DOI: 10.5061/dryad.s7h44j1g2
title: Data from: Impacts on microbial communities in sediment by aquaculture farming during one salmon cycle

description: In recent years, the salmon farming industry has grown significantly
 worldwide, and in the Faroe Islands, it has become a major industry with
 an annual production of over 94,000 tonnes, yielding 24% of the GDP.
 According to environmental regulations, the ocean floor is monitored
 during every production cycle at all farming sites, involving macrofaunal,
 sensory, and chemical analyses. However, the impact of farming activity on
 microorganisms in the Faroe Islands remains unknown. This study aimed to
 assess the impact of Atlantic salmon farming on benthic microbial
 communities, giving a better understanding of the effects on the
 foundation of the benthic food web and to assess if these are more prone
 to environmental impact than traditional macrofaunal biomonitoring.
 Sediment cores were sampled along a transect from directly below the
 salmon cages to a background reference site. The sampling occurred prior
 to the release of salmon into the cages (‘before stocking’) and
 immediately before the salmon were harvested (‘peak biomass’). The 16S
 rRNA (V4-V5) gene was sequenced on an Illumina MiSeq from our sediment
 samples at the surface, 3 cm, and 10 cm depth. Significant shifts in
 microbial community composition were observed between ‘before stocking’
 and ‘peak biomass’, as well as between different depth layers. Microbial
 diversity increased with increasing distance from the cages and was at its
 highest ‘before stocking’, indicating a significant impact of the salmon
 farming on the microbial community structure. In contrast to the regularly
 executed environmental monitoring, the results from this study showed an
 impact on the sediments by the salmon farming, underlining the powerful
 alternative of DNA-metabarcoding when biomonitoring an aquaculture area.
description: <strong>Sample collection and
 preparation</strong> Sediment samples were
 collected on the 25th of September 2019 and 15th July 2020 at the fish
 farming area A-83 in Sørvágar, Faroe Islands (Figure 1). The first
 sampling effort was conducted after a three-month fallowing period, and
 the second sampling effort was carried out when the salmon biomass was at
 its highest. Starting from the cage station RS20, six
 stations were sampled along a transect (Figure 1). The first station was
 collected directly at the periphery of the cage (0 m), and then
 approximately at 12 m, 40 m, 150 m, 190 m, and 600 m from RS20. The
 transect into the fjord follows the prevailing current direction, measured
 approximately 225 m west of the farm (Norði et al., 2023) (Figure 1). The
 sampling station at 600 meters was designated as a background sample,
 based on findings from a study indicating that the maximum impact range of
 organic enrichment from fish farms in Faroese fjords is 200 m (Mortensen
 et al., 2021). Our background site, 600 meters away, was based on a
 threshold set by the Aquaculture Stewardship Council (ASC) of &gt;500
 m distance between fish farm and reference station (Mortensen et al.,
 2021). However, the 600 meters sampling station is taken at a slightly
 shallower depth (≈ 35 m depth) than the other samples (≈ 45 m depth). Due
 to the small size of the fjord, we chose the best fitting reference point
 in a 500 m radius. During the ‘peak biomass’ sampling effort, two
 additional samples (1+ and 2+, illustrated in Figure 1) were taken due to
 the relocation of cages (RS20, RS22, RS24 and RS26) during farming cycles.
 To ensure consistent comparison with the ‘before stocking’ sampling
 effort, the additional samples were collected from RS28 (representing 0 m
 and 12 m distance), which was the outermost cage station on the same
 transect. Thus, samples were collected at stations 1, 2, 3, 4, 5, and 6 on
 both sampling events but only at stations 1+ and 2+ during ‘peak biomass’.
 This resulted in a total of 14 stations. Samples were
 collected with a kayak corer, consisting of 47 cm plex tubes with a
 diameter of 44 mm (Supplementary File 1). Each of the 14 sediment cores
 was sliced into 1 cm intervals down to a depth of 10 cm. Three sediment
 layers were analyzed: the surface (scraping the surface), 3 cm depth, and
 10 cm depth (Supplementary File 1). Three replicates were collected from
 each core and layer, resulting in a total of 126 samples. The 10 cm layer
 was the deepest layer that could be collected from all samples. The
 samples were stored at -18°C within 2-5 hours after collection and kept
 until DNA extraction, which was conducted 2-7 weeks later. Concurrently
 with our sample collection, an environmental condition assessment of the
 area was performed. This assessment is a statutory requirement before
 smolts are led into the cages and when the biomass is at its highest
 (i.e., before slaughter). Samples for the legislated
 national environmental condition assessment, as described in ICES (2023),
 were collected by an impartial company. The environmental condition
 assessment was conducted in accordance with Norwegian Standard 9410:2016,
 which is also used by the Faroese Environmental Agency (Agency, 2018). The
 impact status is categorized as follows: ‘no impact’, ‘some impact’, ‘high
 impact’ and ‘very high impact’ (Agency, 2018).
 <strong>DNA extraction and
 sequencing</strong> The samples were thawed at
 room temperature and then homogenized to ensure uniform consistency. Each
 sample was divided into three laboratory analysis replicates and DNA was
 extracted using the Qiagen DNeasy PowerSoil kit according to the
 manufacturer’s instructions. The DNA yields from the extractions were
 quantified using a nanophotometer (3117, Implen). Average DNA yields for
 the samples were 41 ± 62 ng/mL, with an average A260/A280 ratios of 1.863
 ± 0.304. A schematic of the sampling and laboratory protocol is shown in
 Supplementary File 2. <strong>PCR and PCR
 clean-up</strong> Sequencing was done of the
 V4-V5 region on the 16S rRNA gene using the primers 515F-Y and 926R
 according to Parada et al. (2015). PCR reactions were carried out in
 triplicate for each laboratory replicate, with a 1:10 dilution for all DNA
 extracts to reduce PCR inhibitors (Apprill et al., 2015; Djurhuus et al.,
 2017). In brief, 1 mL DNA template was added to the master mix, consisting
 of 12.5 mL 2X Phusion Master Mix (Thermo Fisher Scientific, USA), 10.50 mL
 nuclease-free water, and 0.5 mL of each primer (0.2 mM) (Parada et al.,
 2015), resulting in a 25 mL reaction. The PCR reaction occurred at 98°C
 for 30 s, followed by 27 cycles of 98°C for 10 s, 50°C for 30 s, and 72°C
 for 30 s, with a final extension at 72°C for 10 min. After PCR, the
 triplicates were pooled. To confirm the presence of targeted bands and to
 check for clean negative controls, the pooled amplicon products were run
 on 1.5% agarose gels using UView (Bio-Rad) for visualization. All
 non-template controls (NTCs) and blanks tested negative. The pooled
 amplicon products were purified using 1x magnetic Agencourt AMPure XP
 beads (Beckman Coulter, USA), following the manufacturer’s protocols. The
 concentration of all clean PCR products was quantified using a
 nanophotometer. A second PCR reaction was conducted to attach dual barcode
 indices and Illumina sequencing adapters with the Nextera XT Index Kit v2.
 In brief, 5 mL of each DNA amplicon was added to a master mix consisting
 of 25 mL 2X KAPA HiFi (Kapa Biosystems Inc., Woburn, U.S.) HotStart
 ReadyMix, 10 mL nuclease-free water, and 5 mL of primers Nextera XT Index
 1 and Nextera XT Index 2, resulting in a total volume of 50 mL. PCR was
 performed with the following cycling conditions: 95°C for 3 min, 8 cycles
 of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, followed by a final
 extension at 72°C for 5 min. Subsequently, the products were purified
 using AMPure XP beads and quantified using the Qubit 2.0 Fluorometer and
 the Qubit dsDNA HS Assay Kit (Invitrogen, USA). Following quantification,
 library normalization was performed to get an even sequencing depth per
 sample. Sequencing libraries were verified using an Agilent Bioanalyzer
 2100 (Agilent Technologies, USA) to check the sizes of PCR libraries.
 These were then sequenced on an Illumina MiSeq platform, generating 2 x
 250 bp paired-end reads.
description: # Impacts on microbial communities in sediments by aquaculture farming
 during one salmon cycle **DOI:** 10.3389/fmars.2024.1266410 ####
 Authors: Bjarta O. Johansen Environmental Department, SMJ
 Consulting Engineers, Tórshavn, Faroe Islands. Faculty of Science and
 Technology, University of the Faroe Islands, Tórshavn, Faroe Islands.
 [ojbjarta@gmail.com](mailto:ojbjarta@gmail.com) Svein-Ole Mikalsen Faculty
 of Science and Technology, University of the Faroe Islands, Tórshavn,
 Faroe Islands. Eyðfinn Magnussen Faculty of Science and Technology,
 University of the Faroe Islands, Tórshavn, Faroe Islands. Esbern J.
 Patursson Department of Sea Farming, Hiddenfjord, Sandavágur, Faroe
 Islands Gunnvør Á Norði Department of Ecology, Firum, Hvalvík, Faroe
 Islands Anni Djurhuus Faculty of Science and Technology, University of the
 Faroe Islands, Tórshavn, Faroe Islands.
 [Annid@gmail.com](mailto:Annid@gmail.com) ### Sampling in A83 Sørvágur,
 before stocking and peak biomass
 [https://doi.org/10.5061/dryad.s7h44j1g2](https://doi.org/10.5061/dryad.s7h44j1g2) This file contains datasets from two samplings taken in Sørvágur in September 2019 and July 2020, within aquaculture area A83 (with the fish cages) managed by Hiddenfjord. The data files are in FASTQ format. The sequencing data was generated using the Illumina MiSeq Sequencer, operating MiSeq Control Software v2.5 with a MiSeq flow cell (v3) and MiSeq Reagent Kit (v3). The sequencing format included 301 cycles for read 1, 8 cycles for Index 1, 301 cycles for read 2, and 8 cycles for Index 2. The results from this study showed an impact on the sediments by salmon farming, underlining the powerful alternative of DNA metabarcoding for biomonitoring in an aquaculture area. #### **Description of the Data and File Structure** ##### **Raw Data:** All the FASTQ files from the two samplings: before stocking (first sampling) and peak biomass (second sampling). * The first number (1 in the example) in the sample indicates whether it is sample 1, 2, 3, 4, etc. * The letters A, B, or C distinguish which laboratory replicate we have. * The letters/number Y, 3, or 10 indicate whether it is a surface sample (Y), 3 cm depth layer (3), or 10 cm depth layer (10). * Each sample has a forward (R1) and a reverse (R2) FASTQ file. Examples of file names: * 1AY_S1_L001_R1_001.fastq.gz * 1AY_S1_L001_R2_001.fastq.gz * 1BY_S2_L001_R1_001.fastq.gz * 1BY_S2_L001_R2_001.fastq.gz * 1CY_S3_L001_R1_001.fastq.gz * 1CY_S3_L001_R2_001.fastq.gz * 1A3_S4_L001_R1_001.fastq.gz * 1A3_S4_L001_R2_001.fastq.gz * 1B3_S5_L001_R1_001.fastq.gz * 1B3_S5_L001_R2_001.fastq.gz * 1C3_S6_L001_R1_001.fastq.gz * 1C3_S6_L001_R2_001.fastq.gz * 1A10_S7_L001_R1_001.fastq.gz * 1A10_S7_L001_R2_001.fastq.gz * 1B10_S8_L001_R1_001.fastq.gz * 1B10_S8_L001_R2_001.fastq.gz * 1C10_S9_L001_R1_001.fastq.gz * 1C10_S9_L001_R2_001.fastq.gz ##### Metadata: The metadata contains the following information: * **SampleID:** The ID of the samples. * **LibID:** Position on the sequencing plate. * **SeqID:** The ID of each sample on the Illumina sequencing machine. * **Barcode_fwd:** The ID of the forward barcodes. * **Barcode_fwd_seq:** Sequences of each forward barcode. * **Barcode_rv:** The ID of the reverse barcodes. * **Barcode_rv_seq:** Sequences of each reverse barcode. * **fwd_primer:** Barcodes of the forward primers. * **rv_primer:** Barcodes of the reverse primers. * **ExtConc(ng/uL):** DNA concentration in ng/ul after DNA extraction. * **LibConc(ng/uL):** DNA concentration in ng/ul after PCR clean-up. * **SampleContent:** Specifies if it is a sediment or water sample. * **SampleType:** Specifies if the sample collection was done with a grab or kayak corer. * **GPS_Latitude_N:** GPS latitude (North). * **GPS_Longitude_W:** GPS longitude (West). * **Date(yyyy-mm-dd):** Date of the sampling. * **Biomass:** Indicates if the biomass is low (before stocking) or high (peak biomass). * **Distance(meter):** Distance from sample 1. * **Layer_cm:** Depth of the sample (surface, 3 cm depth, or 10 cm depth). * **Samplee:** Describes if it is low (before stocking) or high (peak biomass) and which sample it is (Sample 1, 2, 3, etc.). * **Samples2:** Describes if it is sample 1, 2, 3, etc. * **SampleLayer_:** Describes which sample it is and at which depth. ##### **OTU Table and taxatable:** These files are also provided, containing additional data related to the samples. ###### OTU table: The first row/column of the OTU table file contains the sample IDs, which correspond to the sample IDs in the metadata. Each subsequent row contains the OTUs (Operational Taxonomic Units) found, with the numbers indicating the frequency of each OTU in the respective sample ID columns. ###### **Taxatable:** The first row of the taxonomy table shows the taxonomic system: "Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Species". The subsequent rows show the OTU sequences and their respective positions in the taxonomic system, starting from the kingdom and moving down as far as they can be identified. Some entries may be identified all the way down to the species level, while others may only be identified up to the family level.