Synthetic gut microbiome: Advances and challenges
| dc.contributor.author | Mabwi, Humphrey A. | |
| dc.contributor.author | Kim, Eunjung | |
| dc.contributor.author | Song, Dae-Geun | |
| dc.contributor.author | Yoon, Hyo Shin | |
| dc.contributor.author | Pan, Cheol-Ho | |
| dc.contributor.author | Komba, Erick V.G. | |
| dc.contributor.author | Ko, GwangPyo | |
| dc.contributor.author | Hyun Cha, Kwang | |
| dc.date.accessioned | 2025-09-24T09:23:20Z | |
| dc.date.available | 2025-09-24T09:23:20Z | |
| dc.date.issued | 2020 | |
| dc.description | Journal article | |
| dc.description.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 micro- biome, 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 manip- ulated 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 commu- nity 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. | |
| dc.description.sponsorship | intramural grant (2Z06220) from the Korea Institute of Science and Technology (KIST), Republic of Korea, in collaboration with the Regional Schol- arship and Innovation Fund of the Partnership for Skills in Applied Sciences, Engineering and Technology (RSIF-PASET). | |
| dc.identifier.citation | https://doi.org/10.1016/j.csbj.2020.12.029 | |
| dc.identifier.uri | https://www.suaire.sua.ac.tz/handle/123456789/7037 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.subject | Synthetic microbiota | |
| dc.subject | Gut ecosystem | |
| dc.subject | Omics | |
| dc.subject | Mathematical modelling | |
| dc.title | Synthetic gut microbiome: Advances and challenges | |
| dc.type | Article |