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Updated: Aug 14, 2026

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
Published on: August 29, 2014
Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in
Jessica Rieder1,2,3, Adamandia Kapopoulou2,3, Claudia Bank2,3
1Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, Institute for Fish and Wildlife Health, University of Bern, Länggasstrasse 122, 3001, Bern, Switzerland.
Background:
Microbial communities in recirculating aquaculture systems (RAS) play a role in system success, nutrient cycling, and water quality. Considering the increasing socio-economic role of fish farming, e.g., regarding food security, an in-depth understanding of aquaculture microbial communities is also relevant from a management perspective, especially regarding the growth, development, and welfare of the farmed animal. However, the current data on the composition of microbial communities within RAS is patchy, which is partly attributable to diverging method choices that render comparative analyses challenging. Therefore, there is a need for accurate, standardized, and user-friendly methods to study microbial communities in aquaculture systems.
Results:
We compared sequencing approach performances (3 types of 16S short amplicon sequencing, PacBio long-read amplicon sequencing, and amplification-free shotgun metagenomics) in the characterization of microbial communities in two commercial RAS fish farms. Results showed that 16S primer choice and amplicon length affect some values (e.g., diversity measures, number of assigned taxa or distinguishing ASVs) but have no impact on spatio-temporal patterns between sample types, farms and time points. This implies that 16S rRNA approaches are adequate for community studies. The long-read amplicons underperformed regarding the quantitative resolution of spatio-temporal patterns but were suited to identify functional services, e.g., nitrification cycling and the detection of pathogens. Finally, shotgun metagenomics extended the picture to fungi, viruses, and bacteriophages, opening avenues for exploring inter-domain interactions. All sequencing datasets agreed on major prokaryotic players, such as Actinobacteriota, Bacteroidota, Nitrospirota, and Proteobacteria.
Conclusion:
The different sequencing approaches yielded overlapping and highly complementary results, with each contributing unique data not obtainable with the other approaches. We conclude that a tiered approach constitutes a strategy for obtaining the maximum amount of information on aquaculture microbial communities and can inform basic research on community evolution dynamics. For specific and/or applied questions, single-method approaches are more practical and cost-effective and could lead to better farm management practices.
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