Aquaculture Europe 2023

September 18 - 21, 2023


Add To Calendar 21/09/2023 10:00:0021/09/2023 10:15:00Europe/ViennaAquaculture Europe 2023THE COMBINATION OF METAGENOMICS AND METABARCODING DATA TO EXPLORE THE SPATIOTEMPORAL DYNAMICS OF MICROBIAL COMMUNITIES IN RECIRCULATING AQUACULTURE SYSTEMS (RAS)Stolz 0The European Aquaculture Societywebmaster@aquaeas.orgfalseDD/MM/YYYYaaVZHLXMfzTRLzDrHmAi181982


Jessica Rieder1,2*, Adamandia Kapopoulou2, Claudia Bank2, Irene Adrian-Kalchhauser1


1. Institute for Fish and Wildlife Health, University of Bern, Länggassstrasse 122, 3012, Bern, Switzerland

2. Institute for Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012, Bern, Switzerland




In recirculating aquaculture systems (RAS), an enclosed aquaculture system for cultivating animals in a controlled manner, microbial communities are critical for maintaining water quality and animal health (Rieder et al., 2023). Despite their systemic importance, the composition of the microbial communities within most RAS remains largely unknown. Establishing accurate, standardized, and user-friendly methods to study microbial communities in RAS may lead to better-designed RAS, improved management practices, and natural ways to prevent disease outbreaks, thereby securing sustainable food production (Moschos, Kormas and Karayanni, 2022).


This study investigated the effects of sampling, data generation, and analysis strategies on the inference of microbial community composition in RAS. To understand the key aspects of microbial community structure and dynamics, we collected water and biofilm samples (Fig 1A) from tanks (Farm A & B) and the biofilter compartment (Farm B) within two perch freshwater RAS (Fig 1B). Furthermore, to understand the advantages and disadvantages of different sequencing resolutions, we compared two amplicon sequencing approaches, short-read with Illumina Miseq and long-read with PacBio, and amplicon-free shotgun metagenomics with Illumina NovaSeq 6000 (Fig. 1D-F).

Results and Discussion

In the short-read dataset, the community composition varied between farms, the tank and biofilter compartment within farm A, the different sample types (biofilm vs. water), and between biofilms of different ages (> 1 week vs. < 1 week) (Fig 2). In the long-read dataset, in a semi-quantitative manner, we could identify the most abundant species in each farm and sample type and found complementary results to the Illumina amplicon sequencing concerning spatial patterns. For example, tank biofilm and tank water samples had the most considerable overlap of species, while between the biofilm sample groups, environmental farm conditions had a more substantial impact on shaping the communities than sample type (Fig. 3). The shotgun metagenomics sequencing yielded impressively comparable results to Illumina amplicon sequencing. Among the top 0.5% phyla, similar bacterial phyla appear. In addition, we can detect taxonomic groups that the short amplicon approach is blind to, such as Ascomycota (sac fungi) and Streptophyta (green algae) (Fig 4). The fungal signal will be interesting to study further and understand interactions between bacteria and fungi because the dynamics between these two groups play a role in animal health.


The results show that microbial communities in RAS are highly dynamic and that management routines create a state of continuous succession and recolonization that can be detected with various sequencing methods. Also, different compartments feature unique microbial communities, despite the permanent water circulation, demonstrating the immense impact of environmental parameters on the community composition.

The results presented here contribute to the overall understanding of the microbial community and dynamic and complex interactions in RAS. They also indicate that further research of microbial communities in aquaculture will be helpful to farm management (e.g., biofilter start-up or disease prevention), to understand basic biological principles (e.g., the link between environmental stressors and microbiome dysbiosis), and to clarify medical relevant interactions (e.g., between host-microbiome-environment interaction and disease development).


Moschos, S., Kormas, K. Ar., and Karayanni, H (2022) "Prokaryotic diversity in marine and freshwater recirculating aquaculture systems", Reviews in Aquaculture, 14(4), pp. 1861-1886. Available at

Rieder, J. et al. (2023) "Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in freshwater recirculating aquaculture systems", Enviromental Microbiome, 18(1), p. 8. Available at: