis, treatment, or prognosis of bone and soft tissue infections caused by Staphylococcus aureus, thereby proposing a new treatment method for bone and soft tissue infections that precisely targets infected macrophages. This method simultaneously achieves efficient clearance of intracellular bacteria, blocks immune escape by infected macrophages, and restores immune function in the local microenvironment, thereby breaking the vicious cycle of "immune escape-immunosuppression-persistent infection" mediated by infected macrophages and ultimately improving the success rate of bone and joint infection treatment.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] One of the technical solutions of the present invention provides the use of the Spp1 gene, the mRNA expressed by the Spp1 gene, or the Spp1 protein expressed by the Spp1 gene in the preparation of reagents / kits for auxiliary diagnosis, treatment or prognosis of bone and soft tissue infections caused by Staphylococcus aureus; and the use in the preparation and screening of drugs for treating bone and soft tissue infections caused by Staphylococcus aureus.

[0008] Furthermore, the nucleotide sequence of the Spp1 gene is NCBI Reference Sequence: NC_000071.7. The Spp1 gene includes polynucleotides of the Spp1 gene and any functional equivalents of the Spp1 gene.

[0009] Furthermore, the Spp1 gene, the mRNA expressed by the Spp1 gene, or the Spp1 protein expressed by the Spp1 gene is used as a target for treating bone and soft tissue infections caused by Staphylococcus aureus.

[0010] A second technical solution of the present invention provides a diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus, wherein the kit contains a detection reagent for detecting the content of the Spp1 gene, mRNA expressed by the Spp1 gene, or Spp1 protein expressed by the Spp1 gene.

[0011] Furthermore, the kit includes:

[0012] (1) Reagents for extracting nucleic acids; (2) Primer pairs for specifically amplifying the gene; (3) qPCR reaction buffer and fluorescent probe; (4) positive and negative controls.

[0013] The kit may also include other reagents for detecting genes and their expression (including transcription and translation) levels. These reagents can be replaced according to different detection levels without affecting the creativity of the present invention.

[0014] Furthermore, the method for using the diagnostic kit comprises the following steps:

[0015] 1) Collecting samples to be tested, and measuring the mRNA expression level or protein expression level of the Spp1 gene in the samples to be tested;

[0016] 2) Take normal specimens and test the same indicators as in 1) using the same method;

[0017] 3) Comparing the test results in 1) and 2), if the mRNA expression level or protein expression level of the Spp1 gene in the test specimen is higher than that in the normal specimen, it indicates that the test specimen has bone and soft tissue infection caused by Staphylococcus aureus.

[0018] Furthermore, the specimen to be tested in step 1) is selected from clinical specimens of bone and soft tissue infection; in experimental studies, it is selected from time-series tissues of mouse models of skin and soft tissue infection, osteomyelitis, and periprosthetic infection;

[0019] Furthermore, the detection of the mRNA expression level in step 1) refers to detecting the abundance of the mRNA transcribed from the gene at the transcription level, and the detection of the protein expression level refers to detecting the abundance of the protein encoded by the gene at the translation level.

[0020] Furthermore, the detection of the mRNA expression level can be based on sequencing technology, including chain terminator (Sanger) sequencing technology and dye terminator sequencing technology, and also includes next-generation sequencing technology (i.e., deep sequencing / high-throughput sequencing technology); the present invention can use second-generation sequencing and third-generation sequencing to detect the transcriptome in cDNA, and then detect the expression level of the Spp1 gene. The present invention can also use Nanopore sequencing to directly detect the RNA expression level, thereby quantifying the expression level of the Spp1 gene. The detection of the mRNA expression level can also be based on PCR technology, quantified by RT-PCR or digital PCR (dPCR).

[0021] Furthermore, the detection of protein expression levels can be based on antibody recognition and quantified by Western Blot, enzyme-linked immunosorbent assay (ELISA), immunohistochemistry (IHC) / immunofluorescence (IF) or flow cytometry; it can also be a mass spectrometry-based proteomics method, which can be quantified by chromatography, mass spectrometry, laser, etc. and their combination.

[0022] The above methods for detecting mRNA expression levels and protein expression levels cannot be used to limit the creativity of the present invention.

[0023] A third technical solution of the present invention provides a method for screening drugs for treating bone and soft tissue infections caused by Staphylococcus aureus, comprising the following steps:

[0024] 1) Establish an in vitro cell model that stably overexpresses the Spp1 gene, Spp1 mRNA, or Spp1 protein;

[0025] 2) incubating the candidate drug with the model described in step 1);

[0026] 3) Detecting the expression of the Spp1 gene, Spp1 mRNA, or Spp1 protein in the cell model before and after incubation with the drug candidate. If the expression level decreases, it indicates that the drug candidate can be used for further development.

[0027] Furthermore, the drug intervenes in the expression of Spp1 gene, Spp1 mRNA, or Spp1 protein, and is used to reverse the immunosuppression and immune exhaustion in the infection microenvironment and reverse the infection process.

[0028] Compared with the prior art, this application has at least the following beneficial effects:

[0029] This study, based on a self-built multi-omics database of clinical and mouse bone and soft tissue infections, provides new insights into the pathogenesis and outcomes of bone and soft tissue infections through spatiotemporal cell subset analysis, providing a theoretical basis for the development of new therapeutic targets and diagnostic markers. The sophisticated CRISPR-Cas9 gene editing and Confetti / tdTomato / GFP mouse lineage tracing system enable multi-dimensional and more precise screening and verification of key therapeutic targets.

[0030] 1) Based on clinical and animal sample libraries and multi-omics databases for bone and soft tissue infections, this study identified four molecular subtypes of bone and soft tissue infections and verified the heterogeneity between these subtypes and disease outcomes. ScRNA-seq and unsupervised cluster analysis of macrophages in infected foci of mice with bone and joint infections revealed significant specificity for infected macrophages in CM4-type infections, which are associated with the worst prognosis. This subpopulation of infected macrophages had significantly higher intracellular bacterial counts than other macrophage subpopulations.

[0031] 2) The present invention analyzed the differentially expressed genes and signaling pathways between infected macrophages and other macrophage subsets, and found that the expression of genes related to autoantigen processing and presentation and regulatory T cell function in infected macrophages was significantly changed. In vitro co-culture suggested that CD8 + T cell activation was significantly inhibited, while the expression of exhaustion-related genes was upregulated. Flow cytometric analysis further confirmed that CD8 + Increased PD1 expression on T cells, accompanied by CD8 + The expression of T cell effector factors Granzyme B and IFN-γ was significantly downregulated.

[0032] 3) Based on proteomic analysis, the present invention found that compared with uninfected macrophages, the expression of multiple proteins represented by membrane proteins in infected macrophages was significantly different. Further analysis of the transcriptome expression of candidate membrane proteins showed that the related differential gene analysis results showed that genes such as Spp1 and Nos2 were significantly overexpressed. Fluorescence staining results of samples from infected patients showed that Spp1 +The proportion of macrophages increased significantly. In addition, specific knockout of Spp1 in mouse macrophages and in vitro co-culture experiments showed that knocking down the Spp1 gene in infected macrophages could reverse T cell suppression and alleviate infection. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1A-Figure 1D The bone and soft tissue infection mouse model provided in Example 1 was constructed and the temporal and spatial sequence immune microenvironment analysis diagram was constructed, wherein: Figure 1A Indicates dimensionality reduction clustering of bone and soft tissue infected cell subpopulations, Figure 1B Indicates the naming of each cell subpopulation infected with bone and soft tissue according to the database, Figure 1C Indicates the distribution changes of various cell subpopulations at different time points of bone and soft tissue infection, Figure 1D Indicates the changes in the proportion of each cell subset at different time points in bone and soft tissue infection; in the figure, C01-C28 represent 28 cell subsets obtained by single-cell sequencing of all cells in bone and soft tissue infection tissues and clustering through dimensionality reduction, and are not defined;

[0034] Figure 2A-2D The molecular subtype identification of bone and soft tissue infection and its correlation with prognosis are provided in Example 2, wherein: Figure 2A Indicates molecular typing of bone and soft tissue infection, Figure 2B Indicates the correlation between each molecular classification and prognosis, Figure 2C Represents dimensionality reduction clustering of macrophage-related subpopulations in bone and soft tissue infection, Figure 2D Indicates that the C03 macrophage subset in bone and soft tissue infection highly expresses Spp1; C01-C20 in the figure represent 20 subdivided cell subsets obtained by further dimensionality reduction clustering of all macrophages in bone and soft tissue infection tissues;

[0035] Figure 3A-Figure 3E Provided in Example 3 the Spp1 in bone and soft tissue infection + Figure 2. Research diagram of macrophage functional characteristics, including: Figure 3A Spp1 in bone and soft tissue infection + Differential genes between macrophages and other macrophages, Figure 3B Represents the functional enrichment analysis of differentially expressed genes in two types of macrophages. Figure 3C 、 3D , 3E indicates Spp1 in vitro + Macrophages on CD8 + the effects of T cell expression of PD1, Granzyme B, and IFN-γ;

[0036] Figures 4A-4C Provided in Example 4 the Spp1 in bone and soft tissue infection + Diagram of screening and functional validation of key macrophage intervention targets, including: Figure 4A Spp1 in bone and soft tissue infection + Macrophage characteristic protein profile, Figure 4B Spp1 + Macrophages significantly express genes such as Spp1 and Nos2. Figure 4C indicated that Spp1 was found to colocalize with macrophages in clinical samples of bone and soft tissue infections;

[0037] Figure 5 The Spp1 flox mice provided in Example 4 are shown, indicating the PCR primer sequences and agarose electrophoresis scanning results used to construct the Spp1 gene knockout mice;

[0038] Figures 6A-6C Provided in Example 4 the Spp1 in bone and soft tissue infection + Diagram of screening and functional validation of key macrophage intervention targets, including: Figure 6A It was shown that knocking out Spp1 in mouse macrophages significantly reduced the bacterial load and the number of infected macrophages after infection. Figure 6B Flow cytometry showed that knocking out Spp1 in macrophages increased the expression of CD8 + The role of T cell effector function, Figure 6C It indicates that knocking out Spp1 in macrophages increases CD8 + T cell proliferation activity. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail below with reference to specific embodiments. It should be noted that the following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0040] Unless otherwise specified, all raw materials in the present invention are not particularly limited in their sources and can be purchased from the market or prepared according to conventional methods well known to those skilled in the art.

[0041] The experimental ideas provided in the embodiment are as follows:

[0042] 1) Collect clinical specimens of bone and soft tissue infection, as well as time-sequential tissue specimens from mouse models of skin and soft tissue infection, osteomyelitis, and periprosthetic joint infection. Analyze single-cell transcriptomes and the Consensus Cluster algorithm to establish an immune cell atlas of bone and soft tissue infection, and further perform unsupervised cluster analysis of macrophage subsets.

[0043] 2) Use GFP-Staphylococcus aureus to construct an infected macrophage model, sort the infected macrophages by flow cytometry, and use the STAR dynamic algorithm and integrated machine learning methods to screen potential intervention targets in infected macrophages at high throughput. Use CRISPR / Cas9 gene editing technology to verify its ability to reverse the immune escape and immunosuppression of infected macrophages, and select key intervention targets in infected macrophages.

[0044] 3) Use GFP-Staphylococcus aureus to establish mouse models of skin and soft tissue infection, osteomyelitis, and periprosthetic infection, observe the expression of key intervention targets in vivo, construct gene knockout mice for key intervention targets in macrophages, and establish bone and soft tissue infection models to analyze the role and mechanism of key intervention targets in macrophages in bone and soft tissue infection.

[0045] Example 1. Construction of a mouse model of bone and soft tissue infection and analysis of the spatiotemporal immune microenvironment

[0046] To explore the dynamic changes in the immune microenvironment during bone and soft tissue infection, this example established a mouse bone and soft tissue infection model. The specific method is as follows:

[0047] (1) Ten-week-old C57BL / 6 female mice were inoculated with 1x10^5 CFU of Staphylococcus aureus USA300 LAC into the femoral bone marrow cavity and femoral muscle to establish an infection model. (2) The animals were sacrificed at specific time points after infection (specific time points included: 1, 3, 7, 14, and 28 days), and the infected foci tissues were collected. (3) The infected tissue samples were subjected to single-cell transcriptome sequencing (scRNA-seq).

[0048] The experimental results are shown in Figure 1. Through the systematic analysis of single-cell transcriptome sequencing (scRNA-seq) data of bone and soft tissue infection models, the following key findings were obtained: First, strict quality control was performed on the original sequencing data, and low-quality cells with a mitochondrial gene ratio of >20% or a detected gene number of <200 were eliminated, and genes expressed in <3 cells were filtered. The SCTransform algorithm was then used for normalization to eliminate technical noise and library size differences. Principal component analysis (PCA) was performed based on highly variable genes (top 2000), and after clustering using the Louvain algorithm (k=20 neighborhood graph), 28 cell subpopulations with significant transcriptome differences were finally identified ( Figure 1A ).

[0049] Further biological annotation of these subgroups was performed based on the conserved marker genes of CellMarker and PanglaoDB authoritative database: CD4 + T cells (marker genes Cd3d, Cd4), CD8 +Major immune and stromal cell types, including T cells (Cd8a, Gzmb), regulatory T cells (Treg; Foxp3, Il2ra), B cells (Cd79a, Ms4a1), neutrophils (S100a8, S100a9), macrophages (Adgre1, Csf1r), monocytes (Ly6c2, Ccr2), dendritic cells (Itgax, Hla-dra), fibroblasts (Col1a1, Pdgfra), and endothelial cells (Pecam1, Cdh5) Figure 1B ).

[0050] Focus on in-depth analysis of macrophage-related subpopulations (accounting for 15-30% of the total number of cells): further subdivide subpopulations based on the expression patterns of classic functional marker genes, including pan-macrophage marker Adgre1 (F4 / 80), inflammatory macrophage marker Itgax (CD11c), repair-type M2 macrophage marker Mrc1 (CD206), antigen presentation-related *H2-Ab1* (MHC-II), monocyte-derived macrophage marker Ly6c2, and special functional subpopulations defined by the core target of this study, Spp1 (osteopontin) ( Figure 1C Time series dynamic analysis showed that the proportion of macrophages reached a peak (about 25%) in the early stage of infection (day 3), accompanied by Ly6c2 + Monocyte-derived macrophages expanded significantly; by the late infection period (day 28), the proportion dropped to 10%, but Spp1 + Subpopulations are continuously enriched ( Figure 1D This spatiotemporal distribution suggests that macrophage subset reprogramming plays a key role in the infection process.

[0051] Example 2. Identification of molecular subtypes of bone and soft tissue infection and their association with prognosis

[0052] Based on the bone and soft tissue infection single cell database established in Example 1, the ConsensusCluster clustering algorithm was used to perform unsupervised cluster analysis on the infected tissue scRNA-seq data. The results revealed that there were four molecular subtypes (CM1, CM2, CM3, and CM4) with significant heterogeneity in bone and soft tissue infection ( Figure 2A ), further association analysis revealed significant heterogeneity between the four molecular subtypes and the prognosis of bone and soft tissue infection. Among them, CM4 patients had the worst prognosis ( Figure 2B Innate immune cells (mainly macrophages and neutrophils) in bone and soft tissue infections are the first line of defense against bacterial infection. Therefore, we re-clustered and analyzed the innate immune cells in bone and soft tissue infections to obtain 20 cell subpopulations. We found that the characteristic marker Spp1 of the C03 macrophage subpopulation was significantly overexpressed ( Figure 2C , Figure 2D The above results indicate that bone and soft tissue infection is a disease with significant heterogeneity. The inventors established four molecular subtypes of bone and soft tissue infection and found that Spp1 + Macrophages are a characteristic cell subset among them.

[0053] Example 3. Spp1 in bone and soft tissue infections + Study on the functional characteristics of macrophages

[0054] To further study Spp1 + The function of macrophages in bone and soft tissue infection is divided into Spp1 + Macrophages (highly expressing Spp1 gene) and Spp1 - Macrophages (almost no expression of Spp1 gene) and further compared Spp1 + Differentially expressed genes (DEGs) between macrophage subsets and other macrophage subsets.

[0055] Gene set enrichment analysis (GSEA) showed that Spp1 + Significant changes in gene expression in macrophages in signaling pathways related to self-antigen processing and presentation (downregulation of MHC-II-related genes) and regulation of T cell function (upregulation of immunosuppressive ligand genes) were observed. Figure 3A , Figure 3B ).

[0056] A mouse model of bone and soft tissue infection was established using Staphylococcus aureus, and Spp1 was obtained by flow cytometry. + macrophages and in vitro + T cells were co-cultured. CD8 T cells were analyzed by flow cytometry. + T cell functional characteristic markers, the results showed: CD8 + The expression of T cell effector molecules (PD1, Granzyme B, IFN-γ) was significantly downregulated ( Figure 3C , Figure 3D , Figure 3E The above results together indicate that Spp1 + Macrophage subsets have a significant inhibitory effect on CD8 + The role of T cell function may be the key reason for the poor prognosis of bone and soft tissue infections.

[0057] Example 4. Spp1 in bone and soft tissue infections + Screening and functional verification of key intervention targets in macrophages

[0058] Spp1 +Proteomic analysis of macrophages and uninfected macrophages was performed. Analysis of differentially expressed proteins revealed that Spp1 + The expression of multiple proteins represented by membrane proteins (based on subcellular localization information) in macrophages was significantly different. The differentially expressed membrane proteins were compared with the known membrane protein information in the UniProt database, and 23 candidate membrane proteins were screened ( Figure 4A ).

[0059] The expression of genes corresponding to candidate membrane proteins at the transcriptome level was further analyzed. The results of differential gene analysis (based on scRNA-seq or bulk RNA-seq data) showed that genes Spp1 (encoding osteopontin OPN) and Nos2 (encoding inducible nitric oxide synthase iNOS) were expressed in Spp1. + Significantly high expression in macrophage subsets ( Figure 4B ).

[0060] Multiplex immunofluorescence staining (mIHC) was performed using tissue samples from a clinical sample library for bone and soft tissue infection. The results showed that Spp1 expression in infected patient samples was significantly higher than that in healthy control samples. + The proportion of macrophages increased significantly ( Figure 4C ).

[0061] Construction of Spp1 based on Cre / LoxP recombination system flox / + Mouse, through Spp1 flox / + Spp1 flox / flox Mouse. Spp1 flox / flox Mice and Lyz2 Cre+ mice and obtained Spp1 flox / + Lyz2 Cre+ mice, and then combined them with Spp1 flox / flox The mice were hybridized and the genotype was Spp1 flox / flox Lyz2 Cre+ Macrophage conditional Spp1 knockout mice; flox / flox Lyz2 Cre- Mice were used as control group. PCR and agarose gel electrophoresis were used to identify the flox genotype of mice ( Figure 5 ).

[0062] By in vitro and in vivo gene knockout (based on CRISPR-Cas9 gene editing technology, a method well known to those skilled in the art, the relevant steps are not repeated here, the upstream and downstream primers related to gene knockout are shown in Table 1) to specifically reduce the expression of the Spp1 gene in infected macrophages ( Figure 6A ). Macrophages were then combined with CD8 + Flow cytometry analysis showed that after Spp1 knockdown, CD8 + The inhibition of T cell activation was significantly reversed (expressed by CD8 + T cell activation markers increased, exhaustion markers decreased, and effector molecule expression recovered)( Figure 6B , Figure 6C This suggests that Spp1 (also known as osteopontin) is a key molecule in the T cell suppressive function mediated by infected macrophages. Interfering with its expression can reverse the immunosuppression and immune exhaustion in the infected microenvironment and reverse the infection process.

[0063] Table 1 Upstream and downstream primers used for gene knockout

[0064]

[0065] The above description of the embodiments is intended to facilitate understanding and use of the invention by those skilled in the art. It will be apparent that those skilled in the art can readily make various modifications to these embodiments and apply the general principles described herein to other embodiments without requiring inventive effort. Therefore, the present invention is not limited to the above-described embodiments. Improvements and modifications made by those skilled in the art based on the disclosure of the present invention, without departing from the scope of the present invention, should be within the scope of protection of the present invention.

Claims

1. Use of the Spp1 gene, mRNA expressed by the Spp1 gene, or Spp1 protein expressed by the Spp1 gene in the preparation of reagents / kits for auxiliary diagnosis, treatment, or prognosis of bone and soft tissue infections caused by Staphylococcus aureus.

2. Use of the Spp1 gene, mRNA expressed by the Spp1 gene, or Spp1 protein expressed by the Spp1 gene in the preparation and screening of drugs for treating bone and soft tissue infections caused by Staphylococcus aureus.

3. The use according to any one of claim 1 or claim 2, characterized in that: The nucleotide sequence of the Spp1 gene is shown in NCBI Reference Sequence: NC_000071.

7.

4. A diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus, characterized in that: The kit contains a detection reagent for detecting the content of the Spp1 gene, the mRNA expressed by the Spp1 gene, or the Spp1 protein expressed by the Spp1 gene.

5. The diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus according to claim 4, characterized in that: The kit includes: (1) Reagents for extracting nucleic acids; (2) a primer pair that specifically amplifies the gene; (3) qPCR reaction buffer and fluorescent probe; (4) Positive and negative controls.

6. The diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus according to claim 4, characterized in that: The method for using the diagnostic kit comprises the following steps: 1) Collecting samples to be tested, and measuring the mRNA expression level or protein expression level of the Spp1 gene in the samples to be tested; 2) Take normal specimens and test the same indicators as in 1) using the same method; 3) Comparing the test results in 1) and 2), if the mRNA expression level or protein expression level of the Spp1 gene in the test specimen is higher than that in the normal specimen, it indicates that the test specimen has bone and soft tissue infection caused by Staphylococcus aureus.

7. The diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus according to claim 6, characterized in that: In step 1), the specimen to be tested is selected from clinical specimens of bone and soft tissue infection.

8. The diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus according to claim 6, characterized in that: The detection of the mRNA expression level in step 1) refers to detecting the abundance of mRNA transcribed from the gene at the transcription level.

9. The diagnostic kit for bone and soft tissue infection caused by Staphylococcus aureus according to claim 6, characterized in that: The detection of the protein expression level in step 1) refers to detecting the abundance of the protein encoded by the gene at the translation level.

10. A method for screening drugs for treating bone and soft tissue infections caused by Staphylococcus aureus, characterized in that: The following steps are involved: 1) Establish an in vitro cell model that stably overexpresses the Spp1 gene, Spp1 mRNA, or Spp1 protein; 2) incubating the candidate drug with the model described in step 1); 3) Detecting the expression of the Spp1 gene, Spp1 mRNA, or Spp1 protein in the cell model before and after incubation with the drug candidate. If the expression level decreases, it indicates that the drug candidate can be used for further development.

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