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Multi-Solvent Extraction Procedure for the Pioneer Fecal Metabolomic Analysis-Identification of Potential Biomarkers in Stable Kidney Transplant Patients.

ABSTRACT: Metabolic alteration plays a functional role in kidney allograft complications. Metabolomics is a promising high-throughput approach in nephrology but is still limited by the lack of overlap in metabolite coverage. We performed an untargeted fecal metabolomic analysis of forty stable kidney allograft recipients and twenty non-transplant controls. First, we applied the ultra-high performance liquid chromatography (UHPLC) analysis coupled with the Diod Array detector. The potential biomarkers were then collected and identified by gas chromatography-mass spectrometry (GCMS). In order to allow for complete coverage of the fecal polar and non-polar metabolites, the performance of five organic solvents with increasing polarity was investigated successively. UHPLC analysis revealed that the fecal metabolite profiles following the five extractions were significantly different between controls and kidney allografts. GC-MS analysis showed that the best predictors' metabolites belonged mainly to long-chain fatty acids, phenolic compounds, and amino acids. Collectively, our results showed the efficiency of our pioneer method to successfully discriminate stable kidney-transplant recipients from controls. These findings suggest that distinct metabolic profiles mainly affect fatty acid biosynthesis and amino acid metabolism. In such a context, the novel insights into metabolomic investigation may be a valuable tool that could provide useful new relevant biomarkers for preventing kidney transplant complications.

SUBMITTER: Kouidhi S

PROVIDER: S-EPMC8229050 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Being able to identify patients in whom immunological tolerance has been established or is developing would allow an individually tailored approach to post-transplant management of kidney allograft recipients. Ex vivo immunological monitoring was performed on samples from five groups of European renal transplant recipients (“IOT samples”): ten drug-free tolerant recipients who were functionally stable despite remaining immunosuppression-free for more than one year (Tol-DF); also functionally stable patients on minimal immunosuppression (<10 mg/day prednisone, s-LP); stable patients maintained with calcineurin inhibitors (s-CNI); stable patients maintained on CNI-free immunosuppression regimen (s-nCNI); patients showing signs of chronic rejection (CR) and healthy controls (HC). Among the investigation of other biomarkers and bioassays, gene expression profiles were generated on custom Agilent 8x15K 60mer oligonucleotide microarrays (“RISET 2.0”) on the IOT cohort (training set) and on an independent cohort of patients from the ITN (USA) that contained similar groups of patients and included 23 tolerant recipients (“ITN samples”, test set). Set of genes were identified, whose expression on whole blood allowed the identification of 100% of the tolerant recipients in the training set and 84% in the test set. Keywords: classification of clinical samples, tolerance prediction IOT samples: 13 samples from 10 Tol-DF patients, 16 samples from 11 s-LP patients, 8 samples from 8 s-nCNI patients, 40 samples from 28 s-CNI patients, 10 samples from 9 CR patients, and 8 samples from 8 HC donors were analysed on a custom Agilent 8x15K 60mer oligonucleotide microarray encomprising 5069 probes in triplicates. The microarray is dedicated to transplantation research and was designed based on current literature and published and unpublished data provided by the RISET consortium. For the probe selection procedure we specially focused on the detection of multiple transcript variants of a gene, on optimized hybridization properties of the probes, and on the avoidance of crosshybridization. The sampling dates of replicate samples from the same patient range from one day to 1.5 years. ITN samples: 31 samples from 23 Tol-DF patients, 14 samples from 11 s-LP patients, 52 samples from 34 s-CNI patients, 25 samples from 18 CR patients, and 20 samples from 20 HC donors were analysed on the same microarray platform and served as test set. The samples of the two cohorts differ in the protocol of RNA preparation.

Dataset Information

Multi-Solvent Extraction Procedure for the Pioneer Fecal Metabolomic Analysis-Identification of Potential Biomarkers in Stable Kidney Transplant Patients.

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