Resistance and resilience of fish gut microbiota to silver nanoparticles
Understanding mechanisms governing the resistance and resilience of microbial communities is essential for predicting their ecological responses to environmental disturbances. Although we have a good understanding of such issues for soil and lake ecosystems, how ecological resistance and resilience...
Main Authors: | , , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
American Society for Microbiology
2021
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
LEADER | 03521nam a2200721Ia 4500 | ||
---|---|---|---|
001 | 10.1128-mSystems.00630-21 | ||
008 | 220427s2021 CNT 000 0 und d | ||
020 | |a 23795077 (ISSN) | ||
245 | 1 | 0 | |a Resistance and resilience of fish gut microbiota to silver nanoparticles |
260 | 0 | |b American Society for Microbiology |c 2021 | |
856 | |z View Fulltext in Publisher |u https://doi.org/10.1128/mSystems.00630-21 | ||
520 | 3 | |a Understanding mechanisms governing the resistance and resilience of microbial communities is essential for predicting their ecological responses to environmental disturbances. Although we have a good understanding of such issues for soil and lake ecosystems, how ecological resistance and resilience regulate the microbiota in the fish gut ecosystem remains unclear. Using the zebrafish model, we clarified the potential mechanisms governing the gut microbiota after exposure to silver nanoparticles (AgNPs). Here, we explored the ecological resistance and resilience of gut microbiota in zebrafish exposed to different concentrations of AgNPs (i.e., 10, 33 and 100 mg/liter) for 15, 45, 75 days. The high-throughput sequencing analysis of the 16S rRNA gene showed that AgNP exposure significantly reduced the a-diversity of gut microbiota and resulted in obvious dynamics of community composition and structure. However, the rebound of zebrafish gut microbiota was pushed toward an alternative state after 15 days of AgNP exposure. We found that homogeneous selection was a more prevalent contributor in driving gut community recovery after AgNP exposure. The resilience and resistance of gut microbiota responses to AgNP disturbance might be mainly determined by the predominant keystone taxa such as Acinetobacter and Gemmata. This study not only expanded our understanding of fish gut microbiota's responses to pollutants but also provided new insights into maintaining host-microbiome stability during environmental perturbations. © 2021 Chen et al. | |
650 | 0 | 4 | |a Acinetobacter |
650 | 0 | 4 | |a adult |
650 | 0 | 4 | |a Akkermansia |
650 | 0 | 4 | |a animal experiment |
650 | 0 | 4 | |a Article |
650 | 0 | 4 | |a bacterial RNA |
650 | 0 | 4 | |a Citrobacter |
650 | 0 | 4 | |a community structure |
650 | 0 | 4 | |a concentration (parameter) |
650 | 0 | 4 | |a controlled study |
650 | 0 | 4 | |a ecosystem resilience |
650 | 0 | 4 | |a environmental exposure |
650 | 0 | 4 | |a female |
650 | 0 | 4 | |a Firmicutes |
650 | 0 | 4 | |a Fusobacteria |
650 | 0 | 4 | |a Gemmata |
650 | 0 | 4 | |a Gut microbiota |
650 | 0 | 4 | |a hierarchical clustering |
650 | 0 | 4 | |a high throughput sequencing |
650 | 0 | 4 | |a intestine flora |
650 | 0 | 4 | |a male |
650 | 0 | 4 | |a microbial community |
650 | 0 | 4 | |a microbial diversity |
650 | 0 | 4 | |a nonhuman |
650 | 0 | 4 | |a physical resistance |
650 | 0 | 4 | |a pollutant |
650 | 0 | 4 | |a Proteobacteria |
650 | 0 | 4 | |a rebound |
650 | 0 | 4 | |a Resilience |
650 | 0 | 4 | |a Resistance |
650 | 0 | 4 | |a RNA 16S |
650 | 0 | 4 | |a silver nanoparticle |
650 | 0 | 4 | |a Silver nanoparticles |
650 | 0 | 4 | |a Thermus |
650 | 0 | 4 | |a zebra fish |
650 | 0 | 4 | |a Zebrafish |
700 | 1 | |a Chen, P. |e author | |
700 | 1 | |a Chen, X. |e author | |
700 | 1 | |a He, Z. |e author | |
700 | 1 | |a Hu, R. |e author | |
700 | 1 | |a Huang, J. |e author | |
700 | 1 | |a Rao, L. |e author | |
700 | 1 | |a Wu, Y. |e author | |
700 | 1 | |a Xiao, F. |e author | |
700 | 1 | |a Xu, K. |e author | |
700 | 1 | |a Yan, Q. |e author | |
700 | 1 | |a Yu, H. |e author | |
700 | 1 | |a Yu, Y. |e author | |
700 | 1 | |a Zheng, X. |e author | |
700 | 1 | |a Zhu, W. |e author | |
773 | |t mSystems |