Intrahepatic donor microbiota-based metataxonomic signature detected in organ preservation solution enables prediction of short-term liver transplant outcomesOriginal paper
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.
Read MoreWhat was studied?
This study characterized the microbial DNA profile present in organ preservation solution (OPS) used during liver transplantation, using 16S rRNA sequencing. The researchers asked whether specific microbial taxa detected in the OPS, reflecting the intrahepatic graft's native microbiota, are associated with short-term clinical outcomes after transplant. They also built machine learning models to predict outcomes from these microbial features and used RNA sequencing of matched liver biopsies to validate host-microbiome interactions.
Who was studied?
The discovery cohort consisted of 110 liver transplant donors, with an independent validation cohort of 29 additional donors. Microbial signatures were derived from the organ preservation solution collected in association with each donor's liver, rather than from patient stool or blood samples. Clinical outcome data for recipients were linked to these donor-derived OPS samples using MaAsLin2-adjusted statistical models.
What were the most important findings?
The microbial DNA signature detected in the OPS closely resembled known liver and bile microbiome profiles and was dominated by Proteobacteria. Specific bacterial genera, including Bacillus and Prevotella, were differentially abundant and statistically associated with adverse post-transplant outcomes, being hyperabundant in cases with worse results. Gene pathway enrichment analysis and RNA sequencing of matched liver biopsies were used to explore host-microbiome interactions underlying these associations.
What are the greatest implications of this study?
This work suggests that the intrahepatic graft's own microbiota, detectable in the preservation solution at the time of transplant, carries prognostic information that has previously been overlooked in favor of gut microbiota studies. Machine learning models built on these OPS-derived microbial features could enable early risk stratification for liver transplant recipients before complications arise. If validated further, this approach could support a practical, minimally invasive tool for predicting short-term transplant outcomes.