16S rRNA gene sequencing from feedstock and biogas reactors fed marine aquaculture sludge

The fish sludge was collected at a full-scale land-based Atlantic salmon producer (Andfjord Salmon) on the north coast of Norway, and frozen in 60L batches and thawed prior to use. Andfjord Salmon is a flow-through facility, using sea water from 30-40 m deep (below parasitic salmon louse levels) for the fish. The cow manure was collected at Ås gård, Ås, southeast Norway and stored at 4 ˚C. The initial inoculum was collected from a mesophilic lab scale CSTR reactor operated with cow manure as substrate. The chemical composition of the IN was determined, and the substrates were measured weekly throughout the experiment. The values for substrates and inoculum pH levels, content of dry matter (DM), organic dry matter, volatile solids (VS), total chemical oxygen demand (tCOD), total nitrogen (tot-N), total phosphorous (tot-P, not analyzed in IN), total ammonium (tot-NH4+), FOS = short chained organic acids / TAC = buffer capacity, CaCo3 ratios and volatile fatty acids (VFA) are shown in table 1. The MAS content of heavy metals (analyzed by Eurofins®) is shown in table 2. The composition of ions (Na+, Cl-, Po43-, SO42-, NH4+, K+, Ca and Mg+ ) in the CM and MAS were analyzed on an ionic chromatograph (IC) equipped with the anion column Metrosep A Supp 5–150/4.0 (Metrohm), and the cation column Metrosep C6–150/4.0 (Metrohm), values are shown in table 3. The DM and VS were measured using standard procedure of loss of drying and loss of ignition. The COD and tot-NH4+ were measured spectrophotometrically. Tot-N and tot-P were analyzed externally (Eurofins ®). The VFAs were separated and quantified using high pressure liquid chromatography (HPLC), with an Aminex isocratic column (flow 0.6 mL/min). The FOS/TAC ratios were determined by autotitration with sulfuric acid (H2SO4) and calculated using a modified Norman method. Samples from the reactors were collected and frozen every week for further analysis. All sampling was performed on replicate samples, except the heavy metal- and ionic composition analysis. Table 1. Chemical composition of the raw materials inoculum (IN), cow manure (CM) and marine aquaculture sludge (MAS) Table 2. Content of heavy metals in the marine aquaculture sludge 2.2 Reactors and experimental design Two lab scale continuously stirred tank reactors (CSTRs); Belach® Dolly twins were used in the experiment. The reactor's volume was 10L with an effective volume of 7L. The reactors were operated at 38 ˚C, and hydraulic retention time (HRT) of 28 days (volumetric loading rate, VLR = 250 mL / d). The reactors feed stock was a mix of cow manure (CM) and saline aquaculture sludge (MAS), and the amount of sludge was gradually increased, from 20% to 100% volume fish sludge (total experimental duration = 310 d). One of the reactors were in addition to the substrate feed stock mix added 10% recirculated effluents (volume % of VLR) (R1), the other received only the substrate mix (R2). The organic loading rate (OLR) and concentrations of Na+, Cl-, Po43-, SO42-, NH4+, K+, Ca and Mg+ is shown in tables 3 and 4, respectively. The biogas production volume (mL) and content of CH4 and CO2 was continuously measured and monitored. The gas volume was analyzed by water displacement, and the gas composition was measured by gas chromatography (GC, SRI) [29]. Table 3. Ionic composition in the feedstocks CM and MAS Table 4. Organic loading rate in the reactors (R1 and R2) feedstocks 2.3 Isolation and quantification of DNA Samples from the original inoculum (IN), substrates CM and MAS, and from both reactors (R1 & R2) loaded with 20, 60 and 100 % MAS were collected and sent to DNASsense ApS (Ålborg east, Denmark). The samples were collected a few days prior to increasing the amount of MASsludge and stored at -21 °C. FastDNA spin kit for soil (MP Biomedicals, USA) was used for DNA isolation. In short, 500 μL of sample was added to a lysing matrix E tube including 480 μL sodium phosphate buffer and 120 μL MT buffer. Bead beating to crush cells was conducted at 6 m/s for 4 × 40 s. The following DNA purification was determined by Gel electrophoresis applying Tapestation 2200 and D1000/High sensitivity D1000 screentapes (Agilent, USA). The DNA concentration was determined using Qubit dsDNA HS/BR Assay kit (Thermo Fisher Scientific, USA). 2.4 Amplicon sequencing of 16s RNA genes Amplificon libraries for bacteria/archaea 16S RNA gene (i.e., regions 1-8 (bV18-A) and 4-9 (aV49-A)) were prepared based on a custom protocoll. Extracted DNA (up to 25 ng) was used as template for PCR amplification, and each PCR reaction (50 μL) contained 0.2 mM dNTP mix, 0.01 units of Platinum SuperFi DNA Polymerase (Thermo Fisher Scientific, USA), and 500 nM of each forward and reverse primer in the supplied SuperFI Buffer. The forward and reverse PCR primers used include custom 24 nt barcode sequences followed by the sequences targeting bV18-A: [8F] AGRGTTYGATYMTGGCTCAG and [1391R] GACGGGCGGTGWGTRCA (Bacteria) and aV49-A: [515FB] GTGYCAGCMGCCGCGGTAA and [SSU1000ArR] GGCCATGCAMYWCCTCTC (Archaea) The resulting amplicon libraries were purified using the standard protocol for CleanNGS SPRI beads (CleanNA, NL) with a bead to sample ratio of 3:5. DNA was eluted in 25 μL of nuclease free water (Qiagen, Germany). Sequencing libraries were prepared from the purified amplicon libraries using the SQK-LSK114 kit (Oxford Nanopore Technologies, UK) according to manufacturer protocol with the following modifications: 500 ng total DNA was used as input, and CleanNGS SPRI beads for library clean-up steps. DNA concentration was measured using Qubit dsDNA HS Assay kit (Thermo Fisher Scientific, USA). Gel electrophoresis using Tapestation 2200 and D1000/High sensitivity D1000 screentapes (Agilent, USA) was used to validate product size and purity of a subset of amplicon libraries. Resulting sequencing library was loaded onto a PromethION R10.4.1 flowcell and sequenced using the MinKNOW 24.06.15 software (Oxford Nanopore Technologies, UK). Reads were basecalled and de-multiplexed with MinKNOW guppy Dorado 7.4.14 using the super accurate basecalling algorithm (config r10.4.1_400bps_sup.cfg) and custom barcodes. 2.5 Downstream processing of sequenced reads The sequenced reads in the demultiplexed and basecalled fastq files were filtered for length (320 - 2000 bp) and quality (phred score > 17) using a local implementation of filtlong (v.0.2.1) with the settings –min_length 320 –max_length 2000 –min_mean_q 98. The Greengenes 2022.10 database in RESCRIPt format was downloaded from the QIIME on 29. September 2022. Potential generic place holders and dead-end taxonomic entries were cleared from the taxonomy flat file, i.e. entries containing uncultured, metagenome or unassigned, were replaced with a blank entry. The filtered reads were mapped to the Greengenes 2022.10 database with minimap2 v2.24-r1122 using the -ax map-ont command and downstream processing using samtools v1.14. Mapping results were filtered such that query sequence length relative to alignment length deviated < 5 %. Additionally, each individual read must be observed at least 10 times within a sample to pass the denoising step. Noteworthy, low-abundant OTUs making up < 0.1 % of the total mapped reads within each sample were disregarded as a data denoising step. Further bioinformatic processing was done via RStudio IDE (2024.4.1.748) running R version 4.4.1 (2024-06-14) and using the R packages: ampvis2 (2.8.9), tidyverse (2.0.0), seqinr (4.2.36), ShortRead (1.62.0) and iNEXT (3.0.1). Relative abundance plots, and alpha- and beta-diversity plots were created using RStudio (v. 4.4.3) using the vegan package.