© 2002 by The Society for Integrative and Comparative Biology
Comparative Microbial Diversity in the Gastrointestinal Tracts of Food Animal Species1
1 Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
2 Department of Fisheries, Animal and Veterinary Sciences, University of Rhode Island, Kingston, Rhode Island 02881, USA
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Molecular tools based on small subunit (SSU) rDNA gene sequences offer a powerful and rapid tool for the analysis of complex microbial communities found in the gastrointestinal tracts (GIT) of food animal species. Extensive comparative sequence analysis of SSU rRNA molecules representing a wide diversity of organisms shows that different regions of the molecule vary in sequence conservation. Oligonucleotides complementing regions of universally conversed SSU rRNA sequences are used as universal probes, while those complementing more variable regions of sequence are useful as selective probes targeting species, genus, or phylogenetic groups. Different approaches derive different information and this is highly dependent on the type of target nucleic acid employed and the conceptual and technical basis used for nucleic acid probe design. Generally these approaches can be divided into DNA-based methods employing empirically characterized probes and rRNA-based methods based on comparative sequence analysis for design and interpretation of "rational" probes. Polymerase chain reaction (PCR) based techniques can also be applied to the analysis of microbial communities in the GIT. Direct cloning of SSU rDNA genes amplified from these complex communities can be used to determine the extent of diversity in these GIT communities. Denaturing gradient gel electrophoresis (DGGE) is another powerful tool for profiling microbial diversity of microbial communities in GI tracts. Sequence analysis of the excised DGGE amplicons can then be used to presumptively identify predominant bacterial species. Examples of how these molecular approaches are being used to study the microbial diversity of communities from steers fed different diets, swine fed probiotics, and Atlantic salmon fed aquaculture diets are presented.
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INTRODUCTION |
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The microbial community inhabiting the gastrointestinal tract (GIT) is represented by all major groups of microbes and is characterized by high population density, wide diversity and complexity of interactions (Hespell et al., 1996
; Stewart et al., 1997). Resident microbial populations have been described in herbivores, omnivores, carnivores, and in a wide range of zoological classes where they contribute to the nutrition, physiology, immunology and protection of the host (Mackie and White, 1997; Mackie et al., 1997). Despite this vast amount of knowledge, the basic prerequisites for ecological studies, namely enumeration and identification of all community members have tremendous limitations. These limitations can be overcome using molecular ecology techniques based on sequence comparisons of nucleic acids (DNA and RNA) and can be used to provide a molecular characterization, while at the same time providing a classification scheme that predicts phylogenetic relationships (Pace et al., 1985; Stahl, 1986; Stahl, 1988; Ward, 1989; Olsen and Woese, 1993). Application of a variety of nucleic acid probes and the polymerase chain reaction (PCR) can potentially provide a complete description of an organisms genetic composition, the extent to which these activities are expressed, as well as, taxonomic information. Thus nucleic acid probes serve to evaluate the presence of specific sequences in the community and provide a link between knowledge obtained in pure culture and the microbial populations they represent in the GIT. Thus development and use of these techniques will result in greater insights into community structure and activity of gut microbial ecosystems, as related to functional, spatial, and temporal interactions between different microorganisms. The successful development and application of these methods, promises to provide the first opportunity to link distribution and identity of gastrointestinal microbes in their natural environment with their genetic potential and in situ activities. |
APPLICATION OF NUCLEIC ACID BASED ANALYSIS OF GASTROINTESTINAL COMMUNITIES |
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In molecular ecology it is important to distinguish between identification, quantification and monitoring of function and activity. The information derived from each approach is highly dependent on the type of target nucleic acid employed and the conceptual and technical basis used for nucleic acid probe design. Generally these can be divided into DNA-based methods employing empirically characterized probes and rDNA-based methods based on comparative sequence analysis for design and interpretation of "rational" probes (Pace et al., 1985
; Stahl and Amann, 1991; Ward et al., 1992; Olsen and Woese, 1993; Stahl, 1993b; Raskin et al., 1997). Molecular approaches for the characterization of microbial communities have been reviewed extensively. Two recent reviews (Mackie et al., 2000a, b) describe these approaches in gastrointestinal microbiology. It is clear from these reviews that all of the techniques used to describe community structure have limitations. Therefore, it is critical that one use a variety of these methodologies. The principles and practice involved in small subunit (SSU) rRNA based methods have also been extensively reviewed (Pace et al., 1985; Stahl, 1986, 1988, 1993a, b; Ward, 1989; Sayler and Layton, 1990; Stahl and Amann, 1991; Ward et al., 1992; Olsen and Woese, 1993; Hugenholtz and Pace, 1996; Raskin et al., 1997). Extensive comparative sequence analysis of 16S rRNA molecules (
1,500 bp) representing a wide diversity of organisms shows that different regions of the molecule vary in sequence conservation. Oligonucleotides complementing regions of universally conversed 16S rRNA sequence are used as universal probes while those complementing more variable regions of sequence are useful as selective probes targeting species, genus, or phylogenetic groups.
One approach for directly determining the genetic diversity of complex microbial populations is based on electrophoresis of PCR-amplified 16S rDNA fragments in polyacrylamide gels containing a linear gradient of denaturants. In denaturing gradient gel electrophoresis (DGGE, Muyzer et al., 1993), DNA fragments of the same length but different base-pair sequences can be separated. This procedure has been applied to the analysis of PCR fragments derived from the V3 region of the 16S rRNA (Muyzer et al., 1993). These fragments were obtained after amplification of 16S rDNA genes from genomic DNA from uncharacterized mixtures of microorganisms. Subsequent hybridization with group-specific oligonucleotide probes was used to identify particular constituents of the population (Muyzer et al., 1993). This procedure allows one to directly identify the presence and relative abundance of different species and to profile microbial populations in both a qualitative and semi-quantitative way. Thus, the DGGE profiling method can be used for the assessing the relative abundance of microorganisms such as Archaea and Bacteria in samples obtained from different communities.
Recent studies have demonstrated that DGGE is a tool which can be used to examine complex microbial communities (Ferris and Ward, 1997; Ferris et al., 1997; Heuer and Smalla, 1997; Kowalchuk et al., 1997; Muyzer and Smalla, 1998). These studies have previously been limited to observation of differences or changes within a very defined environmental community, such as hot spring microbial mats, biofilms, tidal sands, and individual species interactions. These studies produced "simpler" banding patterns that only had a restricted number of community members. Molecular analysis of the GIT bacterial community, which is not only highly complex, but also difficult to characterize due to its abundant and varied populations, is still a novel, yet expanding area for this application.
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ANALYSIS OF THE RUMEN BACTERIAL DIVERSITY UNDER TWO DIFFERENT DIET CONDITIONS |
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The microbiota of the rumen is one of the best studied gastrointestinal systems (Hespell et al., 1996
; Stewart et al., 1997) and it has been a subject of more than forty years of intensive research efforts. Until recently, the methods of studying the rumen microbiota have been essentially based on various cultivation techniques. Numerous studies describing a wide variety of aerobic, facultative and anaerobic bacterial strains from ruminants of different age, health conditions, geographical locations, seasons, and diets have been published (for reviews see Bryant, 1959; Hungate, 1966; Dehority and Orpin, 1988; Stewart and Bryant, 1988; Stewart et al., 1997). However, limitations imposed by these culture based studies have precluded a standardized description of the rumen microbiota. Recently, community SSU rDNA libraries have been used in studies of the rumen microbiota (Whitford et al., 1998; Tajima et al., 1999). Despite the universality and accuracy of this approach, these studies remain relatively time- and labor-intensive and are expensive. Our alternative approach is to use DGGE of the variable (V3) region of SSU rRNA genes with subsequent sequence and phylogenetic analyses. In our study, the ruminal bacterial populations of two groups of steers (eight total) maintained on different diets two diets (70% corn or 70% hay) were studied (Kocherginskaya et al., 2001). In order to validate this approach, whole community libraries of the 16S rDNA V3 region were generated and analyzed from the same samples. The resulting sequence and phylogenetic data were used to define operational taxonomic units (OTUs) or phylotypes and compare the phylotype similarity, diversity, richness, and evenness in four clone libraries (DGGE and random sequencing libraries from the two groups of steers).
DGGE analysis of rumen contents from the steers fed different diets showed a DGGE amplicon polymorphism which was relatively simple, with about twelve bands represented from each diet. Cluster analysis of these DGGE fingerprint patterns placed the samples according to the diet with a high degree of confidence. The major amplicons from these DGGE patterns (five from the corn diet and four from the hay diet) were cloned and subjected to DNA sequence analysis. Sequence analysis of individual DGGE amplicons revealed the presence of multiple amplicons, and therefore, phylotypes, in each of the major amplicons. There were 23 and 19 phylogroups (OTUs) found in the corn- and hay-fed animals, respectively, while the DGGE banding pattern suggests the presence of no more than twelve phylogroups. This is in contrast to our recent calculations which show that there might be more than a hundred OTUs belonging to the Cytophaga-Flavobacter-Bacteroides (CFB) phylum alone in the rumen ecosystem (unpublished data). Nonetheless, the DGGE based approach yielded results that were consistent with previously generated libraries (Whitford et al., 1998; Tajima et al., 1999), and our own whole community SSU rDNA libraries generated from the same samples used for DGGE. According to our data, the majority of phylotypes within the three ruminal phyla (CFB, Low-G+C Gram-positive bacteria; LGCGPB, and Proteobacteria) found in two different diets do not overlap with each other and correspond to dietary conditions. Thus, this analysis can be used for defining a functionally important predominant species on a given diet. Further, the SSU rDNA sequence information may be used as a tagging tool, with the possibility of selected isolation, this establishing the metabolic characteristics of isolates that are predominant and significant for rumen function under specific dietary conditions.
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MOLECULAR ANALYSIS OF THE GIT MICROBIOTA OF SWINE FED PROBIOTICS |
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The porcine GIT microbiota has been studied to increase production efficiency, improve product quality, and help reduce disease. During the developmental period from birth through weaning, the intestinal microbiota undergoes a rapid ecological succession. There is interest in developing a monitoring technique that allows for analysis of bacterial population levels and shifts within the pig intestine.
The diversity of the porcine GIT microbiota was studied after introduction of exogenous Lactobacillus reuteri strain MM53 using 16S rDNA techniques (Simpson et al., 2000). Piglet treatment groups (control animals, daily-dosed animals, and 4th-day-dosed animals) were dosed with L. reuteri and fecal samples collected over a 20 day period. Fecal PCR products for V1 and V3 regions of 16S rDNA were analyzed by DGGE. Use of bacterial-specific V3 region DGGE primers facilitated examination of general GIT population changes in response to dosing and time. DGGE profiles indicated that each individual maintains a unique GIT bacterial population which is stable over time. Additionally, distinct time-dependent separations within animal DGGE patterns were also observed. V1 primers designed specifically to restrict DGGE analysis to a select group of lactobacilli allowed examination of inter-species relationships and abundance as influenced by dosing. L. reuteri was distinguishable within V1 patterns based upon relative band migration distance and sequence determination.
Many specific primers and probes have been designed for detection of different lactobacilli within the V1 region of the 16S rRNA gene (Klijn et al., 1991; Vogel et al., 1994). The V1 region primer set used was designed to amplify the Lactobacillus species that cluster in the L. reuteri phylogenetic group (L. fermentum, L. oris, L. pontis, and L. vaginalis) (Simpson et al., 1999). Primers were designed complementary to E. coli consensus positions 0092 (Lacto #1) and 0338 (Lacto #2). Primer Lacto #2 is the complement of the bacterial-specific probe S-D-Bact-0338-a-A-18, applied in a reverse orientation to obtain a 350 bp fragment.
The DGGE analysis for V3 region PCR amplicons demonstrated relatively stable banding patterns throughout the collection period. Differences were found in positions of specific amplicons, intensity of amplicons, and number of amplicons present. Each animal had its own unique amplicon pattern, indicating that within-animal variation was less than between-animal variation. There were daily variations in banding intensities among piglets and some appearance or disappearance of bands, but for each individual animal the overall 20-day pattern was sufficiently stable to observe shifts in individual bands representing temporal changes in bacterial populations.
As expected, the V1 DGGE amplicon pattern observed for fecal lactobacilli was much simpler than that of V3 DGGE banding patterns. The total number of amplicons was reduced to no more than 8, with an average of 4. The Dice similarity coefficients (Dsc) calculated for the V1 region had an overall wider range than that observed for the V3 regions, although percent similarities were higher. All nine animals had Dsc values between 95 to 100% similarity for the V1 region. The V3 region had Dsc values between 85 and 90%, with only one animal having a data point at 95%. This closer relationship between patterns for the V1 region was most likely a statistical effect of a simplified amplicon pattern.
The control animals showed an oscillation pattern, with cycle intervals repeated every two days, indicating a periodic fluctuation for this group. Comparisons of fluctuation patterns with the daily-dosed animals indicated a possible suppression effect on the normal cycling of the indigenous L. reuteri population, resulting from the frequent introduction of the dosed strain. After discontinuing the daily treatments, a two-day cyclic pattern emerged. For the 4th-day-dosed animals, peaks were observed following dosage days. Peaks occurred on days 5, 7, 10, and 13 which corresponded with dosing days 5, 9, and 13. The last two peaks (days 16 and 18) occurred after the trial period and followed the oscillation pattern of 2 to 3 day intervals observed for the previous periods.
V1 DGGE analysis indicated that a background population of L. reuteri was present. However, the changes observed in the L. reuteri amplicon pattern intensities correlated to dosing schedules and were significantly above background levels. Frequent inoculation of L. reuteri influenced the cyclic pattern fluctuations in both the daily-dosed and 4th-day-dosed groups. However, following termination of dosing, cyclic patterns for both the daily-dosed and 4th-day-dosed animals became similar to the controls, indicating that this was possibly a normal occurrence, although more investigation is necessary for confirmation.
In summary, DGGE can be applied effectively to the pig GIT system to monitor changes in bacterial populations throughout the GIT. These studies describe the application of DGGE for monitoring changes in gastrointestinal microbiota of piglets after the introduction of an exogenous strain of L. reuteri. These results provide evidence that each individual exhibits a unique bacterial community as demonstrated by stable and repeatable amplicon patterns. Using bacterial specific primers within the V3 region of the SSU rDNA allows examination of population changes, either as a result of dosing or time. Examination of patterns using primers specific for a select group of Lactobacillus permitted a detailed look into inter-species relationships and abundance as influenced by dosing. The significance of this study for GIT health in general, is that this technique will be useful for monitoring changes in the microbiota of individuals with GIT disorders or under treatment with alternative supplements. Organisms of medicinal interest can be administered, detected and their influence upon other bacteria monitored over time. The effect of different factors such as diet or antibiotics, on GIT bacterial relationships can now be explored.
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MICROBIAL DIVERSITY IN THE GIT OF ATLANTIC SALMON |
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The recent proliferation of the aquacultural industry is a response to the worldwide demand for an efficient supply of high protein food. It has been reported that productivity of the fish farming industry has increased from 10 million metric tons in 1984 to over 20 million metric tons in 1996. Additionally, 90 million metric tons of wild fish are caught every year (Csavas, 1994
; Hjul, 1997). Defining the microbial ecology of aquatic gastrointestinal ecosystems facilitates the understanding of microbial relationships pertaining to the animal's health. Therefore, gastrointestinal microbial populations have a direct effect on efficiency of animal production. Likewise, the impact of aquaculture on the environment is also effected by the microbial ecology of the aquacultural processes. In the end, the sustainability of the aquaculture industry will benefit from a description of the gastrointestinal biota of aquatic organisms. However, the molecular approaches described previously have not been widely applied toward monitoring the microbial ecology of aquatic intestinal systems (Cahill, 1990). Therefore, we examined the effect of starvation over time on the intestinal microbiota of Atlantic salmon. Specifically, the microbial populations of the GIT were profiled using DGGE. DGGE analysis demonstrated observable changes to the microbial community profile in response to starvation. Both lumenal and mucosal samples were analyzed. There were at least three amplicons in the control fish mucosal samples which differed from samples from fish starved either 3 days or 7 days. Similarly, at least five of the amplicons from the mucosal sample of the 7 day starved Atlantic salmon appear to be different from GIT samples from the control or 3 day starved Atlantic salmon. Amplicons that were predominant and/or unique in lumenal and mucosal samples of 7 day starved Atlantic salmon were selected for DNA sequence analysis. Sequence data obtained from amplicons obtained from mucosal samples of 7 day starved Atlantic salmon resulted in a diverse set of phylogroups including two amplicons in the CFB phylum (most closely related to Prevotella species or Bacteroides vulgatus), one amplicon in the LGCGPB (most closely related to Clostridium cellulolyticum), and one amplicon in Gamma Proteobacteria (most closely related to Salmonella typhimurium). Sequence data obtained from amplicons obtained from lumenal samples of 7 day starved Atlantic salmon resulted in a less diverse set of phylogroups. All amplicons were including in the Proteobacteria phylum with two falling in the Beta Proteobacteria (most closely related to the Oxalobacter group or a Dunganella sp.), and the other two falling in the Gamma Proteobacteria (both most closely related to Shewanella sp.). This study suggests that a change in the microbial community occurs in the GIT during starvation and that the application of molecular techniques toward aquatic GIT ecosystems facilitates the description of the microbial response to environmental factors.
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CONCLUSIONS |
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It is clear that the use of molecular ecology techniques will lead to major advances in the description of gastrointestinal ecosystems. The successful development and application of these methods, promises to provide the first opportunity to link distribution and identity of gastrointestinal microbes in their natural environment with their genetic potential and in situ activities. This will result in an increased understanding and a complete description of gastrointestinal community of production animals under different feeding regimes, and lead to new strategies for improving animal growth. Finally, in the future, of central importance will be the development of in situ methods for determining the activity of individual organisms, therefore assessing population dynamics as well as community functionality.
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ACKNOWLEDGMENTS |
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This work was supported by the U.S. Department of Agriculture National Research Initiative Programs in Animal Health and Well Being and Improving Animal Growth and Nutrient Utilization, by the Agricultural Experimental Station of the University of Illinois, and by the Illinois Council on Food and Agricultural Research.
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FOOTNOTES |
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1 From the Symposium Living Together: The Dynamics of Symbiotic Interactions presented at the Annual Meeting of the Society for Integrative and Comparative Biology, 3–7 January 2001, at Chicago, Illinois.
2 E-mail: b-white2{at}uiuc.edu
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