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Keywords:

  • rpoB;
  • DGGE;
  • phylogenetics;
  • rumen

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Two new primer sets based on the rpoB gene were designed and evaluated with bovine and ovine rumen samples. The newly developed rpoB-DGGE primer set was used along with the 16S rRNA gene-V3, and another (old) rpoB-DGGE-based primer set from a previous study to in vitro compare the bovine and ovine rumen ecosystems. The results indicate a significant (P<0.001) difference in the microbial population between the two ruminants irrespective of the primers used in the analysis. Qualitative comparison of the data provides evidence for the presence of similar phyla profiles between the 16S rRNA gene and the newly developed rpoB primers. A comparison between the two rpoB-based primer sets (old and new) showed that the old rpoB-based primers failed to amplify phylum Bacteroidetes (a common phylum in the rumen) in both bovine and ovine rumen samples. The old and new rpoB-DGGE-based primers amplified a large number of clones belonging to phylum Proteobacteria, providing a useful insight into the microbial structure of the rumen. ChaoI, ACE, Simpson, and Shannon–Weaver index analysis estimated the bovine rumen to be more diverse than the ovine rumen for all three primer sets. These results provide a new insight into the community structure among ruminants using the newly developed primers in this study.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The gastrointestinal tract of the ruminant is comprised of a complex ecosystem that plays an important role in providing necessary nutrition to the host and is involved in the maintenance of animal health (Hungate, 1966). The microbial population of the rumen is composed of numerous yet undetermined numbers of protozoal, fungal, archaeal, and bacterial species (Hungate, 1966; Russell & Rychlik, 2001; Edwards et al., 2004). Like other microbial ecosystems, the species present and their relative abundance can change with time, age of the animal, seasons of the year, use of therapeutic agents, growth-promoting antibiotics, and the diet of the host animal (Dehority & Orpin, 1997).

The use of gene sequences as molecular markers for determining evolution and phylogenetic relationships was first proposed by Zuckerkandl and Pauling (1965). Woese and colleagues (Fox et al., 1980; Woese, 1987) introduced a novel classification system that utilizes the small subunit rRNA gene as a universal marker for classifying microorganisms. The 16S rRNA gene has provided microbiologists with the necessary tool to identify and evaluate microbial communities by direct amplification (Woese et al., 1975; Woese et al., 1976). Most microbial ecologists, as well as microbial pathologists, have utilized the 16S rRNA gene marker to understand microbial community structure and function (Deutschbauer et al., 2006; Green & Keller, 2006; Xu, 2006) and in specific ecosystems such as cow rumen under different feeding strategies (Zhou et al., 2009), human gut flora (Ley et al., 2006; Ley et al., 2008a), and in enumerating ocean bacteria (Rappe et al., 2002).

The 16S rRNA gene maker, however, has two limitations when used to analyze complex microbial communities. The first limitation is the heterogeneity in gene copy number (1–13 copies) among bacterial species, making it inaccurate when estimating population changes (Dahllöf et al., 2000; Case et al., 2007). The second limitation of this marker is its inability to differentiate closely related species/strains, which makes it difficult to accurately analyze the lineages of various medically important bacteria (Kim et al., 2003; Khamis et al., 2004). These disadvantages have led researchers to look at alternative universally present genes that occur as a single copy and can be used in conjunction with the 16S rRNA gene marker.

Housekeeping genes such as dnaK (Griffiths & Gupta, 2001; Stepkowski et al., 2003; Eardly et al., 2005), gyrB (Rodrigues & Tiedje, 2007; Volokhov et al., 2007), and rpoB (Mollet et al., 1997; Bourne & Munn, 2005; Rigouts et al., 2007) have become increasingly popular in understanding bacterial systematics and evolutionary processes (Kupfer et al., 2006). These markers are also ubiquitous in prokaryotes, occur in a single gene copy, and have less susceptibility to lateral gene transfer (Case et al., 2007). In particular, the RNA polymerase β subunit (rpoB) gene provides a better phylogenetic resolution either as a nucleotide or as a protein sequence (Case et al., 2007). Like the 16S rRNA gene marker, the rpoB gene consists of both conserved and variable regions. Studies have indicated that the hypervariable region of the rpoB gene is located between positions 2300 and 3300 bp of the gene (Adekambi et al., 2009). Further, due to the size of the gene (approximately 3500 bp), there is greater flexibility in designing probes and primers for differentiating bacteria at the inter/intra species level.

The objectives of this study were to design, validate, and compare in vitro new rpoB-based primers for denaturant gradient gel electrophoresis (DGGE) and cloning (larger fragment amplifying) to estimate bacterial populations in the rumen. The robustness of the newly developed primer sets was tested with pure culture isolates and in vitro rumen samples obtained from the bovine (Bos taurus) and ovine (Ovis aries). Further, the new rpoB-DGGE primers were compared with a previously developed old rpoB-DGGE primer set (Dahllöf et al., 2000) for its efficiency to amplify pure culture isolates and rumen communities. The new rpoB-DGGE phylogenetic associations were compared with in silico generated 16S rRNA gene trees to elucidate tree topology differences. DGGE, cloning, and phylogenetic analysis were performed to determine the species composition of the rumen microbial community present in these ruminant samples.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Bacterial cultures and media

A list of bacteria, media, and growth conditions used in this study is described elsewhere (Supporting Information, Table S1). Aerobic bacterial cultures of bacteria were grown either on tryptic soy broth or on Luria–Bertani (LB) broth (Elbing & Brent, 2002). Complex media (Supporting Information) were used for the routine growth of anaerobic bacteria. Bacterial cultures were transferred from a cryo-freezer and grown at appropriate temperatures (Table S1) for 2 days, before extraction of genomic DNA.

Cattle and sheep diets, experimental setup, and whole rumen fluid (WRF) collection

WRF samples were collected from fistulated Holstein cows (n=2) and from fistulated wethers (n=3). The Holstein cattle were fed a diet of 63% grass hay, 30% concentrates, and 7% crude protein. The sheep diet consisted of 100% grass hay. Animals were housed in an independent semi-enclosed barn enclosure. A 30 mL volume of rumen fluid was collected from each animal (bovine or ovine) in a sterile prewarmed CO2-flushed thermos. The samples were transported to the laboratory, respective samples were pooled, homogenized, and DNA was isolated immediately.

Genomic and plasmid DNA isolation

Genomic DNA was extracted using the Gentra puregene kit (Qiagen, Valencia, CA). Plasmid DNA was extracted as per ABI's (Applied Biosystems, Foster City, CA) modified alkaline lysis protocol using PEG 8000 and chloroform.

Design of new rpoB primers

A total of 141 rpoB sequences, elucidated from whole genome sequences, were obtained from the GenBank database (Benson et al., 2010). Multiple alignments were performed using clustal w v1.8 (Thompson et al., 1994). The alignments were imported into a computer program called geneious (Biomatters Ltd, Auckland) (Drummond et al., 2010), and based on the percentage of nucleotide consensus, regions of homology were chosen (Rozen & Skaletsky, 2000). Potential primer pairs were analyzed using the nucleotide blast tool (Altschul et al., 1990). Primer sets were designed to amplify a shorter DGGE fragment and a longer cloning fragment. A GC clamp was added to the forward DGGE primer set (Muyzer et al., 1993).

PCR setup

The reagents used were common to all PCR reactions. Two separate PCR reactions were performed for amplifying the DGGE fragment and the longer rpoB fragment. For the DGGE fragment, PCR thermocycling was carried out using recombinant AmpliTaq® Gold polymerase (Applied Biosystems) in a PTC-200 thermocycler (MJ Research Inc., Watertown, MA). PCR conditions were optimization with the following parameters: amount of DNA, primer annealing temperature, Mg+ concentration, primer concentration, bovine serum albumin (BSA), and the type of polymerase. Based on these optimization reactions, the final PCR protocol is given below. Each 50 μL PCR reaction contained 75 ng of purified chromosomal DNA from WRF or <10 ng of pure culture DNA, 200 μmol of each dNTP, 5 μL of 10 × PCR buffer, 5 μL of 25 mM MgCl, 20 ng of BSA, each primer concentration at 25 pmol, 0.25 U polymerase, and the remaining volume made up with sterile double-distilled H2O. Amplification of the DGGE rpoB fragment was achieved using a touchdown thermocycling program that consisted of an initial 9-min denaturation cycle at 95 °C, followed by subsequent denaturation at 95 °C for 20 s. The initial PCR reaction was performed at 57 °C with a reduction of 0.5 °C at each cycle for 15 cycles. The annealing time was 45 s for each cycle and the final touchdown temperature was set at 49 °C for an additional 15 cycles. A final extension was performed at 72 °C for 10 min. For the longer rpoB fragment, the reaction mixture constituents were similar to the DGGE setup described above. The PCR amplification was performed under the following conditions: the initial denaturation temperature was set at 95 °C for 9 min and the subsequent denaturation at 95 °C for 20 s, annealing at 53 °C for 40 s, and a primer extension at 72 °C for 1.5 min for 25 cycles with a final extension time of 10 min at 72 °C.

The hypervariable region, V3, of the 16S rRNA gene was also used as a gene marker for amplifying the rumen bacterial population of the two ruminants. The primers and protocol for amplifying the 16S rRNA gene-V3 gene marker have been described previously (Muyzer et al., 1993). The old rpoB-based primer set was amplified as per previously published protocols (Dahllöf et al., 2000). PCR products were run on a 1.2% agarose gel and stained with ethidium bromide.

Cloning, archiving of PCR products, and plasmid extraction

PCR products were visualized using a 1.2% agarose gel and products purified using the QIAquick PCR purification kit (Qiagen) according to the manufacturer's recommendations. PCR products were quantified using a Nanodrop ND-1000 spectrophotometer (Thermo Fisher, Waltham, MA), cloned using the TOPO® TA Cloning Kit for sequencing (Invitrogen Corporation, Carlsbad, CA) and transformed into competent Escherichia coli cells as per manufacturer's recommendations. Transformants were plated on LB agar (EMD Chemicals Inc., Gibbstown, NJ) supplemented with 50 μg mL−1 kanamycin (EMD Chemicals Inc.) and incubated overnight at 37 °C. Picked clones were archived in 1.5 mL LB supplemented with 50 μg mL−1 kanamycin and 1 × Hogness buffer (Sebat et al., 2003). Colonies were stored at −80 °C. The colonies were retransferred into LB broth supplemented with 50 μg mL−1 kanamycin and grown overnight at 37 °C for plasmid isolation.

Plasmid DNA was extracted using the QIAprep spin kit (Qiagen), quantified (Nanodrop), and stored at −20 °C.

DGGE setup

The DCode system for DGGE (BioRad, Hercules, CA) was used to analyze PCR fragments. The rpoB PCR products were separated on an 8% polyacrylamide (37.5 : 1, acrylamide/bis-acrylamide) (BioRad) gel with a denaturing gradient of 30–65%. The rpoB PCR products were mixed with 10 μL of 2 × loading dye (BioRad) and brought to a final volume of 20 μL with TE (pH 8.0) to yield a DNA concentration of 10–15 ng for the pure culture samples. DNA concentrations at 100 ng per well were used for the whole rumen samples. Gels were run for 16 h at 60 V in 1 × Tris–acetate–EDTA (TAE) at 60 °C. Gels were either stained using SYBR Gold stain (Invitrogen Corporation) or silver staining (BioRad) according to the manufacturer's instructions. Gels were visualized on a fluorescent light box (Star X-ray, Amityville, NY) and gel images were captured using a digital camera.

Sequencing and phylogenetics

Sequencing was performed using the BigDye® Terminator v. 3.1 Cycle Sequencing Kit (Applied Biosystems) using an ABI Prism® 3730 Genetic Analyzer at the Center for Genomic Research and Biocomputing (CGRB), Oregon State University. For sequencing, cloned DGGE products from the 16S rRNA gene, old rpoB, and new rpoB clones were read utilizing either the T3 or the T7 primer end. The longer rpoB fragments were read from both directions of the TOPO® cloning vector. The raw sequence files were extracted, processed, and compared with existing sequences using the blastn algorithm (Altschul et al., 1990). Based on E-value hits, sequences were included in the final alignment. The sequences were aligned using the muscle alignment program (Edgar, 2004). The nexus alignment was modified to an XML-formatted file using the beauti program included in the beast program suite (Drummond & Rambaut, 2007) with the addition of the GTR model and generation time. The nucleotide alignment was run twice for 10 million generations and the resulting tree files from both runs were combined using the logcombiner package provided with the beast program. Of the 20 000 trees that were produced, 50% of the trees were excluded from the final analysis. The final consensus tree was viewed and edited using the software program figtree (http://tree.bio.ed.ac.uk/software/figtree/).

The RDPII website tools classifier and libcompare were used for processing the 16S rRNA gene-V3 clone data. For the rpoB-associated data, manual classification was undertaken using the GenBank database (Benson et al., 2010). The mothur software package v 1.11.0 (Schloss et al., 2009) was used for the analysis of collectors, rarefaction curves, Libshuff analysis, and to calculate diversity indices such as ACE, Simpson, and Shannon–Weaver Indices. All sequence data were submitted to the GenBank database under accession numbers (GU304662GU305194, GU305195GU305532, and GU305533GU305690).

In silico analysis of 16S rRNA gene fragments

From the GenBank database, 23 full-length 16S rRNA gene sequences were obtained. These 16S rRNA gene sequences were aligned using the muscle program mentioned above. A Bayesian phylogenetic tree was constructed using the parameters mentioned in the above section.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Design for the new rpoB-based DGGE and large fragment primers

Out of the total 141 primary sequences imported from GenBank, 39 sequences from the phyla [Proteobacteria (16), Firmicutes (11), Actinobacteria (8), Bacteroidetes (2), Aquificae (1), and Deinococcus-Thermus (1)] (Table S2) were finally included for primer development. Ten primer sets were initially developed (data not shown) and only one set of rpoB-DGGE primers (Table 1) could amplify all the test bacteria.

Table 1.   The rpoB-DGGE and cloning primers developed and used in this study
Primer nameNucleotide sequenceReference
  • *

    Represents GC clamp added to the 5′ end of the primer.

New rpoB-DGGE (F)5′-TCA CGG TAA CAA RGG-3′*This study
New rpoB-DGGE (R)5′-AGT GCC CAT ACT TCC AT-3′This study
Long fragment (F)5′- GCG AAC ATG CAA CGT CAG GC-3′This study
Long fragment (R)5′-AGT GCC CAT ACT TCC AT-3′This study
Old rpoB-DGGE (F)5′-AAC ATC GGT TTG ATC AAC-3′*Dahllöf et al. (2000)
Old rpoB-DGGE (R)5′-CGTTGCATG TTGGTA CCCAT-3′Dahllöf et al. (2000)

The new DGGE forward primer aligned to E. coli position 3205–3221 and the reverse primer aligned to E. coli position 3817–3834 of the rpoB gene. The forward primer amplified a part of the rpoB variable region (approximately 70 bp) (Adekambi et al., 2009). The rpoB-DGGE forward primer had a degeneracy of R at the 13th nucleotide that represents a base substitution for purine (A) or a pyrimidine (G) near the 3′ end of the forward primer (Table 1). Primer sets designed without the degeneracy amplified fewer bacterial strains (16 bacterial strains vs. 27 bacterial species with the degeneracy) (data not shown). PCR amplification of E. coli resulted in a 620-bp fragment (data not shown). There were visible size differences in PCR products between Gram-positive and Gram-negative bacterial strains (Fig. S4b). The Gram-positive bacterial strains generated a PCR fragment close to 450–500 bp, while Gram-negative bacterial strains generated a 550–650-bp fragment. For the longer cloning fragment, the forward primer aligned to E. coli position 2047–2066, while the reverse primer was the same as that used in the DGGE primer design (Table 1) and aligned to E. coli positions 3817–3834 bp. The product formed with this amplification would amplify the entire hypervariable region of the rpoB gene, which is situated from 2300 to 3300 bp of the gene (Adekambi et al., 2009).

The DGGE primer set was tested against 27 pure cultures of bacteria (21 rumen-associated bacteria and six general bacterial species) (Table 2) to evaluate the formation of single bands (Figs S1–S3). The primers also elucidated visual interspecies differences within the genus Ruminococcus sp. (Fig. S1, lanes 5, 6, and 7 represent three species of Ruminococcus sp. namely Ruminococcus albus 7, R. albus 8, and Ruminococcus flavenflaciens C94).

Table 2.   Bacterial strains used to test the newly developed rpoB primers, the comparison of primers, and development of the large fragment amplifying primers
PhylumBacterial cultures (Genus species)SourceDGGE*DGGE primer comparisonLarge fragment
This study Dalhöff
  • *

    Amplification of pure cultures using the DGGE primers developed in this study.

  • Comaprison of DGGE primers developed in this sudy against Dalhöff primers (Fig. S4).

  • Fig. S5.

  • +, Postive amplification; −, no amplification; NT, not tested; P, partial amplification (enough products for cloning); DNS, data not shown.

Actinobacteria BacteroidetesPeptostreptococcus heliotrinreducensRumen++NT
Prevotella ruminicola GA33Rumen++P
Prevotella albensis M384Rumen++P+
Fibrobacteres FirmicutesFibrobacter succinogenes S85Rumen++PP
Streptococcus bovis IFO 12057Rumen++++
Clostridium pasteurianum 5Rumen+++
Lactobacillus vitulinus T-185Rumen+++
Streptococcus caprinus 2.3Rumen++P+
Ruminococcus albus 7Rumen++NT
Ruminococcus albus 8Rumen++NT
Ruminococcus flavenflaciens C94Rumen++P
Streptococcus bovis JB1Rumen++++
Staphylococcus epidermidisHuman++PNT
Staphylococcus aureusHuman++P+
Megasphaera elsdenii T 81Rumen++++
Butyrivibrio fibrisolvens D1Rumen++++
Butyrivibrio fibrisolvens nxyRumenNT+
Selenomonas ruminantium PC-18Rumen+++
Selenomonas ruminantium HD4Rumen++P
Succinogenes dextrisolvensRumen++++
Anaerovibrio lipolyticaRumen+++P
Bacillus subtilisSoil+DNSNTNT
Eubacterium ruminantium GA 195Rumen+++
ProteobacteriaSalmonella typhimuriumSoil++PNT
Pseudomonas fluorescensSoil+DNSNTNT
Vibrio choleraeSoil+DNSNTNT
Klebsiella pneumoniaeSoil+DNSNTNT
Escherichia coliSoil++++/DNS

For the longer fragment, 19 bacterial species were tested. Eight bacterial species produced PCR bands with high intensities and 11 bacterial strains produced PCR products with light intensities (Table 2) (Fig. S5). Although band intensities were light, there was enough PCR product for downstream analysis, i.e. cloning and sequencing. Butyrivibrio fibrisolvens 49 (Table 2) (Fig. S5, lane 12) was the only bacterial isolate that failed to amplify, although a related strain B. fibrisolvens D1 (Fig. S5, lane 11) (Table 2) produced PCR products. Differences in the length of the PCR products were similar to the DGGE products. Gram-negative bacteria generated longer fragments (E. coli fragment length 1800 bp) than Gram-positive bacteria (approximately1300–1400 bp).

Comparison between old and new rpoB-DGGE primer sets

The robustness of the newly developed primers was compared with the old rpoB-DGGE primers from a published study (Dahllöf et al., 2000) (Table 2). Twenty-five strains of rumen bacteria were tested with the new rpoB-DGGE primers developed in this study. Twenty-four DNA samples amplified with very good intensity, with the exception of B. fibrisolvens nxy, (Table 2) (Fig. S4b, lane 14), which showed no product formation. The primers amplified B. fibrisolvens D1 (Fig. S4b, lane 15), a closely related species to B. fibrisolvens nxy. The same set of 25 bacterial strains was also used to amplify the old rpoB-DGGE primer set. The old rpoB-DGGE primers amplified no more than seven bacteria (Table 2) and resulted in light product formation in six other test bacteria (Fig. S4a).

Analysis of new rpoB large fragment amplifying primers

A longer rpoB amplifying fragment was also tested using the newly developed primers. Of the 19 clones that were amplified with this primer set (Fig. S5), only five bacterial species were sequenced. The sequenced representatives also included PCR products from lower intensity bands. The sequenced bacteria were B. fibrisolvens, Fibrobacter succinogenes S85, Streptococcus caprinus 2.3, Selenomonas ruminantium PC-18, and R. flavenflaciens C94. The percentage identity of the blast hits occurred in the range of 78–97% (Table 3). Three sequenced clones (B. fibrisolvens, S. caprinus, and R. flavenflaciens C94) showed close matches to known rpoB references. The clone of F. succinogenes S85 matched other rpoB sequences with lesser specificity. Selenomonas ruminantium PC-18 had the least coverage at 94% and a maximum identity of 87%.

Table 3. blast hits for the large amplifying rpoB fragment
Bacterial strains (Genus species)Closest blast hit (Genus species)Query coverage (%)Max indent (%)E-valueLength of sequence (bp)
Butyrivibrio fibrisolvensButyrivibrio fibrisolvens99950.01455
Fibrobacter succinogenes S85Streptococcus equinus99970.01306
Strepotoccus caprinus 2.3Streptococcus equinus99930.01304
Selenomonas ruminantium PC-18Veillonella detocariosa94875e−661480
Ruminococcus flavenflaciens C94Ruminococcus sp. (Draft genome)92785e−861508

Phylogenetic classification of rumen fluid by the 16S rRNA gene-DGGE (V3) marker

There were visual differences (not quantified) in the banding pattern in the bacterial subpopulation of rumen fluid [Fig. 1, lanes D (Bovine) and A (Ovine)]. The PCR products were cloned and sequence data were processed using the RDPII Classifier (Wang et al., 2007) at a cutoff at 50% (Claesson et al., 2009).

image

Figure 1.  DGGE analysis of 16S rRNA gene and the rpoB gene marker of bovine and ovine rumen fluid samples. A 30–65% DGGE gel was cast. All samples were loaded with equal amounts of DNA (100 ng per well) from purified PCR products. The DGGE was run for 16 h at 60 V and silver stained. Lane A (ovine) DNA amplified with the 16S rRNA gene-DGGE (V3) primer set, lane B (ovine) DNA amplified with the old rpoB-DGGE primer set, lane C (ovine) DNA amplified with the new rpoB-DGGE primer set, lane D (bovine) DNA amplified with the 16S rRNA gene primer set, lane E (bovine) DNA amplified with the old rpoB-DGGE primer set, and Lane F (bovine) DNA amplified with the new rpoB-DGGE primer set.

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In the bovine rumen treatment, 168 sequences were used to quantify the operational taxonomic units (OTUs). The RDP Classifier placed the majority of sequences into two main phyla. The largest OTU section was assigned to phylum Firmicutes and followed by the phylum Bacteroidetes (Table 4). Minor components of the bovine rumen were composed of the phyla TM7, Proteobacteria, and SR (Table 4). Nearly 8% of the sequences were unclassified bacteria.

Table 4.   Taxonomic classification of 16S rRNA gene-V3 and the two rpoB–DGGE primer clone data
PhylumBovine,#Ovine,#Bovine,#Ovine,#Bovine§,#Ovine§,#
No. of clonesTotal (%)No. of clonesTotal (%)No. of clonesTotal (%)No. of clonesTotal (%)No. of clonesTotal (%)No. of clonesTotal (%)
  • Clones were sequenced, trimmed, and chimera was checked. The fasta files of 16S rRNA gene sequence data were classified using the RDPII Classifier tool. The rpoB sequences were manually classified using GenBank data.

  • DNA amplified with 16S rRNA gene-DGGE (V3) primers.

  • DNA amplified with old rpoB-DGGE primers.

  • §

    DNA amplified with new rpoB-DGGE primers developed in this study.

  • Unclassified bacteria.

  • Uncultured bacteria.

  • *

    Indicates libcompare significance (P<0.001).

  • #

    Indicates Libshuff significance between primer pairs (P<0.001).

Acidobacteria    1(1.32)      
Actinobacteria  1(0.63)14(18.42)2(2.47)  3(3.26)
Bacteroidetes31(18.45)90*(56.96)    33(36.26)26(28.26)
Chlorobi    2(2.63)  1(1.10)  
Cyanobacteria      1(1.23)5(5.49)  
Fibrobacteres      26(32.10) (13.19)2(2.17)
Firmicutes115*(68.45)33(20.89)16(21.05)12(14.81)12(16.48)2(2.17)
Proteobacteria3(1.79)1(0.63)24(31.53)6(7.14)15(23.08)57(61.96)
Spirochaetes  1(0.63)    21(2.20)1(1.09)
SR11(0.60)      2   
Tenericutes    2(2.63)1(1.23)    
TM74(2.38)5(3.16)        
Uncla. bacteria14(8.33)27(17.09)10(13.16)7(8.64)  1(1.09)
Unclu. bacteria    7(9.21)26(32.10)2(2.20)  
Total168100.00158100.0076100.0081100.0091100.0092100.00

At the genera level, of the115 clones that were classified as phylum Firmicutes, the clones were distributed among 15 genera, with the three largest clone associations belonging to unclassified Firmicutes, Butyrivibrio, and Fastidiosipila (Table S3). The genera associated with the phylum Bacteroidetes were Prevotella and Paraprevotella (Table S3). The similarity of the RDPII hits for all clones ranged from 70% to 99% (data not shown).

In the ovine rumen sample, the RDPII Classifier placed most sequences into the phyla Bacteroidetes and Firmicutes. The minor components of the ovine rumen were composed of the phyla TM7, Proteobacteria, Spirochetes, and Actinobacteria (Table 4). Seventeen percent of the sequences were comprised of unclassified bacteria.

At the genera level, of the 90 clones that were classified as phylum Bacteroidetes, the majority of clones belong to the genus Prevotella (Table S4). The phylum Firmicutes was comprised of 10 genera, with the phyla Butyrivibrio forming the single largest population. Phylum TM7 had seven clones that were associated with the genus TM7 genera incertae sedis (Table S4).

A Libshuff analysis showed that the difference between the microbial communities in the two ruminates was significant (P<0.0001). To deduce the phyla responsible for this difference, a libcompare analysis (Wang et al., 2007) was performed showing significance in clone libraries associated with the phyla Bacteroidetes (P<0.0001) and Firmicutes (P<0.0001).

Phylogenetic classification of rumen fluid by an old rpoB-DGGE primer

There were visual differences (not quantified) in the banding patterns in the bacterial populations of the two-rumen fluid samples [Fig. 1, lanes E (Bovine) and B (Ovine)]. The bovine rumen samples amplified with the old rpoB-DGGE-based primers grouped the majority of the sequences into the phyla Proteobacteria, Firmicutes, and Actinobacteria. The minor phyla included Chlorobi, Tenericutes, and Acidobacteria (Table 4). The Phylum Proteobacteria comprised 31% of the total sequences. Thirteen percent of the clones did not find any suitable match with the GenBank database (no similarity) and 9% of the sequences were assigned to uncultivable bacteria. The blast hits included sequences that belonged to 23 different bacterial species (genus/species), with Acidovorax sp. (12 clones) representing the single most abundant species (Table S5). Phylum Fibrobacteres-associated clones were absent in the bovine rumen samples.

The ovine rumen samples amplified with the old rpoB-based primers placed 32% of the sequences in the phylum Fibrobacteres, 32% in uncultured bacteria, 15% in the phylum Firmicutes, and 7% in the phylum Proteobacteria. The minor phyla included Cyanobacteria, Tenericutes, and Acidobacteria (Table 3). Data suggested that there were 13 different genera associated with the clone data and F. succinogenes made up the single largest represented species (Table S6).

In order to examine differences in community composition, the Libshuff analysis was performed. The statistical analysis showed a significant difference (P<0.0001) between the two-rumen samples. Unfortunately, due to the lack of a libcompare-like analysis for the rpoB gene, the precise phyla responsible for the significance could not be determined statistically.

Phylogenetic classification of rumen fluid using a new rpoB-DGGE primer

For the bovine sample, the manual classification using the taxonomic browser at the phyla level placed 36% of the sequences into the phylum Bacteroides, 23% into phylum Proteobacteria, 16% into phylum Firmicutes, and 13% into the phylum Fibrobacteres. The minor phyla included Cyanobacteria, Spirochaetes, Chlorobi, and Acidobacteria (Table 4). The clone data were made up of 31 unique bacterial species, with Bacteroides vulgatus, Chitonophage pinensis, and F. succinogenes comprising the largest clone populations (Table S7).

The manual classification of the ovine samples placed the majority of sequences into two phyla. The phylum Proteobacteria comprised 62% of the total sequences, followed by 28% classified as the phylum Bacteroides. The minor phyla included Actinobacteria, Firmicutes, Fibrobacteres, and Spirochaetes (Table 4). Twenty-three different genus/species associations were made with the clone data and Desulfovibrio desulfuricans represented the single largest clone population (Table S8).

The Libshuff analysis was conducted and showed a difference (P<0.0001) between the two-rumen samples.

Rarefaction analysis, ACE, Shannon–Weaver, Simpson index of rumen samples

A total of 664 sequences were used for the analysis of both rumen samples by three gene markers (16S rRNA gene-V3 and two rpoB-based primers). Observed and estimated OTUs were calculated at 97% sequence similarity or 0.03% distance for the 16S rRNA gene-V3 primer and 100% or 0.00% for the rpoB-DGGE primers based on single copy number (Table 5). The results also show (Tables 5 and 6) the various cutoffs (0.05% and 0.10%) for all three-gene markers and the number of OTU assignment in all tested categories.

Table 5.   Phylogenetic analyses of clone data of bovine and ovine sample to determine the observed and estimated OTUs
  Observed OTUsEstimated OTUs
PrimersCutoff (%)*BovineOvineCommonBovineOvineCommon
  • Sequence data were processed through the mothur program and data represented as 0.03, 0.05, and 0.10% cutoffs for all primer sets.

  • *

    Estimate at 100%, 97%, 95%, and 90% cutoffs.

  • ChaoI analysis of bovine and ovine samples.

  • Number of OTUs common to bovine and ovine treatment.

  • NA, data not analyzed.

16S rRNA gene-V30.00NANANANANANA
0.03113.0086.0023.00305.36173.3552.92
0.0596.0072.0028.00243.40139.5756.19
0.1057.0047.0022.0088.5084.5050.41
Old rpoB-DGGE0.0048.0042.001.0092.0079.801.00
0.0343.0033.002.0080.8059.252.00
0.0542.0033.002.0071.5459.252.00
0.1042.0030.003.0071.5449.123.00
New rpoB-DGGE0.0057.0038.0011.00101.3678.6220.75
0.0344.0029.0013.0065.6650.3719.85
0.0541.0028.0013.0049.6649.8521.25
0.1038.0024.0013.0041.6033.4219.00
Table 6.   ACE, Simpson, and Shannon–Weaver index analysis
PrimersCutoff (%)*ACESimpson indexShannon–Weaver index
BovineOvineBovineOvineBovineOvine
  • Sequence data were processed through the mothur program and data represented as 0.03, 0.05, and 0.10% cutoffs for all primer sets.

  • *

    Percentage of homology at 100%, 97%, 95%, and 90%.

  • ND, not determined.

16S rRNA gene-V30.00NDNDNDNDNDND
0.03368.91298.530.010.014.634.18
0.05376.11204.720.010.024.423.88
0.10119.10130.670.030.043.743.30
Old rpoB-DGGE0.00100.19186.060.020.053.623.31
0.0388.5767.240.020.093.462.85
0.0578.7567.240.030.093.442.85
0.1078.7555.520.030.123.442.69
New rpoB-DGGE0.00111.3678.620.020.033.763.19
0.0375.6650.370.020.103.592.54
0.0559.6649.850.030.263.212.52
0.1051.6033.420.030.273.052.43

The observed OTU similarities between the two-rumen systems were limited to 23 phylotypes with the 16S rRNA gene primer, one with the old rpoB-DGGE based primer, and 11 with the new rpoB-DGGE primer (Table 5). The ChaoI analysis estimated the bovine rumen to consist of more phylotypes than the ovine rumen irrespective of the primer used at various cutoffs (Table 5). The rarefaction curves showed no trend toward reaching a plateau, which also indicates the need for more sampling in order to observe all the diversity present in the rumen for all primer sets (Fig. 2). Between the rpoB primers, the new primer set estimated more phylotypes in the bovine sample compared with the old rpoB-DGGE primer set at 100% and 97% cutoff. At cutoffs set at 95% and 90%, the old rpoB-DGGE primer set showed higher values than the new rpoB-DGGE primer set. This trend was very similar in both observed and estimated OTUs.

image

Figure 2.  Rarefaction plot of 16S rRNA gene (V3) and two rpoB-based OTUs. The estimates plotted represent a distance of 0.03 for the bovine rumen samples (B) amplified with 16S rRNA gene primers (♦), ovine rumen samples (○) amplified with 16S rRNA gene primers ( inline image), bovine samples amplified with the old rpoB-DGGE primers (DB) (•), bovine rumen samples amplified with the new rpoB-DGGE primers (PB) (▴), ovine rumen samples amplified with the old rpoB-DGGE primers (DO) (▪), and ovine rumen samples amplified with the new rpoB-DGGE primers (PO)(▾).

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ACE, Simpson, and Shannon–Weaver indices were also used to estimate diversity and species richness in the two ruminant ecosystems (Table 6). The ACE analysis showed that the bovine rumen had more phylotypes with the 16S rRNA gene and new rpoB-DGGE primers. The old rpoB-DGGE based primers switched these results by showing greater diversity with the ovine than the bovine rumen samples. Simpson and Shannon–Weaver index results were consistent with bovine rumen having more diversity than the ovine rumen, except for old rpoB-DGGE primers. These species richness scores are comparable to other complex ecosystems (Borneman & Triplett, 1997).

Analysis of new rpoB and 16S rRNA gene tree topologies

The sequence data from new rpoB-DGGE clones and reference GenBank blast hits were included to generate a Bayesian tree as mentioned in Materials and methods (Fig. 3). A similar 16S rRNA gene in silico tree was assembled using sequences imported from the GenBank database (Fig. 4)

image

Figure 3.  Bayesian analysis of the rpoB-DGGE fragments. Nucleotide data and reference blast hit data were aligned using muscle. Bayesian analysis was performed to 10 million generations using beast. Two runs produced 20 000 trees and the final burnin set at 50%. GenBank reference sequences are provided with accession numbers where applicable and ATCC/DSZM strains are provided for the test bacteria. Branch lengths indicate the posterior probability.

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image

Figure 4.  Bayesian analysis of the 16S rRNA gene sequences. Nucleotide sequences were aligned using muscle. Bayesian analysis was performed to 10 million generations using beast. Two runs produced 20 000 trees and the final burnin set at 50%. GenBank reference sequences are provided with accession numbers. Branch lengths indicate the posterior probability.

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It has been shown previously that there is a good phylogenetic association between rpoB- and 16S rRNA gene-based trees (Case et al., 2007). In general, most of the bacteria sequenced belonged to the phylum Firmicutes and tree topologies suggest good associations within this group with both primers (Streptococcus sp. and Bacillus sp. sequences). The Corynebacterium sp. (Corynebacterium freneyi, Corynebacterium xerosis, and Corynebacterium kutscheri) also formed similar associations with both phylogenetic markers. Few sequences did not show complete congruence between the two primer sets. For example, in the new rpoB-DGGE tree, phylum Bacteroides was represented by three strains (Bacteroides vulgates, Prevotella ruminicola, and Prevotella albensis). One of the above-mentioned bacteria (P. ruminicola) associated itself with the reference strain, while the other strain (P. albensis) associated with Anaerovibrio lipolytica, a member of the phylum Firmicutes. The P. albensis M384 and A. lipolytica sequences closely associated with Corynebacterium sp. in the new rpoB-based tree and showed a different topology in the 16S rRNA gene tree. Because there were no reference rpoB sequences at the GenBank database, the two strains of Ruminococcus and Butyrivibrio associated very closely with each other and were similar to their 16S rRNA gene-based topologies.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The goals of this study were to develop and test new rpoB-based primer sets (DGGE and a longer fragment amplifying) specifically for evaluating microbial communities in the rumen ecosystems. The 16S rRNA gene marker has been used as a phylogenetic anchor for classifying microorganisms in numerous ecosystems. One important feature for a gene marker is the presence of both variable and conserved regions for phylogenetic quantification. Both markers (16S and rpoB) have variable and conserved regions (Adekambi et al., 2009), giving them flexibility to be used in microbial community analysis.

The rpoB gene averages (approximately) 3500 bp and a single region of homology that encompassed all 141 sequences was not found in the development of either a forward or a reverse primer. Subsequently, the primers were designed based on the latter part of the rpoB gene using a reductionist approach. Finally, 39 reference sequences were selected for developing the new rpoB-DGGE and larger fragment amplifying primer sets (Table S2). Because very limited number of rumen bacterial genomes has been sequenced at the time of primer design, 39 reference sequences were selected based on the prevalence of certain phyla in the rumen and the ability to find a region of consensus during the alignment process. A few phyla were represented in higher numbers (Firmicutes vs. Bacteroides) in the final composition of the reference sequences. There were also differences in the size of the rpoB gene when compared between Gram-positive (Staphylococcus aureus, 3552 bp) and Gram-negative bacteria (E. coli, 4029 bp). The occurrence of such significant differences in gene size in other household gene markers is unclear. The DGGE and longer fragment amplifying primer sets designed in this study make use of this region for a simple visual distinction. This difference was consistent with all the strains analyzed in this study (Fig. S4b). The primers also amplified a very small variable region of the rpoB gene (approximately 70 bp) with the DGGE primer and a complete variable region with the large fragment amplifying primer set, making them suitable for distinguishing closely related bacterial species.

In this study, the use of degeneracy at the 3′ end of the forward primer was successful due to the presence of either an A or a G nucleotide at the specific nucleotide position in most of the reference sequences. Primer sets designed without degeneracy were selective in amplifying fewer bacterial strains and failed to outperform the degeneracy-based primer by 40% in bacteria amplified. These results support the use of primer sets with a single degeneracy as long as sequences have a limited number of nucleotide transversions. The new rpoB-DGGE primer set was more robust than the previously developed old rpoB primer set (Dahllöf et al., 2000) both in pure culture and in vitro testing. The robustness of the new rpoB-DGGE primer set is due to the cumulative effect of utilizing more reference sequences in the design/alignment process (four sequences vs. 39 sequences), using a specific degeneracy for the forward primer and optimization of PCR using a touchdown protocol.

With an exponential increase in sequenced bacterial genomes, an in silico analysis was performed to test the amplification potential of the new rpoB-DGGE primers. The primers matched 240 rpoB sequences derived from bacterial genomes, with few genera represented by single isolates. The significantly represented genera were Acinetobacter, Bacillus, Desulfovibrio, Enterobacter, Escherichia, Eubacterium, Geobacillus, Geobacter, Haemophilus, Klebsiella, Paenibacillus, Staphylococcus, Streptococcus, Vibrio, and Yersinia (data not shown). Although in silico analysis with sequenced genomes estimated the potential amplification range, both the new rpoB primers (DGGE and longer amplifying) would need further evaluation to be used in other ecosystems.

The 16S rRNA gene marker was used as a reference classification for the two-rumen samples. In the present study, using the 16S rRNA gene marker, it was determined that the two phyla predominantly present in the bovine and ovine rumen are Firmicutes and Bacteroidetes. These results correlate well with other published research that has characterized the rumen using the 16S-based gene marker (Whitford et al., 1998; Tajima et al., 2001; Nelson et al., 2003; Edwards et al., 2004; An et al., 2005). Prevotella sp. has been reported to be the most dominant genus and account for 42–60% of the bacterial 16S rRNA gene sequences (Stevenson & Weimer, 2007). In the present study, the genus Prevotella accounted for 13% of the sequences in the bovine samples and 32% of sequences for the ovine samples.

Although, in this study, the rumen was not sampled in its entirety and similar numbers of clones were not used for comparison, this study's data qualitatively represent the major phyla present in the rumen. The16S rRNA gene-DGGE primers and the newly designed rpoB-DGGE-based primers showed similar phyla-level-based associations (Table 4). The old rpoB-DGGE primers failed to amplify the phylum Bacteroidetes in both the pure culture as well as the in vitro analysis. It has been shown previously that bacteria associated with the phylum Bacteroidetes are a principal component of the rumen flora and are mainly associated with fiber degradation (Koike et al., 2003).

Both the rpoB primer sets (old and new rpoB-DGGE primer sets) provided a unique perspective on the rumen community structure by reporting a large percentage of clones associated with the phylum Proteobacteria. Percentages of clones associated with phylum Proteobacteria were more predominant in the bovine rumen sample amplified with both rpoB-DGGE gene markers (23% clones with the new rpoB-DGGE primer set and 24% with the old rpoB-DGGE primers) when compared with the 16S rRNA gene-V3 gene marker (3% of clones). Because members of the phylum Proteobacteria are generally associated with soil, these microorganisms could be a transient population entering the rumen due to grazing. Other possible introductions could be due to the variety of grass fed or a function of animal enrichment/physiology. A useful approach for determining the truly dominant components of the gastrointestinal ecosystem would involve next-generation sequencing combined with direct in situ hybridization with genus/species-specific oligonucleotide probes (Amann et al., 1995).

The phylogenetic analysis of the rumen samples consistently showed that bovine rumen was much more diverse than the ovine rumen. Comparison of the primers showed a higher number of OTUs associated with the 16S rRNA gene marker than the two-rpoB gene markers used in this study. However, the abundance values must be compared with caution because the number of sequences used in the estimation was not equal and the rarefaction curves were not asymptotic (Fig. 2). The cutoffs for assigning OTUs were chosen at 97% for the 16S rRNA gene and 100% for the rpoB gene due to the single copy number of the rpoB gene. Between the two rpoB-DGGE primer sets, the bovine samples amplified with the new rpoB-DGGE primers showed higher observed and estimated OTU numbers with cutoffs set at 100% and 97%. This trend was not consistent and there was a reduction in OTU estimation with the new rpoB-DGGE primer set at 95% and 90% compared with the old rpoB-DGGE primer set. Such a reduction could be due to the region of the rpoB gene or the clustering algorithm used in the analysis. Further analysis pertaining to influence by region of amplification (conserved vs. variable regions) between the two rpoB-DGGE primer sets has to be carried out to arrive at a clear conclusion.

The ovine rumen samples amplified with the new rpoB-DGGE primer set showed lesser diversity in all phylogenetic analyses compared with the old rpoB-DGGE primer counterpart due to the bias induced by the presence of 48 clones of D. desulfurican belonging to the phylum Proteobacteria. This over-representation of one sequence type undervalued downstream analysis such as ChaoI estimate, ACE, Simpson, and Shannon–Weaver indices. An explanation for such biases could be the various factors such as the time of sampling the rumen, animal characteristic, primers, PCR, and cloning biases. Primer-based biases have been evaluated in the 16S rRNA gene marker in ecosystems (Forney et al., 2004) and have been corrected or modified to amplify a wider range of microorganisms (Baker et al., 2003).

This study shows a difference in the species composition of the bovine and ovine rumen irrespective of the gene marker used. This difference in the microbial diversity in the two ruminants is likely to diverge with more sampling and utilization of improved sequencing technology such as next-generation sequencing. Anthropogenic management strategies, size of rumen, diet, co-evolution, immunity (Dethlefsen et al., 2007), and selection-based immunity of the host animal could also be responsible for differences between the two ruminants (Ley et al., 2008b).

Because of the differences in the evolution of 16S rRNA gene and the rpoB gene, it is recommended not to compare these two phylogenetic markers, but to use them in conjunction with each other to analyze communities. There are two limitations in using the rpoB-based gene marker. The primary limitation in using housekeeping genes for primer development is codon usage and nucleotide substitution (Case et al., 2007). The second limitation is implementation of tools such as the RDPII database, classifier, and libcompare. With increased bacterial genomes sequenced, such databases and tools would be easy to duplicate for the rpoB gene.

In conclusion, the 16S rRNA gene and new rpoB-DGGE primers designed in this study have qualitatively similar diversity profiles when tested in ruminants. The significant number of clones associated with phylum Proteobacteria when the bovine rumen community was analyzed by independently developed rpoB-DGGE primer sets leads to an important question about the true rumen diversity. Moreover, it is suggested, based on the data presented here, that true phylogenetic analysis of a ecosystem would require analysis with more than one gene marker to completely estimate diversity in a ecosystem. A computational approach could be used to add a weight matrix to each gene analysis and compute to a ‘true’ phylogenetic tree.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

This material is based on research supported and jointly funded by the Oregon Agricultural Experiment Station project ORE00871 and by the U.S. Department of Agriculture, under project number 6227-21310-007-00D agreement numbers 58-6227-8-044 and 58-1265-6-076. Any opinions, findings, conclusion, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture. The authors would like to thank Mr Rogan Rattary for assistance during this project, Ms. Kelsey Hughson for help with the DGGE, and Ms. Zelda Zimmerman for editorial assistance. The authors also thank the reviewers for help with the discussion and presentation of this manuscript.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Appendix S1. Materials and methods.

Fig. S1. DGGE analysis of pure culture isolates, lanes 1–13.

Fig. S2. DGGE analysis of pure culture isolates, lanes 14–25.

Fig. S3. DGGE analysis of pure culture isolates, lanes 26 and 27.

Fig. S4. PCR products of the new rpoB-DGGE primers amplified and run on a 1.2% agarose gel with 1X TAE buffer.

Fig. S5. PCR products of the large amplifying new rpoB primers amplified and run on a 1.2% agarose gel with 1X TAE buffer.

Table S1. Bacterial pure cultures used in this study to test newly developed rpoB primers.

Table S2. Reference bacterial strains used for the development of rpoB primers in this study.

Table S3. 16S rRNA gene-V3 (Bovine).

Table S4. 16S rRNA gene-V3 (Ovine).

Table S5.rpoB-Dahllöf (Bovine).

Table S6.rpoB-Dahllöf (Ovine).

Table S7.rpoB – this study (Bovine).

Table S8.rpoB – this study (Ovine).

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