The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing

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Veterinary Microbiology journal homepage: www.elsevier.com/locate/vetmic

Review

The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing Hyeun Bum Kim a,*, Richard E. Isaacson b,** a b

Department of Animal Resources Science, Dankook University, Dandae-ro 119, Cheonan, South Korea Department of Veterinary and Biomedical Science, University of Minnesota, 1971 Commonwealth Ave., Saint Paul, USA

A R T I C L E I N F O

A B S T R A C T

Article history: Received 12 October 2014 Received in revised form 6 February 2015 Accepted 14 March 2015

The importance of the gut microbiota of animals is widely acknowledged because of its pivotal roles in the health and well being of animals. The genetic diversity of the gut microbiota contributes to the overall development and metabolic needs of the animal, and provides the host with many beneficial functions including production of volatile fatty acids, re-cycling of bile salts, production of vitamin K, cellulose digestion, and development of immune system. Thus the intestinal microbiota of animals has been the subject of study for many decades. Although most of the older studies have used culture dependent methods, the recent advent of high throughput sequencing of 16S rRNA genes has facilitated in depth studies exploring microbial populations and their dynamics in the animal gut. These culture independent DNA based studies generate large amounts of data and as a result contribute to a more detailed understanding of the microbiota dynamics in the gut and the ecology of the microbial populations. Of equal importance, is being able to identify and quantify microbes that are difficult to grow or that have not been grown in the laboratory. Interpreting the data obtained from this type of study requires using basic principles of microbial diversity to understand importance of the composition of microbial populations. In this review, we summarize the literature on culture independent studies of the pig gut microbiota with an emphasis on its succession and alterations caused by diverse factors. ß 2015 Elsevier B.V. All rights reserved.

Keywords: Swine gut microbiota Microbial diversity Microbiota 16S rRNA gene

Contents 1. 2. 3. 4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16S rRNA genes to determine taxonomic identity . . . . . . . . . . . . . . . . . . . . . . . . . . Next-generation high throughput sequencing of the bacterial 16S ribosomal RNA to describe bacterial community structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Succession of the pig gut microbiota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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* Corresponding author. Tel.: +82 41 550 3653. E-mail address: [email protected] (H.B. Kim). ** Corresponding author. Tel.: +1 612 624 0701. E-mail address: [email protected] (R.E. Isaacson). http://dx.doi.org/10.1016/j.vetmic.2015.03.014 0378-1135/ß 2015 Elsevier B.V. All rights reserved.

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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5. 6. 7. 8. 9.

Microbial composition of different pig gut locations . Genetic effects on pig gut microbiota . . . . . . . . . . . . . Effects of probiotics on pig gut microbiota. . . . . . . . . Pig gut microbial shifts by antibiotics . . . . . . . . . . . . Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction The mammalian gastrointestinal tract (GIT) has been estimated to contain 500–1000 bacterial species that constantly interact with the host and other members of the microbial community. The microbiota of GIT, the collection of microbe living inside the gut, is estimated to be composed of approximately 1014 bacteria (Savage, 1977; Xu and Gordon, 2003). The term ‘‘microbiome’’ is used to describe the totality of the microbes, their genetic elements (genomes including extrachromosomal elements), and the environmental interactions in a particular environment (Dubos et al., 1965). Frequently the term ‘‘microbiome’’ has been restricted to bacteria (Holmes et al., 2008; Isaacson and Kim, 2012). The genetic diversity of the microbiota in the mammalian GIT is very large. The gut microbiota may contain more than 100 times the number of genes in mammalian genome and has the potential to add numerous biological activities that the host lacks (Backhed et al., 2005). The interactions between the microbiota and the host were postulated by Dubos et al. (1965) who suggested that the host and its microbes coevolved. The intimate interactions that occurred between host and microbes resulted in a give and take that drove anatomical and functional evolution of the GIT. As such, the indigenous microbiota within the GIT is known to provide important benefits to its mammalian host (Berg, 1996). For instance, the mammalian distal intestine is a bioreactor containing anaerobic bacteria that are capable of degrading a variety of otherwise indigestible polysaccharides (Backhed et al., 2005). The gut microbiota is known to provide other beneficial functions for the host including the re-cycling of bile salts, production of vitamin K, and the production of exogenous alkaline phosphatases (Yolton and Savage, 1976; Gilliland and Speck, 1977; Ramotar et al., 1984). The gut microbiota is also an essential stimulus that results in the maturation of the animal’s gut immune system (Berg, 1996; Bik, 2009). Because most of the bacterial species that comprise the animal intestinal microbiota have not been cultured, it has been difficult to extensively explore microbial diversity in the healthy gut using the culture-dependent methods. Even though culture based systems to explore gut bacterial diversity have been important in determining the major groups of bacteria in the gut, the vast majority of the gut bacteria have never been grown outside the gut. It has been estimated that at least 50% of microbiota of GIT cannot be grown outside the gut (Shanahan, 2002; Sears, 2005). Therefore, using culture dependent methods, the composition and roles of gut bacteria have not been comprehensively defined. Using high throughput DNA sequencing the

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composition and distribution of the microbiota are only now being extensively described. In-depth descriptions of the gut microbiota are being facilitated by using high throughput DNA sequencing of 16S r RNA genes. The use of the 16S rRNA gene has become the de facto tool to determine taxonomic identities of bacterial populations and the sequence data provides a means to extensively describe the gut bacteria when coupled with a variety of bioinformatics tools (Woese and Fox, 1977; Schuster, 2008; van Dijk et al., 2014). Thus, these technical developments have provided the tools to comprehensively study the composition of microbial populations in the gut. The diversity of the gut microbiota and its related functions can be described in-silico using diverse tools and observations used in the study of microbial population ecology. Deciphering the sequences of 16S rRNA genes and its aggregate genetic information requires base line knowledge of sequencing techniques, normal bacterial composition in a certain niche, and basic principles of microbial ecology. The objective of this review is to provide details of the pig gut microbial community. Important questions concerning the pig gut microbial diversities will be discussed. 2. 16S rRNA genes to determine taxonomic identity The pioneering work of Carl Woese, who studied the sequences of bacterial 16S rRNA genes, led to the understanding that the 16S rRNA gene could be used to infer taxonomic designations for bacteria (Woese and Fox, 1977; Fox et al., 1980). Woese et al. showed that prokaryotes could be classified into two distinct groups: Bacteria and Archaea, based on differences in their 16S rRNA genes (Woese and Fox, 1977). Using constructed recombinant clone libraries, Olsen et al. showed that the sequences of the 16S rRNA gene could be used to describe complex microbial structures (Pace et al., 1986; Olsen et al., 1986). The 16S rRNA gene is unique in that it is present in all prokaryotes and is structurally composed of multiple conserved sequences that are maintained in all species and that flank unique hyper variable regions. The hypervariable regions correlate with species (Van de Peer et al., 1996; McCabe et al., 1999). In its simplest implementation, physical methods such as denaturing gradient gel electrophoresis coupled with the subsequent cloning and sequencing of the 16S rRNA gene can be used to differentiate between different bacterial species (Nocker et al., 2007). Recently, next generation sequencing has provided 16S rRNA gene sequence reads that can be further analyzed to provide in depth bacterial taxonomic assignments (Claesson et al., 2010; Liu et al., 2012; van Dijk et al., 2014).

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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Initially direct amplification and complete sequencing of 16S rRNA genes replaced culture-dependent techniques to perform taxonomic studies and identify bacterial species (Bik, 2009). The 16S rRNA gene in prokaryotes encodes the 16S rRNA of the small ribosomal subunit, and is about 1550 base pairs long. Several characteristics of 16S rRNA genes make them suitable for phylogenetic analysis. The 16S rRNA gene is composed of nine ‘‘hypervariable regions’’ (V1-V9) (Olsen et al., 1986; Van de Peer et al., 1996; Clarridge, 2004; Chakravorty et al., 2007). Closely related bacterial species share more similar sequences than those of more distant bacterial groups. The comparison of the 16S rRNA gene sequences enable us to differentiate between bacteria, therefore, the 16S rRNA genes can be used for accurate taxonomic identification down to the genus level (Clarridge, 2004; Wang et al., 2007). In addition, they have been used to identify a single bacterial species or differentiate among a limited number of different species or genera (Becker et al., 2004). The conserved DNA sequences that flank the nine hypervariable regions can be used to design PCR primers that enable universal amplification of specific regions of 16S rRNA genes using PCR amplification (Munson et al., 2004; Chakravorty et al., 2007; Wang and Qian, 2009). Single variable regions as well as combinations of multiple regions (e.g. V1–V3) have been used in the bacterial taxonomic identification after high throughput sequencing (Chakravorty et al., 2007; Claesson et al., 2010; Looft et al., 2014a). Hamady and Knight (2009) stated that there is no consensus on a single ‘‘best’’ region, and consequently different researchers are using different regions or multiple regions for 16S rRNA gene sequencing. A comparison of taxonomic accuracy of different variable regions indicated that none gives exactly equal results, and different variable regions are used in different laboratories (Claesson et al., 2009, 2010; Hamady and Knight, 2009). Nonetheless, it has been reported that the widely used V2 and V4 of 16S rRNA genes are appropriate single regions to be used in the taxonomic assignment and bacterial community analysis with the lowest error rates compared to other single regions (Wang et al., 2007; Liu et al., 2007, 2008). Another commonly used region is V6. However, V6 appears to be biased against the certain major bacterial phyla in the gut. For example, V6 sequences from a sample could miss a large number of bacteria in the phyla Verrucomicrobia and Bacteroidetes (Hamady and Knight, 2009). Others have reported that the V3–V4 regions are superior to other combinations of variable regions with the highest classification accuracies (Claesson et al., 2010). Thus, there is no consensus on which variable regions to use. This does indicate that interpretation of data across a broad range of studies must consider the differences that might occur as a result of differences in variable region usage. 3. Next-generation high throughput sequencing of the bacterial 16S ribosomal RNA (rRNA) gene libraries to describe bacterial community structure Next generation sequencing has played an important role in rapid discovery of the roles that bacteria play in biological functions of environments including animals.

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Commonly used modern techniques to describe microbial communities are dependent on sequencing the 16S rRNA genes using next generation sequencing platforms such as Roche 454. Other next-generation sequencing platforms used in 16S rRNA gene analysis include Illumina, SOLiD, and IonTorrent platforms (Claesson et al., 2010; Liu et al., 2012; van Dijk et al., 2014). Compared to Sanger sequencing, high throughput DNA sequencing provides a larger number of sequence reads at lower cost for a greater depth of the bacterial community structure (Schuster, 2008; van Dijk et al., 2014). Roche 454 pyrosequencing has been one of the most commonly used massively parallel sequencing technologies to describe the microbiota in highly diverse communities because it generates longer DNA sequence reads. Roche 454 pyrosequencing can generate sequence lengths of approximately 700 bp while other sequencing platforms provide 75–400 bp read lengths. However, other sequencing platforms such as Illumina yield larger number of sequence reads at a lower cost compared to Roche 454 pyrosequencing (Claesson et al., 2010; van Dijk et al., 2014). Therefore, there have been studies of 16S rRNA gene analysis using Illumina, SOLiD, or IonTorrent platforms (Whiteley et al., 2012; Caporaso et al., 2012; Mitra et al., 2013). These sequencing platforms are the good alternatives for 454 sequencing technology to conduct the 16S rRNA gene analyses. Furthermore, Roche plans to discontinue its 454 pyrosequencing platform in mid-2016 (Nature, 2013). In general, community DNAs derived from samples are used to create PCR amplicon libraries of 16S rRNA genes. Community DNA extraction can be biased for certain bacteria because of differences in cell wall structure. Often, a mechanical disruption of the bacterial cell wall, beadbeating, is incorporated in the community DNA extraction method to surmount DNA extraction bias (Guo and Zhang, 2013; Wesolowska-Andersen et al., 2014). A frequent artifact of PCR amplification of 16S rRNA genes is the formation of chimeric molecules that originate from two or more 16S rRNA genes (Haas et al., 2011). Bacterial community analysis based on PCR-amplified 16S rRNA gene sequences can be influenced by the formation of chimeric 16S rRNA amplification products. Chimeras are formed during the PCR amplification process when Taq polymerase stalls and the DNA chain extension is aborted. The short amplification product can then anneal to and prime the wrong template. This will result in a new amplicon that was derived from two different 16S rRNA genes. More chimeras are formed when a higher number of PCR cycles is used in the amplification process and when low quality polymerases are used. Therefore, the use of the small number of PCR cycles (i.e. 20 cycles) and high-fidelity proofreading enzyme minimize the formation of chimeric 16S rRNA amplification products, but does not eliminate the formation of chimeras (Lahr and Katz, 2009; Haas et al., 2011). Several bioinformatics tools have been developed to detect chimeric 16S rRNA genes. Chimera Slayer and UCHIME can be used to detect chimeras (Edgar et al., 2011; Haas et al., 2011). The sequences of the target hypervariable region(s) of the 16S rRNA genes are obtained using the high throughput next generation sequencing platform selected. During the

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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sequencing process, sequences with base calling errors are formed. Base calling error rates of the 454 pyrosequencing is about 0.1%, and the types of errors usually are insertions and deletions in homopolymer runs (Shendure and Ji, 2008; Liu et al., 2012). Bioinformatics tools such as PyroNoise implemented in QIIME and Mothur have been utilized to remove low quality sequence reads from a data set (Schloss et al., 2009; Quince et al., 2009; Caporaso et al., 2010). Taxonomic assignments employ a variety of bioinformatics tools such as Ribosomal Database Project (RDP) classifier, QIIME, and Mothur (Wang et al., 2007; Schloss et al., 2009; Caporaso et al., 2010). Well-annotated sets of 16S rRNA genes are necessary for accurate taxonomic assignments including Ribosomal Database Project, Greengenes, SILVA, and ExTaxon (DeSantis et al., 2006; Pruesse et al., 2007; Chun et al., 2007; Cole et al., 2009). While these databases help us to interpret highthroughput sequence data, improvements are still needed because many sequences remain unclassified. Operational taxonomic units (OTUs) are then identified by comparing each DNA sequence to the others for diversity analyses (Wang et al., 2007; Schloss et al., 2009; Caporaso et al., 2010). The designation of an OTU is based on a pre-defined similarity cutoff depending upon the level of taxonomic resolution desired. Since OTUs are inferred to exist based on sequence data, OTUs are not necessarily equivalent to traditional taxonomic classification (Dethlefsen et al., 2008). However, sequences with greater than 80% identity are typically assigned to the same phylum (Schloss et al., 2009). At the phylum level, the fragments of the 16S rRNA gene sequences longer than 100 bases can be accurately classified. It has been shown that the classification accuracy of the sequences longer than 100 bases was greater than 99% (Wang et al., 2007). Overall, the results of the first studies on gut microbiota have shown that real microbial communities are more complex and diverse than previously thought. The huge increase in sequence data has been used to rapidly enhance our knowledge of phylogenetic relationships between microbial taxa. 4. Succession of the pig gut microbiota Animals are thought to be bacteria-free prior to birth. However, during the birthing process animals are exposed

to a variety of bacteria in the vagina and from fecal contamination on the dam or in the environment. The concept of microbial succession in animals is an ecological principle that has been long recognized. The composition of the gut microbiota is not static and shifts over time. There is a succession of microbes over time that culminates in a ‘‘climax’’ community, which is more stable (Palmer et al., 2007). Many factors contribute to the succession process including the physiological changes that occur in the gut as it transitions to an anaerobic environment. The consumption of solid foods is another major factor that triggers a shift toward a bacterial assemblage characteristic of the adult microbiota (Palmer et al., 2007). A recent study of pig fecal microbial shifts during the weaning transition has contributed to our understanding of microbial transitions that occur in this physiologically stressful time for animals (Pajarillo et al., 2014a). In that study, the fecal microbiota of 15 commercial pigs was measured during the weaning transition using pyrosequencing of the V1–V3 (pre-weaning at 4 weeks of age and post-weaning at 6 weeks of age) (Table 1). At the phylum level gut microbial communities during the pre-weaning period were primarily comprised of the phyla Firmicutes (54%), Bacteroidetes (38.7%), Proteobacteria (4.2%), Spirochaetes (0.7%) and Tenericutes (0.2%) (Fig. 1). In comparison, at the post-weaning period the compositions of the fecal microbiota of these pigs, while containing the same major phyla, show marked changes in the relative proportion of each phylum: Bacteroidetes (59.6%), Firmicutes (35.8%), Spirochaetes (2.0%), Proteobacteria (1%), and Tenericutes (1%). Overall, Firmicutes and Bacteroidetes were the most abundant phyla in fecal microbiota of piglets accounting for more than 90% of the fecal bacterial community at both pre-weaning and post-weaning periods. Firmicutes were most abundant in pre-weaning piglets, shifting gradually to Bacteroidetes after weaning (Pajarillo et al., 2014a). At the genus level, Bacteroides, Blautia, Dorea, Escherichia and Fusobacterium were abundant before weaning. After weaning Prevotella and Clostridium became more abundant while there was a decrease in Bacteroides (Pajarillo et al., 2014a). It was speculated that the greater abundance of Bacteroides during the pre-weaning period might be due to their ability to utilize monosaccharides and oligosaccharides

Table 1 Background information of the studies cited. Reference

Age of pigs

Samples

Target

Sequencing technology

Allen et al. (2011) Cousin et al. (2012) Dowd et al. (2008) Isaacson and Kim (2012) Kim et al. (2011) Kim et al. (2012) Looft et al. (2012) Looft et al. (2014a) Looft et al. (2014b) Pajarillo et al. (2014a) Pajarillo et al. (2014b) Pedersen et al. (2013) Riboulet-Bisson et al. (2012) Upadrasta et al. (2013)

3–7 weeks 7 weeks 3–4 weeks 11 weeks 10–22 weeks 10–22 weeks 3–6 weeks 3 months 3–9 weeks 4–6 weeks 15 weeks 4 years 6–10 weeks 4–5 weeks

Feces Colon contents Ileum contents Gut contents Feces Feces Feces Gut contents Feces Feces Feces Colon and cecum contents Feces Feces

V1–V3 V5–V6 V4–V6 V3 V3 V3 V3 V1–V3 V1–V3 V1–V3 V1–V3 V5 V4–V5 V4

454 Titanium 454 Titanium 454 FLX 454 FLX 454 FLX 454 FLX 454 FLX and Titanium 454 Titanium 454 Titanium 454 Titanium 454 Titanium Illumina HiSeq2000 454 Titanium 454 Titanium

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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Fig. 1. Pig gut microbiota succession. Taxonomic classification of the sequence reads at phylum level is presented. While Pedersen et al. (2013) conducted Illunina sequencing of V5, Pajarillo et al. (2014a) and Kim et al. (2011) used 454 pyrosequencing of V1–V3 and V3, respectively. Pajarillo et al. (2014a) and Kim et al. (2011) prepared community DNAs from the feces while Pedersen et al. (2013) used colon and cecum contents.

present in sow’s milk, and the increased abundance of Prevotella during the post-weaning was due to their ability to degrade hemiculluloses such as xylans in plant-based feed (Hayashi et al., 2007; Lamendella et al., 2011). It has also been suggested that microbial shifts during weaning transition might be due to a combination of multiple factors such as chemical composition of the diet, stress resulting from the weaning process, and other physiological factors (Pajarillo et al., 2014a). After weaning, shifts in the composition of the gut microbiota continued until market age (22 weeks of age). Firmicutes and Bacteroidetes were also the most abundant phyla in fecal microbiota of the growing-finishing pigs using pyrosequencing of the V3 region of the 16S rRNA gene (Table 1 and Fig. 1) (Kim et al., 2011, 2012). Kim et al. (2011) described the fecal microbial succession from a total of 20 commercial growing-finishing pigs from two different farms. They sampled pigs starting when they were 10 weeks of age and then at three-week intervals until the pigs were 22 weeks of age. In that study, the fecal microbiota was comprised of major five phyla, Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, and Spirochaetes regardless of age. Firmicutes and Bacteroidetes accounted for approximately 90% of all bacteria present between 10 and 22 weeks of age. The proportion of bacteria in the phylum Firmicutes increased over time while the proportion of bacteria in the phylum Bacteroidetes decreased (Fig. 1). From a genus level perspective, the predominant genus was Prevotella which is in the phylum Bacteroidetes. Prevotella represented up to 30% of all classifiable bacteria when the pigs were 10 weeks of age. However, by the time these pigs were 22 weeks of age, Prevotella accounted for only 3.5–4.0% of the bacteria. As

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the levels of Prevotella decreased, there was a pronounced increase in Anaerobacter (in the phylum Firmicutes). Among the 15 most abundant genera Anaerobacter, Sporacetigenium, Oscillibacter, and Sarcina increased as pigs aged, whereas Prevotella, Lactobacillus, Megasphaera, Faecalibacterium and Dialister decreased. A comparison of individual pigs revealed some variation between animals but groups of animals of the same age were more similar to each other compared to pigs of different ages (Kim et al., 2011). Correlated with this observation there was a tight clustering of microbial OTUs between pigs at the same age as measured by principal coordinate analysis. Overall the results from Kim et al. (2011) indicated that microbial ecosystems in each pig continued to change and converged toward a profile characteristic climax community of the GIT of adult pigs as the pigs aged (Kim et al., 2011). The fecal microbiota of 4-year old Gottingen mini-pigs was analyzed using Illumina-based sequencing of the V5 region of the 16S rRNA gene (Table 1) (Pedersen et al., 2013). They found that the members of the phyla Firmicutes and Bacteroidetes accounted for about 90% of all bacteria present (Fig. 1) (Pedersen et al., 2013), which is consistent with what is found in commercial pigs. In the study by Pedersen et al. (2013), about 50% of the sequence reads were classified as unknown genera while the genus Prevotella constituted 9.4% of the fecal microbiota. Overall, studies of pig fecal microbial diversities have shown that fecal microbiota mainly consist of the phyla Firmicutes and Bacteroidetes regardless of age. Results from the above studies provide us with basic knowledge of pig gut bacterial succession; however, they may not provide us with a baseline because they described the microbiota from a limited number of pigs under specific settings and feed regimens. Pigs under the influence of different environmental conditions are likely to have different bacterial compositions. For a comprehensive characterization of the pig gut microbiota and their roles in animal physiology, broad and in-depth analyses of gut microbiota will be required through a research program such as the Human Microbiome Project (Human Microbiome Project Consortium, 2012). 5. Microbial composition of different pig gut locations The GIT is functionally and anatomically diverse and culture dependent studies have shown that composition of microbial populations throughout the intestinal system varies by location. Using culture independent technologies, Isaacson et al. (2012) and Looft et al. (2014a) have confirmed differences in compositions of the microbiota in different locations of the pig gut. When microbial communities of comparable age piglets (about 3 months old) were compared, the results from both studies were very similar to each other (Isaacson and Kim, 2012; Looft et al., 2014a). At the phylum level, Isaacson et al. (2012) showed that the microbial compositions of the ileum of 11 weeks old piglets were quite different from those of the cecum and colon (Table 1 and Fig. 2). In the ileum, Firmicutes were the dominant phylum representing more than 95% of the bacteria detected (Isaacson and Kim, 2012). However, the compositions of the microbiota of the colon

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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Fig. 2. Microbial composition of different pig gut locations. Taxonomic classification of the sequence reads at phylum level is presented. Isaacson and Kim (2012) and Looft et al. (2014a) used 454 pyrosequencing of V3 and V1–V3, respectively. Community DNAs were prepared from the gut contents sampled at 11 and 12 weeks of age for the studies of Isaacson and Kim (2012) and Looft et al. (2014a).

and cecum at phylum level were very similar to each other and to those previously described with members of the phyla Firmicutes and Bacteroidetes representing greater than 90% of the bacteria detected (Fig. 2) (Isaacson and Kim, 2012). Similarly, the study using pyrosequencingbased analysis of the V1-V3 region of the 16S rRNA gene by Looft et al. (2014a) showed that the lumen of the ileum was dominated exclusively by the phylum Firmicutes while the bacterial profiles of the cecum and mid-colon were highly similar to each other but different from the ileum (Table 1 and Fig. 2). Differences between the ileum and colon were the result of the dominance of the genera Anaerobacter and Turicibacter in the ileum and various genera in the colon such as Prevotella, Oscillibacter and Succinivibrio (Looft et al., 2014a). In addition, Looft et al. (2014a) showed that bacterial communities in the lumen were different than those associated with the gut mucosa. The microbial compositions of the ileum were different between lumen and mucosa, and these differences were because of a greater abundance on the mucosa including Prevotella, Coprococcus and Papillibacter (Looft et al., 2014a). In another study, the microbiota in the ileum from weaned piglets was shown to be dominated by members of Firmicutes such as Clostridium, Lactobacillus, Streptococcus and Sarcina (Dowd et al., 2008), which is in agreement with above studies. 6. Genetic effects on pig gut microbiota Several studies have shown important interactions between genetic and environmental factors in shaping the gut microbiota of mice and humans (Ley et al., 2006, 2008; McKnite et al., 2012). The composition of the gut microbiota in swine is also likely to be shaped by host genetics. An interesting study was performed to investigate the similarities and differences in the pig fecal

microbiota among three 15-week old purebred pig lines including Duroc, Landrace and Yorkshire (Table 1) (Pajarillo et al., 2014b). The comparison showed that these three breeds shared similar gut bacterial compositions, but also were distinct between breeds. Like the results from other pig studies, Bacteroidetes and Firmicutes comprised of more than 90% of all the fecal microbial communities regardless of breeds. However, at the genus level Catenibacterium, Phascolarctobacterium, and Subdoligranulum were more abundant in Duroc pigs, whereas Dialister was more abundant in Yorkshire pigs. This was a controlled study in which all the pigs were fed the same feed without any antibiotic treatment or feed additives, and they were housed in an environmentally controlled private breeding facility. Therefore, the authors of this study suggested that the differences in gut bacterial communities might be due to specific genetic effects of each breed. However, they did state that they could not absolutely exclude environmental factors such as pen and seasonal effects on microbial shifts when they evaluated genetic effects on pig gut microbiota (Pajarillo et al., 2014b). 7. Effects of probiotics on pig gut microbiota The use of probiotics has become a topic of great interest because they are thought to have beneficial effects on animals such as production of antimicrobial substances, inhibition of digestive diseases, enhancement of a beneficial balance among the indigenous microbial community in the gut, and/or increase in a growth performance. If the claims for probiotics are verified, they are likely to be important tools in pig production especially as the use of antimicrobials continues to decrease. Probiotics are products that contain well-characterized strains of bacteria. The claimed mechanisms of actions of probiotics include the production of antimicrobial substances, host immunomodulation, competitive exclusion of pathogenic bacteria, and gut microbiota modulation (Cammarota et al., 2014). The effects of probiotics on the gut microbiota have been the subjects of numerous research study areas over the past few years because of their expected potential to improve animal health and growth. From the animal health perspective, understanding the effects of probiotics on the gut bacterial community is important considering the importance of the microbiota in animal health. Other than beneficial effects, it is also important to evaluate if microbial alterations induced by these probiotics are associated with intestinal disorders (Riboulet-Bisson et al., 2012). Gram-positive Lactobacilli, which are commonly found in foods such as yogurt, are commonly used as probiotics. Lactobaccilli are members of the lactic acid bacteria, and are considered to have probiotic effects. Some Lactobaccilli produce antimicrobial bacteriocins that may help shape the composition of the gut microbiota. Lactobacillus salivarius UCC118, which produces bacteriocin Abp118, was tested in 6–10 weeks old pigs. The composition of the gut microbiota was compared to pigs not receiving this strain (Table 1) (Riboulet-Bisson et al., 2012). Abp118 producing L. salivarius decreased the relative proportion of bacteria in the phylum Spirochaetes. The relative

Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014

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proportions of Sudboligranulum, Oribacterium, and Hallella increased while those of Treponema, Anaerostipes, and Lactonifactor decreased in pigs administered Abp118 producing L. salivarius (Riboulet-Bisson et al., 2012). While Abp118 producing L. salivarius have a potentially beneficial effect by protecting pigs against the opportunistic pathogen Treponema, it did not enhance growth and productivity of pigs (Riboulet-Bisson et al., 2012). Propionibacterium freudenreichii is another probiotic microbe. In a study by Cousin et al. (2012) using 454 pyrosequencing of V5-V6 regions of the 16S rRNA gene (Table 1), P. freudenreichii did not alter the composition of the pig gut microbiota at the phylum level but improved pig growth and feed intake (Cousin et al., 2012). However, members of the family Porphyromonadaceae were present at significantly lower levels in pigs treated with P. freudenreichii compared to non-treated pigs. Other than this, the authors did not find differences between treated and non-treated pigs (Cousin et al., 2012). A number of studies have reported that supplementation of pig feeds with live yeast improved the growth performance in weanling pigs (Li et al., 2006; Upadrasta et al., 2013). Unlike other bacterial based probiotics, spent cider yeast significantly altered the composition of the pig gut microbiota at the phylum level causing a reduction in the proportion of Firmicutes and an increase in the proportion of Bacteroidetes (Upadrasta et al., 2013). The results from this study showed that cider yeast had the potential to selectively inhibit pathogenic enterobacteria such as Salmonella and Escherichia spp. (Upadrasta et al., 2013).

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‘‘climax’’ community. This shift then results in beneficial growth promoting effects (Kim et al., 2012). Before the tylosin treatment, the composition of the fecal microbiota were similar between tylosin treated and untreated pigs. However, as shown in Fig. 3, there was a pronounced shift in the distribution and quantity of less abundant microbes (in regions A and B) in feces from pigs treated with tylosin starting when pigs were 16 weeks of age compared to nontreated pigs. When untreated pigs reached maturity (22 weeks of age), the composition of the fecal microbiota became similar to the pigs in the tylosin treatment group. Therefore, the authors concluded that tylosin sped up the development or maturation of the unique ‘‘adult-like’’ fecal microbiota but that eventually pigs in the non-treatment groups did catch up (Fig. 3). Thus, one mechanism whereby AGPs act might be to speed up the maturation of the fecal microbiota (Kim et al., 2012). Carbadox is another in-feed antibiotic that is widely used in swine production to prevent dysentery and to

8. Pig gut microbial shifts by antibiotics Antibiotics have been used for over 60 years to improve the growth of livestock animals including pigs. The use of antibiotics as growth promoters (AGPs) probably has been a contributor to increased selection for antibiotic resistant bacterial pathogens. It has been proposed that one mechanism by which antibiotics enhance the growth of livestock animals is by alteration of their gut microbiota (Schwarz and Chaslus-Dancla, 2001; Dibner and Richards, 2005), and several studies have been conducted to evaluate the effect of antibiotics on the pig gut microbiota. For example, Kim et al. (2012) characterized the microbiota of pigs receiving one AGP, tylosin, compared with untreated pigs using 454 pyrosequencing of V3 region of the 16S rRNA gene (Table 1) (Kim et al., 2012). They determined that the fecal microbiota of pigs receiving tylosin compared with untreated pigs had shifts in the composition of the microbiota that represented an increase in the rate of microbial succession and microbial maturation in response to the use of tylosin. In that study, quantitative and qualitative analyses showed that tylosin caused microbial population shifts in both abundant and less abundant species. In particular, Lactobacillus, Sporacetigenium, Acetanaerobacterium, and Eggerthella were detected more frequently in the group of pigs receiving the AGP tylosin compared to the non-treated group. In addition, results from that study suggested that tylosin may speed up the development and maturation of the microbiota to the adult

Fig. 3. Distribution of OTUs in the two treatment groups in the study of Kim et al. (2012). The heat map was created using OTUs with an OTU definition at a similarity cutoff of 95%. Each column represents groups and each row indicates OTUs. OTUs were sorted with the most abundant OTUs displayed at the top and the least abundant OTUs at the bottom. T and NT indicate tylosin and no-tylosin group, respectively, and numbers indicates weeks of age. Abundant OTUs were red color-coded and white blanks indicate missing OTUs. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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improve feed efficiency (Looft et al., 2014b). The effect of carbadox as an AGP on the pig gut microbiota was evaluated. A phylotype analysis using 16S rRNA gene sequences was performed using samples taken before, during, and following treatment with carbadox (Table 1). There were significant differences in bacterial communities between carbadox treated and non-treated pigs. A diet change caused an increase in E. coli populations. However, carbadox pre-treatment prevented an increase of E. coli populations even after the diet change. Interestingly, in-feed carbadox use caused striking effects within 4 days of administration, with significant alterations in bacterial communities. A relatively large increase in Prevotella in pigs receiving carbadox was observed. However, this increase was attributed to a decrease in the overall abundance of other gut bacteria. Looft et al. (2012) reported effects of a combination of chlortetracycline, sulfamethazine, and penicillin (ASP250) on the pig gut microbiota and the community metagenome (Looft et al., 2012). At 20 weeks of age (2 weeks of treatment) there were decreases in bacteria in the phylum Bacteroidetes along with decreases in the genera Anaerobacter, Barnesiella, Papillibacter, Sporacetigenium, and Sarcina. There was an increase in members of the phylum Proteobacteria and that increase was correlated with increases in E. coli. It also was observed that genes associated with resistance to antibiotics increased in pigs treated with ASP250. There was an increase in genes such as aminoglycoside O-phosphotransferase, which encode enzymes involved in resistance to aminoglycoside antibiotics. What was interesting was that ASP250 did not contain an aminoglycoside antibiotic and therefore this selection occurred by an unknown and probably indirect co-selection process. In addition, analysis of the metagenomes showed that functional genes of the microbiota related to energy production and conversion were increased in pigs with the ASP250 treatment suggesting a more efficient capture of energy from the food source (Looft et al., 2012). ASP250 also caused a decrease in bacterial members of the genus Streptococcus. Correlated with this decrease was an increase in the number of streptococcal bacteriophages genomes. It was assumed that lysogenic bacteriophages were induced by treatment with ASP250 and the drop in the concentration of Streptococcus was the result of bacteriophage mediated cell lysis (Allen et al., 2011). Overall, different patterns of the microbial population shift occurred when different AGPs were administered to pigs (Allen et al., 2011; Kim et al., 2012; Looft et al., 2012, 2014b). These differences are likely related to differences in the AGP used. In addition, commercial pigs in a production setting compared to experimental isolation facilities where access to different sets of microbes in different environments and differences in feed might be responsible for this inconsistency. 9. Concluding remarks The objective of this review was to provide basic information of pig gut microbiota to better understand how differences in the composition of the gut microbiota

regulate animal health and growth. Important questions concerning the diversity in pig gut microbiota were addressed. With the combined use of next generation high throughput sequencing and 16S rRNA gene analysis, we have a better understanding of age-related pig gut microbial dynamics (Kim et al., 2011; Pedersen et al., 2013; Pajarillo et al., 2014a), microbial community structures in different gut locations (Dowd et al., 2008; Isaacson and Kim, 2012; Looft et al., 2014a), and the effects of diverse variables on pig gut microbiota (Kim et al., 2012; Looft et al., 2012, 2014a,b; Riboulet-Bisson et al., 2012; Cousin et al., 2012; Upadrasta et al., 2013; Pajarillo et al., 2014b). Overall, the lessons from these studies indicate that microbial ecosystems in each pig gut continue to change as pigs grow, and that the variations of gut bacterial populations of swine are caused by a variety of factors including antibiotics, genetics, and probiotics. These studies will broaden the understanding of the pig gut microbiota profile, and provide us with fundamental knowledge for later studies such as development of alternative ways to replace AGPs. Nonetheless, it should be noted that the comparisons of studies that use different methods require caution. For example, each variable region of 16S rRNA genes has different discriminatory power. Therefore, comparing study results that used different variable regions might mislead or biased outcomes. A better understanding of complex dynamics of gut microbial community will likely provide us with key information that will be used to enhance productivity in food animals. However, considering the important roles of the gut microbiota in animal health and well-being, what is now lacking is how alterations of gut microbiota are related to animal health and well-being. Current data are primarily descriptive and are limited to be used to correlate compositional changes with corresponding functional aspects in the animal. Thus further studies using different approaches such as metatranscriptomics and metabolomics will be needed to elucidate causes and effects of sub-groups of gut microbiota, their roles in health and disease. Acknowledgement The present study was conducted by the research fund of Dankook University in 2014. References Allen, H.K., Looft, T., Bayles, D.O., Humphrey, S., Levine, U.Y., Alt, D., Stanton, T.B., 2011. Antibiotics in feed induce prophages in swine fecal microbiomes. MBio 2,, http://dx.doi.org/10.1128/mBio.0026011, Print 2011. Backhed, F., Ley, R.E., Sonnenburg, J.L., Peterson, D.A., Gordon, J.I., 2005. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920. Becker, K., Harmsen, D., Mellmann, A., Meier, C., Schumann, P., Peters, G., von Eiff, C., 2004. Development and evaluation of a quality-controlled ribosomal sequence database for 16S ribosomal DNA-based identification of Staphylococcus species. J. Clin. Microbiol. 42, 4988–4995. Berg, R.D., 1996. The indigenous gastrointestinal microflora. Trends Microbiol. 4, 430–435. Bik, E.M., 2009. Composition and function of the human-associated microbiota. Nutr. Rev. 67 (Suppl. 2), S164–S171.

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Please cite this article in press as: Kim, H.B., Isaacson, R.E., The pig gut microbial diversity: Understanding the pig gut microbial ecology through the next generation high throughput sequencing. Vet. Microbiol. (2015), http://dx.doi.org/ 10.1016/j.vetmic.2015.03.014