Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Characterization of Intestinal Bacteria in Wild and Domesticated Adult Black Tiger Shrimp (Penaeus monodon)

  • Wanilada Rungrassamee,

    Affiliation Microarray Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

  • Amornpan Klanchui,

    Affiliation Microarray Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

  • Sawarot Maibunkaew,

    Affiliation Microarray Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

  • Sage Chaiyapechara,

    Affiliation Aquatic Molecular Genetics and Biotechnology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

  • Pikul Jiravanichpaisal,

    Affiliation Aquatic Molecular Genetics and Biotechnology Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

  • Nitsara Karoonuthaisiri

    nitsara.kar@biotec.or.th

    Affiliation Microarray Laboratory, National Center for Genetic Engineering and Biotechnology (BIOTEC), Khlong Luang, Pathum Thani, Thailand

Abstract

The black tiger shrimp (Penaeus monodon) is a marine crustacean of economic importance in the world market. To ensure sustainability of the shrimp industry, production capacity and disease outbreak prevention must be improved. Understanding healthy microbial balance inside the shrimp intestine can provide an initial step toward better farming practice and probiotic applications. In this study, we employed a barcode pyrosequencing analysis of V3-4 regions of 16S rRNA genes to examine intestinal bacteria communities in wild-caught and domesticated P. monodon broodstock. Shrimp faeces were removed from intestines prior to further analysis in attempt to identify mucosal bacterial population. Five phyla, Actinobacteria, Fusobacteria, Proteobacteria, Firmicutes and Bacteroidetes, were found in all shrimp from both wild and domesticated environments. The operational taxonomic unit (OTU) was assigned at 97% sequence identity, and our pyrosequencing results identified 18 OTUs commonly found in both groups. Sequences of the shared OTUs were similar to bacteria in three phyla, namely i) Proteobacteria (Vibrio, Photobacterium, Novosphingobium, Pseudomonas, Sphingomonas and Undibacterium), ii) Firmicutes (Fusibacter), and iii) Bacteroidetes (Cloacibacterium). The shared bacterial members in P. monodon from two different habitats provide evidence that the internal environments within the host shrimp also exerts selective pressure on bacterial members. Intestinal bacterial profiles were compared using denaturing gradient gel electrophoresis (DGGE). The sequences from DGGE bands were similar to those of Vibrio and Photobacterium in all shrimp, consistent with pyrosequencing results. This work provides the first comprehensive report on bacterial populations in the intestine of adult black tiger shrimp and reveals some similar bacterial members between the intestine of wild-caught and domesticated shrimp.

Introduction

Characterization of microbiota in animal intestines has been central in advancing understanding of the relationship between host and microorganism [1][3]. Microbial communities in humans and mice are estimated to comprise >1,000 taxa [1], [3]. While some microbes can be pathogenic to their hosts, other microbial symbionts are beneficial to the development and physiology of their host [4][6], playing roles in nutrient absorption, immune response, and epithelial development [7][9]. Maintaining a balance in the population of intestinal bacteria is crucial to the health of the host [10]. In turn, several host factors, such as diet, developmental stage and physiological condition have been identified to affect intestinal bacterial composition [1], [11], [12]. The host, by its own gut immune system and gut environment (e.g. pH and bile acids), also shapes the composition of intestinal bacteria to maintain a relatively stable level of diversity [13], [14].

In addition to understanding the host-microbiota relationship, characterization of intestinal bacteria will help identify bacteria with potential to become probiotics, which are increasingly used as an alternative means for preventive medicine in humans and animals [15][18]. In aquatic animal farming, the concept of replacing antibiotic use with probiotics will help prevent environmental contamination and adverse health effects for consumers. Indeed, several studies have developed probiotic applications for aquaculture [19][21]. This is no exception for Penaeus monodon (black tiger shrimp), which has been a commercially important marine crustacean for the past few decades in many Asian countries and Australia [22], [23]. With increasingly high shrimp consumption, the decline of wild harvests has forced domestication to become the major source of shrimp production [24]. However, the farming industry has been deteriorating due to several factors, in particular the outbreak of disease.

As alternative means to address the disease outbreak problem, disease control using probiotics or maintaining healthy intestinal bacterial balance requires comprehensive understanding of bacterial diversity in the intestines of commonly farmed aquatic animals. Although there have been several studies on bacterial diversity in commonly cultured aquatic species animals from the wild such as P. merguiensis (banana shrimp) [25], Salmo salar L (Atlantic salmon) [26], Gadus morhua L (Atlantic cod) [27], and Danio rerio (zebrafish) [2], there are limited findings on the intestinal bacteria of P. monodon. It was only recently that studies of bacterial diversities in the intestines of P. monodon post-larval and juvenile stages were reported [28], [29], yet there has been no report on the intestinal bacteria of wild-caught P. monodon, which feed on slow-moving benthic animals such as small crabs, shrimp, mollusks, and polychaetes [30]. In contrast, domesticated shrimp in rearing facilities are fed with commercial feed pellets and reared in monoculture with higher stocking density. Comparing the differences in intestinal bacteria of wild-caught and domesticated shrimp can unveil changes in intestinal bacteria as shaped by aquaculture. These changes have implications for shrimp health and consequently, application of this knowledge may improve survival rates of P. monodon under domestication.

In this study, we examined bacterial populations associated with the intestines of wild-caught and domesticated adult black tiger shrimp using high-throughput next-generation pyrosequencing analysis in parallel with denaturing gradient gel electrophoresis (DGGE). Similarities and differences in intestinal bacteria between wild and domesticated shrimp provide initial evidence for a core bacterial community as well as probiotic candidates for P. monodon.

Materials and Methods

Ethics Statement

An ethics statement is not required for this work. No specific permits were required for the described field studies. The field location is not privately owned or protected in any way, and the field studies did not involve endangered or protected species.

Intestine Sample Collection from Wild-caught and Domesticated Black Tiger Shrimp Broodstocks

Wild-caught broodstocks (WC, n = 3) were obtained from the Andaman Sea (salinity ∼31 ppm) and 10-month-old domesticated broodstocks (DB, n = 3) were reared in a cement tank with seawater pumping in from the Gulf of Thailand (salinity ∼30 ppm) at the Shrimp Genetic Improvement Center (Surat Thani province, Thailand) (Fig. 1). The domesticated shrimp were fed three times per day with commercial pellets containing >35% protein, 5%> lipid, <12% moisture and <4% ash (Charoen Pokphand Food PCL, Thailand). Average shrimp weight was 179.03±14.89 g for WC, and 44.94±7.08 g for DB. Shrimp intestines from each group were aseptically dissected, and fecal matter was removed before storage in liquid nitrogen. Genomic DNA was extracted from individual intestines using the QIAamp DNA stool mini kit (Qiagen).

thumbnail
Figure 1. Penaeus monodon from wild and domesticated habitats (A).

Wild-caught P. monodon adults (WC) were captured from the Andaman Sea, whereas 10-month-old domesticated adults (DB) were reared at the Shrimp Genetic Improvement Center, Surat Thani, Thailand (B). The map was adapted from http://www.mapsofworld.com/thailand/thailand-political-map.html.

https://doi.org/10.1371/journal.pone.0091853.g001

Barcode Pyrosequencing Analysis for Bacterial Diversity in Shrimp Intestines

The primer pair 338F (5′ ACTCCTACGGGAGGCAGCAG 3′) and 786R (5′ CTACCAGGGTATCTAATC 3′), targeting the V3 and V4 variable regions of the 16S rRNA gene (between nucleotide positions 338 and 786) was modified with a barcode tag by adding a random 8-base sequence to the 5′ end of each primer pair. DNA libraries for bacterial diversities in WC and DB intestines were amplified with the barcode-tagged primer pairs 338F and 786R using high-fidelity DNA polymerase (KOD hotstart, Novagen, USA). The PCR products were purified with Qiaquick gel extraction kit (Qiagen), and then ligated to 454-adapters. The samples were sent for pyrosequencing at the Genomic Research Laboratory, Genome Institute, BIOTEC, using the Genome Sequencer platform according to Roche protocol (454 GS FLX System, Roche, USA) [31], [32].

Pyrosequencing Data Analysis

Pyrosequencinc data were processed using Mothur software to remove low quality sequences [33], which were defined as sequences with <200 bases, with ambiguous bases and homopolymers >6 bases, or without a barcode and a primer sequence. Sequences identified as chimeras by UCHIME [34] were removed before the RDP II Classifier analysis using an 80% confidence threshold [35]. Mothur was used to assign operational taxonomy units (OTUs) using the average neighbor algorithm at 97% similarity level [36], and to calculate Shannon and Chao1 indices for each shrimp library. In addition, the coverage index was calculated by 1−(n/N), where n is the number of phylotypes and N is the total number of sequences [37]. A hierarchical tree was constructed for each library to visualize relative abundance of each genus from wild and domesticated shrimp. MEGAN was used to construct taxonomic trees using taxonomical assignment by the RDP classifier [38]. Principal coordinates analysis (PCoA) was assessed with R script to compare bacterial community structures based on weighted-UniFrac from each library. Statistical analyses of weighted-UniFrac distances were calculated by analysis of molecular variance (AMOVA) in Mothur to compare significant differences between bacterial communities in wild and domesticated shrimp [39], [40]. A calculated P-value <0.05 was considered to be statistically significant. All pyrosequences in this study were deposited into GenBank database with accession numbers: KF329429–KF334451 for the WC1 library, KF334452–KF344403 for the WC2 library, KF344404–KF355928 for the WC3 library, KF322280–KF325238 for the DB1 library, KF325239–KF328420 for the DB2 library, and KF328421–KF329428 for the DB3 library.

PCR-denaturing Gradient Gel Electrophoresis Analysis and Statistical Analysis of Bacterial Profiles

Denaturing gradient gel electrophoresis (DGGE) was performed to analyze bacterial profiles of individual shrimp. The 16S rRNA PCR fragments were amplified with genomic DNA from each intestine (50 ng) as the template with primer pair, 338F-GC (5′ CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGGACTCCTACGGGAGGCA 3′) and 518R (5′ ATTACCGCGGCTGCTGG 3′), in which the underlined sequence represents the GC-clamp region [41]. PCR cycling conditions involved initial denaturation at 94°C for 3 min, 30 cycles of denaturation at 94°C for 30 sec, annealing at 55°C for 1 min, and extension at 72°C for 2 min, and final extension at 72°C for 5 min. PCR products were purified by gel extraction (Illustra GFX PCR purification kit, GE Healthcare), and determined concentration by a spectrophotometer (NanoDrop ND8100). DGGE was performed as previously described [29] with slight modifications. Briefly, 600 ng of PCR-DGGE fragments were loaded into each well of an 8% polyacrylamide gel with a 40–60% denaturing vertical gradient. A DNA standard of known PCR-DGGE fragments prepared in-house was used to ensure efficiency and quality of DGGE separation. Electrophoresis was performed at 80 volts for 14 hr in DCODE universal mutation detection system (BIO-RAD, USA) before the gels were stained in SYBR gold (Invitrogen) according to the supplier’s instructions. Selected DNA bands from DGGE were excised, transferred to 50 µl of sterile TE buffer, and incubated overnight at 4°C. DNA in TE (1 µl) was used as the template for PCR amplification with a primer pair containing M13 priming sequences (underlined) (338GCF-M13R 5′ CAGGAAACAGCTATGACGGGCGGGGCGGGGGCACGGGGGGACTCCTACGGGAGGCA 3′ and 518R-AT-M13F 5′ GTAAAACGACGGCCAGTAAATAAAATAAAAATGTAAAAAAATTACCGCGGCTGCTGG 3′) [42]. The purified PCR product of each DGGE band was directly sequenced using the M13R primer. The obtained sequences were compared to the ribosomal database (http://rdp.cme.msu.edu/) to identify sequences of nearest similarity, where a sequence with similarity greater than 97% was classified to the closest type species [35], [43], and similarity of 90–97% was classified to the nearest genus. DGGE profiles were clustered using the unweighted-pair-group method with arithmetic averages (UPGMA) based on Pearson correlation of densitometric curves by InfoQuestFP (Biorad, USA).

Results

Overview of 16S rRNA Pyrosequencing Analysis

Barcode pyrosequencing of 16S rRNA sequences was employed to determine bacterial populations in intestines of six individual adult shrimp from wild (WC, n = 3) and domesticated (DB, n = 3) habitats (Fig. 1). A total of 61,499 reads were obtained from pyrosequencing of the V3-4 regions of 16S rRNA genes (Table 1). The barcodes assigned the sequences to distinct libraries: WC1 (5,029 sequences), WC2 (9,969 reads), WC3 (11,532 reads), DB1 (2,961 reads), DB2 (3,190 reads) and DB3 (1,009 reads). Sequences were clustered into operational taxonomic units (OTUs) at 0.03 dissimilarity levels, in which each OTU represented a unique phylotype. The total numbers of OTUs ranged from 138 to 806, where the WC group exhibited higher variation in the number of OTUs. The OTUs were further classified to genus level using the RDP II Classifier [35]. All six bacterial communities contained five phyla: Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria. DB1 from the DB group had the lowest number of bacteria genera (21, 43 and 28 genera for DB1, DB2 and DB3, respectively), whereas the highest number of bacteria genera was detected in WC2 from the WC group (39, 89, and 52 genera for WC1, WC2 and WC3, respectively).

thumbnail
Table 1. Summary of pyrosequencing read analysis, bacterial diversity richness (OTUs), sample coverage (Good’s coverage), diversity index (Shannon) and estimated OTU richness (Chao1) for intestinal bacterial diversity analysis of wild-caught (WC, n = 3) and domesticated (DB, n = 3) P. monodon.

https://doi.org/10.1371/journal.pone.0091853.t001

To estimate and compare bacterial diversity in each individual shrimp, bacterial diversity indices were calculated from OTUs of each library. Good’s coverage indices, used to estimate the percentage of total bacterial OTUs represented in a sample, were in the range of 0.90–0.97, suggesting the 16S rRNA results from each library represented the majority of bacteria in the shrimp intestines. Bacterial diversity estimated by the Shannon index varied from 2.45 to 3.21 in the WC group, and 2.61–3.58 in the DB group, suggesting a similar range of diversity between the two environments. Chao1 analysis for bacterial richness estimated a range of 597 to 2,454 phylotypes, higher than the actual observed OTUs in each library, indicating that the true bacterial richness in P. monodon intestines was underestimated. Additionally, rarefraction analysis was carried out to determine whether OTUs from each library had been adequately obtained from pyrosequencing analysis (Fig. 2). Consistent with the Chao1 analysis, rarefraction curves for the WC (Fig. 2A) and DB groups (Fig. 2B) did not plateau, suggesting that bacterial richness of adult P. monodon intestines were not yet determined. Additional sequence sampling will still be required to capture the true intestinal bacterial diversity of adult P. monodon. Even with the help from the next-generation pyrosequencing technique, a microbial ecology study to reveal a complete picture of bacterial communities is still very challenging. For instance, in soil bacteria community analyses, rarefraction curves have not been saturated, even when a range of 5,000 to 10,000 pyrosequencing reads were obtained [44].

thumbnail
Figure 2. Rarefaction analysis of shrimp intestines.

Operational taxonomic units (OTUs) were clustered based on 97% sequence similarity for the (A) wild-caught group (WC1, WC2, and WC3) and (B) the domesticated group (DB1, DB2, and DB3). The number of sequences sampled represents the number of pyrosequencing reads.

https://doi.org/10.1371/journal.pone.0091853.g002

Taxonomic Composition of Intestinal Bacteria in P. monodon from Pyrosequencing Data

The five major phyla associated with P. monodon intestines were Actinobacteria, Fusobacteria, Bacteroides, Firmicutes and Proteobacteria (Fig. 3). Among them, Proteobacteria (>70% of total sequences) dominated in all shrimp intestines, followed by Firmicutes, except for the WC2 library. WC2 library had 69% of total sequences belonging to Firmicutes, and 26% of total sequences were from Proteobacteria. Considering intra-group diversity, WC shrimp had more variation in phyla distribution whereas DB shrimp had relatively similar distributions, with Proteobacteria being the major phylum followed by Firmicutes (Fig. 3). To visualize bacterial composition in hierarchical orders, pie charts were constructed to represent bacterial abundance in intestines of WC and DB P. monodon (Fig. 4 and Fig. S1). Only phyla containing >100 total pyrosequencing reads were constructed into taxonomic nodes. Vibrio and Photobacterium were dominant in all six libraries, suggesting that these bacterial genera were well-adapted to conditions in P. monodon intestines and surrounding aquatic environments. Surprisingly, Lactobacillus was also present at high abundance in the WC2 library (Fig. S1A). Lactobacillus can be found in intestines of aquatic animals and marine environments [45], [46], thus, the unexpectedly high abundance of Lactobacillus in the WC2 library could be possibly acquired from ingested food.

thumbnail
Figure 3. Frequency distribution of bacterial phyla in Penaeus monodon intestines from pyrosequencing libraries of the wild-caught group (WC1, WC2 and WC3), and the domesticated group (DB1, DB2 and DB3).

https://doi.org/10.1371/journal.pone.0091853.g003

thumbnail
Figure 4. Comparison of bacterial compositions in wild-caught (WC1, WC2 and WC3) and domesticated (DB1, DB2 and DB3) shrimp intestines.

Pie charts of the hierarchical tree reflect relative abundance for each genus from each library (red represents DB1, blue represents DB2, green represents DB3, yellow represents WC1, pink represents WC2, and light blue represents WC3).

https://doi.org/10.1371/journal.pone.0091853.g004

While the WC libraries were widely distributed in all taxonomic nodes, the DB libraries were mostly distributed in classes Gammaproteobacteria and Clostridia (Fig. S1). Interestingly, Fusibacter (class Clostridia) were found in higher proportions in the DB group than the WC group (Fig. S1B). Bacterial frequency and their classification are summarized in Table S1. Pyrosequencing reads that could not be classified at genus level were classified to the nearest taxonomic ranking (Table S1).

Evidence for Common Intestinal Bacterial Populations in P. monodon Adults

From the OTU (97% similarity) distribution among the six libraries (Fig. 5), 1,541 OTUs were found to be unique within the WC libraries, and only 37 OTUs were shared within the group (2.4%) (Fig. 5A). On the other hand, 689 unique OTUs were obtained within the domesticated libraries, and 18 OTUs were common within this group (2.6%) (Fig. 5B), reflecting bacterial variations among individual WC and DB P. monodon. These bacteria could perhaps represent transient bacterial populations. Shared OTUs were assigned to the nearest species based on Blast analysis to determine common bacterial species (Fig. 5C). Interestingly, all 18 OTUs shared in the domesticated libraries were a subset of those 37 OTUs shared within the WC libraries, and these may be part of the core intestinal bacteria in P. monodon adults. The shared OTUs were classified to Proteobacteria, Firmicutes and Bacteroidetes. Phylum Proteobacteria contained the most shared OTUs among the six libraries, comprising Novosphingobium, Photobacterium, Pseudomonas, Sphingomonas, Undibacterium, and Vibrio (Fig. 5C). Among Firmicutes, a shared OTU was classified to Fusibacter paucivorans, whereas the other OTU could only be classified to phylum level. Only Cloacibacterium normanense from phylum Bacteroidetes was common across the WC and DB libraries.

thumbnail
Figure 5. Shared OTU analysis of pyrosequencing reads from Penaeus monodon intestines.

The Venn diagram represents the unique and shared OTUs at 97% similarity level in libraries of (A) wild-caught group (WC1, WC2, and WC3) and (B) the domesticated group (DB1, DB2 and DB3). The shared reads were classified based on BLAST (C) with the following criteria; similarity of ≥97% were classified to the nearest type strain, ≥90% to the nearest genus, and ≤90% to the nearest phylum.

https://doi.org/10.1371/journal.pone.0091853.g005

On the other hand, there were distinct differences between the microbial structures of the WC and the DB shrimp. From 37 OTUs found from the WC libraries, the 19 OTUs absent in the domesticated included several bacteria previously found in marine sediment or marine organisms such as Gilvibacter sediminis [47], Microbulbifer sp. [48], Donghicola xiamenensis [49],Tenacibaculum crassostreae [50], Maritimibacter alkaliphilus [51], Phaeobacter daeponensis [52], and Roseovarius pacificus [53]. In addition, two Vibrio species were found only in the WC. Interestingly, an antibiotic-producing bacterium Janthinobacterium lividum was also found only in the WC [54].

Principal coordinate analysis (PCoA) based on weighted-UniFrac distance showed that bacterial communities in the intestines of each shrimp in the WC were separated from one another, suggesting individual variation, whereas the DB group were clustered closer together (Fig. 6). The PCoA pattern suggested that bacterial populations in DB P. monodon showed more similarities within the group whereas the WC shrimp had higher variation. However, the statistical analysis of intestinal bacterial diversity did not show significant differences (P-value >0.05) between the WC and DB shrimp.

thumbnail
Figure 6. Principal coordinate analysis (PCoA) based on weighted-UniFrac analysis of bacterial populations associated with P. monodon intestines from the wild-caught group (WC1, WC2, and WC3) and the domesticated group (DB1, DB2 and DB3).

https://doi.org/10.1371/journal.pone.0091853.g006

Analysis of Bacterial Diversity by Denaturing Gradient Gel Electrophoresis

The bacterial patterns in intestines of WC and DB shrimp were compared by denaturing gradient gel electrophoresis (DGGE) (Fig. 7). DGGE bands from each sample were selected for sequencing (Fig. 7A). The majority of DGGE bands from all six libraries were highly similar to bacteria from Vibrio and Photobacterium. One dominant DGGE band similar to Lactobacillus sp. (Fig. 7A, band B1) was only found in WC2. A sequence similar to Thalassomonas sp. (band C1) was also found in WC3. Sequences of DGGE bands similar to Fusibacter were found in DB1 and DB2. Consistent with the pyrosequencing result, cluster analysis of DGGE band profiles based on the Pearson distance matrix revealed that bacterial populations in WC shrimp showed higher individual variation than those in DB shrimp (Fig. 7B).

thumbnail
Figure 7. Denaturing gradient gel electrophoresis (DGGE) analysis of intestinal bacterial communities in Penaeus monodon.

The bacteria profiles were from intestines of wild-caught shrimp (WC1, WC2, and WC3) and domesticated shrimp (DB1, DB2, and DB3). The selected DGGE bands were sequence to identify bacteria (A) and DGGE profiles were clustered using UPMGA based on Pearson correlation (B).

https://doi.org/10.1371/journal.pone.0091853.g007

Discussion

The influence of intestinal bacteria on their hosts has been mostly elucidated in vertebrate hosts, with profound effects on host genes involved in nutrient absorption, mucosal modification and immune response. Some intestinal bacteria have been linked to the health status of their hosts [16]. Due to the influence of intestinal microbiota on animal fitness, characterization of gut microbiota would be essential for farm animals. Here, we characterized bacterial populations associated with the intestines of P. monodon, an economically important shrimp species in Asia [55]. To identify a core bacterial population, intestinal bacterial communities were determined in P. monodon obtained from wild and domesticated environments using a high-throughput pyrosequencing approach in parallel with DGGE analysis.

In this study, pyrosequencing analysis revealed some OTUs shared among P. monodon intestines from wild and domesticated environments. Although these OTUs represent only a small percentage of the total intestinal bacterial population, the dominant OTUs in each shrimp were commonly found in all six shrimp libraries. The closest relatives were classified to six genera from Proteobacteria (Vibrio, Photobacterium, Pseudomonas, Sphingomonas, Novosphingobiumcommon and Undibacterium), two genera from Firmicutes (Fusibacter and Lactobacillus), and one genus from Bacteroidetes (Cloacibacterium). Among the shared bacterial genera in this study, Vibrio, Photobacterium, Pseudomonas, Sphingomonas and Novosphingobium were found to be highly prevalent in the intestines collected from P. monodon post-larva and juveniles in our previous study [29]. In particular, Vibrio and Photobacterium are commonly associated with marine habitats [56] and many marine organisms such as crustaceans [25], [57], oyster [58], and fish [59]. Although the bacteria in these genera have been characterized as free-living or commensal in marine animal digestive tracts, the consistent detection of Vibrio, Photobacterium, Pseudomonas, Sphingomonas and Novosphingobium genera in this work and previous studies could imply that they are an indigenous bacterial population in P. monodon intestines. Some have been reported as pathogens in aquaculture, such as Vibrio harveyi, an opportunistic pathogen that causes infection in shrimp under conditions of high nutrient concentrations and high animal density in rearing environments [60], [61]. Fusibacter were commonly found in shrimp from both groups. Thus far, bacteria isolates belonging to the genus Fusibacter have been found to be strictly anaerobic and halotolerant bacteria [62], [63]. Interestingly, Lactobacillus was also found to be associated with P. monodon intestines. Members of Lactobacillus are indeed employed as probiotics in many animals, including some aquatic organisms [64], [65]. For instance, the group of Litopenaeus vannamei (Pacific white shrimp) fed with Lactobacillus plantarum supplemented diet shows a higher survival rate under pathogen exposure than the control diet group [66]. The detection of Lactobacillus in P. monodon intestines in this report as well as our previous work [29] also suggests that the bacterium could withstand P. monodon gut and aquatic environments. Hence, application of Lactobacillus as probiotics is a promising mean to enhance disease resistance in the P. monodon farming. Despite diverse intestinal bacteria members associated in P. monodon adults, the dominant bacteria detected in intestines of WC and DB P. monodon were Proteobacteria, followed by Firmicutes and Bacteroidetes. This observation is consistent with previous reports on intestinal bacteria in P. monodon post-larvae and juveniles [28], [29]. The prevalence of these phyla in animal intestines has been reported in aquatic organisms such as Fenneropenaeus chinensis (Chinese shrimp), P. merguiensis (banana prawn), Nephrops norvegicus (Norway lobster) and Danio rerio (zebrafish) [2], [25], [67], [68].

The similarity of bacterial communities among the wild and domesticated shrimp suggested the establishment of specific bacteria by selective pressures from the environment within the host gut [69], [70]. For instance, a germ-free mice model study reveals that mucosal environment influences selection and establishment of bacteria in the gastrointestinal tract [3]. The mucosal immune system in a host’s digestive tract has been demonstrated to play important roles on maintaining commensal bacteria [69], [71]. Although understanding of P. monodon gut physiology remains elusive, expression of P. monodon immune-related genes upon pathogenic bacteria challenge provides evidence of a shrimp gut immune system [72]. Furthermore, the observation of shared bacterial members is congruent with previous comparative studies of other wild and domesticated model animals. For instance, comparison of bacteria in intestines of D. Rerio (zebrafish) from wild and lab-reared environments showed similar bacterial members [2]. Analyses of bacterial communities in wild and domesticated Mus musculus (mice) [73], Drosophila melanogaster (fruit flies) [74] or Hydra species (Hydra) [70] reveal shared bacterial members regardless of individual variation, and similar bacteria compositions were observed at the phylum or class level in both wild and domesticated hosts. Finally, the similarities of intestinal bacteria in P. monodon with different life histories also imply that there has been long-term co-evolution between intestinal bacteria and host shrimp.

Although shared OTUs were observed among intestines of the six adult shrimps, there were still a vast number of unique OTUs, which reflect the high degree of bacterial variation among individual P. monodon, especially in wild-caught shrimp. In this study, bacterial profiles from the DGGE analysis were congruent with pyrosequencing results in that there was higher individual variation in intestinal bacterial populations among the wild-caught than the domesticated shrimp. As intestinal bacteria can be influenced by bacteria present in the surrounding aquatic habitats [75]. Domesticated shrimp reared in the same water tank would therefore experience less fluctuation in bacterial composition in the surrounding water compared to wild habitats. Transiently persistent bacteria and those associated with ingested food could also inflate the observed individual bacterial variation. As wild P. monodon fed on smaller live animals, unlike domesticated shrimp fed mainly with dried feed pellets, the small live animals ingested by wild P. monodon might influence the number of intestinal bacteria genera, resulting in higher numbers of genera detected in the wild-caught P. monodon than the domesticated group. To further determine the effect of diets on intestinal bacteria, the characterization of bacterial compositions in P. monodon intestines is underway to compare differences between P. monodon feeding on live food (e.g. polychaete worms) to those fed with commercial feed pellets.

Most intestinal bacterial population analyses in penaeid shrimp have been characterized by both culture-dependent and culture-independent techniques based on Sanger sequencing of 16S rRNA genes [25], [28], [76] and a recent study has applied the high-throughput 454 pyrosequencing platform to the analysis of intestinal bacterial diversity in P. monodon [29]. The introduction of pyrosequencing technology has enabled a greater depth to bacterial population analysis in various environments; for instance, bacterial richness in the deep sea environment has been reported to be one or two orders of magnitude higher than those obtained under the traditional Sanger based approaches [77]. Despite its advantages, even pyrosequencing may not uncover the entire range of bacterial diversity. Although the reading length obtained from pyrosequencing technology has been continuously improving, the full length of 16S rRNA (∼1.5 kb) has not yet been achieved with current 454 pyrosequencing capability [78]. Primer selection and their target regions influence bacterial diversity analyses [79], [80], and indeed the detection of phyla Verrucomicrobia, Planctomycetes and Chlamydiae is highly variable with 16S rRNA primer sets [79]. We chose primers target variable regions 3 and 4 of the 16S rRNA gene, which may not be effective in detecting the presence Verrucomicrobia and Planctomycetes [80]. Nonetheless, these bacteria phyla were not found in high abundance in P. monodon intestines in a previous study using full-length 16S rRNA clone library approach [28]. While pyrosequencing analysis provided more comprehensive view of bacterial diversity in a community, the DGGE analysis in parallel provided an overview of structures of dominant bacterial groups, which can be used for comparison of bacterial patterns [81].

Our work reports intestinal bacterial composition in wild-caught and domesticated P. monodon adults by using the 454-pyrosequencing approach and bacterial patterns were also compared by DGGE analysis. We provided evidence of common intestinal bacteria in P. monodon intestines, and suggest that the intestine may be viewed as a selective environment that allows only certain bacterial taxa to persist. Characterization of the bacterial composition in P. monodon intestines is fundamental to understanding of the beneficial effects of bacteria and the importance of host-microbe interaction in a non-model organism.

Conclusion

Recent studies have reported the importance of balanced gut microbiota to the health of animal hosts. Hence, the main purposes of this study were to utilize a culture-independent high-throughput pyrosequencing technique to extend our knowledge concerning the breadth of bacterial diversity in intestines of adult P. monodon, and to determine the composition of bacterial communities in P. monodon from the wild and those under domestication. The bacterial profiles showed similar dominant genera in wild-caught and domesticated shrimp, suggesting the occurrence of a resident bacterial population in P. monodon. We identified shared bacterial members associated with adult shrimp intestines from wild and domesticated environments. This work provides evidence that host intestinal conditions exert stronger selective pressure for bacterial community establishment in P. monodon than rearing environments.

Supporting Information

Figure S1.

The hierarchical trees reflect bacterial abundance for (A) wild-caught shrimp (WC1, WC2, and WC3) and (B) domesticated shrimp (DB1, DB2, and DB3).

https://doi.org/10.1371/journal.pone.0091853.s001

(DOC)

Table S1.

Taxonomical assignments of 16S rRNA sequences from pyrosequencing using the RDP classifier with a confidence threshold of 80%.

https://doi.org/10.1371/journal.pone.0091853.s002

(DOC)

Acknowledgments

We thank Dr. Rungnapa Leelatanawit (BIOTEC) and Somjai Wongtripob (Shrimp Genetic Improvement Center) for providing the intestine samples of domesticated broodstocks. We thank Dr. Sithichoke Tangphatsornruang and his staff from the Genomic Research Laboratory (BIOTEC) for pyrosequencing of PCR amplicons and Dr. Samaporn Teeravechyan for proofreading the manuscript. We are grateful to Prof. Morakot Tanticharoen, Dr. Kanyawim Kirtikara and Dr. Sirawut Klinbunga for their mentorship.

Author Contributions

Conceived and designed the experiments: NK WR. Performed the experiments: WR SM AK. Analyzed the data: WR AK. Contributed reagents/materials/analysis tools: WR SC PJ. Wrote the paper: WR NK.

References

  1. 1. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, et al. (2005) Diversity of the human intestinal microbial flora. Science 308: 1635–1638.
  2. 2. Roeselers G, Mittge EK, Stephens WZ, Parichy DM, Cavanaugh CM, et al. (2011) Evidence for a core gut microbiota in the zebrafish. ISME J 5: 1595–1608.
  3. 3. Gillilland MG 3rd, Erb-Downward JR, Bassis CM, Shen MC, Toews GB, et al. (2012) Ecological succession of bacterial communities during conventionalization of germ-free mice. Appl Environ Microbiol 78: 2359–2366.
  4. 4. Hooper LV, Midtvedt T, Gordon JI (2002) How host-microbial interactions shape the nutrient environment of the mammalian intestine. Annu Rev Nutr 22: 283–307.
  5. 5. Li M, Wang B, Zhang M, Rantalainen M, Wang S, et al. (2008) Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci USA 105: 2117–2122.
  6. 6. Xu J, Gordon JI (2003) Inaugural Article: Honor thy symbionts. Proc Natl Acad Sci USA 100: 10452–10459.
  7. 7. Hooper LV, Wong MH, Thelin A, Hansson L, Falk PG, et al. (2001) Molecular analysis of commensal host-microbial relationships in the intestine. Science 291: 881–884.
  8. 8. Rawls JF, Samuel BS, Gordon JI (2004) Gnotobiotic zebrafish reveal evolutionarily conserved responses to the gut microbiota. Proc Natl Acad Sci USA 101: 4596–4601.
  9. 9. Brune A, Friedrich M (2000) Microecology of the termite gut: structure and function on a microscale. Curr Opin Microbiol 3: 263–269.
  10. 10. Sekirov I, Russell SL, Antunes LC, Finlay BB (2010) Gut microbiota in health and disease. Physiol Rev 90: 859–904.
  11. 11. Dethlefsen L, Huse S, Sogin ML, Relman DA (2008) The Pervasive Effects of an Antibiotic on the Human Gut Microbiota, as Revealed by Deep 16S rRNA Sequencing. PLoS Biol 6: e280.
  12. 12. Dethlefsen L, McFall-Ngai M, Relman DA (2007) An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature 449: 811–818.
  13. 13. Rawls JF, Mahowald MA, Ley RE, Gordon JI (2006) Reciprocal gut microbiota transplants from zebrafish and mice to germ-free recipients reveal host habitat selection. Cell 127: 423–433.
  14. 14. Islam KBMS, Fukiya S, Hagio M, Fujii N, Ishizuka S, et al. (2011) Bile Acid Is a Host Factor That Regulates the Composition of the Cecal Microbiota in Rats. Gastroenterology 141: 1773–1781.
  15. 15. McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, et al. (2013) Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci USA 110: 3229–3236.
  16. 16. Fujimura KE, Slusher NA, Cabana MD, Lynch SV (2010) Role of the gut microbiota in defining human health. Expert Rev Anti Infect Ther 8: 435–454.
  17. 17. Blaut M, Clavel T (2007) Metabolic diversity of the intestinal microbiota: implications for health and disease. J Nutr 137: 751S–755S.
  18. 18. Gaggia F, Mattarelli P, Biavati B (2010) Probiotics and prebiotics in animal feeding for safe food production. International Journal of Food Microbiology 141 Supplement: S15–S28
  19. 19. Rengpipat S, Phianphak W, Piyatiratitivorakul S, Menasveta P (1998) Effects of a probiotic bacterium on black tiger shrimp Penaeus monodon survival and growth. Aquaculture 167: 301–313.
  20. 20. Rengpipat S, Tunyanun A, Fast AW, Piyatiratitivorakul S, Menasveta P (2003) Enhanced growth and resistance to Vibrio challenge in pond-reared black tiger shrimp Penaeus monodon fed a Bacillus probiotic. Dis Aquat Organ 55: 169–173.
  21. 21. Browdy CL (1998) Recent developments in penaeid broodstock and seed production technologies: improving the outlook for superior captive stocks. Aquaculture 164: 3–21.
  22. 22. Rosenberry B (2001) World Shrimp Farming. Shrimp News International.
  23. 23. Waqairatu SS, Dierens L, Cowley JA, Dixon TJ, Johnson KN, et al. (2012) Genetic analysis of Black Tiger shrimp (Penaeus monodon) across its natural distribution range reveals more recent colonization of Fiji and other South Pacific islands. Ecol Evol 2: 2057–2071.
  24. 24. Lebel L, Mungkung R, Gheewala SH, Lebel P (2010) Innovation cycles, niches and sustainability in the shrimp aquaculture industry in Thailand. Environ Sci Policy 13: 291–302.
  25. 25. Oxley AP, Shipton W, Owens L, McKay D (2002) Bacterial flora from the gut of the wild and cultured banana prawn, Penaeus merguiensis. J Appl Microbiol 93: 214–223.
  26. 26. Holben WE, Williams P, Gilbert M, Saarinen M, Sarkilahti LK, et al. (2002) Phylogenetic analysis of intestinal microflora indicates a novel Mycoplasma phylotype in farmed and wild salmon. Microb Ecol 44: 175–185.
  27. 27. Dhanasiri AK, Brunvold L, Brinchmann MF, Korsnes K, Bergh O, et al. (2011) Changes in the intestinal microbiota of wild Atlantic cod Gadus morhua L. upon captive rearing. Microb Ecol 61: 20–30.
  28. 28. Chaiyapechara S, Rungrassamee W, Suriyachay I, Kuncharin Y, Klanchui A, et al. (2011) Bacterial Community Associated with the Intestinal Tract of P. monodon in Commercial Farms. Microb Ecol 63: 938–953.
  29. 29. Rungrassamee W, Klanchui A, Chaiyapechara S, Maibunkaew S, Tangphatsornruang S, et al. (2013) Bacterial Population in Intestines of the Black Tiger Shrimp (Penaeus monodon) under Different Growth Stages. PLoS ONE 8: e60802.
  30. 30. Marte CL (1980) The food and feeding habit of Penaeus monodon Fabricius collected from Makato River, Aklan, Philippines (Decapoda Natantia). Crustaceana 38: 225–236.
  31. 31. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, et al. (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437: 376–380.
  32. 32. Zou Z, Najar F, Wang Y, Roe B, Jiang H (2008) Pyrosequence analysis of expressed sequence tags for Manduca sexta hemolymph proteins involved in immune responses. Insect Biochem Mol Biol 38: 677–682.
  33. 33. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, et al. (2009) Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Appl Environ Microbiol 75: 7537–7541.
  34. 34. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27: 2194–2200.
  35. 35. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73: 5261–5267.
  36. 36. Kunin V, Engelbrektson A, Ochman H, Hugenholtz P (2010) Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ Microbiol 12: 118–123.
  37. 37. Good IJ (1953) The population frequencies of species and the estimation of population parameters. Biometrica 40: 237–264.
  38. 38. Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data. Genome Res 17: 377–386.
  39. 39. Schloss PD (2008) Evaluating different approaches that test whether microbial communities have the same structure. ISME J 2: 265–275.
  40. 40. Martin AP (2002) Phylogenetic Approaches for Describing and Comparing the Diversity of Microbial Communities. Appl Environ Microbiol 68: 3673–3682.
  41. 41. Muyzer G, de Waal EC, Uitterlinden AG (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl Environ Microbiol 59: 695–700.
  42. 42. Wongwilaiwalin S, Rattanachomsri U, Laothanachareon T, Eurwilaichitr L, Igarashi Y, et al. (2010) Analysis of a thermophilic lignocellulose degrading microbial consortium and multi-species lignocellulolytic enzyme system. Enzyme and Microbial Technology 47: 283–290.
  43. 43. Yarza P, Richter M, Peplies J, Euzeby J, Amann R, et al. (2008) The All-Species Living Tree project: a 16S rRNA-based phylogenetic tree of all sequenced type strains. Syst Appl Microbiol 31: 241–250.
  44. 44. Roesch LF, Fulthorpe RR, Riva A, Casella G, Hadwin AK, et al. (2007) Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J 1: 283–290.
  45. 45. Ringo E, Gatesoupe F-J (1998) Lactic acid bacteria in fish: a review. Aquaculture 160: 177–203.
  46. 46. Lee H-I, Kim MH, Kim KY, So J-S (2010) Screening and selection of stress resistant Lactobacillus spp. isolated from the marine oyster (Crassostrea gigas). Anaerobe 16: 522–526.
  47. 47. Khan ST, Nakagawa Y, Harayama S (2007) Sediminibacter furfurosus gen. nov., sp. nov. and Gilvibacter sediminis gen. nov., sp. nov., novel members of the family Flavobacteriaceae. Int J Syst Evol Microbiol 57: 265–269.
  48. 48. Wang CS, Wang Y, Xu XW, Zhang DS, Wu YH, et al. (2009) Microbulbifer donghaiensis sp. nov., isolated from marine sediment of the East China Sea. Int J Syst Evol Microbiol 59: 545–549.
  49. 49. Tan T, Wang B, Shao Z (2009) Donghicola xiamenensis sp. nov., a marine bacterium isolated from seawater of the Taiwan Strait in China. Int J Syst Evol Microbiol 59: 1143–1147.
  50. 50. Lee YS, Baik KS, Park SY, Kim EM, Lee DH, et al. (2009) Tenacibaculum crassostreae sp. nov., isolated from the Pacific oyster, Crassostrea gigas. Int J Syst Evol Microbiol 59: 1609–1614.
  51. 51. Lee K, Choo YJ, Giovannoni SJ, Cho JC (2007) Maritimibacter alkaliphilus gen. nov., sp. nov., a genome-sequenced marine bacterium of the Roseobacter clade in the order Rhodobacterales. Int J Syst Evol Microbiol 57: 1653–1658.
  52. 52. Yoon JH, Kang SJ, Lee SY, Oh TK (2007) Phaeobacter daeponensis sp. nov., isolated from a tidal flat of the Yellow Sea in Korea. Int J Syst Evol Microbiol 57: 856–861.
  53. 53. Wang B, Tan T, Shao Z (2009) Roseovarius pacificus sp. nov., isolated from deep-sea sediment. Int J Syst Evol Microbiol 59: 1116–1121.
  54. 54. O’Sullivan J, McCullough J, Johnson JH, Bonner DP, Clark JC, et al. (1990) Janthinocins A, B and C, novel peptide lactone antibiotics produced by Janthinobacterium lividum. I. Taxonomy, fermentation, isolation, physico-chemical and biological characterization. J Antibiot (Tokyo) 43: 913–919.
  55. 55. Briggs M, Funge-Smith S, Subasinghe RP, Phillips M (2005) Introductions and movement of two penaeid shrimp species in Asia and the pacific. FAO Fisheries Technical Paper. Rome: FAO.
  56. 56. Thompson FL, Iida T, Swings J (2004) Biodiversity of Vibrios. Microbiol Mol Biol R 68: 403–431.
  57. 57. Wang Y, Zhang X-H, Yu M, Wang H, Austin B (2010) Vibrio atypicus sp. nov., isolated from the digestive tract of the Chinese prawn (Penaeus chinensis O’sbeck). Int J Syst Evol Microbiol 60: 2517–2523.
  58. 58. Ortigosa M, Garay E, Pujalte Ma-Js (1994) Numerical Taxonomy of Vibrionaceae Isolated from Oysters and Seawater Along an Annual Cycle. Syst Appl Microbiol 17: 216–225.
  59. 59. Navarrete P, Espejo RT, Romero J (2009) Molecular Analysis of Microbiota Along the Digestive Tract of Juvenile Atlantic Salmon (Salmo salar L.). Microb Ecol 57: 550–561.
  60. 60. Vaseeharan B, Ramasamy P (2003) Abundance of potentially pathogenic micro-organisms in Penaeus monodon larvae rearing systems in India. Microbiol Res 158: 299–308.
  61. 61. Kraxberger-Beatty T, McGarey DJ, Grier HJ, Lim DV (1990) Vibrio harveyi, an opportunistic pathogen of common snook, Centropomus undecimalis (Bloch), held in captivity. J Fish Dis 13: 557–560.
  62. 62. Ben Hania W, Fraj B, Postec A, Fadhlaoui K, Hamdi M, et al. (2012) Fusibacter tunisiensis sp. nov., isolated from an anaerobic reactor used to treat olive-mill wastewater. Int J Syst Evol Microbiol 62: 1365–1368.
  63. 63. Ravot G, Magot M, Fardeau M-L, Patel BKC, Thomas P, et al. (1999) Fusibacter paucivorans gen. nov., sp. nov., an anaerobic, thiosulfate-reducing bacterium from an oil-producing well. Int J Syst Bacteriol 49: 1141–1147.
  64. 64. Verschuere L, Rombaut G, Sorgeloos P, Verstraete W (2000) Probiotic bacteria as biological control agents in aquaculture. Microbiol Mol Biol Rev 64: 655–671.
  65. 65. Desriac F, Defer D, Bourgougnon N, Brillet B, Le Chevalier P, et al. (2010) Bacteriocin as Weapons in the Marine Animal-Associated Bacteria Warfare: Inventory and Potential Applications as an Aquaculture Probiotic. Marine Drugs 8: 1153–1177.
  66. 66. Kongnum K, Hongpattarakere T (2012) Effect of Lactobacillus plantarum isolated from digestive tract of wild shrimp on growth and survival of white shrimp (Litopenaeus vannamei) challenged with Vibrio harveyi. Fish & Shellfish Immunology 32: 170–177.
  67. 67. Liu H, Wang L, Liu M, Wang B, Jiang K, et al. (2011) The intestinal microbial diversity in Chinese shrimp (Fenneropenaeus chinensis) as determined by PCR-DGGE and clone library analyses. Aquaculture 317: 32–36.
  68. 68. Meziti A, Mente E, Kormas KA (2012) Gut bacteria associated with different diets in reared Nephrops norvegicus. Syst Appl Microbiol 35: 473–482.
  69. 69. Jarchum I, Pamer EG (2011) Regulation of innate and adaptive immunity by the commensal microbiota. Curr Opin Immunol 23: 353–360.
  70. 70. Fraune S, Bosch TC (2007) Long-term maintenance of species-specific bacterial microbiota in the basal metazoan Hydra. Proc Natl Acad Sci U S A 104: 13146–13151.
  71. 71. Schluter J, Foster KR (2012) The Evolution of Mutualism in Gut Microbiota Via Host Epithelial Selection. PLoS Biol 10: e1001424.
  72. 72. Soonthornchai W, Rungrassamee W, Karoonuthaisiri N, Jarayabhand P, Klinbunga S, et al. (2010) Expression of immune-related genes in the digestive organ of shrimp, Penaeus monodon, after an oral infection by Vibrio harveyi. Dev Comp Immunol 34: 19–28.
  73. 73. Wilson KH, Brown RS, Andersen GL, Tsang J, Sartor B (2006) Comparison of fecal biota from specific pathogen free and feral mice. Anaerobe 12: 249–253.
  74. 74. Cox CR, Gilmore MS (2007) Native microbial colonization of Drosophila melanogaster and its use as a model of Enterococcus faecalis pathogenesis. Infect Immun 75: 1565–1576.
  75. 75. Sullam KE, Essinger SD, Lozupone CA, O’Connor MP, Rosen GL, et al. (2012) Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol Ecol 21: 3363–3378.
  76. 76. Johnson CN, Barnes S, Ogle J, Grimes DJ, Chang Y-J, et al. (2008) Microbial Community Analysis of Water, Foregut, and Hindgut during Growth of Pacific White Shrimp, Litopenaeus vannamei, in Closed-System Aquaculture. J World Aquacult Soc 39: 251–258.
  77. 77. Sogin ML, Morrison HG, Huber JA, Mark Welch D, Huse SM, et al. (2006) Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc Natl Acad Sci USA 103: 12115–12120.
  78. 78. Ronaghi M (2001) Pyrosequencing Sheds Light on DNA Sequencing. Genome Research 11: 3–11.
  79. 79. Cai L, Ye L, Tong AHY, Lok S, Zhang T (2013) Biased Diversity Metrics Revealed by Bacterial 16S Pyrotags Derived from Different Primer Sets. PLoS One 8.
  80. 80. Ghyselinck J, Pfeiffer S, Heylen K, Sessitsch A, De Vos P (2013) The Effect of Primer Choice and Short Read Sequences on the Outcome of 16S rRNA Gene Based Diversity Studies. PLoS ONE 8: e71360.
  81. 81. Cleary DF, Smalla K, Mendonca-Hagler LC, Gomes NC (2012) Assessment of variation in bacterial composition among microhabitats in a mangrove environment using DGGE fingerprints and barcoded pyrosequencing. PLoS ONE 7: e29380.