BetaEntity Annotation Prototype
← Back to diseases

Annotated abstract

Intrahepatic donor microbiota-based metataxonomic signature detected in organ preservation solution enables prediction of short-term liver transplant outcomes

gutjnl · 2025-11-10 · canonical JSON source

3 visible annotations · policy: published · automated confidence ≥ 75.00%

Document resource

Background Liver transplantation (LT) remains hampered by post-transplant complications. While gut microbiota dysbiosis has been linked to transplant outcomes, the role of the intrahepatic graft’s native microbiota remains unexplored.Objective To characterise the microbial profile detected in organ preservation solution (OPS) and determine whether specific microbial taxa are associated with short-term clinical outcomes, and to develop predictive models for risk stratification.Design We analysed the OPS microbiota-based metataxonomic signature from 110 LT donors (discovery cohort) and an independent validation cohort (n=29) using 16S rRNA sequencing. Microbial DNA signatures associated with clinical outcomes were identified through MaAsLin2-adjusted models, and relevant gene pathways were uncovered via data mining and enrichment analysis. Machine learning (ML) models were developed to predict outcomes based on microbial features, and host–microbiome interactions were validated through RNA sequencing (RNA-seq of matched liver biopsies).Results OPS-derived microbial DNA signature closely resembled liver/bile microbiomes (Proteobacteria-dominated). Specific genera (eg, Bacillus, Prevotella) were differentially abundant in adverse outcomes (p<0.05): hyperabundant in non-survivors and hepatic artery thrombosis, hypoabundant in acute rejection (AR). Gene mining linked these taxa to immune/metabolic pathways relevant to LT outcomes. RNA-seq validated upregulation of chemokines (CCL/CXCL families) in liver grafts from non-surviving recipients. ML models accurately predicted global survival (area under the curve (AUC)=0.95) and AR (AUC=0.96) based on microbial features, with generalisability confirmed in the validation cohort (AUC=0.85–0.88).Conclusion Donor intrahepatic microbial DNA signature predicts LT outcomes via immune-metabolic modulation. While causality requires further study, these findings position the graft microbiome as a novel biomarker and potential therapeutic target, paving the way for microbiome-informed precision care in transplantation.