Microbiome and metabolome patterns after lung transplantation reflect underlying disease and chronic lung allograft dysfunction.

Background: Progression of chronic lung disease may lead to the requirement for lung transplant (LTx). Despite improvements in short-term survival after LTx, chronic lung allograft dysfunction (CLAD) remains a critical challenge for long-term survival. This study investigates the molecular and microbial relationships between underlying lung disease and the development of CLAD in bronchoalveolar lavage fluid (BALF) from subjects post-LTx, which is crucial for tailoring treatment strategies specific to allograft dysfunctions.

Methods: Paired 16S rRNA gene amplicon sequencing and untargeted LC-MS/MS metabolomics were performed on 856 BALF samples collected over 10 years from LTx recipients (n = 195) with alpha-1-antitrypsin disease (AATD, n = 23), cystic fibrosis (CF, n = 47), chronic obstructive pulmonary disease (COPD, n = 78), or pulmonary fibrosis (PF, n = 47). Data were analyzed using random forest (RF) machine learning and multivariate statistics for associations with underlying disease and CLAD development.

Results: The BALF microbiome and metabolome after LTx differed significantly according to the underlying disease state (PERMANOVA, p = 0.001), with CF and AATD demonstrating distinct microbiome and metabolome profiles, respectively. Uniqueness in CF was mainly driven by Pseudomonas abundance and its metabolites, whereas AATD had elevated levels of phenylalanine and a lack of shared metabolites with the other underlying diseases. BALF microbiome and metabolome composition were also distinct between those who did or did not develop CLAD during the sample collection period (PERMANOVA, p = 0.001). An increase in the average abundance of Veillonella (AATD, COPD) and Streptococcus (CF, PF) was associated with CLAD development, and decreases in the abundance of phenylalanine-derivative alkaloids (CF, COPD) and glycerophosphorylcholines (CF, COPD, PF) were signatures of the CLAD metabolome. Although the relative abundance of Pseudomonas was not associated with CLAD, the abundance of its virulence metabolites, including siderophores, quorum-sensing quinolones, and phenazines, were elevated in those with CF who developed CLAD. There was a positive correlation between the abundance of these molecules and the abundance of Pseudomonas in the microbiome, but there was no correlation between their abundance and the time in which BALF samples were collected post-LTx.

Conclusions: The BALF microbiome and metabolome after LTx are particularly distinct in those with underlying CF and AATD. These data reflect those who developed CLAD, with increased virulence metabolite production from Pseudomonas, an aspect of CF CLAD cases. These findings shed light on disease-specific microbial and metabolic signatures in LTx recipients, offering valuable insights into the underlying causes of allograft rejection. Video Abstract.