Mechanistic links between gut microbial community dynamics, microbial functions and metabolic health

被引:89
作者
Ha, Connie W. Y. [1 ,2 ]
Lam, Yan Y. [3 ]
Holmes, Andrew J. [1 ,2 ]
机构
[1] Univ Sydney, Sch Mol Biosci, Camperdown, NSW 2006, Australia
[2] Univ Sydney, Charles Perkins Ctr, Camperdown, NSW 2006, Australia
[3] Pennington Biomed Res Ctr, Baton Rouge, LA 70808 USA
关键词
Microbiome; Dysbiosis; High fat diet; Bile; Intestinal mucosa; Microbe-associated molecular patterns; Short chain fatty acids; Immunomodulation; Enteroendocrine cells; CHAIN FATTY-ACIDS; DIET-INDUCED OBESITY; PROTEIN-COUPLED RECEPTOR; INFLAMMATORY-BOWEL-DISEASE; INCREASED INTESTINAL PERMEABILITY; GLUCAGON-LIKE PEPTIDE-1; LOW-GRADE INFLAMMATION; REGULATORY T-CELLS; GERM-FREE MICE; INSULIN-RESISTANCE;
D O I
10.3748/wjg.v20.i44.16498
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Gut microbes comprise a high density, biologically active community that lies at the interface of an animal with its nutritional environment. Consequently their activity profoundly influences many aspects of the physiology and metabolism of the host animal. A range of microbial structural components and metabolites directly interact with host intestinal cells and tissues to influence nutrient uptake and epithelial health. Endocrine, neuronal and lymphoid cells in the gut also integrate signals from these microbial factors to influence systemic responses. Dysregulation of these host-microbe interactions is now recognised as a major risk factor in the development of metabolic dysfunction. This is a two-way process and understanding the factors that tip host-microbiome homeostasis over to dysbiosis requires greater appreciation of the host feedbacks that contribute to regulation of microbial community composition. To date, numerous studies have employed taxonomic profiling approaches to explore the links between microbial composition and host outcomes (especially obesity and its comorbidities), but inconsistent host-microbe associations have been reported. Available data indicates multiple factors have contributed to discrepancies between studies. These include the high level of functional redundancy in host-microbiome interactions combined with individual variation in microbiome composition; differences in study design, diet composition and host system between studies; and inherent limitations to the resolution of rRNA-based community profiling. Accounting for these factors allows for recognition of the common microbial and host factors driving community composition and development of dysbiosis on high fat diets. New therapeutic intervention options are now emerging. (C) 2014 Baishideng Publishing Group Inc. All rights reserved.
引用
收藏
页码:16498 / 16517
页数:20
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