J Hanusrichterova, E Baranovicova, R Barosova, M Kolomaznik, P Mikolka, P Kosutova, D Mokra, J Mokry, A Calkovska
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引用次数: 0
Abstract
Introduction: Based on distinct triggers, bacterial and allergen-induced inflammatory reactions have different pathophysiology. Metabolomic analysis is high-throughput technique that can provide potential biomarkers to distinguish between these responses.
Objectives: In order to find out the metabolic profiles of two types of inflammation, metabolites were analysed in blood plasma and bronchoalveolar lavage fluid (BALF) of guinea pigs subjected to bacterial lipopolysaccharide (LPS) or allergen ovalbumin (OVA).
Methods: Hydrogen-1 nuclear magnetic resonance (1H NMR) spectroscopy for metabolite analysis was performed in samples of blood plasma and BALF of guinea pigs.
Results: Random forest algorithm built on combination of levels of circulating and BALF metabolites resulted in almost ideal discrimination between acute allergic and bacterial inflammation. The differences between inflammation triggered by LPS and OVA were manifested in shift in energy metabolism, metabolism of branched-chain amino acids (BCAAs)/branched-chain keto acids (BCKAs) with alterations in alanine and glutamine, which are linked with both, ammonia homeostasis as well as gluconeogenesis.
Conclusion: Distinct molecule nutrients are to be utilized during acute bacterial and allergic inflammatory response.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.