Infection caused by Staphylococcus (S.) aureus is an endemic health problem worldwide (Chen et al., 2022; Park et al., 2021; Miller et al., 2020). S. aureus is a common invasive bacterial pathogen that produces staphylococcal enterotoxin (SE), which causes intestinal tract dysfunction (Dicks et al., 2021; Omar et al., 2021) and is responsible for almost all staphylococcal food poisoning. Staphylococcal food poisoning results from food contamination by S. aureus enterotoxin, accounting for 33% of total bacterial foodborne infections in the United States (Haghi et al., 2021). More than 45% of foodborne diseases are caused by S. aureus in Canada (Greco et al., 2020). Therefore, S. aureus pathogenicity and its underlying virulence mechanisms have been a primary research focus. Staphylococcus aureus causes high mortality, which is associated with early excessive inflammation of unknown mechanisms (Wang et al., 2023). Staphylococcus aureus has a powerful virulence secretion system to evade the host’s immune response, and may even promote excessive inflammatory response (Mu et al., 2023); therefore, the host’s regulation of the immune response, especially the key mechanisms controlling inflammation, is crucial for successful resistance to Staphylococcus aureus.

A pathogenic gene permits a pathogen to cause disease (Kotnik et al., 2023). Understanding the role of virulence genes in disease has become a central focus of medical research for the purpose of developing preventive measures, diagnostic tools, treatment approaches, and therapeutic strategies (Jonas et al., 2020). Previous studies on S. aureus pathogenicity have been mainly focused on the expression and function of a single gene using gene knockout, gene silencing, RNA interference, and other genetic approaches (Kane et al., 2018; Scherr et al., 2015). However, these methods are typically laborious and time-consuming, inefficient, and require extensive training, leading to limited success in meeting the needs of clinical medicine. Advanced omics technologies, including gene chip and big data analytics (Giulieri et al., 2020) particularly CRISPR/CAS9 (Chen et al., 2017; Penewit et al., 2018), can simultaneously identify nearly one million sites in genomic DNA, which allows for association analysis between S. aureus-infected diseases and genetic variation. Thus, these technologies provide powerful tools to investigate pathogenic gene regulatory networks and diagnostic targets. However, scientists are challenged by the increasing amounts of transcriptomic data created by high-throughput techniques, including how best to handle and analyze the millions of data points identified by genetic studies of S. aureus-infected diseases with appropriate mathematical and statistical strategies.

The objective of this study was to identify novel S. aureus pathogenic gene regulatory networks and diagnostic targets using the NCBI GEO DataSets database and functional enrichment analysis. In the present study, the gene expression profiles of S. aureus-infected mice were selected from the NCBI GEO Datasets database to assess differentially expressed genes (DEG) using a combination of the linear models and empirical Bayesian methods in limma, an R software package (https://www.r-project.org/), with the traditional t-test. Gene function analysis (GO-analysis) and signal pathway analysis (Pathway-Analysis) were performed using DAVID (Database for Annotation, Visualization and Integrated Discovery) and KEGG (Kyoto Encyclopedia of Genes and Genomes) to select DEG sets that were integrated into TRED (Transcriptional Regulatory Element Database) to construct the S. aureus antimicrobial resistance gene regulatory network. Associations between a given disease and network genes were analyzed using the DAVID online annotation tool.

Staphylococcus aureus predominantly resides on the skin and in the nasopharynx of humans, and it is the most prevalent cause of nosocomial and community-acquired bloodstream infections, skin and soft tissue infections, and pneumonia in almost all geographic areas. Thus, S. aureus poses a serious threat to human health and global stability. Methicillin-resistant S. aureus is unresponsive to 60% of antibiotics (Mitevska et al., 2021; Paudel et al., 2021), which is a major underlying cause of several difficult-to-treat life-threatening infections. Therefore, there is an unmet need to understand S. aureus pathogenesis to develop effective prevention and treatment of infection. In the present study, we identified 437 DEGs, from which 15 TFs and their predicted corresponding target genes were used to develop a TF regulatory network. We found several key factors closely related to inflammation and the immune system that are regulated by S. aureus TF regulatory networks. Our findings provide new information and reference values for virulence genes in the transcriptional regulation of S. aureus infection.

We hypothesized that inflammatory and immune system diseases caused by S. aureus are likely regulated by three genes: jun, c3, and spil. Staphylococcus aureus is the most common pathogen that causes inflammatory and immune system diseases, including a variety of suppurative (pus-forming) infections (Carrel et al., 2017), pneumonia, pseudomembranous colitis, pericarditis, and even sepsis (Agarwal et al., 2018). Jun, c3, and spi1 are believed to be involved in inflammation and immune responses. Jun has been reported to inhibit inflammatory factors and participate in immune system regulation, which is supported by Xie et al. (2014) who showed that downregulation of jun decreased expression of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interferon β (IFN-β), and interleukin 6 (IL-6), but upregulated expression of anti-inflammatory cytokines, including IL-10. Jun is also closely associated with systemic lupus erythematosus (SLE), an autoimmune disease involving multiple organs and systems (Maria et al., 2017). Doníz et al. (2011) reported that jun expression was significantly elevated in peripheral blood mononuclear cells (PBMC) in SLE patients compared to normal controls. C3, the most important molecule encoded by gene c3 in the complement system (Lu et al., 2018), is located at the intersection node of both classical and alternative complement activation pathways, as well as the mannose-binding lectin pathway, indicating that C3 plays an important regulatory role in the complement system, inflammation, and the immune system (Yuan et al., 2024). The complex and diverse C3 cleavage fragments and their binding proteins regulate the complement system via activating the complement cascade and through self-activation and cleavage, as well as by interacting with a variety of relevant factors that promote immune adhesion and pathogen phagocytosis (Fagan et al., 2017). Spi1 affects the immune system by regulating mature B cells in the spleen (Batista et al., 2017). In the present study, we first reported that jun (corresponding to 120 target genes), c3 (corresponding to 62 target genes), and spi1 (corresponding to 49 target genes) regulated most of the target genes, strengthening our hypothesis that jun, c3 and spi1 regulate inflammation and the immune system.

We further revealed that jun and spil are core genes in the S. aureus regulatory network, while c3 plus il6 are secondary core genes. Regulation of core genes in inflammation and immune system diseases is executed mainly by regulating target genes met, mmp13, il12b, il4, tnf, ptgs2, and ctsl. In the present study, we found that all of these genes were regulated by at least four TFs (Figure 2). Met, mmp13, il12b, il4, and ptgs2 were regulated by jun and spil. Met, mmp13, and il12b were simultaneously regulated by il6. Ctsl, ptgs2, and il4 were regulated by jun and c3. In addition to jun, c3, and spil, il6 was has been shown to be involved in inflammatory and immune system diseases, where il6 acted not only as a TF but also as a target gene regulated by a TF. A previous study revealed a close association of il6 with the immune system (Leal et al., 1999) by activating proinflammatory and other cytokines in B cells, hepatocytes, hybridoma cells, and plasma cells to improve the body’s resistance to S. aureus infection. However, it has also been reported that il6 inhibits the adverse effects of macrophages to IFN-γ responsiveness (Saleh et al., 2021). Met, mmp13, and ctsl are all related to cancer (Mo et al., 2017; Yang et al., 2017; Zhang et al., 2016). Further analysis should focus on understanding the molecular mechanism of the core genes that interact with TFs and their corresponding target genes in inflammation and the immune system (Gao et al., 2024).

This study provides evidence that immune functions, including immune response, cellular response to lipopolysaccharide, and the inflammatory response, are regulated by network nodes that contain ptgs2, mmp13, il12b, and met, together with TF jun. In the present study, we identified 14 genes in 10 nodes, of which only four genes (ptgs2, mmp13, il12b, and met) were regulated by four TFs (Table 4). In addition to met, which was regulated by most TFs, ptgs2, mmp13, and il12b significantly regulated TFs and network nodes. All network nodes were compared to previous studies (Kondo et al., 2000; Yamaguchi et al., 2005; Gokulnath et al., 2017; Utsugi et al., 2010; Cui et al., 2013) and we found that most of the network nodes were related on a certain level and strongly correlated with TF jun. The main GO terms of these network nodes are cytokine activity and growth factor activity, functioning immune response, cellular response to lipopolysaccharide, and inflammatory response. In addition, the most significant 10 pathways were associated with immune-related diseases, including S. aureus infection (Dusane et al., 2018), leishmaniasis (Jaton et al., 2016; Cui et al., 2017), rheumatoid arthritis (Insa et al., 2017), and tuberculosis (Ashtekar et al., 2016); however, immune-related TFs and information pathways, including the chemokine signaling (Joanna et al., 2017) and TNF signaling (Nandi et al., 2017) pathways, were closely associated with other diseases. Therefore, in general, these diseases and pathways were associated with immune function.

We successfully identified 437 DEGs from the GEO database to develop a TF regulatory network of S. aureus. We analyzed the genes met, mmp13, il12b, il4, tnf, ptgs2 and ctsl and transcription factors Jun, C3, Spil and il6 pathways, and found that most of these genes were on the TNF signaling pathway. At last, we hypothesized that met, mmp13, il12b, il4, tnf, and ptgs2 function together with TFs jun, c3, spil, and il6 to regulate inflammation and the immune system. The present study thus provides information and reference values for understanding the regulatory mechanisms of TFs and their network of S. aureus virulence genes.