Urinary metabolomic profiling from spontaneous tolerant kidney transplanted recipients shows enrichment in tryptophan-derived metabolites

Lactobacillus species ameliorate membranous nephropathy through inhibiting the aryl hydrocarbon receptor pathway via tryptophan-produced indole metabolites

BACKGROUND AND PURPOSE

Membranous nephropathy (MN) is an immune-mediated glomerular disease in adults. Antibody- and antigen-bonding mechanisms have been largely clarified, but the subepithelium immune complex deposition-mediated downstream molecular mechanisms are currently unresolved. Increasing evidence has suggested that gut microbiota contribute to MN pathogenesis.

EXPERIMENTAL APPROACH

In this study, we identified alterations in faecal gut microbiota and serum metabolites that mediate an aryl hydrocarbon receptor (AhR) mechanism in cationic bovine serum albumin (CBSA)-induced MN rats and in patients with idiopathic MN (IMN).

KEY RESULTS

Impaired renal function correlated with the relative abundance of reduced faecal probiotics, Lactobacillus and Bifidobacterium, and altered serum levels of tryptophan-produced indole derivatives (TPIDs) in MN rats. Further results showed that reduced relative abundance of five probiotics, namely Lactobacillus johnsonii, Lactobacillus murinus, Lactobacillus vaginalis, Lactobacillus reuteri and Bifidobacterium animalis, positively correlated with decreased levels of indole-3-pyruvic acid, indole-3-aldehyde and tryptamine and negatively correlated with increased levels of indole-3-lactic acid and indole-3-acetic acid in serum of MN rats. Altered five probiotics and five TPIDs also were observed in patients with IMN. Further studies showed that MN rats exhibited a significant increase in intrarenal mRNA expression of AhR and its target genes CYP1A1, CYP1A2 and CYP1B1, which were accompanied by protein expression of down-regulated cytoplasmic AhR, but up-regulated nuclear AhR, in MN rats and IMN patients.

CONCLUSION AND IMPLICATIONS

Activation of the intrarenal AhR signalling pathway may involve five TPIDs. These data suggest that gut microbiota could influence MN through TPIDs that engage host receptors.

"Transplantomics" for predicting allograft rejection: real-life applications and new strategies from Network Medicine

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppression therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cellular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision medicine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The application of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.