Emmanuel Hitayezu , Intan Rizki Mauliasari , Seonmi Yu , Sung Hyun Moon , Bo-Ram Cho , Yoon-Han Kang , Sang Kyun Lim , Kwang Hyun Cha
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引用次数: 0
Abstract
Obesity is a global health concern closely linked to changes in gut microbiota and other metabolic disorders. In this study, we used 16S rRNA gene amplicon sequencing to analyze the gut microbiota composition of normal and obese fecal samples. We further investigated the influence of a beneficial gut microbiota combination, consisting of Phocaeicola vulgatus KBL981, Roseburia intestinalis KBL982, and Akkermansia muciniphila KBL983, strains considered beneficial for obesity management, using in vitro feces cultivation. Results showed a significant difference between the microbiota composition of normal and obesity fecal samples, with the obesity group displaying lower diversity and higher levels of pathogenic Shigella boydii and inflammation-related Bacteroides fragilis. The ideal beneficial gut microbiota mixture (1:1:100) significantly enhanced microbial diversity, balanced the short-chain fatty acid ratio, promoted the growth of beneficial bacteria, and inhibited the growth of harmful obesity-related species. However, oversupplementation of beneficial microbiota reduced the microbial diversity and disrupted the microbial ecosystem. The current study demonstrates that a combined beneficial gut microbiota treatment can help manage obesity-related dysbiosis.
期刊介绍:
The Journal of Microbiological Methods publishes scholarly and original articles, notes and review articles. These articles must include novel and/or state-of-the-art methods, or significant improvements to existing methods. Novel and innovative applications of current methods that are validated and useful will also be published. JMM strives for scholarship, innovation and excellence. This demands scientific rigour, the best available methods and technologies, correctly replicated experiments/tests, the inclusion of proper controls, calibrations, and the correct statistical analysis. The presentation of the data must support the interpretation of the method/approach.
All aspects of microbiology are covered, except virology. These include agricultural microbiology, applied and environmental microbiology, bioassays, bioinformatics, biotechnology, biochemical microbiology, clinical microbiology, diagnostics, food monitoring and quality control microbiology, microbial genetics and genomics, geomicrobiology, microbiome methods regardless of habitat, high through-put sequencing methods and analysis, microbial pathogenesis and host responses, metabolomics, metagenomics, metaproteomics, microbial ecology and diversity, microbial physiology, microbial ultra-structure, microscopic and imaging methods, molecular microbiology, mycology, novel mathematical microbiology and modelling, parasitology, plant-microbe interactions, protein markers/profiles, proteomics, pyrosequencing, public health microbiology, radioisotopes applied to microbiology, robotics applied to microbiological methods,rumen microbiology, microbiological methods for space missions and extreme environments, sampling methods and samplers, soil and sediment microbiology, transcriptomics, veterinary microbiology, sero-diagnostics and typing/identification.