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Development of Electronic-nose Technologies for Early Disease Detection based on Microbial Dysbiosis
* 1 , 2
1  USDA Forest Service
2  USDA Forest Service, Southern Research Station, Government Contractor

Abstract:

A new frontier in clinical disease diagnostics was launched by a series of recent discoveries of a new phenomenon that makes important connections between the metabolic activities of resident microbes and human diseases. Numerous recent studies have demonstrated that the mechanisms leading to disease development involve not only pathogenesis, but also activities and interactions between the complex assemblage of microbes (microbiota) in the oral cavity, lungs, and gut, the microbial metabolites they produce, and the host immune system. These interactions may occur by either metabolism-dependent or metabolism-independent pathways. Consequently, dysbiosis or changes in microbiota composition, often modulate disease development by at least two different mechanisms, including disease-induced dysbiosis and alterations in dysbiotic patterns caused by abiotic, exogenous factors (diet, drug use, and various environmental factors). This paper summarizes recent evidence demonstrating how electronic-nose (e-nose) technologies with multisensor arrays could potentially be used to identify specific changes in microbiome composition, microbiome diversity, and related alterations in patterns of metabolic pathways at different locations in the body. This could be achieved through detections and discriminations between specific chemical VOC-biomarkers, products of microbial metabolism, identified in healthy patients and those related to dysbiosis associated with specific diseases. Recent advances in e-nose technologies, having capabilities of detecting complex mixtures of VOC-metabolites in the headspace of clinical samples, offer new tools for exploiting the common occurrence of microbial dysbiotic mechanisms for noninvasive early disease detection.

Keywords: bacterial dysbiosis; disease biomarkers; early noninvasive diagnoses; electronic aroma detection; e-nose devices; microbiome composition; volatile organic compounds
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