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Cited by 269

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Exploring fish microbial communities to mitigate emerging diseases in aquaculture

Open access
de Bruijn, Irene, Liu, Yiying, Wiegertjes, Geert F, Raaijmakers, Jos M·2018·FEMS Microbiology Ecology

Abstract

Aquaculture is the fastest growing animal food sector worldwide and expected to further increase to feed the growing human population. However, existing and (re-)emerging diseases are hampering fish and shellfish cultivation and yield. For many diseases, vaccination protocols are not in place and the excessive use of antibiotics and other chemicals is of substantial concern. A more sustainable disease control strategy to protect fish and shellfish from (re-)emerging diseases could be achieved by introduction or augmentation of beneficial microbes. To establish and maintain a 'healthy' fish microbiome, a fundamental understanding of the diversity and temporal-spatial dynamics of fish-associated microbial communities and their impact on growth and health of their aquatic hosts is required. This review describes insights in the diversity and functions of the fish bacterial communities elucidated with next-generation sequencing and discusses the potential of the microbes to mitigate (re-)emerging diseases in aquaculture.

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Crossref · 10.1093/femsec/fix161

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Metadata

Authors
de Bruijn, I., Liu, Y., Wiegertjes, G. F., & Raaijmakers, J. M.
Venue
FEMS Microbiology Ecology
Published
2017-11-29
Volume
94
Issue
1
ISSN
  • 0168-6496 (ISSN-L)
  • 1574-6941
OpenAlex
W2769418101
Cited by
269
References
12
FWCI
5.13
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Exploring fish microbial communities to mitigate emerging diseases in aquaculture. https://app.cochat.ai/papers/10.1093/femsec/fix161
The paper
de Bruijn, I., Liu, Y., Wiegertjes, G. F., & Raaijmakers, J. M. (2018). Exploring fish microbial communities to mitigate emerging diseases in aquaculture. FEMS Microbiology Ecology. https://doi.org/10.1093/femsec/fix161

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.