Exploring the gut-lung axis in post-liver transplant acute lung injury: A multi-omics approach

Acute lung injury (ALI) is a significant post-operative complication of liver transplant (LT), with mounting evidence suggesting a role for the gut-lung axis. However, the mechanistic link between gut microbiota dysbiosis and ALI pathogenesis in LT recipients remains poorly understood. This hybrid translational investigation integrates transcriptomic profiling (bulk and single-cell RNA-seq), immune infiltration analysis, fecal microbiota composition (16S rRNA), and predictive functional profiling in ALI vs. non-ALI (NALI) LT patients. Machine learning algorithms (LASSO, SVM-RFE, Random Forest) were used to identify key gene biomarkers. Microbiota-host gene correlations and canonical correspondence analysis (CCA) were performed to evaluate multi-omic relationships. ALI patients exhibited reduced gut microbial diversity and increased abundance of Enterococcus and Escherichia-Shigella, alongside a depletion of beneficial taxa (Faecalibacterium, Bacteroides). CXCL3, CD48, and IRAK3 were identified as robust ALI biomarkers (Area Under the Curve >0.83), validated in both serum and Bronchoalveolar Lavage Fluid. These genes correlated positively with pro-inflammatory microbes and immune cell infiltration. Functional prediction revealed enrichment in lipopolysaccharide biosynthesis, Toll-like receptor signaling, and bacterial chemotaxis. CCA confirmed that microbiota variation significantly explained host transcriptomic variance. Our study uncovers a functional gut-lung immunological axis in post-LT ALI. Gut dysbiosis modulates immune gene expression and lung inflammation, suggesting that the microbiome serves as a potential source of diagnostic biomarkers and therapeutic targets in transplant-associated lung injury.