Cargando…

The Alteration of Akkermansiaceae/Lachnospiraceae Ratio Is a Microbial Feature of Antibiotic-Induced Microbiota Remodeling

Antibiotic treatment has been shown to cause gut microbiota dysbiosis. However, lacking critical features defining gut microbiota dysbiosis makes it challenging to prevent. By co-occurrence network analysis, we found that despite short antibiotic courses eliminating certain microbial taxa, the Akker...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Pei-Chen, Lin, Ming-Shian, Lin, Tien-Ching, Kang, Ting-Wei, Ruan, Jhen-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108413/
https://www.ncbi.nlm.nih.gov/pubmed/37077899
http://dx.doi.org/10.1177/11779322231166229
Descripción
Sumario:Antibiotic treatment has been shown to cause gut microbiota dysbiosis. However, lacking critical features defining gut microbiota dysbiosis makes it challenging to prevent. By co-occurrence network analysis, we found that despite short antibiotic courses eliminating certain microbial taxa, the Akkermansia genus played the role of a high-centrality hub to maintain microbiota homeostasis. When the antibiotic courses continued, the elimination of Akkermansia induced a significant microbiota remodeling of the gut microbiota networks. Based on this finding, we found that under long-term antibiotic stress, the gut microbiota was rearranged into a stable network with a significantly lower Akkermansiaceae/Lachnospiraceae (A/L) ratio and no microbial hub. By functional prediction analysis, we confirmed that the gut microbiota with a low A/L ratio also had enhanced mobile elements and biofilm-formation functions that may be associated with antibiotic resistance. This study identified A/L ratio as an indicator of antibiotic-induced dysbiosis. This work reveals that besides the abundance of specific probiotics, the hierarchical structure also critically impacts the microbiome function. Co-occurrence analysis may help better monitor the microbiome dynamics than only comparing the differentially abundant bacteria between samples.