Synthetic gut microbiome: Advances and challenges
| Autor: | Dae-Geun Song, Kwang Hyun Cha, Erick V.G. Komba, Hyo Shin Yoon, Humphrey A. Mabwi, Cheol-Ho Pan, GwangPyo Ko, Eunjung Kim |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Gut ecosystem
Biophysics Omics Computational biology Review Article Biology Biochemistry digestive system 03 medical and health sciences Human health 0302 clinical medicine Human gut Structural Biology Genetics Microbiome Synthetic microbiota 030304 developmental biology 0303 health sciences Mathematical modelling digestive oral and skin physiology Gut microbiome Computer Science Applications 030220 oncology & carcinogenesis Functional activity TP248.13-248.65 Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 363-371 (2021) |
| ISSN: | 2001-0370 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|