DOI: 10.5061/dryad.fj6q5740x
title: Chinook salmon digestion data within predatory largemouth bass and channel catfish through controlled feed trials

description: Diet analysis is a vital tool for understanding trophic interactions and
 is frequently used to inform conservation and management.
 Molecular approaches can identify diet items that are impossible
 to distinguish using more traditional visual-based methods. Yet, our
 understanding of how different variables, such as predator
 species or prey ration size, influence molecular diet analysis is
 still incomplete. Here, we conducted a large feeding trial to assess the
 impact that ration size, predator species, and temperature had on
 digestion rates estimated with visual identification, qPCR, and
 metabarcoding. Our trial was conducted by feeding two rations of Chinook
 salmon (Oncorhynchus tshawytscha) to two piscivorous fish species
 (largemouth bass (Micropterus salmoides)) and channel catfish (Ictalurus
 punctatus)) held at two different temperatures (15.5°C and 18.5°C) and
 sacrificed at regular intervals up to 120 hours from the time of
 ingestion to quantify the prey contents remaining in the digestive tract.
 We found that ration size, temperature, and predator species all
 influenced digestion rate, with some indication that ration size
 had the largest influence. DNA based analyses were able to identify
 salmon smolt prey in predator gut samples for much longer than
 visual analysis (~12 hours for visual analysis versus ~72 hours
 for molecular analyses). Our study provides evidence that
 modeling the persistence of prey DNA in predator guts for
 molecular diet analyses may be feasible using a small set of
 controlling variables for many fish systems.
description: <strong>Overview</strong> We dissected digestives tracts from largemouth bass
 and channel catfish that were sacrificed at regular intervals post
 ingestion of a meal to determine how different covariates affect digestion
 rates. We define digestion rates as the reduction in prey item DNA
 detected in predator gut contents through time due to the processes of
 degradation, digestion, and evacuation. We used two different molecular
 methods to quantify the amount of DNA within the digestive tracts at each
 time interval and then used generalized linear models to quantify effects
 of multiple covariates (i.e., species, ration size, and temperature) on
 digestion rates. <strong>Controlled
 Experiment</strong> We
 conducted experiments on wild-caught and hatchery-reared largemouth bass
 (n fish=382) and hatchery-reared channel catfish (n fish=220) to
 investigate how temperature, predator species, and ration size influence
 digestion rates (Table 1). Hatchery largemouth bass (n = 202) and channel
 catfish (n = 220) were obtained from a private aquaculture facility in
 Galt, CA (The Fishery Inc.). The wild largemouth bass (n = 225) were
 captured via electroshocking in the Delta. All fish were transported to
 the University of California – Davis Center for Aquatic Biology and
 Aquaculture (UC – Davis CABA) for gastric evacuation experiments. Predator
 fish were transported at 20˚C, then held at 18.5˚C for three days to
 initiate acclimation and reduce the stress from transport. After the
 initial three-day acclimation period, fish were placed in their respective
 3 m flow through temperature treatment tanks (15.5 ˚C and 18.5 ˚C) and
 cages for acclimation. The treatment temperatures were selected based on
 the range of temperatures observed in the Delta during the outmigration
 period of fall and late-fall Chinook (March – June), which are the most
 abundant ecotypes. We held 55 predators within each treatment tank, for a
 total of 110 predators per trial. Acclimation for two weeks was deemed
 necessary to 1) ensure previously digested material was eliminated and, 2)
 reduce overall stress and allow digestion rates to return to  normal
 levels (Brandl et al., 2016). Ration sizes of one and three smolts were
 chosen based on the typical amount of prey found within a piscivore’s
 stomach (Nobriga & Feyrer, 2007). Within each treatment tank, fish
 were placed into 4 cages to organize the predators based on time of
 ingestion throughout the feeding trials. We started the trials with 5
 predators for each combination of temperature and ration (e.g., 15 ˚C and
 1 smolt), thus, ideally we would have a total of 200 samples throughout 10
 dissection intervals (see below). Each tankcontained 5 spare predators in
 the case of mortality or regurgitation.  Prey items for the diet study were fall run Chinook
 salmon smolts received from state run hatchery in  elements, California
 (Mokelumne hatchery). Smolts were reared in 1.2 m flow through tanks set
 to 12˚ C and fed fish pellets through automated feeders. Smolts were
 sacrificed by a single strike to the top of the skull, wet weighed (g),
 fin clipped for DNA identification, and force fed to predators. For the
 feeding trial with hatchery-reared largemouth bass, smolts were divided
 into smaller portions due to smaller stomach sizes of the hatchery-reared
 predators. Smolts were cut near the posterior portion of the gill
 operculum and fish were fed the ⅓ portion that included the head while the
 remainder of the smolt was discarded. After a two-week acclimation period,
 predators were anesthetized in a buffered solution of MS-222, tagged for
 identification (Floy tags, Seattle, Washington), measured to nearest fork
 length (mm), and force fed their respective smolt ration. Feeding was
 conducted by placing euthanized smolts down the pharynx of immobilized
 predators using forceps. Once fed, predators were promptly returned to
 their respective treatment tanks and cages for recovery. During the first
 30 minutes of recovery, predators were observed for regurgitation. If
 regurgitation occurred, the predator sample was removed and a new predator
 from the acclimated spares was fed and added to the tank. If regurgitation
 was suspected beyond the 30-minute observation period, a spare predator
 was force-fed and added to that trial as a replacement. Throughout all
 experimental treatments, a total of 10 regurgitations and 8 premature
 mortalities were observed (Supplemental Table 1). Regurgitations occurred
 across all species, temperatures, and feed ration sizes. Although
 regurgitation occurred across all trials, more occurred within warm water
 treatments (7 in 18.5°C vs 3 in 15.5°C). We also note that premature
 mortalities were observed only on wild largemouth bass, and not on
 hatchery subjects of either species. We hypothesize that the stress
 associated with electroshocking and transport affected the survival of
 wild largemouth bass. At regular
 intervals post-ingestion, a subset of five predators from each treatment
 were euthanized by a single strike to the top of the skull and the
 digestive tracts were removed. The entire digestive tract was considered a
 single sample and consisted of the trachea, the pyloric cecum, stomach,
 pyloric sphincter, intestinal tract, and anal cavity. To remove these
 samples, a sterile surgical scalpel was used to make an incision from the
 predator’s anal cavity along the ventral side of their body, anterior to
 the gill plate. A second sterile scalpel was then used to make incisions
 internally until the entire digestive tract could be removed. Digestive
 tract samples were injected with a 3ml solution of 100% non-denatured
 ethanol (EtOH) to halt enzymatic digestion and stored in 200 ml conical
 vials. Conical vials were filled with 100% non-denatured EtOH ensuring
 that the sample to liquid ratio was approximately 2:3. Sample vials were
 refreshed with 100% non-denatured EtOH 24 hours post dissection and
 wrapped in parafilm to prevent evaporation. Samples were then stored at
 room temperature until DNA extraction began. To investigate the
 persistence of ingested prey over time, study subjects were sacrificed,
 and gut contents were sampled at regular intervals after the feeding
 treatments, with the earliest dissections commencing 6hrs post ingestion
 followed by regularly spaced dissections at 12h, 24h, 36h, 48h, 60h, 72h,
 84h, 96h and a final dissection period at 120h. A total of 50 predator
 samples per species were targeted per temperature per 231   ration
 size. <strong>Visual diet
 analysis</strong> After
 isolating the diet samples, we conducted a visual assessment to quantify
 the relative amount of prey material within the digestive tract. The two
 goals of this assessment were: (1) to determine if the quantity of
 material in the digestive tract was correlated with prey DNA quantity, and
 (2) to determine if the quality of digestive tract material (i.e., the
 ratio of tissue vs. stool) affected the molecular analyses. To conduct the
 visual assessment, we first removed the prey contents from the entire
 digestive tract (stomach and intestines) and preserved them in ethanol.
 While removing the prey contents, we noted whether stool was present or
 absent and whether it was a low, medium, or high amount relative to other
 samples (rank from 0 for absent to 3 for high). We used the same scoring
 system for undigested tissue. Each sample could therefore have a score
 from 0 (no stool or tissue present) to 6 (high stool and high tissue).
 Stool was defined as relatively large and generally dark in color, while
 undigested tissue was lighter in color and in chunks of variable size and
 shape. For undigested tissue, we also noted whether we could identify the prey item’s taxa based on
 external characteristics. After visual assessment, we prepared each
 stomach for DNA extraction. First, we pipetted as much stool as possible
 into a 1.5 ml tube. If no stool was visually present, we still pipetted
 approximately 700 µl of ethanol from the bottom of the vial used to
 preserve the stomach into the tube for extraction. To sample chunks of
 partially digested tissue, a small piece was taken from each visible chunk
 to ensure thorough sampling. We recognize that our sampling approach is
 not fully quantitative but it represented a logistically feasible approach
 that should be semi-quantitative. DNA was extracted from this mixture of
 stool and tissue (see below). <strong>Molecular
 Methods</strong> Before
 extraction, stomach and intestinal contents were centrifuged for 3 minutes
 at 5,724 x g and any ethanol was removed by pipette and discarded. Excess
 ethanol was then allowed to evaporate overnight. Extractions were
 conducted with DNA stool kits (Macherev Nagel Necleospin 96) modified by
 replacing bead-induced lysis with enzymatic lysis, using a per-sample
 volume of 25 µl proteinase-k with 850 µl lysis buffer ST1. Samples were
 incubated overnight at 56°C, and the subsequent extraction followed the
 standard manufacturer protocol. One negative control was included on each
 96-well extraction plate. It is important to note that the samples were
 extracted and PCR was conducted in a laboratory space where Chinook salmon
 tissue is extracted and genotyped for nuclear SNPs (PCR and extraction
 rooms are kept separate). We are confident that contamination did not
 influence our findings as it is clear that our molecular results reflected
 known biological processes (i.e. DNA detectability decreases as digestion
 progresses). However, our laboratory setup would not be appropriate for a
 study where stomachs from wild populations were analyzed because
 contamination could significantly impact results.    All extracted stomach samples were analyzed with
 qPCR using an assay designed to quantify Chinook salmon DNA (Brandl et
 al., 2015). To prepare a standard curve, extracted genomic DNA from
 Chinook salmon available from Shi et al. (in press) was quantified using
 an assay kit (Qubit 1X HS dsDNA kit), visualized on a 2% agarose gel to
 determine average fragment size and calculate copy number, and then
 serially diluted. Each 96-well plate included seven standards in
 triplicate and three no-template-controls. Reactions were conducted in 10
 µl volumes each containing 1x 5 µl master mix (Applied Biosystems TaqMan
 Universal PCR Master Mix), 0.9 µM concentration of each primer, 0.7 µM
 concentration of probe, and 3 µL template DNA. Thermocycling was performed
 using a real-time PCR system (QuantStudio 12K Flex) with the following
 profile: 10 min at 95 °C, and then 40 cycles of 15 seconds at 95 °C for 15
 s and 60 °C for 1 minute. All samples were run in triplicate and the mean
 copy number was calculated for each sample. Amplification was considered
 successful if the Cq &gt; 0 and amplification above baseline was
 registered for an unknown sample using the PCR system software
 (QuantStudio). If some replicates did not show amplification for a given
 sample the mean was calculated using the replicates that did
 amplify. We also conducted
 metabarcoding on all diet samples using the MiFish 12S primer set (Miya et
 al., 2015). No PCR replicates were conducted for this analysis. Libraries
 were prepared with a two-step PCR similar to the GT-seq protocol outlined
 in Campbell et al. (2015). Initial PCR reactions were performed in 12 µl
 volumes using 2 µl of template DNA and 10 µl of PCR master mix. The PCR
 master mix consisted of per reaction volumes of: 6 µl master mix (Qiagen
 Multiplex PCR Plus), 3.4 µl sterile water and 0.3 µl each of the MiFish
 forward and reverse primer at 10 µM. Thermal cycling was performed as
 follows: 95°C for 5 minutes, followed by 35 cycles of 95°C for 30 seconds,
 65 °C for 15 seconds, and 72°C for 15 seconds, an extension at 72°C for 5
 minutes, and a 8°C hold.  PCR products were indexed in a barcoding PCR as
 dictated by Campbell et al. (2015), modified by reducing working i05
 primer concentrations to 0.5 µM and working i07 primer concentrations to 1
 µM. Following this, each 96-well plate was subsequently pooled without
 normalizing the amount of DNA per sample to maintain a relationship with
 the initial concentration of DNA in the extract. A double-sided bead size
 selection was performed using paramagnetic beads (Beckman Coulter AMPure
 XP beads), using ratios of beads to library of 0.5x to remove non-target
 larger fragments and then 0.7x to remove dimer and retain the desired
 amplicon. Libraries were sequenced with a next-generation sequencing
 platform (MiSeq Illumina) using a single v2 300-cycle kit with 2 x 150 bp 
 aired-end (PE) chemistry with 15% PhiX to compensate for the low diversity
 library. The lane included  82 samples loaded at equal concentrations, 163
 of which were not part of the current study, and 16 of which were
 no-template-controls (PCR negatives). Sequencing reads were assigned to
 individual samples using the sequencing platform analysis software
 (Illumina MiSeq Analysis Software). Primers were trimmed from forward and
 reverse reads using open-source software (Cutadapt) and reads without
 primer sequences were discarded (Martin, 2011). Primer-trimmed fastq files
 were imported into open-source software (DADA2; Callahan et al., 2016) in
 R for quality filtering, chimera removal, and identifying amplicon
 sequence variants (ASV) using the pseudo-pool option for the core dada2
 algorithm (additional parameters included truncLen = c(110,100), maxN=0,
 maxEE=c(2,4) and truncQ=2). Forward and reverse reads were merged and then
 off-target sequences that likely amplified non-fish amplicons were removed
 using a length filter of 166-172 bp based on the expected amplicon size
 for MiFish (with primers removed). Output files included a table of the
 number of reads per ASV per sample (ASV table) and the sequence identity
 for each ASV, which was used as input for a nucleotide database search
 (BLASTn; Camacho et al., 2009) using a local copy of the National Center
 for Biotechnology Information (NCBI) nucleotide database and a minimum 96
 percent sequence identity (for the entire 166-172 bp amplicon). The
 software program taxonkit (Shen & Ren, 2021) was used to match
 taxonomic lineage to the BLASTn results. This taxonomy information was
 imported into R and custom scripts were used to assign ASV sequences to
 the appropriate taxonomic level. When multiple species matched the same
 ASV within 2% sequence identity of one another, taxonomic levels (i.e.,
 genus, family, order) were iteratively increased until matches were
 unambiguous. Species-level assignments were only accepted at 98% identity,
 whereas matches to all other taxonomic levels were retained at 96%
 sequence identity. This taxonomic information was combined with samples
 and read count data. The minimum threshold for retaining metabarcoding
 data was two reads per taxon per sample. We recognize that this value is
 lower than many empirical studies but we felt it was appropriate because
 we wanted as much data available to model and because this was a
 controlled experiment rather than an empirical study with the goal of
 detecting prey items in wild populations. <strong>Data
 Analysis</strong> Correspondence of visual assessments and molecular
 gut content analysis We hypothesized that the quality of the prey DNA
 would degrade over time through the process of digestion. To test this
 hypothesis, we used Pearson correlations to determine if the quantity of
 diet contents (stool + prey tissue scores) was correlated with smolt prey
 item read counts (metabarcoding) or the log transformed copy number (qPCR)
 from molecular analyses. We analyzed each species separately, but we
 pooled gut samples across temperature and ration treatments to ensure we
 had a sufficient sample size at each dissection time interval post prey
 ingestion. <strong>Regression
 modeling of digestion rates</strong> We used a generalized linear model (GLM) with a
 Tweedie distribution to determine what factors were most correlated with
 the abundance of prey item DNA in sampled guts. Models were fit separately
 for the two molecular methods, with read count the response variable for
 metabarcoding diet analysis and copy number the response variable for qPCR
 analyses. The responses of both methods contained a substantial number of
 zeros values as prey DNA was digested away or evacuated. Furthermore, both
 qPCR and metabarcoding were implemented using minimum genetic material
 thresholds that need be exceeded to generate positive DNA detection
 (&gt; 2 reads for metabarcoding, Cq &gt; 0 for qPCR; see above).
 Thus, we used GLMs with a Tweedie distribution, which is a special case of
 the exponential distribution that is very flexible and can account for
 data that contains a large number of zeros (Tweedie, 1984). Tweedie GLMs
 also have an advantage over zero-inflated models because the zeros are
 handled uniformly, which improves the interpretability of model
 coefficients (Shono, 2008). The package “glmmTMB” (Brooks et al., 2017)
 was used within R (R, Development Core Team, 2021) to fit the GLM. Due to
 the non-normality of our model, we used quantile residuals simulated using
 the “DHARMa” package (Hartig, 2022) to assess model
 diagnostics.  We selected four
 factors (time post-injection, species, temperature, and meal size) to
 include in our model based on a priori hypotheses regarding their
 relationship with digestion rates. The first factor was time
 post-ingestion, which is expected to reduce DNA quantity due to the
 physical and chemical digestion of prey tissue (Moran et al., 2016). The
 second factor was species, because there are numerous behavioral and
 physiological differences betweenlargemouth bass and channel catfish.
 These two species have substantially different feeding ecologies, but
 similar temperature preferences. Both largemouth bass and channel catfish
 prefer relatively warm temperatures in the 25-30 °C range, but can
 tolerate a large range of temperatures (Venables et al., 1978; Wellborn,
 1990). Largemouth bass are visual predators and become piscivorous as
 early as 5 cm in length, leading to a predominantly piscivorous life
 history (Davis & Lock, 2007). In contrast, channel catfish are
 generally classified as omnivores, feeding on fish but also plants,
 invertebrates, amphibians, and other organisms (Braun & Phelps,
 2016; Hill et al., 1995). Carnivores typically have shorter intestines and
 faster digestion rates, whereas herbivores and omnivores have longer
 digestive tracts and slower digestion rates (reviewed in Volkoff &
 Rønnestad, 2020). The third factor in our model was temperature, which can
 affect digestion rates differently depending on gut morphology (Volkoff
 & Rønnestad, 2020). Therefore, as water temperatures change
 throughout a season, digestion rates in largemouth bass and channel
 catfish may not respond in the same way. In our experiment, water
 temperature was designated as a binary factor based on the two average
 temperatures of the treatment tanks: 15.5˚C and 18.5˚C. Higher tank
 temperature is expected to increase the metabolic rate of fish and
 subsequently increase evacuation rate (Brett & Groves, 1979). In
 contrast, cooler temperatures are expected to slow digestion rates,
 potentially prolonging DNA detection. The last factor in our model was
 meal size, which could influence digestion rates due to longer processing
 times for larger prey items (Beamish, 1972). The binary rations of 1 and 3
 smolts were transformed to a continuous factor called predator-to-prey
 ratio (PPR) because we hypothesized that the relative size of the prey was
 more informative to the digestion rate than the ration size (Supplemental
 Figure 1). PPR has been used frequently in food web and community sized
 predation studies to understand metabolic constraints of predators
 (Woodward & Warren, 2007). We hypothesize that we would observe an
 inverse relationship between PPR and digestion rate, whereby a larger PPR
 would decrease gastric processing time. To calculate PPR, smolts were wet
 weighed to nearest 0.1 g and predator weights were estimated based on
 length-weight regressions. Predators fork lengths were measured to nearest
 1 mm and weight-at-length regressions from the literature were used to
 estimate individual predator weights (Henson, 1991; Keenan et al., 2011).
 We used the following weight-at-length regression for largemouth
 bass:                                                                               ?(?) = (??)?  where weight in grams (w) at length in mm (l). An alternative formulation of the model was used for channel catfish:                                                                           ?(?) = (L)lb<strong> </strong> where L is equal to the standard length of a catfish at 1 kg (Keenan et al., 2011). We used this alternative formulation for Channel catfish because they are known to have a lean, longer form at higher weights compared to largemouth bass. No morphological differences were observed between the two sources of largemouth bass, so the same length-weight regression was used on hatchery and wild largemouth bass. We then divided the calculated predator mass by their respectively fed prey mass to calculate the PPR. Higher PPR means that the predator was large relative to the size of the meal. In other words, a predator of a given size that ate a small meal would have a higher PPR than the same predator that ate a large meal. After calculating this ratio, we determined that the PPR was correlated with predator weights and that 14 catfish had much higher PPRs (&gt;300) than all other fish in the study (Supplemental Figure 1). Furthermore, these large catfish were all in the single fish ration treatment. To better compare evacuation rates between species based on the experimental treatments, we excluded these 14 large catfish from our modeling analysis. We assessed support for different model structures in our regressions of feeding trial factors against molecular diet analysis assay outcomes (read counts for metabarcoding and copy number for qPCR) using Akaike’s Information Criterion (AIC; Burnham, 1998). Our primary model selection goal was to identify the top AIC-supported regression amongst a larger candidate model set made up of plausible model structures. Time post-ingestion was expected to have the largest effect on the measured quantity of DNA, and therefore was included in each candidate model. Temperature, PPR, and species were included in models as main effects and as an interaction with time post-ingestion. The interactions between time and each of the other covariates were included to determine if there was an effect of any covariate on the digestion rate. We also included an interaction term between species and PPR because we hypothesized that ration size could influence ingested prey evacuation rates differently across species due to differences in metabolism and digestive morphology. Finally, we included an interaction between species and temperature because largemouth bass and channel catfish have different physiologies. Thus, their prey digestion rates may not change proportionally to changes in temperature. Interaction terms were only included if the variable was included in the model as a main effect. We conducted model selection using the “MuMIn” package (Barton, 2022). <strong>Genetic half-life of prey DNA</strong> While our GLM regressions on molecular diet analysis read counts (metabarcoding) or copy number (qPCR) characterize the influence of feeding trial factors on the persistence of detectable prey item DNA, we also calculated prey DNA genetic half-life values to provide a convenient single metric to facilitate DNA loss comparisons across samples. Detectability half-life provides a measure reflective of the rate that detectable prey item DNA is lost from a predator gut as prey rations are digested, degraded, and evacuated from the gut tract. Wedefine detectability half-life as the duration it takes for smolt DNA in gut content samples to reduce to half of its initial value. To calculate the genetic half-life (HL) of prey item DNA in predator gut content samples, we used the following equation:                                                                              HL =    ??                                                                                      ?????,?                                                                                   ???0.5 ???? Where t is amount of time that passed between interval (i) and interval (j) and ?DNA is the difference in DNA quantity between interval (i) and interval (j). DNA quantities at intervals i and j were predicted from the respective top AIC-supported GLM regression models fit to read count (metabarcoding) or copy number (qPCR) molecular diet analysis data described above (see:‘Regression modeling of prey DNA loss’). Because they were estimated based on the model, we will refer to them as ‘GLM-estimated half-life’ values. Prey item DNA half-life values were summarized across all combinations of feeding trial factors (species, temperature, and PPR). We used parametric bootstrapping (1000 samples) to estimate the 95% confidence interval for our half-life estimates based on the mean and standard deviation of the predicted DNA quantity. To further assess the relative strength of influence of different feeding trial factors on digestion rates we calculated a half-life ratio. The half-life ratio (HLrat) was calculated using the equation:                                                                                           ??k                                                                               ????? = ??l Where HLk is the half-life value for one factor at level k (e.g., species = CCF) and HLl is the half-life value for the same factor at level l (e.g., species = LMB) when the other two covariates are equal (e.g., temperature = 15.5 & PPR = low). This was repeated for every combination of factors.
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