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GNPS - Multi-omic analysis of antagonistic interactions among free-living Pseudonocardia from diverse ecosystems

ABSTRACT: Multi-omic analysis of antagonistic interactions among free-living Pseudonocardia

INSTRUMENT(S): Q Exactive

ORGANISM(S): Pseudonocardia Petroleophila (ncbitaxon:37331) Pseudonocardia Oceani Pseudonocardia Abyssalis Pseudonocardia Sp. Krd291 Pseudonocardia Ammonioxydans (ncbitaxon:260086) Pseudonocardia Sp. Cns139 Pl04 (ncbitaxon:378601) Pseudonocardia Antitumoralis (ncbitaxon:1070982) Pseudonocardia Sediminis (ncbitaxon:1397368) Pseudonocardia Profundimaris (ncbitaxon:1804989) Pseudonocardia Hydrocarbonoxydans (ncbitaxon:76726) Pseudonocardia Sp. Vo44-3 (ncbitaxon:1673802)

SUBMITTER: Katherine Duncan

PROVIDER: MSV000091009 | GNPS | Wed Jan 04 16:23:00 GMT 2023

REPOSITORIES: GNPS

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Project description:A multi-omic approach in a clinical experimental study identified circulating biomarkers reflecting glucocorticoid exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study. Methods: In a randomized, crossover, single-blind trial, subjects with primary adrenal insufficiency received intravenous hydrocortisone infusion in a circadian pattern (physiological GC exposure) or isotonic saline (GC withdrawal) over 22 hours. Samples were collected at 7 AM (end of infusion). Integrated multi-omic analysis was used because of the complexity in GC action and the low number of subjects. The transcriptome in peripheral blood mononuclear cells (PBMCs) and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions. Replication of the plasma miRNA findings was performed in three independent studies. Results: During GC withdrawal, overnight urinary cortisol and cortisone excretion were undetectable. Correlation and hypernetwork analyses identified a transcriptomic profile derived from PBMCs and adipose tissue predictive of GC exposure, and a multi-omic cluster predictive of GC exposure. From the circulating ‘omic data, decreased expression of plasma miR-122-5p was associated with increased GC exposure. This finding was reproduced in three independent studies. Conclusion: We developed a human experimental model for physiological GC exposure and withdrawal. The integrated multi-omic data identified circulating miRNAs and metabolites associated with GC-responsive genes. In independent studies, miR-122-5p was shown to be associated with GC exposure. Background: Endogenous glucocorticoids (GC) are mechanistically linked to common diseases and are important as drugs in the treatment of many disorders. There is no marker that can measure and quantify GC action. Our aim was to identify circulating biomarkers of GC action using a clinical experimental study.

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GNPS - Multi-omic analysis of antagonistic interactions among free-living Pseudonocardia from diverse ecosystems

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