Fecal samples were collected from 15 fish representing four different genetic families. The parents of these families originated from a growth-selected line at NCCCWA (year class 2014) that was previously described[4, 18]. Families were produced and reared until ~18 months post-hatch. Briefly, full-sibling families were produced from single-sire × single-dam mating events. All sires were siblings from a single family while dams exhibited low relatedness (coefficient of relatedness < 0.16). Eggs were reared in spring water, and water temperatures were manipulated between approximately 7-13 °C to synchronize hatch times. Each family was reared separately from hatch through approximately 20 g (7 months post hatch) when 15 fish per family were uniquely tagged by inserting a passive integrated transponder (Avid Identification Systems Inc., Norco, CA) into the peritoneal cavity. Tagged fish were comingled for the remainder of the grow-out period. Fish were fed a commercial fishmeal-based diet (42% protein, 16% fat; Ziegler Bros Inc., Gardners, PA) using automatic feeders (Arvotec, Huutokoski, Finland). Feed was provided at or just below satiation for the entire grow-out period. This study includes four families with high variance in adult body weight. From each family, four fish were selected, two that were considered fast-growing (>1952 g) and two that were slow-growing (<1572 g). Of the 16 fish selected for sampling, one slow-growing fish from family two exhibited morphological signs of disease during sample collection and was excluded from analysis, reducing the total number of samples to 15. The statistical significance of the rank body mass between the two groups was tested by a one-way Mann-Whitney U test with an alpha of p<0.001 (GraphPad Software, Inc., La Jolla, CA).
To characterize the gut microbiome and compare it to the surrounding water and food source, samples were collected from fish feces, water and feed. For fecal sampling, fish were anesthetized with tricane methanesulfonate (150 mg mL−1) (Tricaine-S, Western Chemical, Ferndale, WA) and then manually stripped to collect the fecal samples in sterile Eppendorf tubes (Eppendorf, Hauppauge, NY). Water samples of 1.5-liter volume were collected from both the inlet water source and tank (n= 4 total samples), then filtered twice through a clean sterile membrane filter with pore size 0.45μm. DNA was isolated from filters to sample bacteria present in the environment. Feed samples were also collected by taking 100 g of feed and storing it in a Ziploc bag. All samples were stored at -80 °C until DNA extraction.
DNA isolation and sequencing
For comparison of extraction methods, fecal samples from 8 fast-growing and 7 slow-growing fish were pooled together and DNA extraction was done in triplicate using five different extraction methods including PowerSoil® DNA Isolation Kit (MO BIO Laboratories, Inc., West Carlsbad, CA), Promega Maxwell DNA Isolation Kit (Promega Corporation, Madison, WI), Qiagen Blood and Tissue, Qiagen Stool (Qiagen, Germantown, MD) and phenol-chloroform (Phenol: Chloroform 5:1, SIGMA) extraction method . Three of the mentioned DNA extraction methods were chosen to study the gut microbiome of fast-growing versus slow-growing trout: MO BIO kit, Promega Maxwell, and phenol-chloroform extraction. More detail of the DNA extraction methods is provided in Additional file 1. Once DNA was extracted, concentration and quality were measured, and integrity of genomic DNA was checked by gel electrophoresis. All DNA extractions were stored at -80 °C until library preparation.
Before library preparation, concentrations of all DNA samples were normalized to 2 ng/μL for PCR amplification using a Qubit fluorometer (v3.11) (Invitrogen, Carlsbad, CA). The primers 515F and 926R (Integrated DNA Technologies) (EMP; http://www.earthmicrobiome.org/emp-standard-protocols/16s/), were used to target the 16S rRNA marker gene using polymerase chain reaction (PCR). The final PCR reaction consisted of 5μL buffer, 1.5 μL 50mM MgCl2, 2 μL 10mM dNTP, 0.2 μL Taq polymerase, 3 μL Kb extender, 1 μL 10 μM primer, 5 μL DNA template and 7.3 μL nuclease-free water. PCR amplification and sample indexing was performed according to the standard earth microbiome project protocols. The amplification conditions were 94 °C for 45 sec, 50 °C for 60 sec, 72 °C for 90 sec for 35 cycles. Amplification was preceded by a 10-minute preheating step at 94 °C and followed by a 10-minute elongation step at 72 °C. Amplification of each sample was performed in triplicate and combined to a final volume of 75 μL. The indexed samples were then normalized (240ng/reaction) and pooled for sample purification purposes. The pooled amplicon was purified using Promega PCR purification kit (Promega Corporation, Madison, WI) and visualized on a 1.5 % agarose gel stained with ethidium bromide. A DNA fragment of size approximately 370 bp for each sample was excised from the DNA gel with a clean, sharp scalpel and collected in nuclease-free sterile tubes. QIAquick gel extraction kit was used to purify DNA from the resulting gel slice (Qiagen, Germantown, MD) according to the manufacturer’s recommendation. The concentration of the gel-extracted library was assessed with a Qubit fluorometer (Invitrogen, Carlsbard, CA) and fragment size was determined using an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, California). Final qPCR-based quantification of the library was done using a KAPPA quantification kit (Roche, Pleasanton, CA). Sequencing was done using 250bp-paired end sequencing using a 300 cycle V2 reagent cartridge on an Illumina Miseq flow cell (Illumina, Inc., San Diego, CA) according to manufacturer’s instructions (Miseq System Guide). The output file was demultiplexed and converted to fastq on the Illumina MiSeq (Illumina, Inc., San Diego, CA).
Sequencing data (3,972,613 raw sequences reads) were analyzed using Mothur (v.1.40.2, www.mothur.org) according to the Mothur Illumina Miseq standard operating procedure (SOP)  with several modifications. After forming contigs, we determined the median length (371 bp) of the sequences. Chops.seqs was used to keep the first 371 bp of each sequence. Sequences with ambiguous base pairs were removed by using the screen. seqs command. The split.abund command was used to keep abundant sequences with greater than two reads. Sequences were aligned to the SILVA v123 database and sequences that failed to align, or classified as Archaea, chloroplast, eukaryotic mitochondrial, or unknown sequences, were excluded from the analysis. Sequences detected by UCHIME as chimeric were removed from the analysis. The remaining sequences were clustered using VSEARCH at a threshold of >97% sequence similarity. The remove. rare command was used to remove operational taxonomic units (OTUs) having less than ten reads among shared samples. Two samples (one fast-growing extracted using Promega Maxwell method and one slow-growing fish extracted using phenol chloroform method) were excluded from the analysis because sequences in these samples did not pass the quality control and filtering steps. The parameters and the command used to analyze the data are included in additional file 2.
To study the effect of DNA extraction methods on microbial community profiling, Bray-Curtis distances were compared and nMDS ordination was used for visualization. To test for a significant effect of extraction method, we used Permutational Multivariate Analysis of Variance (PERMANOVA) on the basis of Bray-Curtis dissimilarity matrices by considering extraction technique as a fixed effect and using type III sum of squares and unrestricted permutation of data with 999 permutations. SIMPROF (Similarity Profile) was performed to test the inter-sample variation on the replicate samples with a significant cut off value of 0.5 (95% similarity).
Beta diversity of the gut and environmental samples were calculated using Bray-Cutis dissimilarity matrices representing pairwise (sample to sample) distances to test the variation among gut and environmental samples (feed and water). Non-metric multidimensional scaling ordination (nMDS) was used to explore the microbial communities in the fast-growing and slow-growing fish by considering the dissimilarity distance matrices among the samples. One-way PERMANOVA was used to assess the effect of sample type (feces, feed and water) as predictive of the microbiome.
To understand the effect fish growth rate on the microbiome, values from Bray-Curtis dissimilarity matrices were compared and visualized using nMDS ordination. A one-way PERMANOVA was used to determine if the growth rate or fish breeding family, both considered as fixed effects, were predictive of the microbiome.
An indicator analysis was done in Mothur in order to statistically and independently select bacterial taxa that are indicative of fast-/slow-growing fish or fish breeding family. Taxa with indicator values greater than 40 and a p-value (<0.05) were considered as indicative of fish growth rate or breeding family. All data files for reproduction of the bioinformatics and statistical analyses are included in additional files 3 – 8.