Conclusions
This study provides a detailed view of the molecular mechanisms underlying inflammation in macrophages and reveals a dynamic genetic landscape crucial for further research. Our findings underscore the complex interaction between gene expression, metabolic shifts, and ribosomal functions in response to LPS-induced inflammation.
Methods
We utilized RNA sequencing (RNA-seq) to analyze dynamic changes in gene expression in RAW264.7 macrophages treated with LPS at multiple time points. Differentially expressed genes (DEGs) were identified using the edgeR package. Short Time-series Expression Miner (STEM) and KEGG pathway enrichment analyses were conducted to determine temporal expression patterns during inflammation.
Results
We identified 2,512 DEGs, with initial inflammatory responses occurring in two distinct phases at 1 h and 3 h. Venn diagram analysis revealed 78 consistently dysregulated genes throughout the inflammatory process. A key module of 18 dysregulated genes was identified, including Irg1, which may exert an inhibitory effect on inflammation. Further, a second metabolic shift in activated macrophages was observed at the late middle stage (12 h). Multi-omics analysis highlighted the ribosome's potential regulatory role in the inflammatory response. Conclusions: This study provides a detailed view of the molecular mechanisms underlying inflammation in macrophages and reveals a dynamic genetic landscape crucial for further research. Our findings underscore the complex interaction between gene expression, metabolic shifts, and ribosomal functions in response to LPS-induced inflammation.