Knowledge graph-driven curation of heme-TLR4 interactions in inflammatory pathways

Abstract

Heme, a vital iron-containing molecule, serves fundamental roles in oxygen transport and electron transfer but also acts as an extracellular signaling entity, significantly influencing inflammatory responses. Elevated levels of labile heme resulting from hemolytic events or therapeutic treatments may activate inflammatory signaling pathways, particularly through the Toll-like receptor 4 (TLR4). In this study, we systematically expanded the previously developed Heme Knowledge Graph (HemeKG) to comprehensively incorporate recent findings regarding heme-TLR4 interactions. By employing rigorous literature curation and validation using Biological Expression Language (BEL) standards and the e:BEL Python package, we successfully integrated newly identified molecular entities, notably activator protein 1 (AP-1), interleukin-12 (IL-12), cluster of differentiation 80 (CD80), cluster of differentiation 86 (CD86), and chemokine (C-X-C motif) ligand 1 (CXCL1), into the existing HemeKG framework. Pathway enrichment analysis across Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and WikiPathways databases robustly supported these integrations, consistently identifying significant enrichment of the TLR4 signaling cascade. The updated HemeKG thus provides an integrated and predictive platform, enhancing our understanding of the complex interactions between heme-driven inflammatory pathways and metabolic dysregulation.