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This paper provides supplementary data to the research paper ''Presence and habitats of bacterial fish pathogen relatives in a marine salmon post-smolt RAS'' [1]. Here, environmental samples from a marine recirculating aquaculture system (RAS) were subjected to microbiome studies. This data article adds value to the research article by providing open access to data files that increased information retrieval from the 16S rRNA sequence library. A fasta file of full-length 16S rRNA sequences from fish pathogenic microbes was deposited in the Mendeley data repository, a collection named “Fish Pathogen Database”. Alignment of this database against the short sequences in the 16S rRNA library revealed the fish pathogen-relatives. Furthermore, a link to a CSV file containing Pearson correlation data was provided, an analysis based on the relative abundance information of all operational taxonomic units defined in the microbiome dataset. Included also, the methodological description of the Pearson correlation analysis, as well as a table where correlation data for the defined fish pathogen-relatives was retrieved from the large data file (Table 1).

Recycling aquaculture system (RAS) requires well-functioning microbial communities to support fish welfare and to minimize the risk of spreading diseases. In this study of a marine post-smolt RAS we searched for groups of bacteria containing known salmon pathogens in a 16S RAS library that covered samples from four different sites over a year. In the first of the four production cycles included, there was a severe outbreak of fish skin ulcers associated with over 50 % loss of the fish population. To study the presence of potentially pathogenic bacteria from various habitats in the RAS, we used a refined 16 S rRNA gene library approach. The short library sequences of 250 bp were aligned towards 16 S sequences of recognized fish pathogenic bacteria 750-1500 bp long. The latter sequences were widely defined and gathered from GenBank into a fish pathogens database (FPD) prior to the alignment. Pathogen-relatives detected were Moritella viscosa, Psychrobacter immobilis and Aeromonas salmonicida, all with 100 % similarity; Tenacibaculum dicentrarchi, Pseudoalteromonas piscicida, Mycobacterium simiae, Aliivibrio wodanis and Fransicella philomiragia that had 97-99 % similarity and Shewanell puterfaciens, Flavobacterium johnsoniae, Piscirickettsia salmonis, and Bacillus mycoides that had 90-95 % sequences similarity. The pathogen-relatives habituated differently in the RAS as their relative abundances changed between the sites and over time in response to changing operational conditions. The biofilter biofilm was a unique site due to its remarkable low abundance of the pathogen-relatives, whereas three pathogen-relatives with high similarity to classical salmon winter ulcers strains were highly present in the fish skin ulcers. All pathogen-relatives identified were also detected in the production water, three of them at high relative abundance. Thus, we recommend the fish skin and the production water as the best sampling sites for pathogens early warning and specific screening approaches.

A marine aquaculture recycling system (RAS) for the production of post-smolt was monitored for microbial community structures during the first year of operation. Sample material was obtained monthly from the biofilter biofilm carriers, the production water (tank 3), the fish skin (tank 3) and the tank 3 wall biofilm. Additional samples were taken during outbreaks of fish skin wounds, washing of the plant, UV filtration of the inlet water and from various wall biofilms. Samples for depth profiles from all fish tanks were also collected. The sampling tools were a ladle for capturing biofilter biofilm carriers, toothbrushes for wall biofilm capture, filters for capture of water microbes and scalpels for skin tissue slicing. The sampling times were indicated by the production cycle number (cycle 2-5) and the week number within the cycle (W). Prior to bacterial community analysis, the stored samples were exposed to cell lysis and extraction of environmental DNA by commercial kits. All samples were subjected for PCR amplification of 16S rDNA sequences for library formations and prepared for Ion Torrent technology, which sequences 250 bp fragments. A total of 1.1 million reads were obtained from the 100 RAS samples analysed. The process from Ion Torren analysis to library involved bioinformatics steps with sorting, filtering, adjustment and taxonomic identification, and the final output was shown in a table as operational taxonomic units (OTUs) and relative abundance at different sampling sites and sampling time points. Of a total of 450 taxonomically assigned OTUs, 45% were classified at genus level. The 16S library raw data are deposited in the Mendeley data repository and cited in this Data in Brief article co-submitted with the article “Microbial colonization and stability in a marine post-smolt RAS inoculated with a commercial starter culture.” [1]. So far, the raw data are referenced in four more publications in progress. These cover microbial shifts and enrichments between sampling times, sulfur cycling, “in vivo biofilm” and identification of relatives of fish pathogens in RAS. All library sequences are available in GenBank with accession numbers MN890148-MN891672.

The performance of a commercial starter culture was investigated in a new marine post-smolt RAS, analyzing the microbial communities of 100 samples collected monthly over a year from biofilter biofilm carriers, tank wall biofilm, production water and fish skin. Totally 139 operational taxonomic units (OTUs) were defined in the starter culture, of which the classified members of Rhodobacterales, Bacteroidetes, Alteromonadales and Planctomycetes were largely the first colonizers of the biofilter carriers. Early colonizing OTUs that dominated biofilter biofilm carriers (> 5% relative abundance) were stably present over time, but the development went slowly from a few OTUs with very high relative abundance to several dominant ones with lower relative abundance. Operating taxonomic units not associated with the starting culture became prominent on the biofilter biofilm carriers only towards the end of the trial period. These were termed environmental OTUs. Comparing the two OTU quantitives in a ratio, where counts were based on all OTUs in the sample, the starter culture OTUs:environmental OTUs were 1.2 and 0.9 at the first and last sampling time for the biofilter biofilm carriers. Correspondingly, for all defined OTUs in the RAS sampling sites together, the ratio changed from 0.8 to 0.6 during experiment. Independent of origin, omniscient OTUs at a sampling site, did also have the highest relative abundances and were normally shared between biofilter biofilm carriers and the production water. New and lost OTUs between sampling times were on average 44 % of the OTUs defined, and this OTUflow was strongest for low abundant environmental OTUs. The maturation of the biofilter with respect to nitrification took long time, and the Nitrospira strain in the starter culture was not adapted to marine salinities. Still, we report a controlled colonization of the marine RAS by the starter culture.

This paper provides supplementary data to the research paper ''Presence and habitats of bacterial fish pathogen relatives in a marine salmon post-smolt RAS" [1]. Here, environmental samples from a marine recirculating aquaculture system (RAS) were subjected to microbiome studies. This data article adds value to the research article by providing open access to data files that increased information retrieval from the 16S rRNA sequence library. A fasta file of full-length 16S rRNA sequences from fish pathogenic microbes was deposited in the Mendeley data repository, a collection named "Fish Pathogen Database". Alignment of this database against the short sequences in the 16S rRNA library revealed the fish pathogen-relatives. Furthermore, a link to a CSV file containing Pearson correlation data was provided, an analysis based on the relative abundance information of all operational taxonomic units defined in the microbiome dataset. Included also, the methodological description of the Pearson correlation analysis, as well as a table where correlation data for the defined fish pathogen-relatives was retrieved from the large data file (Table 1)., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2022 The Author(s).)

A marine aquaculture recycling system (RAS) for the production of post-smolt was monitored for microbial community structures during the first year of operation. Sample material was obtained monthly from the biofilter biofilm carriers, the production water (tank 3), the fish skin (tank 3) and the tank 3 wall biofilm. Additional samples were taken during outbreaks of fish skin wounds, washing of the plant, UV filtration of the inlet water and from various wall biofilms. Samples for depth profiles from all fish tanks were also collected. The sampling tools were a ladle for capturing biofilter biofilm carriers, toothbrushes for wall biofilm capture, filters for capture of water microbes and scalpels for skin tissue slicing. The sampling times were indicated by the production cycle number (cycle 2-5) and the week number within the cycle (W). Prior to bacterial community analysis, the stored samples were exposed to cell lysis and extraction of environmental DNA by commercial kits. All samples were subjected for PCR amplification of 16S rDNA sequences for library formations and prepared for Ion Torrent technology, which sequences 250 bp fragments. A total of 1.1 million reads were obtained from the 100 RAS samples analysed. The process from Ion Torren analysis to library involved bioinformatics steps with sorting, filtering, adjustment and taxonomic identification, and the final output was shown in a table as operational taxonomic units (OTUs) and relative abundance at different sampling sites and sampling time points. Of a total of 450 taxonomically assigned OTUs, 45% were classified at genus level. The 16S library raw data are deposited in the Mendeley data repository and cited in this Data in Brief article co-submitted with the article "Microbial colonization and stability in a marine post-smolt RAS inoculated with a commercial starter culture." [1]. So far, the raw data are referenced in four more publications in progress. These cover microbial shifts and enrichments between sampling times, sulfur cycling, "in vivo biofilm" and identification of relatives of fish pathogens in RAS. All library sequences are available in GenBank with accession numbers MN890148-MN891672., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2021 The Author(s). Published by Elsevier Inc.)

Lumpfish can efficiently remove sea lice from Atlantic salmon in net-pens, and production of lumpfish in closed fish farms is a new, fast developing industry in Norway. However, periodic outbreaks of bacterial diseases in the fish farms represent a large problem, both economically and ethically. Therefore it is important to obtain a better understanding of how microbial communities develop in these production facilities. Knowledge on the characteristics of microbial communities associated with healthy fish could also enable detection of changes associated with disease outbreaks at an early stage. In this study we have monitored microbial communities in a fish farm for lumpfish during normal operational conditions with no disease outbreak by using 16S rRNA gene amplicon sequencing. The study involved weekly samplings of water and biofilms from fish tanks, and fish. The results revealed that the microbial communities in fish tank water were different from the intake water. The water and biofilm in fish tanks were highly similar in regards to microbial community members, but with large differences in relative abundances for some taxa. The sampled fish were associated with mostly the same taxa as in tank water and biofilm, but more variation in relative abundances of different taxonomic groups occurred. The microbial communities in the fish farm seemed stable over time, and were dominated by marine bacteria and archaea within Alphaproteobacteria , Epsilonproteobacteria , Flavobacteria , Gammaproteobacteria , Thaumarchaeota , Planctomycetes , Sphingobacteriia , and Verrucomicrobiae (>10% relative abundance). Bacterial genera known to include fish-pathogenic strains were detected in all types of sample materials, but with low relative abundances (<5%). Exceptions were some samples of fish, biofilm and water with high relative abundance of Tenacibaculum (<85.8%) and Moritella (<82%). In addition, some of the eggs had a high relative abundance of Tenacibaculum (<89.5%). Overall, this study shows that a stable microbial community dominated by various genera of non-pathogenic bacteria is associated with a healthy environment for rearing lumpfish. Taxa with pathogenic members were also part of the microbial communities during healthy conditions, but the stable non-pathogenic bacteria may limit their growth and thereby prevent disease outbreaks.

In this study we characterized and sequenced the genome of Arcobacter anaerophilus strain IR-1 isolated from enrichment cultures used in nitrate-amended corrosion experiments. A. anaerophilus IR-1 could grow lithoautotrophically on hydrogen and hydrogen sulfide and lithoheterothrophically on thiosulfate and elemental sulfur. In addition, the strain grew organoheterotrophically on yeast extract, peptone, and various organic acids. We show for the first time that Arcobacter could grow on the complex organic substrate tryptone and oxidize acetate with elemental sulfur as electron acceptor. Electron acceptors utilized by most Epsilonproteobacteria, such as oxygen, nitrate, and sulfur, were also used by A. anaerophilus IR-1. Strain IR-1 was also uniquely able to use iron citrate as electron acceptor. Comparative genomics of the Arcobacter strains A. butzleri RM4018, A. nitrofigilis CI and A. anaerophilus IR-1 revealed that the free-living strains had a wider metabolic range and more genes in common compared to the pathogen strain. The presence of genes for NAD(+)-reducing hydrogenase (hox) and dissimilatory iron reduction (fre) were unique for A. anaerophilus IR-1 among Epsilonproteobacteria. Finally, the new strain had an incomplete denitrification pathway where the end product was nitrite, which is different from other Arcobacter strains where the end product is ammonia. Altogether, our study shows that traditional characterization in combination with a modern genomics approach can expand our knowledge on free-living Arcobacter, and that this complementary approach could also provide invaluable knowledge about the physiology and metabolic pathways in other Epsilonproteobacteria from various environments.

Heavy carbon steel corrosion developed during nitrate mitigation of a flow rig connected to a water injection pipeline flowing anaerobe saline aquifer water. Genera-specific QPCR primers quantified 74% of the microbial biofilm community, and further 87% of the community of the nonamended parallel rig. The nonamended biofilm hosted 6.3 × 10(6) SRB cells/cm(2) and the S(35)-sulfate-reduction rate was 1.1 μmol SO4(2-)/cm(2)/day, being congruent with the estimated SRB biomass formation and the sulfate areal flux. Nitrate amendment caused an 18-fold smaller SRB population, but up to 44 times higher sulfate reduction rates. This H2S formation was insufficient to form the observed Fe3S4 layer. Additional H2S was provided by microbial disproportionation of sulfur, also explaining the increased accessibility of sulfate. The reduced nitrate specie nitrite inhibited the dominating H2-scavenging Desulfovibrio population, and sustained the formation of polysulfide and Fe3S4, herby also dissolved sulfur. This terminated the availability of acetate in the inner biofilm and caused cell starvation that initiated growth upon metallic electrons, probably by the sulfur-reducing Desulfuromonas population. On the basis of these observations we propose a model of heavy nitrate corrosion where three microbiological processes of nitrate reduction, disproportionation of sulfur, and metallic electron growth are nicely woven into each other.