The human gut microbiota (GM) has been associated, to date, with various complex functions, essentials for the host health. Among these, it is certainly worth noting the degradation of the so-called microbiota-accessible carbohydrates (MACs), which the GM breaks down through specific enzymes, referred to as carbohydrate-active enzymes (CAZymes). This degradation constitutes the first step in the production of short-chain fatty acids (SCFAs), key microbial small molecules having multiple health-promoting effects for the host organism. The decline in MAC dietary intake in urban Western populations forced the shrinkage of CAZyme repertoire in the GM, as shown by the literature comparing the microbiome layout between Western urban citizens and traditional rural populations. Even if this reduction in GM functional complexity has been associated with the onset of the so-called "diseases of civilization," only few information regarding the CAZyme variation within Western populations has been provided to date, and its connections with diet and health are still unexplored. In this scenario, here we explore the GM-encoded CAZyme repertoire across two Italian adult cohorts, including healthy lean subjects consuming a Mediterranean diet and obese patients affected by type 2 diabetes, consuming a high-fat diet. In order to impute the CAZyme panel, a pipeline consisting of publicly available software - QIIME, FragGeneScan and HMMER - was specifically implemented. Our study highlighted the existence of robust clusters of bacterial species sharing a common MAC degradation profile in the Italian GM, allowing the stratification of the individual GM into different steady states according to the carbohydrate degradation profile, with possible connections with diet and health.
Soverini, M., Turroni, S., Biagi, E., Quercia, S., Brigidi, P., Candela, M., et al. (2017). Variation of Carbohydrate-Active Enzyme Patterns in the Gut Microbiota of Italian Healthy Subjects and Type 2 Diabetes Patients. FRONTIERS IN MICROBIOLOGY, 8, 1-8 [10.3389/fmicb.2017.02079].
Variation of Carbohydrate-Active Enzyme Patterns in the Gut Microbiota of Italian Healthy Subjects and Type 2 Diabetes Patients
Soverini, Matteo;Turroni, Silvia;Biagi, Elena;Quercia, Sara;Brigidi, Patrizia;Candela, Marco;Rampelli, Simone
2017
Abstract
The human gut microbiota (GM) has been associated, to date, with various complex functions, essentials for the host health. Among these, it is certainly worth noting the degradation of the so-called microbiota-accessible carbohydrates (MACs), which the GM breaks down through specific enzymes, referred to as carbohydrate-active enzymes (CAZymes). This degradation constitutes the first step in the production of short-chain fatty acids (SCFAs), key microbial small molecules having multiple health-promoting effects for the host organism. The decline in MAC dietary intake in urban Western populations forced the shrinkage of CAZyme repertoire in the GM, as shown by the literature comparing the microbiome layout between Western urban citizens and traditional rural populations. Even if this reduction in GM functional complexity has been associated with the onset of the so-called "diseases of civilization," only few information regarding the CAZyme variation within Western populations has been provided to date, and its connections with diet and health are still unexplored. In this scenario, here we explore the GM-encoded CAZyme repertoire across two Italian adult cohorts, including healthy lean subjects consuming a Mediterranean diet and obese patients affected by type 2 diabetes, consuming a high-fat diet. In order to impute the CAZyme panel, a pipeline consisting of publicly available software - QIIME, FragGeneScan and HMMER - was specifically implemented. Our study highlighted the existence of robust clusters of bacterial species sharing a common MAC degradation profile in the Italian GM, allowing the stratification of the individual GM into different steady states according to the carbohydrate degradation profile, with possible connections with diet and health.File | Dimensione | Formato | |
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