| Synthetic gut microbiome: Advances and challenges | |
|---|---|
| 년도 | 2021 |
| 날짜 | 2020 Dec 24 |
| 페이지 / 학회지명 |
19:363-371 / Computational and Structural Biotechnology Journal |
| 논문저자 | Humphrey A Mabwi 1 2, Eunjung Kim 1, Dae-Geun Song 1, Hyo Shin Yoon 1, Cheol-Ho Pan 1, Erick V G Komba 2, GwangPyo Ko 3 4 5, Kwang Hyun Cha 1 |
| Link |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7787941/
95회 연결
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2 SACIDS Foundation for One Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, Morogoro 25523, Tanzania. 3 Department of Environmental Health Sciences, School of Public Health, Seoul National University, Seoul 08826, Republic of Korea. 4 Center for Human and Environmental Microbiome, Seoul National University, Seoul 08826, Republic of Korea. 5 KoBioLabs, Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea. Abstract An exponential rise in studies regarding the association among human gut microbial communities, human health, and diseases is currently attracting the attention of researchers to focus on human gut microbiome research. However, even with the ever-growing number of studies on the human gut microbiome, translation into improved health is progressing slowly. This hampering is due to the complexities of the human gut microbiome, which is composed of >1,000 species of microorganisms, such as bacteria, archaea, viruses, and fungi. To overcome this complexity, it is necessary to reduce the gut microbiome, which can help simplify experimental variables to an extent, such that they can be deliberately manipulated and controlled. Reconstruction of synthetic or established gut microbial communities would make it easier to understand the structure, stability, and functional activities of the complex microbial community of the human gut. Here, we provide an overview of the developments and challenges of the synthetic human gut microbiome, and propose the incorporation of multi-omics and mathematical methods in a better synthetic gut ecosystem design, for easy translation of microbiome information to therapies. Keywords: Gut ecosystem; Mathematical modelling; Omics; Synthetic microbiota. |
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