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Profiles of Microbial Fatty Acids in the Human Metabolome are Disease-Specific
The human gastrointestinal tract is inhabited by a diverse and dense symbiotic microbiota, the composition of which is the result of host–microbe co-evolution and co-adaptation. This tight integration creates intense cross-talk and signaling between the host and microbiota at the cellular and metabo...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109323/ https://www.ncbi.nlm.nih.gov/pubmed/21687748 http://dx.doi.org/10.3389/fmicb.2010.00148 |
Sumario: | The human gastrointestinal tract is inhabited by a diverse and dense symbiotic microbiota, the composition of which is the result of host–microbe co-evolution and co-adaptation. This tight integration creates intense cross-talk and signaling between the host and microbiota at the cellular and metabolic levels. In many genetic or infectious diseases the balance between host and microbiota may be compromised resulting in erroneous communication. Consequently, the composition of the human metabolome, which includes the gut metabolome, may be different in health and disease states in terms of microbial products and metabolites entering systemic circulation. To test this hypothesis, we measured the level of hydroxy, branched, cyclopropyl and unsaturated fatty acids, aldehydes, and phenyl derivatives in blood of patients with a hereditary autoinflammatory disorder, familial Mediterranean fever (FMF), and in patients with peptic ulceration (PU) resulting from Helicobacter pylori infection. Discriminant function analysis of a data matrix consisting of 94 cases as statistical units (37 FMF patients, 14 PU patients, and 43 healthy controls) and the concentration of 35 microbial products in the blood as statistical variables revealed a high accuracy of the proposed model (all cases were correctly classified). This suggests that the profile of microbial products and metabolites in the human metabolome is specific for a given disease and may potentially serve as a biomarker for disease. |
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