Improved serial analysis of V1 ribosomal sequence tags (SARST-V1) provides a rapid, comprehensive, sequence-based characterization of bacterial diversity and community composition

Serial analysis of ribosomal sequence tags (SARST) is a recently developed technology that can generate large 16S rRNA gene (rrs) sequence data sets from microbiomes, but there are numerous enzymatic and purification steps required to construct the ribosomal sequence tag (RST) clone libraries. We report here an improved SARST method, which still targets the V1 hypervariable region of rrs genes, but reduces the number of enzymes, oligonucleotides, reagents, and technical steps needed to produce the RST clone libraries. The new method, hereafter referred to as SARST-V1, was used to examine the eubacterial diversity present in community DNA recovered from the microbiome resident in the ovine rumen. The 190 sequenced clones contained 1055 RSTs and no less than 236 unique phylotypes (based on > or = 95% sequence identity) that were assigned to eight different eubacterial phyla. Rarefaction and monomolecular curve analyses predicted that the complete RST clone library contains 99% of the 353 unique phylotypes predicted to exist in this microbiome. When compared with ribosomal intergenic spacer analysis (RISA) of the same community DNA sample, as well as a compilation of nine previously published conventional rrs clone libraries prepared from the same type of samples, the RST clone library provided a more comprehensive characterization of the eubacterial diversity present in rumen microbiomes. As such, SARST-V1 should be a useful tool applicable to comprehensive examination of diversity and composition in microbiomes and offers an affordable, sequence-based method for diversity analysis.     

Serial analysis of ribosomal sequence tags (SARST): a high-throughput method for profiling complex microbial communities

Two decades of culture-independent studies have confirmed that microbial communities represent the most complex and concentrated pool of phylogenetic diversity on the planet. There remains a need for innovative molecular tools that can further our knowledge of microbial diversity and its functional implications. We present the method and application of serial analysis of ribosomal sequence tags (SARST) as a novel tool for elucidating complex microbial communities, such as those found in soils and sediments. Serial analysis of ribosomal sequence tags uses a series of enzymatic reactions to amplify and ligate ribosomal sequence tags (RSTs) from bacterial small subunit rRNA gene (SSU rDNA) V1-regions into concatemers that are cloned and sequenced. This approach offers a significant increase in throughput over traditional SSU rDNA clone libraries, as up to 20 RSTs are obtained from each sequencing reaction. To test SARST and measure the bias associated with this approach, RST libraries were prepared from a defined mixture of pure cultures and from duplicate arctic soil DNA samples. The actual RST distribution reflected the theoretical composition of the original defined mixture. Data from duplicate soil libraries (1345 and 1217 RSTs, with 525 and 505 unique RSTs, respectively) indicated that replication provides a strongly correlated RST profile (r(2) = 0.80) and division-level distribution of RSTs (r(2) = 0.99). Using sequence data from abundant soil RSTs, we designed specific primers that successfully amplified a larger portion of the SSU rDNA for further phylogenetic analysis. These results suggest that SARST is a powerful approach for reproducible high-throughput profiling of microbial diversity amenable to medical, industrial or environmental microbiology applications.     

Unexpectedly high bacterial diversity in arctic tundra relative to boreal forest soils, revealed by serial analysis of ribosomal sequence tags

Arctic tundra and boreal forest soils have globally relevant functions that affect atmospheric chemistry and climate, yet the bacterial composition and diversity of these soils have received little study. Serial analysis of ribosomal sequence tags (SARST) and denaturing gradient gel electrophoresis (DGGE) were used to compare composite soil samples taken from boreal and arctic biomes. This study comprises an extensive comparison of geographically distant soil bacterial communities, involving the analysis of 12,850 ribosomal sequence tags from six composite soil samples. Bacterial diversity estimates were greater for undisturbed arctic tundra soil samples than for boreal forest soil samples, with the highest diversity associated with a sample from an extreme northern location (82(o)N). The lowest diversity estimate was obtained from an arctic soil sample that was disturbed by compaction and sampled from a greater depth. Since samples from the two biomes did not form distinct clusters on the basis of SARST data and DGGE fingerprints, factors other than latitude likely influenced the phylogenetic compositions of these communities. The high number of ribosomal sequences analyzed enabled the identification of possible cosmopolitan and endemic bacterial distributions in particular soils.     

Unexpectedly High Bacterial Diversity in Arctic Tundra Relative to Boreal Forest Soils, Revealed by Serial Analysis of Ribosomal Sequence Tags

Arctic tundra and boreal forest soils have globally relevant functions that affect atmospheric chemistry and climate, yet the bacterial composition and diversity of these soils have received little study. Serial analysis of ribosomal sequence tags (SARST) and denaturing gradient gel electrophoresis (DGGE) were used to compare composite soil samples taken from boreal and arctic biomes. This study comprises an extensive comparison of geographically distant soil bacterial communities, involving the analysis of 12,850 ribosomal sequence tags from six composite soil samples. Bacterial diversity estimates were greater for undisturbed arctic tundra soil samples than for boreal forest soil samples, with the highest diversity associated with a sample from an extreme northern location (82^oN). The lowest diversity estimate was obtained from an arctic soil sample that was disturbed by compaction and sampled from a greater depth. Since samples from the two biomes did not form distinct clusters on the basis of SARST data and DGGE fingerprints, factors other than latitude likely influenced the phylogenetic compositions of these communities. The high number of ribosomal sequences analyzed enabled the identification of possible cosmopolitan and endemic bacterial distributions in particular soils.     

Exploring Microbial Diversity and Taxonomy Using SSU rRNA Hypervariable Tag Sequencing

Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the “rare biosphere” than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.     

Phylogenetic analysis of aerobic freshwater and marine enrichment cultures efficient in hydrocarbon degradation: effect of profiling method

Aerobically grown enrichment cultures derived from hydrocarbon-contaminated seawater and freshwater sediments were generated by growth on crude oil as sole carbon source. Both cultures displayed a high rate of degradation for a wide range of hydrocarbon compounds. The bacterial species composition of these cultures was investigated by PCR of the 16S rDNA gene using multiple primer combinations. Near full-length 16S rDNA clone libraries were generated and screened by restriction analysis prior to sequence analysis. Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) was carried out using two other PCR primer sets targeting either the V3 or V6-V8 regions, and sequences derived from prominent DGGE bands were compared to sequences obtained via cloning. All data sets suggested that the seawater culture was dominated by alpha-subgroup proteobacteria, whereas the freshwater culture was dominated by members of the beta- and gamma-proteobacteria. However, the V6-V8 primer pair was deficient in the recovery of Sphingomonas-like 16S rDNA due to a 3' terminal mismatch with the reverse primer. Most 16S rDNA sequences recovered from the marine enrichment were not closely related to genera containing known oil-degrading organisms, although some were detected. All methods suggested that the freshwater enrichment was dominated by genera containing known hydrocarbon-degrading species.     

Phylum- and class-specific PCR primers for general microbial community analysis

Amplification of a particular DNA fragment from a mixture of organisms by PCR is a common first step in methods of examining microbial community structure. The use of group-specific primers in community DNA profiling applications can provide enhanced sensitivity and phylogenetic detail compared to domain-specific primers. Other uses for group-specific primers include quantitative PCR and library screening. The purpose of the present study was to develop several primer sets targeting commonly occurring and important groups. Primers specific for the 16S ribosomal sequences of Alphaproteobacteria, Betaproteobacteria, Bacilli, Actinobacteria, and Planctomycetes and for parts of both the 18S ribosomal sequence and the internal transcribed spacer region of Basidiomycota were examined. Primers were tested by comparison to sequences in the ARB 2003 database, and chosen primers were further tested by cloning and sequencing from soil community DNA. Eighty-five to 100% of the sequences obtained from clone libraries were found to be placed with the groups intended as targets, demonstrating the specificity of the primers under field conditions. It will be important to reevaluate primers over time because of the continual growth of sequence databases and revision of microbial taxonomy.     

Effect of primers hybridizing to different evolutionarily conserved regions of the small-subunit rRNA gene in PCR-based microbial community analyses and genetic profiling

Genetic profiling techniques of microbial communities based on PCR-amplified signature genes, such as denaturing gradient gel electrophoresis or single-strand-conformation polymorphism (SSCP) analysis, are normally done with PCR products of less than 500-bp. The most common target for diversity analysis, the small-subunit rRNA genes, however, are larger, and thus, only partial sequences can be analyzed. Here, we compared the results obtained by PCR targeting different variable (V) regions (V2 and V3, V4 and V5, and V6 to V8) of the bacterial 16S rRNA gene with primers hybridizing to evolutionarily conserved flanking regions. SSCP analysis of single-stranded PCR products generated from 13 different bacterial species showed fewer bands with products containing V4-V5 (average, 1.7 bands per organism) than with V2-V3 (2.2 bands) and V6-V8 (2.3 bands). We found that the additional bands (>1 per organism) were caused by intraspecies operon heterogeneities or by more than one conformation of the same sequence. Community profiles, generated by PCR-SSCP from bacterial-cell consortia extracted from rhizospheres of field-grown maize (Zea mays), were analyzed by cloning and sequencing of the dominant bands. A total of 48 sequences could be attributed to 34 different strains from 10 taxonomical groups. Independent of the primer pairs, we found proteobacteria (alpha, beta, and gamma subgroups) and members of the genus Paenibacillus (low G+C gram-positive) to be the dominant organisms. Other groups, however, were only detected with single primer pairs. This study gives an example of how much the selection of different variable regions combined with different specificities of the flanking "universal" primers can affect a PCR-based microbial community analysis.     

Effect of Primers Hybridizing to Different Evolutionarily Conserved Regions of the Small-Subunit rRNA Gene in PCR-Based Microbial Community Analyses and Genetic Profiling

Genetic profiling techniques of microbial communities based on PCR-amplified signature genes, such as denaturing gradient gel electrophoresis or single-strand-conformation polymorphism (SSCP) analysis, are normally done with PCR products of less than 500-bp. The most common target for diversity analysis, the small-subunit rRNA genes, however, are larger, and thus, only partial sequences can be analyzed. Here, we compared the results obtained by PCR targeting different variable (V) regions (V2 and V3, V4 and V5, and V6 to V8) of the bacterial 16S rRNA gene with primers hybridizing to evolutionarily conserved flanking regions. SSCP analysis of single-stranded PCR products generated from 13 different bacterial species showed fewer bands with products containing V4-V5 (average, 1.7 bands per organism) than with V2-V3 (2.2 bands) and V6-V8 (2.3 bands). We found that the additional bands (>1 per organism) were caused by intraspecies operon heterogeneities or by more than one conformation of the same sequence. Community profiles, generated by PCR-SSCP from bacterial-cell consortia extracted from rhizospheres of field-grown maize (Zea mays), were analyzed by cloning and sequencing of the dominant bands. A total of 48 sequences could be attributed to 34 different strains from 10 taxonomical groups. Independent of the primer pairs, we found proteobacteria (α, β, and γ subgroups) and members of the genus Paenibacillus (low G+C gram-positive) to be the dominant organisms. Other groups, however, were only detected with single primer pairs. This study gives an example of how much the selection of different variable regions combined with different specificities of the flanking “universal” primers can affect a PCR-based microbial community analysis.     

Microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples

Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of the bacterial composition in three fecal and three small intestinal samples from human individuals. As PCR remains a crucial step in sample preparation for both techniques, different forward primers were used for amplification to assess their impact on microbial profiling results. An average of 7,944 pyrosequences, spanning the V1 and V2 region of 16S rRNA genes, was obtained per sample. Although primer choice in barcoded pyrosequencing did not affect species richness and diversity estimates, detection of Actinobacteria strongly depended on the selected primer. Microbial profiles obtained by pyrosequencing and phylogenetic microarray analysis (HITChip) correlated strongly for fecal and ileal lumen samples but were less concordant for ileostomy effluent. Quantitative PCR was employed to investigate the deviations in profiling between pyrosequencing and HITChip analysis. Since cloning and sequencing of random 16S rRNA genes from ileostomy effluent confirmed the presence of novel intestinal phylotypes detected by pyrosequencing, especially those belonging to the Veillonella group, the divergence between pyrosequencing and the HITChip is likely due to the relatively low number of available 16S rRNA gene sequences of small intestinal origin in the DNA databases that were used for HITChip probe design. Overall, this study demonstrated that equivalent biological conclusions are obtained by high-throughput profiling of microbial communities, independent of technology or primer choice.     

Succession of microbial communities during hot composting as detected by PCR-single-strand-conformation polymorphism-based genetic profiles of small-subunit rRNA genes

A cultivation-independent technique for genetic profiling of PCR-amplified small-subunit rRNA genes (SSU rDNA) was chosen to characterize the diversity and succession of microbial communities during composting of an organic agricultural substrate. PCR amplifications were performed with DNA directly extracted from compost samples and with primers targeting either (i) the V4-V5 region of eubacterial 16S rRNA genes, (ii) the V3 region in the 16S rRNA genes of actinomycetes, or (iii) the V8-V9 region of fungal 18S rRNA genes. Homologous PCR products were converted to single-stranded DNA molecules by exonuclease digestion and were subsequently electrophoretically separated by their single-strand-conformation polymorphism (SSCP). Genetic profiles obtained by this technique showed a succession and increasing diversity of microbial populations with all primers. A total of 19 single products were isolated from the profiles by PCR reamplification and cloning. DNA sequencing of these molecular isolates showed similarities in the range of 92.3 to 100% to known gram-positive bacteria with a low or high G+C DNA content and to the SSU rDNA of gamma-Proteobacteria. The amplified 18S rRNA gene sequences were related to the respective gene regions of Candida krusei and Candida tropicalis. Specific molecular isolates could be attributed to different composting stages. The diversity of cultivated bacteria isolated from samples taken at the end of the composting process was low. A total of 290 isolates were related to only 6 different species. Two or three of these species were also detectable in the SSCP community profiles. Our study indicates that community SSCP profiles can be highly useful for the monitoring of bacterial diversity and community successions in a biotechnologically relevant process.     

Composition of microbial communities in hexachlorocyclohexane (HCH) contaminated soils from Spain revealed with a habitat-specific microarray

Microarray technology was used to characterize and compare hexachlorocyclohexane (HCH) contaminated soils from Spain. A library of 2,290 hypervariable 16S rRNA gene sequences was prepared with serial analysis of ribosomal sequence tags (SARST) from a composite of contaminated and uncontaminated soils. By designing hybridization probes specific to the 100 most abundant ribosomal sequence tags (RSTs) in the composite library, the RST array was designed to be habitat-specific and predicted to monitor the most abundant polymerase chain reaction (PCR)-amplified phylotypes in the individual samples. The sensitivity and specificity of the RST array was tested with a series of pure culture-specific probes and hybridized with labelled soil PCR products to generate hybridization patterns for each soil. Sequencing of prominent bands in denaturing gradient gel electrophoresis (DGGE) fingerprints derived from these soils provided a means by which we successfully confirmed the habitat-specific array design and validated the bulk of the probe signals. Non-metric multidimensional scaling revealed correlations between probe signals and soil physicochemical parameters. Among the strongest correlations to total HCH contamination were probe signals corresponding to unknown Gamma Proteobacteria, potential pollutant-degrading phylotypes, and several organisms with acid-tolerant phenotypes. The strongest correlations to alpha-HCH were probe signals corresponding to the genus Sphingomonas, which contains known HCH degraders. This suggests that the population detected was enriched in situ by HCH contamination and may play a role in HCH degradation. Other environmental parameters were also likely instrumental in shaping community composition in these soils. The results highlight the power of habitat-specific microarrays for comparing complex microbial communities.     

Frequency of formation of chimeric molecules as a consequence of PCR coamplification of 16S rRNA genes from mixed bacterial genomes.

PCR is routinely used in amplification and cloning of rRNA genes from environmental DNA samples for studies of microbial community structure and identification of novel organisms. There have been concerns about generation of chimeric sequences as a consequence of PCR coamplification of highly conserved genes, because such sequences may lead to reports of nonexistent organisms. To quantify the frequency of chimeric molecule formation, mixed genomic DNAs from eight actinomycete species whose 16S rRNA sequences had been determined were used for PCR coamplification of 16S rRNA genes. A large number of cloned 16S ribosomal DNAs were examined by sequence analysis, and chimeric molecules were identified by multiple-sequence alignment with reference species. Here, we report that the level of occurrence of chimeric sequences after 30 cycles of PCR amplification was 32%. We also show that PCR-induced chimeras were formed between different rRNA gene copies from the same organism. Because of the wide use of PCR for direct isolation of 16S rRNA sequences from environmental DNA to assess microbial diversity, the extent of chimeric molecule formation deserves serious attention.     

Application of group specific amplified rDNA restriction analysis to characterize swine fecal and manure storage pit samples

Group specific amplified ribosomal-DNA restriction analysis was evaluated as a method to rapidly assess microbial community structure in swine fecal and manure storage pit samples. PCR primer sequences were evaluated for their specificity to ribosomal DNA from selected bacterial groups by optimizing annealing temperatures and determining specificity using a set of primer target and non-target organisms. A number of primer sets were identified targeting the following groups: Bacteroides-Prevotella, clostridial clusters I and II, clostridial clusters IX and XI, clostridial clusters XIVa and XIVb, Lactobacillus, Desulfovibrionaceae and Streptococcus-Lactococcus, as well as an universal primer set to represent total populations. Each bacterial group was digested with at least three restriction enzymes. We applied the group specific amplified ribosomal-DNA restriction analysis to swine fecal and manure storage pit samples obtained on two separate occasions. Fecal and manure storage pit samples obtained on the same day were more similar to each other than to any other samples. Results were consistent with 16S ribosomal DNA sequencing data from bacterial isolates and clones obtained from swine feces and manure storage pit. The group specific amplified ribosomal-DNA restriction analysis technique was able to rapid detect gross bacterial community differences among swine fecal and manure storage pit samples and determine groups of interest for more detailed examination.     

Community analysis of a full-scale anaerobic bioreactor treating paper mill wastewater

To get insight into the microbial community of an Upflow Anaerobic Sludge Blanket reactor treating paper mill wastewater, conventional microbiological methods were combined with 16S rRNA gene analyses. Particular attention was paid to microorganisms able to degrade propionate or butyrate in the presence or absence of sulphate. Serial enrichment dilutions allowed estimating the number of microorganisms per ml sludge that could use butyrate with or without sulphate (10(5)), propionate without sulphate (10(6)), or propionate and sulphate (10(8)). Quantitative RNA dot-blot hybridisation indicated that Archaea were two-times more abundant in the microbial community of anaerobic sludge than Bacteria. The microbial community composition was further characterised by 16S rRNA-gene-targeted Denaturing Gradient Gel Electrophoresis (DGGE) fingerprinting, and via cloning and sequencing of dominant amplicons from the bacterial and archaeal patterns. Most of the nearly full length (approximately 1.45 kb) bacterial 16S rRNA gene sequences showed less than 97% similarity to sequences present in public databases, in contrast to the archaeal clones (approximately. 1.3 kb) that were highly similar to known sequences. While Methanosaeta was found as the most abundant genus, also Crenarchaeote-relatives were identified. The microbial community was relatively stable over a period of 3 years (samples taken in July 1999, May 2001, March 2002 and June 2002) as indicated by the high similarity index calculated from DGGE profiles (81.9+/-2.7% for Bacteria and 75.1+/-3.1% for Archaea). 16S rRNA gene sequence analysis indicated the presence of unknown and yet uncultured microorganisms, but also showed that known sulphate-reducing bacteria and syntrophic fatty acid-oxidising microorganisms dominated the enrichments.     

Evaluation of PCR amplification bias by terminal restriction fragment length polymorphism analysis of small-subunit rRNA and mcrA genes by using defined template mixtures of methanogenic pure cultures and soil DNA extracts

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a widely used method for profiling microbial community structure in different habitats by targeting small-subunit (SSU) rRNA and also functional marker genes. It is not known, however, whether relative gene frequencies of individual community members are adequately represented in post-PCR amplicon frequencies as shown by T-RFLP. In this study, precisely defined artificial template mixtures containing genomic DNA of four different methanogens in various ratios were prepared for subsequent T-RFLP analysis. PCR amplicons were generated from defined mixtures targeting not only the SSU rRNA but also the methyl-coenzyme M reductase (mcrA/mrtA) genes of methanogens. Relative amplicon frequencies of microorganisms were quantified by comparing fluorescence intensities of characteristic terminal restriction fragments. SSU ribosomal DNA (rDNA) template ratios in defined template mixtures of the four-membered community were recovered absolutely by PCR-T-RFLP analysis, which demonstrates that the T-RFLP analysis evaluated can give a quantitative view of the template pool. SSU rDNA-targeted T-RFLP analysis of a natural community was found to be highly reproducible, independent of PCR annealing temperature, and unaffected by increasing PCR cycle numbers. Ratios of mcrA-targeted T-RFLP analysis were biased, most likely by PCR selection due to the degeneracy of the primers used. Consequently, for microbial community analyses, each primer system used should be evaluated carefully for possible PCR bias. In fact, such bias can be detected by using T-RFLP analysis as a tool for the precise quantification of the PCR product pool.     

EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at .