Analysis,Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys

The exploration of microbial communities by sequencing 16S rRNA genes has expanded with low-cost, high-throughput sequencing instruments. Illumina-based 16S rRNA gene sequencing has recently gained popularity over 454 pyrosequencing due to its lower costs, higher accuracy and greater throughput. Although recent reports suggest that Illumina and 454 pyrosequencing provide similar beta diversity measures, it remains to be demonstrated that pre-existing 454 pyrosequencing workflows can transfer directly from 454 to Illumina MiSeq sequencing by simply changing the sequencing adapters of the primers. In this study, we modified 454 pyrosequencing primers targeting the V4-V5 hyper-variable regions of the 16S rRNA gene to be compatible with Illumina sequencers. Microbial communities from cows, humans, leeches, mice, sewage, and termites and a mock community were analyzed by 454 and MiSeq sequencing of the V4-V5 region and MiSeq sequencing of the V4 region. Our analysis revealed that reference-based OTU clustering alone introduced biases compared to de novo clustering, preventing certain taxa from being observed in some samples. Based on this we devised and recommend an analysis pipeline that includes read merging, contaminant filtering, and reference-based clustering followed by de novo OTU clustering, which produces diversity measures consistent with de novo OTU clustering analysis. Low levels of dataset contamination with Illumina sequencing were discovered that could affect analyses that require highly sensitive approaches. While moving to Illumina-based sequencing platforms promises to provide deeper insights into the breadth and function of microbial diversity, our results show that care must be taken to ensure that sequencing and processing artifacts do not obscure true microbial diversity.     

Investigating Microbial Eukaryotic Diversity from a Global Census: Insights from a Comparison of Pyrotag and Full-Length Sequences of 18S rRNA Genes

Next-generation DNA sequencing (NGS) approaches are rapidly surpassing Sanger sequencing for characterizing the diversity of natural microbial communities. Despite this rapid transition, few comparisons exist between Sanger sequences and the generally much shorter reads of NGS. Operational taxonomic units (OTUs) derived from full-length (Sanger sequencing) and pyrotag (454 sequencing of the V9 hypervariable region) sequences of 18S rRNA genes from 10 global samples were analyzed in order to compare the resulting protistan community structures and species richness. Pyrotag OTUs called at 98% sequence similarity yielded numbers of OTUs that were similar overall to those for full-length sequences when the latter were called at 97% similarity. Singleton OTUs strongly influenced estimates of species richness but not the higher-level taxonomic composition of the community. The pyrotag and full-length sequence data sets had slightly different taxonomic compositions of rhizarians, stramenopiles, cryptophytes, and haptophytes, but the two data sets had similarly high compositions of alveolates. Pyrotag-based OTUs were often derived from sequences that mapped to multiple full-length OTUs at 100% similarity. Thus, pyrotags sequenced from a single hypervariable region might not be appropriate for establishing protistan species-level OTUs. However, nonmetric multidimensional scaling plots constructed with the two data sets yielded similar clusters, indicating that beta diversity analysis results were similar for the Sanger and NGS sequences. Short pyrotag sequences can provide holistic assessments of protistan communities, although care must be taken in interpreting the results. The longer reads (>500 bp) that are now becoming available through NGS should provide powerful tools for assessing the diversity of microbial eukaryotic assemblages.     

High-Throughput Sequencing—The Key to Rapid Biodiversity Assessment of Marine Metazoa?

The applications of traditional morphological and molecular methods for species identification are greatly restricted by processing speed and on a regional or greater scale are generally considered unfeasible. In this context, high-throughput sequencing, or metagenetics, has been proposed as an efficient tool to document biodiversity. Here we evaluated the effectiveness of 454 pyrosequencing in marine metazoan community analysis using the 18S rDNA: V1-V2 region. Multiplex pyrosequencing of the V1-V2 region was used to analyze two pooled samples of DNA, one comprising 118 and the other 37 morphologically identified species, and one natural sample taken directly from a North Sea zooplankton community. A DNA reference library comprising all species represented in the pooled samples was created by Sanger sequencing, and this was then used to determine the optimal similarity threshold for species delineation. The optimal threshold was found at 99% species similarity, with 85% identification success. Pyrosequencing was able to identify between fewer species: 67% and 78% of the species in the two pooled samples. Also, a large number of sequences for three species that were not included in the pooled samples were amplified by pyrosequencing, suggesting preferential amplification of some genotypes and the sensitivity of this approach to even low levels of contamination. Conversely, metagenetic analysis of the natural zooplankton sample identified many more species (particularly gelatinous zooplankton and meroplankton) than morphological analysis of a formalin-fixed sample from the same sampling site, suggesting an increased level of taxonomic resolution with pyrosequencing. The study demonstrated that, based on the V1-V2 region, 454 sequencing does not provide accurate species differentiation and reliable taxonomic classification, as it is required in most biodiversity monitoring. The analysis of artificially prepared samples indicated that species detection in pyrosequencing datasets is complicated by potential PCR-based biases and that the V1-V2 marker is poorly resolved for some taxa.     

Design and Experimental Application of a Novel Non-Degenerate Universal Primer Set that Amplifies Prokaryotic 16S rRNA Genes with a Low Possibility to Amplify Eukaryotic rRNA Genes

The deep sequencing of 16S rRNA genes amplified by universal primers has revolutionized our understanding of microbial communities by allowing the characterization of the diversity of the uncultured majority. However, some universal primers also amplify eukaryotic rRNA genes, leading to a decrease in the efficiency of sequencing of prokaryotic 16S rRNA genes with possible mischaracterization of the diversity in the microbial community. In this study, we compared 16S rRNA gene sequences from genome-sequenced strains and identified candidates for non-degenerate universal primers that could be used for the amplification of prokaryotic 16S rRNA genes. The 50 identified candidates were investigated to calculate their coverage for prokaryotic and eukaryotic rRNA genes, including those from uncultured taxa and eukaryotic organelles, and a novel universal primer set, 342F-806R, covering many prokaryotic, but not eukaryotic, rRNA genes was identified. This primer set was validated by the amplification of 16S rRNA genes from a soil metagenomic sample and subsequent pyrosequencing using the Roche 454 platform. The same sample was also used for pyrosequencing of the amplicons by employing a commonly used primer set, 338F-533R, and for shotgun metagenomic sequencing using the Illumina platform. Our comparison of the taxonomic compositions inferred by the three sequencing experiments indicated that the non-degenerate 342F-806R primer set can characterize the taxonomic composition of the microbial community without substantial bias, and is highly expected to be applicable to the analysis of a wide variety of microbial communities.     

Effects of Experimental Choices and Analysis Noise on Surveys of the “Rare Biosphere”

When planning a survey of 16S rRNA genes from a complex environment, investigators face many choices including which primers to use and how to taxonomically classify sequences. In this study, we explored how these choices affected a survey of microbial diversity in a sample taken from the aerobic basin of the activated sludge of a North Carolina wastewater treatment plant. We performed pyrosequencing reactions on PCR products generated from primers targeting the V1-V2, V6, and V6-V7 variable regions of the 16S rRNA gene. We compared these sequences to 16S rRNA gene sequences found in a whole-genome shotgun pyrosequencing run performed on the same sample. We found that sequences generated from primers targeting the V1-V2 variable region had the best match to the whole-genome shotgun reaction across a range of taxonomic classifications from phylum to family. Pronounced differences between primer sets, however, occurred in the “rare biosphere” involving taxa that we observed in fewer than 11 sequences. We also examined the results of analysis strategies comparing a classification scheme using a nearest-neighbor approach to directly classifying sequences with a naïve Bayesian algorithm. Again, we observed pronounced differences between these analysis schemes in infrequently observed taxa. We conclude that if a study is meant to probe the rare biosphere, both the experimental conditions and analysis choices will have a profound impact on the observed results.For nearly 3 decades, investigations of the distribution of microbes in complex environments have focused on the use of rRNA genes (1, 2, 4, 11, 16, 18, 19, 22, 24). Because the full-length 16S rRNA sequence can be obtained with paired-end reads via traditional Sanger sequencing, until recently most studies of the 16S rRNA gene captured most or nearly most of the 16S sequence length. New pyrosequencing technologies, however, have recently been introduced that greatly reduce the per base cost of sequencing but with shorter read lengths than traditional Sanger sequencing (17). This new approach has proven powerful, yielding a previously unobtainable view of rare taxa (7, 12-14, 25).The shorter reads produced by pyrosequencing require the choice of a particular region of the 16S rRNA gene to target for pyrosequencing as well as the choice of an algorithm to classify the taxonomy of the shorter reads. In their initial surveys of microbial diversity with pyrosequencing (12, 14, 25), Sogin and colleagues targeted the V6 variable region, in part because it is was small enough to be captured with the 100-bp reads of the pyrosequencing technology available at the time. Recently, the read length of 454 pyrosequencing machines has been increased to an average of ∼250 bp. This allows for more flexibility in primer design and opens up the possibility of targeting regions of the 16S rRNA gene other than V6. In recent work, Huse et al. took advantage of this new capability to compare the classifications made for the human gut microbiome with the V6 and longer V3 regions (13). Plotting the taxonomic abundance of these two sequence sets against each other yielded an excellent correlation (r² = 0.99), suggesting that the choice of which variable region to target makes little difference. In this report, we introduce a data set examining the performance of sets of primers targeting the V1-V2, V6, and V6-V7 regions. By using a sample for which we have also generated a whole-genome shotgun sequencing run with 250 bp reads, we were able to compare the observed 16S rRNA genes in samples with and without an initial PCR step targeting the 16S rRNA gene. Our results demonstrate that experimental choices such as which region of the 16S rRNA gene to sequence and which algorithm to use to classify taxa are much more likely to affect observations of the “rare biosphere” than more commonly observed taxa.     

Biased Diversity Metrics Revealed by Bacterial 16S Pyrotags Derived from Different Primer Sets

In recent years, PCR-based pyrosequencing of 16S rRNA genes has continuously increased our understanding of complex microbial communities in various environments of the Earth. However, there is always concern on the potential biases of diversity determination using different 16S rRNA gene primer sets and covered regions. Here, we first report how bacterial 16S rRNA gene pyrotags derived from a series of different primer sets resulted in the biased diversity metrics. In total, 14 types of pyrotags were obtained from two-end pyrosequencing of 7 amplicon pools generated by 7 primer sets paired by 1 of 4 forward primers (V1F, V3F, V5F, and V7F) and 1 of 4 reverse primers (V2R, V4R, V6R, and V9R), respectively. The results revealed that: i) the activated sludge exhibited a large bacterial diversity that represented a broad range of bacterial populations and served as a good sample in this methodology research; ii) diversity metrics highly depended on the selected primer sets and covered regions; iii) paired pyrotags obtained from two-end pyrosequencing of each short amplicon displayed different diversity metrics; iv) relative abundance analysis indicated the sequencing depth affected the determination of rare bacteria but not abundant bacteria; v) the primer set of V1F and V2R significantly underestimated the diversity of activated sludge; and vi) the primer set of V3F and V4R was highly recommended for future studies due to its advantages over other primer sets. All of these findings highlight the significance of this methodology research and offer a valuable reference for peer researchers working on microbial diversity determination.     

Short pyrosequencing reads suffice for accurate microbial community analysis

Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced.     

Testing the limits of 454 pyrotag sequencing: reproducibility, quantitative assessment and comparison to T-RFLP fingerprinting of aquifer microbes

The characterization of microbial community structure via 16S rRNA gene profiling has been greatly advanced in recent years by the introduction of amplicon pyrosequencing. The possibility of barcoding gives the opportunity to massively screen multiple samples from environmental or clinical sources for community details. However, an on-going debate questions the reproducibility and semi-quantitative rigour of pyrotag sequencing, similar to the early days of community fingerprinting. In this study we demonstrate the reproducibility of bacterial 454 pyrotag sequencing over biological and technical replicates of aquifer sediment bacterial communities. Moreover, we explore the potential of recovering specific template ratios via quantitatively defined template spiking to environmental DNA. We sequenced pyrotag libraries of triplicate sediment samples taken in annual sampling campaigns at a tar oil contaminated aquifer in Düsseldorf, Germany. The abundance of dominating lineages was highly reproducible with a maximal standard deviation of ~4% read abundance across biological, and ~2% across technical replicates. Our workflow also allows for the linking of read abundances within defined assembled pyrotag contigs to that of specific 'in vivo' fingerprinting signatures. Thus we demonstrate that both terminal restriction fragment length polymorphism (T-RFLP) analysis and pyrotag sequencing are capable of recovering highly comparable community structure. Overall diversity was roughly double in amplicon sequencing. Pyrotag libraries were also capable of linearly recovering increasing ratios (up to 20%) of 16S rRNA gene amendments from a pure culture of Aliivibrio fisheri spiked to sediment DNA. Our study demonstrates that 454 pyrotag sequencing is a robust and reproducible method, capable of reliably recovering template abundances and overall community structure within natural microbial communities.     

High-Resolution Taxonomic Profiling of the Subgingival Microbiome for Biomarker Discovery and Periodontitis Diagnosis

The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis.     

Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.     

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.     

Novel high-rank phylogenetic lineages within a sulfur spring (Zodletone Spring, Oklahoma), revealed using a combined pyrosequencing-sanger approach

The utilization of high-throughput sequencing technologies in 16S rRNA gene-based diversity surveys has indicated that within most ecosystems, a significant fraction of the community could not be assigned to known microbial phyla. Accurate determination of the phylogenetic affiliation of such sequences is difficult due to the short-read-length output of currently available high-throughput technologies. This fraction could harbor multiple novel phylogenetic lineages that have so far escaped detection. Here we describe our efforts in accurate assessment of the novelty and phylogenetic affiliation of selected unclassified lineages within a pyrosequencing data set generated from source sediments of Zodletone Spring, a sulfide- and sulfur-rich spring in southwestern Oklahoma. Lineage-specific forward primers were designed for 78 putatively novel lineages identified within the pyrosequencing data set, and representative nearly full-length small-subunit (SSU) rRNA gene sequences were obtained by pairing those primers with reverse universal bacterial primers. Of the 78 lineages tested, amplifiable products were obtained for 52, 32 of which had at least one nearly full-length sequence that was representative of the lineage targeted. Analysis of phylogenetic affiliation of the obtained Sanger sequences identified 5 novel candidate phyla and 10 novel candidate classes (within Fibrobacteres, Planctomycetes, and candidate phyla BRC1, GN12, TM6, TM7, LD1, WS2, and GN06) in the data set, in addition to multiple novel orders and families. The discovery of multiple novel phyla within a pilot study of a single ecosystem clearly shows the potential of the approach in identifying novel diversities within the rare biosphere.     

Endophyte microbiome diversity in micropropagated Atriplex canescens and Atriplex torreyi var griffithsii

Microbial diversity associated with micropropagated Atriplex species was assessed using microscopy, isolate culturing, and sequencing. Light, electron, and confocal microscopy revealed microbial cells in aseptically regenerated leaves and roots. Clone libraries and tag-encoded FLX amplicon pyrosequencing (TEFAP) analysis amplified sequences from callus homologous to diverse fungal and bacterial taxa. Culturing isolated some seed borne endophyte taxa which could be readily propagated apart from the host. Microbial cells were observed within biofilm-like residues associated with plant cell surfaces and intercellular spaces. Various universal primers amplified both plant and microbial sequences, with different primers revealing different patterns of fungal diversity. Bacterial and fungal TEFAP followed by alignment with sequences from curated databases revealed 7 bacterial and 17 ascomycete taxa in A. canescens, and 5 bacterial taxa in A. torreyi. Additional diversity was observed among isolates and clone libraries. Micropropagated Atriplex retains a complex, intimately associated microbiome which includes diverse strains well poised to interact in manners that influence host physiology. Microbiome analysis was facilitated by high throughput sequencing methods, but primer biases continue to limit recovery of diverse sequences from even moderately complex communities.     

Don't put all your eggs in one basket: a cost‐effective and powerful method to optimize primer choice for rRNA environmental community analyses using the Fluidigm Access Array

With the increasing democratization of high‐throughput sequencing (HTS) technologies, along with the concomitant increase in sequence yield per dollar, many researchers are exploring HTS for microbial community ecology. Many elements of experimental design can drastically affect the final observed community structure, notably the choice of primers for amplification prior to sequencing. Some targeted microbes can fail to amplify due to primer‐targeted sequence divergence and be omitted from obtained sequences, leading to differences among primer pairs in the sequenced organisms even when targeting the same community. This potential source of taxonomic bias in HTS makes it prudent to investigate how primer choice will affect the sequenced community prior to investing in a costly community‐wide sequencing effort. Here, we use Fluidigm's microfluidic Access Arrays (IFC) followed by Illumina^® MiSeq Nano sequencing on a culture‐derived local mock community to demonstrate how this approach allows for a low‐cost combinatorial investigation of primer pairs and experimental samples (up to 48 primer pairs and 48 samples) to determine the most effective primers that maximize obtained communities whilst minimizing taxonomic biases.     

High-resolution analysis of gut environment and bacterial microbiota reveals functional compartmentation of the gut in wood-feeding higher termites (Nasutitermes spp.)

Higher termites are characterized by a purely prokaryotic gut microbiota and an increased compartmentation of their intestinal tract. In soil-feeding species, each gut compartment has different physicochemical conditions and is colonized by a specific microbial community. Although considerable information has accumulated also for wood-feeding species of the genus Nasutitermes, including cellulase activities and metagenomic data, a comprehensive study linking physicochemical gut conditions with the structure of the microbial communities in the different gut compartments is lacking. In this study, we measured high-resolution profiles of H(2), O(2), pH, and redox potential in the gut of Nasutitermes corniger termites, determined the fermentation products accumulating in the individual gut compartments, and analyzed the bacterial communities in detail by pyrotag sequencing of the V3-V4 region of the 16S rRNA genes. The dilated hindgut paunch (P3 compartment) was the only anoxic gut region, showed the highest density of bacteria, and accumulated H(2) to high partial pressures (up to 12 kPa). Molecular hydrogen is apparently produced by a dense community of Spirochaetes and Fibrobacteres, which also dominate the gut of other Nasutitermes species. All other compartments, such as the alkaline P1 compartment (average pH, 10.0), showed high redox potentials and comprised small but distinct populations characteristic for each gut region. In the crop and the posterior hindgut compartments, the community was even more diverse than in the paunch. Similarities in the communities of the posterior hindgut and crop suggested that proctodeal trophallaxis or coprophagy also occurs in higher termites. The large sampling depths of pyrotag sequencing in combination with the determination of important physicochemical parameters allow cautious conclusions concerning the functions of particular bacterial lineages in the respective gut sections to be drawn.     

Denaturing gradient gel electrophoresis analysis with different primers of subgingival bacterial communities under mechanical debridement

DGGE of 16S rDNA is one of the most frequently used methods to study microbial communities. In this study, the DGGE profiles of different 16S rDNA regions of the periodontal pathogens Porphyromonas gingivalis, Fusobacterium nucleatum, and Prevotella nigrescens were investigated. The results suggested that V3-V5 and V6-V8 fragments may be suitable for community analysis of subgingival bacteria. Further analysis of subgingival samples with V3-V5 and V6-V8 regions as target fragments suggested that, in chronic periodontitis, re-colonization by periodontal bacteria with a population very similar to the baseline may occur by 6 weeks after mechanical debridement.     

Quantifying microbial communities with 454 pyrosequencing: does read abundance count?

Pyrosequencing technologies have revolutionized how we describe and compare complex microbial communities. In 454 pyrosequencing data sets, the abundance of reads pertaining to taxa or phylotypes is commonly interpreted as a measure of genic or taxon abundance, useful for quantitative comparisons of community similarity. Potentially systematic biases inherent in sample processing, amplification and sequencing, however, may alter read abundance and reduce the utility of quantitative metrics. Here, we examine the relationship between read abundance and biological abundance in a sample of house dust spiked with known quantities and identities of fungi along a dilution gradient. Our results show one order of magnitude differences in read abundance among species. Precision of quantification within species along the dilution gradient varied from R(2) of 0.96-0.54. Read-quality based processing stringency profoundly affected the abundance of one species containing long homopolymers in a read orientation-biased manner. Order-level composition of background environmental fungal communities determined from pyrosequencing data was comparable with that derived from cloning and Sanger sequencing and was not biased by read orientation. We conclude that read abundance is approximately quantitative within species, but between-species comparisons can be biased by innate sequence structure. Our results showed a trade off between sequence quality stringency and quantification. Careful consideration of sequence processing methods and community analyses are warranted when testing hypotheses using read abundance data.     

PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets

As 16S rRNA gene targeted massively parallel sequencing has become a common tool for microbial diversity investigations, numerous advances have been made to minimize the influence of sequencing and chimeric PCR artifacts through rigorous quality control measures. However, there has been little effort towards understanding the effect of multi-template PCR biases on microbial community structure. In this study, we used three bacterial and three archaeal mock communities consisting of, respectively, 33 bacterial and 24 archaeal 16S rRNA gene sequences combined in different proportions to compare the influences of (1) sequencing depth, (2) sequencing artifacts (sequencing errors and chimeric PCR artifacts), and (3) biases in multi-template PCR, towards the interpretation of community structure in pyrosequencing datasets. We also assessed the influence of each of these three variables on α- and β-diversity metrics that rely on the number of OTUs alone (richness) and those that include both membership and the relative abundance of detected OTUs (diversity). As part of this study, we redesigned bacterial and archaeal primer sets that target the V3-V5 region of the 16S rRNA gene, along with multiplexing barcodes, to permit simultaneous sequencing of PCR products from the two domains. We conclude that the benefits of deeper sequencing efforts extend beyond greater OTU detection and result in higher precision in β-diversity analyses by reducing the variability between replicate libraries, despite the presence of more sequencing artifacts. Additionally, spurious OTUs resulting from sequencing errors have a significant impact on richness or shared-richness based α- and β-diversity metrics, whereas metrics that utilize community structure (including both richness and relative abundance of OTUs) are minimally affected by spurious OTUs. However, the greatest obstacle towards accurately evaluating community structure are the errors in estimated mean relative abundance of each detected OTU due to biases associated with multi-template PCR reactions.