Simulation of the mucosal environment in the re-construction of the synthetic gut microbial ecosystem.


Journal

Journal of microbiological methods
ISSN: 1872-8359
Titre abrégé: J Microbiol Methods
Pays: Netherlands
ID NLM: 8306883

Informations de publication

Date de publication:
12 2021
Historique:
received: 27 08 2021
revised: 22 10 2021
accepted: 22 10 2021
pubmed: 29 10 2021
medline: 21 1 2022
entrez: 28 10 2021
Statut: ppublish

Résumé

Human gut surface-attached mucosal microbiota plays significant roles in human health and diseases. This study sought to simulate the mucosal environment using mucin-agar gel and synthetic mucosal microbial community in vitro. To select suitable culture media, microbial communities were assembled and cultured in seven different media at 37 °C for 36 h. Among the seven media, Bryant & Burkey (BB) and Gifu Anaerobic Media (GAM) were selected considering their microbial biomass and bacterial composition. The communities were again assembled and cultured in these two media with mucin-agar. The results showed that some bacterial genus such as Bifidobacterium, Collinsella, and Roseburia could efficiently colonize in the solid mucin-agar part while Enterococcus, Clostridium, and Veilonella dominated in the liquid part. Metabolic functional prediction for the microbial community in each medium part showed that the gene expression involved in metabolism and cell motility pathways were distinctively differentiated between the liquid and solid medium part, and the functional potential was highly related to the microbial composition. The current results demonstrate that the simulation of the gut microbial ecosystem in vitro can be beneficial to the mucosal environment mimicking and the study on the mechanistic potential of the human gut microbiota for easy translation of microbiome research to therapies.

Identifiants

pubmed: 34710513
pii: S0167-7012(21)00219-0
doi: 10.1016/j.mimet.2021.106351
pii:
doi:

Substances chimiques

Culture Media 0
Mucins 0
Agar 9002-18-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

106351

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Humphrey A Mabwi (HA)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea; SACIDS Foundation for One Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, Morogoro 25523, Tanzania; Department of Veterinary Microbiology, Parasitology and Biotechnology, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, Morogoro, P.O. Box 3019, Tanzania. Electronic address: mabwi.humphrey@kist.re.kr.

Emmanuel Hitayezu (E)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea. Electronic address: 220528@kist.re.kr.

Intan Rizki Mauliasari (IR)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea. Electronic address: intanmauliasari@kist.re.kr.

Kilaza Samson Mwaikono (KS)

Department of Science and Laboratory Technology, Dar es Salaam Institute of Technology, Dar es Salaam 11000, Tanzania. Electronic address: kilazasmsn24@gmail.com.

Hyo Shin Yoon (HS)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea. Electronic address: hsyoon@kist.re.kr.

Erick V G Komba (EVG)

SACIDS Foundation for One Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, Morogoro 25523, Tanzania. Electronic address: ekomba@sua.ac.tz.

Cheol-Ho Pan (CH)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea. Electronic address: panc@kist.re.kr.

Kwang Hyun Cha (KH)

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung 25451, South Korea. Electronic address: chakh79@kist.re.kr.

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Classifications MeSH