In vitro transcriptomic profiling reveals extensive alternative splicing shifts in human PBMCs after LPS exposure, highlighting novel regulatory controls in inflammation.
Background Lipopolysaccharide (LPS), a major component of gram-negative bacterial cell walls, elicits strong innate immune activation and is a widely used model for studying inflammatory responses. While the transcriptional response to LPS stimulation has been characterized, the role of alternative splicing (AS) in modulating this response remains largely unexplored. Using deep RNA sequencing of Peripheral Blood Mononuclear Cells from three healthy female donors, we evaluated for (1) transcriptome-wide differential gene expression and (2) differential alternative splicing in response to LPS stimulation. Results Our global differential gene expression and pathway impact analyses identified 490 differentially expressed genes and 46 significantly perturbed KEGG pathways, recapitulating known LPS-induced inflammatory responses and identifying two previously unidentified novel signaling pathways, (e.g., SNARE interactions in vesicular transport and the mRNA surveillance pathways). Differential alternative splicing analysis revealed critical impacts on immune-related pathways, including Toll-like receptor signaling, PI3K/AKT signaling, and pro-inflammatory macrophage polarization. Notably, we identified alternative splicing events in genes such as MyD88 and TLR4 , which play key roles in terminating inflammatory signaling, as well as splicing of long non-coding RNAs (e.g., MALAT1 , PVT1 ) with potential regulatory functions in immune responses. Conclusion This study is the first transcriptome-wide characterization of alternative splicing in response to LPS stimulation of PBMCs in women. Our findings suggest that alternative splicing is a fundamental regulatory mechanism in the inflammatory response and provides potential targets for therapeutic intervention in immune-related conditions (e.g., infection, disease, neurodegeneration, and adverse side effects of treatments).
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Iglesias et al. (2026) studied this question.
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