Characterization of the gut microbiota of three commercially valuable warmwater fish species

Authors

  • A.M. Larsen,

    1. Aquatic Microbiology Laboratory, School of Fisheries, Aquaculture, and Aquatic Sciences, Center for Advanced Science, Innovation, and Commerce, Auburn University, Auburn, AL, USA
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  • H.H. Mohammed,

    1. Aquatic Microbiology Laboratory, School of Fisheries, Aquaculture, and Aquatic Sciences, Center for Advanced Science, Innovation, and Commerce, Auburn University, Auburn, AL, USA
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  • C.R. Arias

    Corresponding author
    1. Aquatic Microbiology Laboratory, School of Fisheries, Aquaculture, and Aquatic Sciences, Center for Advanced Science, Innovation, and Commerce, Auburn University, Auburn, AL, USA
    • Correspondence

      Cova R. Arias, Aquatic Microbiology Laboratory, School of Fisheries, Aquaculture, and Aquatic Sciences, Center for Advanced Science, Innovation, and Commerce, Auburn University, 559 Devall Drive, Auburn, AL 36849, USA.

      E-mail: ariascr@auburn.edu

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Abstract

Aims

Due to the strong influence of the gut microbiota on fish health, dominant bacterial species in the gut are strong candidates for probiotics. This study aimed to characterize the gut microbiota of channel catfish Ictalurus punctatus, largemouth bass Micropterus salmoides and bluegill Lepomis macrochirus to provide a baseline for future probiotic studies.

Methods and Results

The gut microbiota of five pooled individuals from each fish species was identified using 16S rRNA pyrosequencing. Microbiota differed significantly between fish species in terms of bacterial species evenness. However, all gut communities analysed were dominated by the phylum Fusobacteria, specifically the species Cetobacterium somerae. Relatively high abundances of the human pathogens Plesiomonas shigelloides and Fusobacterium mortiferum, as well as members of the genus Aeromonas, suggest these species are normal inhabitants of the gut.

Conclusions

The overwhelming dominance of the genus Cetobacterium in all species warrants further investigation into its role in the fish gut microbiota.

Significance and Impact of the Study

This study provides the first characterization of the gut microbiota of three economically significant fishes and establishes a baseline for future probiotic trials.

Introduction

Aquaculture is the fastest growing animal food-producing sector and is set to overtake capture fisheries as a source of food fish (Subasighe 2005). Currently, one of the main factors limiting expansion and profitability of aquaculture is lack of disease control (FDA 2012). In the USA, treatment options against bacterial diseases are limited to four US Food and Drug Administration (FDA)-approved drugs, three of which are antibiotics (FDA 2011). Growing concern over the presence of antibiotic compounds in foods and an increase in antibiotic resistant microbes has led to an interest in alternatives to antibiotics such as probiotics for treatment and prevention of diseases (Balcazar et al. 2006; Ringo et al. 2010). Probiotics are live microbial feed supplements which beneficially affect the host by improving its intestinal balance. The goal of administering probiotics is to manipulate the gut microbiota to improve the fitness of the host, mainly through the exclusion of opportunistic pathogens (Balcazar et al. 2006). However, the gut microbiota strongly influences fish health in other ways such as assisting in the development of the gut epithelium, providing essential nutrients and stimulating the innate immune system (Nayak 2010). Thus, alteration of gut bacterial communities with probiotics may prevent disease through a variety of mechanisms.

In choosing potential probiotics, dominant strains from fish species of interest are often good candidates (Verschuere et al. 2000). Nevertheless, most probiotics used in aquaculture include lactic acid bacteria and members of the genus Bacillus isolated from mammals or terrestrial environments (Verschuere et al. 2000). Although there are several examples where exogenous bacteria proved beneficial for fish, many studies using lactic acid bacteria or Bacillus were inconclusive or showed no beneficial effect on the host (Oliva-Teles 2012; Ran et al. 2012). Recent studies (Roeselers et al. 2011; Sullam et al. 2012; Larsen et al. 2013) have shown that ‘host species’ and not the environment is the primary driving force shaping microbial communities in fishes. Hence, the microbial communities of each aquaculture species should be fully characterized to identify significant changes produced by the administration of probiotics, and to provide targets for the development of new probiotics.

In the USA, the top aquaculture species is channel catfish Ictalurus punctatus (Rafinesque 1818) with an estimate value of over $390 million annually (FAO Fisheries and Aquaculture Department, Statistics and Information Service 2011). In addition, aquaculture not only provides fish for the food market but also individuals for stocking of recreational fishing ponds. When it comes to recreational fishing, angler surveys indicate the top targeted species in the USA include largemouth bass Micropterus salmoides (Lacepède 1802), and panfish such as bluegill Lepomis macrochirus Rafinesque 1819 (Leonard 2005). Despite their economic significance, the normal gut microbiota of I. punctatus, M. salmoides and L. macrochirus has not been characterized, and thus, dominant community members that are potential targets for the development of probiotics aimed at these fish species have not been determined.

The purpose of this study was to compare the bacterial diversity associated with the gut of three commercially valuable warmwater fish species I. punctatus, M. salmoides and L. macrochirus using pyrosequencing to provide a baseline for future probiotic studies. We collected sympatric individuals from an experimental recreational fishing pond to minimize the effect of the local environment on the gut microbiota (Sakata et al. 1980; MacFarlane et al. 1986; Bacanu and Oprea 2013).

Methods

Sample collection

Sampling for all fish species occurred at Auburn University's E. W. Shell Research Station pond S8 in Auburn, Alabama (32°40′18·7″N, 85°30′36·00″W) in February 2012. Pond S8 is an experimental recreational fishing pond with limited access that was stocked in 1991 with Micropterus salmoides and Lepomis macrochirus reared at a state hatchery (Dr. DeVries, Auburn University, personal communication). Yearling L. macrochirus were stocked at 2500 fish ha−1 in spring, and age-0 M. salmoides were stocked in fall at 250 fish ha−1. Ictalurus punctatus individuals reached pond S8 as escapees from nearby aquaculture ponds and have maintained a constant population since the late-1990s. Poststocking, fish were allowed to exist naturally without artificial feeding. Five individuals each of I. punctatus, L. macrochirus and M. salmoides were captured as follows. Catfish jugs were baited, set in the evening and allowed to fish overnight for approximately 15 h to collect I. punctatus. Micropterus salmoides and L. macrochirus were caught on baited hooks and spinning reels. Fish were kept alive in separate aerated coolers filled with lake water until processing (approximately 3 h). Total lengths of sampled fish are given in Table S1.

DNA extraction

Upon arrival at the laboratory, fish were immediately euthanized with an overdose of tricaine methanesulfonate (300 mg l−1). The lower one-third of the intestine was aseptically removed, and the contents squeezed into a sterile tube. All five individuals of each species were pooled to form a single sample. This sample was homogenized for 2 min with a hand-held homogenizer. To account for intrinsic variability associated with DNA extraction and downstream nucleic acid analysis, each fish sample was divided into three subsamples of 25 mg. These replicates were immediately subjected to DNA extraction with the DNeasy Blood & Tissue kit (Qiagen, Valencia, CA) following manufacturer's instructions, including pretreatment for lysis of Gram-positive bacteria. DNA was quantified using a NanoDrop ND-1000 (Thermo Scientific, Rochester, NY).

Bacterial community composition determined by sequencing

Samples were subjected to Roche titanium 454 sequencing of the 16S rRNA using individual barcodes and primer 27F (5′-AGRGTTTGATCMTGGCTCAG-3′). Resulting sequences were processed using an exclusive analysis pipeline (MR DNA, Shallowater, TX). Barcodes and primers were removed from the sequences. Sequences with <Q25 (base call error rate <0·3%), <200 base pairs in length, ambiguous base calls and stretches of identical bases longer than 6 base pairs were removed. Denoising was performed, followed by removal of chimeras and singleton sequences. Cut-off for operational taxonomic units (OTUs) was defined at a <3% sequence difference in agreement with the current accepted prokaryote species concept (Rossello-Mora and Amann 2001). OTUs were taxonomically identified using blastn against the Greengenes database (DeSantis et al. 2006). As species richness and evenness can only be compared between samples when sample sizes are equal (Hurlbert 1971), resulting sequences were randomly selected so as to standardize to the sample with the least number of obtained sequences (n = 2109). Rarefaction curves, Good's coverage, abundance-based coverage estimation (ACE), Chao1, Shannon evenness and shared OTUs based on defined OTUs were generated using Mothur ver. 1.30.0 (Schloss et al. 2009). Rarefaction curves were standardized to the sample yielding the least number of total sequences. A one-way anova was performed on all diversity indexes, followed by a Tukey's post hoc test when significant (P < 0·05). A genera abundance table was loaded into primer v6 (Clarke and Gorley 2006) and similarity percentages (SIMPER) analysis was performed to determine the genera responsible for differences between fish species. Cut-off for low contributions was set at the default 90%.

Results

Diversity analysis

Pyrosequencing yielded a total of 58 164 bacterial sequences and 311 OTUs. After standardizing for sample size, 18 981 sequences remained with a total of 278 OTUs. Sequence coverage was ≥97% in all cases (Table 1), supported by the rarefaction curves generated by Mothur (Fig. 1). Total expected richness as calculated by ACE and Chao1 did not differ significantly by fish species. However, the Shannon evenness index was significantly higher in Lepomis macrochirus and Ictalurus punctatus than in Micropterus salmoides. Over 38% of all OTUs were shared by all three fish species (Fig. 2). Micropterus salmoides shared the least with the other two species and also had the highest number of unique OTUs.

Table 1. Diversity indexes as calculated by mothur software (ver. 1.30.0). Operational taxonomic units (OTUs) are defined at 97% sequence similarity
Sample IDFish species# Observed OTUs# Predicted OTUsShannon evennessGood's coverage
ACEChao1
  1. ACE, abundance-based coverage estimation.

  2. Significance among total values for each fish species was determined by a one-way anova followed by Tukey's post hoc test.

  3. a

    Statistically significant (anova: F2,6 = 17·52, < 0·01).

04 Lepomis macrochirus 1461982180·7570·978
05 L. macrochirus 1602502080·7270·975
06 L. macrochirus 1411871990·7320·979
40 Micropterus salmoides 1371771730·6960·981
41 M. salmoides 1201561640·6830·982
42 M. salmoides 1311801890·6790·978
76 Ictalurus punctatus 1482082180·7260·975
77 I. punctatus 1161831530·7290·982
78 I. punctatus 1431921830·7140·978
Totals L. macrochirus 1492122080·7390·977
M. salmoides 1291711750·686a0·980
I. punctatus 1361941850·7190·979
Figure 1.

Rarefaction curves by fish species. Sequences were standardized to equal sample sizes for direct comparison. Red, Lepomis macrochirus; green, Micropterus salmoides; blue, Ictalurus punctatus.

Figure 2.

Venn diagram representing shared operational taxonomic units (OTUs) between fish species. Red, Lepomis macrochirus; green, Micropterus salmoides; blue, Ictalurus punctatus.

Gut microbiota composition

Eight bacterial phyla were identified from the gut content of all fish species (Fig. 3). From each fish species, the phylum Fusobacteria made up the majority of all sequences (82·6% in L. macrochirus, 90·6% in M. salmoides and 94·9% in I. punctatus). Proteobacteria was the second most common phylum, varying in abundance from 5 to 16%. Within the Proteobacteria, each fish microbiota was composed of mostly Gammaproteobacteria, followed by Betaproteobacteria and Alphaproteobacteria. The less common phyla varied in abundances between fish species, with some unique members of each community. For example, only M. salmoides contained Actinobacteria while L. macrochirus and I. punctatus lacked representatives from the cyanobacteria and from the Spring Alpine Meadow; candidate division, respectively.

Figure 3.

Phylum composition of each fish species as obtained through sequencing. (a) Lepomis macrochirus; (b) Micropterus salmoides; (c) Ictalurus punctatus. Pie: Dark grey, Fusobacteria; orange, Proteobacteria; light grey, all other phyla. Bar: Blue, Bacteroidetes; purple, Actinobacteria; peach, ‘Spring Alpine Meadow’ (candidate division); green, cyanobacteria; pink, Firmicutes; black, Tenericutes.

The gut microbiota of each fish species was composed of 11 shared genera and two to four unique genera per fish species (Table 2). Of these, most sequences were identified as Cetobacterium. Other relatively abundant genera included Aeromonas and Fusobacterium in L. macrochirus, Aeromonas in I. punctatus and Plesiomonas in M. salmoides. The 11 shared genera made up >98% of all identified sequences in each species, suggesting highly similar bacterial composition in the gut of these fishes at the genus level.

Table 2. Genus identity of sequences, represented by percentage of total sequences. Only genera accounting for at least 0·01% of sequences in at least one fish species are included. Shared genera are those shared among all three fish species. Unique genera are those present in only one or two fish species
ClassificationAbundance (%)
PhylumClassFamilyGenus Lepomis macrochirus Micropterus salmoides Ictalurus punctatus
Shared genera
FusobacteriaFusobacteriaFusobacteriaceae Cetobacterium 72·0489·994·02
FusobacteriaFusobacteriaFusobacteriaceae Fusobacterium 10·560·660·9
Proteobacteriaα-ProteobacteriaMethylobacteriaceae Methylobacterium 0·030·020·01
Proteobacteriaβ-ProteobacteriaNeisseriaceae Laribacter 2·560·110·03
Proteobacteriaγ-ProteobacteriaAeromonadaceae Aeromonas 10·240·063·18
Proteobacteriaγ-ProteobacteriaEnterobacteriaceae Plesiomonas 2·847·640·39
Proteobacteriaγ-ProteobacteriaEnterobacteriaceae Serratia 0·180·010·05
FirmicutesClostridiaClostridiaceae Clostridium 0·571·240·03
FirmicutesClostridiaLachnospiraceae Epulopiscium 0·010·080·02
BacteroidetesBacteroidiaPorphyromonadaceae Parabacteroides 0·560·060·15
TenericutesMollicutesMycoplasmataceae Mycoplasma 0·040·030·04
Unique genera
ActinobacteriaActinobacteriaMicrococcaceae Kocuria 00·010
Proteobacteriaα-ProteobacteriaUnspecified Pelagibacter 0·0300
Proteobacteriaβ-ProteobacteriaNeisseriaceae Deefgea 0·020<0·01
Proteobacteriaγ-ProteobacteriaShewanellaceae Shewanella <0·00100·01
Proteobacteriaγ-ProteobacteriaXanthomonadaceae Xanthomonas 0·0100
FirmicutesBacilliStaphylococcaceae Salinicoccus 00·010

SIMPER analysis (Table 3) by bacterial genera indicated the largest difference in gut community composition between L. macrochirus and M. salmoides. A majority of the differences between all fish species were due to varying abundances of the genus Cetobacterium. Within this genus, all identified sequences shared high 16S sequence similarity with the bacterium Cetobacterium somerae. High numbers of Fusobacterium in L. macrochirus as compared to I. punctatus contributed to the dissimilarity in gut microbiota between these two species. Fusobacterium mortiferum contributed the majority of sequences from this genus in L. macrochirus, while I. punctatus had approximately equal abundances of Fus. mortiferum and Fusobacterium gonidiaformans. Relatively high abundances of Plesiomonas spp. in M. salmoides contributed to the clearer separation between this species and the other two fish species. All sequences within the genus Plesiomonas were closely related to Plesiomonas shigelloides. Similarly, relatively high abundances of Aeromonas spp. in L. macrochirus separated this fish species from the others. Most Aeromonas species cannot be differentiated by 16S alone (Janda and Abbott 2010), and thus, species composition of this genus cannot be described in this study.

Table 3. SIMPER analysis between each combination of fish species. Average abundances include all three replicates within each fish species
Fish speciesBacteria genusSpecies 1 average abundanceSpecies 2 average abundanceContribution to dissimilarity (%)

1. Lepomis macrochirus

2. Micropterus salmoides

Cetobacterium 3244866976·6
Plesiomonas 1287378·4
Aeromonas 46165·8

1. L. macrochirus

2. Ictalurus punctatus

Cetobacterium 3244492771·1
Fusobacterium 4764711·4
Aeromonas 4611678·5

1. M. salmoides

2. I. punctatus

Cetobacterium 8669492775
Plesiomonas 7372015·5

Discussion

Studies characterizing the microbiota associated with wild fish are often limited to analysis of one fish species (MacFarlane et al. 1986; Ringo and Strom 1994; Ugur et al. 2002; Uchii et al. 2006; Wilson et al. 2008; Wu et al. 2010; Bacanu and Oprea 2013), but results from studies that compared several fish species collected from the same area showed a marked specificity between fish species and microbiota (Skrodenyte-Arbaciauskiene et al. 2008; Smriga et al. 2010; Larsen et al. 2013). Our results showed significant differences in bacterial species evenness between the gut microbiota of Lepomis macrochirus, Micropterus salmoides and Ictalurus punctatus that were sharing the same environment and were not artificially fed. These fish species are known to have varying diet preferences and pond S8 offers a balanced ecosystem to satisfy their feeding requirements. Adult M. salmoides are primarily piscivorous, consuming fish, including Lepomis spp. and crayfish (Hickley et al. 1994; Olson and Young 2003; Wheeler and Allen 2003). Although I. punctatus are omnivorous (Jearld and Brown 1971; Griswold and Tubb 1977), individuals larger than 300–400 mm are reported to be primarily piscivorous (Jearld and Brown 1971; Michaletz 2006). As all of our I. punctatus were larger than 500 mm, they were likely consuming fish as their main diet. Adult L. macrochirus are generalists, eating primarily macroinvertebrates and zooplankton, as well as plants and small fish (Turner 1955; Seaburg and Moyle 1964; Harris 1999). Although stomach content was not analysed in this study, our patterns potentially reflect these diet differences.

Previous studies have seen differences in fish gut microbiota due to diet (Heikkinen et al. 2006; Silva et al. 2011; Mouchet et al. 2012; Sullam et al. 2012; Di Maiuta et al. 2013), and an increased diversity from carnivores to omnivores to herbivores has been demonstrated in mammals (Ley et al. 2008; Tsao 2011). We observed an increase in the number of predicted OTUs from carnivory (M. salmoides I. punctatus) to herbivory (L. macrochirus), but this trend was not statistically significant. Alternatively, species evenness was significantly higher in L. macrochirus and I. punctatus as compared to M. salmoides. McKenney (2011) saw an increased evenness in the gut microbiota of omnivorous primates as opposed to carnivorous ones. However, this statistic is rarely reported in these types of studies thus, the commonality of this pattern is to the best of our knowledge unknown.

Pyrosequencing identified differences between fish species' gut microbiota in terms of bacterial abundances at each taxonomic level. The phylum Fusobacteria was the main component of all three species' gut communities followed by the Proteobacteria. A few studies have shown Fusobacteria as dominant members of the gut microbiota of freshwater fishes (van Kessel et al. 2011; Di Maiuta et al. 2013) but not at the abundances observed in this study. The Fusobacteria are anaerobic, Gram-negative bacilli that produce butyrate (Bennett and Eley 1993), a short-chain fatty acid that is often the end product of the fermentation of carbohydrates including those found in mucins (Titus and Ahearn 1988; von Engelhardt et al. 1998). In mammals, butyrate provides many benefits to the host, including providing a majority of the energy supply to gastrointestinal cells (von Engelhardt et al. 1998; Collinder et al. 2003), enhancing mucus production, acting as an anti-carcinogen and anti-inflammatory, as well as playing a role in satiation (McBain et al. 1997; von Engelhardt et al. 1998; Andoh et al. 1999; Hamer et al. 2007). This fatty acid has been found in the gut of herbivorous and omnivorous fishes (Clements et al. 1994; Clements and Choat 1995), but is not expected to be present in carnivorous species because of their low carbohydrate diets (Schrama et al. 2005). Nuez-Ortin et al. (2012) demonstrated the ability of butyric acid to inhibit potential freshwater fish pathogens, and sodium butyrate is currently sold as a food additive to promote fish health and growth. However, trials using blends of sodium butyrate and other additives have not proven beneficial (Owen et al. 2006; Gao et al. 2011). Due to the large proportion of Fusobacteria in all three of these species, future investigations should determine their role in the fish gut microbiota.

Sequences closely related to the bacterium Cetobacterium somerae constituted over 70% of sequences from each fish species. This was a surprising result as it has been demonstrated that bacterial communities whose relative species abundances are near equal are more resilient to environmental stress than those that rely on dominant species for certain functions (Wittebolle et al. 2009). Cetobacterium somerae, formerly classified as Bacteroides type A (Tsuchiya et al. 2008), are poorly known, microaerotolerant, Gram-negative rods with fermentative metabolism that were originally described from children with late-set autism (Finegold et al. 2003). Since the original description, C. somerae has been found in a variety of freshwater herbivorous fish species (Tsuchiya et al. 2008; Silva et al. 2011; Di Maiuta et al. 2013). In this environment, the bacterium produces high amounts of vitamin B12 (Sugita et al. 1991). Cetobacterium somerae is also capable of inhibiting the growth of other bacterial strains (Sugita et al. 1996). The presence of this bacterium in a number of other freshwater fishes as well as its high abundance in this study warrants further studies into its function in the fish gut.

Interestingly, human pathogens including Fusobacterium mortiferum, Plesiomonas shigelloides (Bourgault et al. 1997; Novotny et al. 2004) and Aeromonas sp. were the second most commonly identified genera in L. macrochirus, M. salmoides and I. punctatus, respectively. This is the second known study to isolate Fus. mortiferum from the gut of a fish (Silva et al. 2005) and its role has yet to be examined in fish; however, it has also been isolated from wounds caused by catfish spines (Hargreaves and Lucey 1990). On the other hand, Ple. shigelloides seems to be a normal component of the gut of other fishes (Vandamme and Vandepitte 1980; Esteve and Garay 1991; Sugita et al. 1996; Silva et al. 2005; Donkeng et al. 2011). The genus Aeromonas not only includes opportunistic human pathogens but also fish pathogens such as A. hydrophila (Cipriano et al. 1984).

In summary, this study provides the first characterization of the gut microbiota of the economically significant I. punctatus, M. salmoides and L. macrochirus. These bacterial communities were isolated from wild individuals from the same lake. The microbiota composition, despite sharing a high percentage of the same bacterial genera, differed in evenness between fish species. Despite their differences, all three fish species harboured by vast majority the species C. somerae, sparking interest in its role in the fish gut. Studies are currently underway to isolate and further characterize this bacterium.

Acknowledgements

We thank Dennis DeVries, Alan Wilson and Russell Wright, Auburn University, for facilitating collection of fish specimens. This work was funded by Auburn University. A.M. Larsen thanks Auburn University for her Cell and Molecular Biology Research Fellowship.

Conflict of interest

The authors have no conflict of interest to declare.

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