Oral microbiome profiles: 16S rRNA pyrosequencing and microarray assay comparison

Objectives

The human oral microbiome is potentially related to diverse health conditions and high-throughput technology provides the possibility of surveying microbial community structure at high resolution. We compared two oral microbiome survey methods: broad-based microbiome identification by 16S rRNA gene sequencing and targeted characterization of microbes by custom DNA microarray.

Methods

Oral wash samples were collected from 20 individuals at Memorial Sloan-Kettering Cancer Center. 16S rRNA gene survey was performed by 454 pyrosequencing of the V3–V5 region (450 bp). Targeted identification by DNA microarray was carried out with the Human Oral Microbe Identification Microarray (HOMIM). Correlations and relative abundance were compared at phylum and genus level, between 16S rRNA sequence read ratio and HOMIM hybridization intensity.

Results

The major phyla, Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Fusobacteria were identified with high correlation by the two methods (r = 0.70∼0.86). 16S rRNA gene pyrosequencing identified 77 genera and HOMIM identified 49, with 37 genera detected by both methods; more than 98% of classified bacteria were assigned in these 37 genera. Concordance by the two assays (presence/absence) and correlations were high for common genera (Streptococcus, Veillonella, Leptotrichia, Prevotella, and Haemophilus; Correlation = 0.70–0.84).

Conclusion

Microbiome community profiles assessed by 16S rRNA pyrosequencing and HOMIM were highly correlated at the phylum level and, when comparing the more commonly detected taxa, also at the genus level. Both methods are currently suitable for high-throughput epidemiologic investigations relating identified and more common oral microbial taxa to disease risk; yet, pyrosequencing may provide a broader spectrum of taxa identification, a distinct sequence-read record, and greater detection sensitivity.     

Ovine pedomics: the first study of the ovine foot 16S rRNA-based microbiome

We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H) and interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR-affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR, respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified because of mismatches in the 16S rRNA universal forward primer (27F). A specific real-time PCR assay was used to demonstrate the presence of D. nodosus, which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (10⁴–10⁹ cells per g tissue) than those with H or VFR feet.     

Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing

Journal of Microbiology - Recent studies on microbiome highlighted their importance in various environments including human, where they are involved in multiple biological contexts such as immune...     

Evaluation of 16S rDNA-based community profiling for human microbiome research

The Human Microbiome Project will establish a reference data set for analysis of the microbiome of healthy adults by surveying multiple body sites from 300 people and generating data from over 12,000 samples. To characterize these samples, the participating sequencing centers evaluated and adopted 16S rDNA community profiling protocols for ABI 3730 and 454 FLX Titanium sequencing. In the course of establishing protocols, we examined the performance and error characteristics of each technology, and the relationship of sequence error to the utility of 16S rDNA regions for classification- and OTU-based analysis of community structure. The data production protocols used for this work are those used by the participating centers to produce 16S rDNA sequence for the Human Microbiome Project. Thus, these results can be informative for interpreting the large body of clinical 16S rDNA data produced for this project.     

Polyphyly in 16S rRNA-based LVTree Versus Monophyly in Whole-genome-based CVTree

We report an important but long-overlooked manifestation of low-resolution power of 16S rRNA sequence analysis at the species level, namely, in 16S rRNA-based phylogenetic trees polyphyletic placements of closely-related species are abundant compared to those in genome-based phylogeny. This phenomenon makes the demarcation of genera within many families ambiguous in the 16S rRNA-based taxonomy. In this study, we reconstructed phylogenetic relationship for more than ten thousand prokaryote genomes using the CVTree method, which is based on whole-genome information. And many such genera, which are polyphyletic in 16S rRNA-based trees, are well resolved as monophyletic clusters by CVTree. We believe that with genome sequencing of prokaryotes becoming a commonplace, genome-based phylogeny is doomed to play a definitive role in the construction of a natural and objective taxonomy.     

MSClust: A Multi-Seeds based Clustering algorithm for microbiome profiling using 16S rRNA sequence

Recent developments of next generation sequencing technologies have led to rapid accumulation of 16S rRNA sequences for microbiome profiling. One key step in data processing is to cluster short sequences into operational taxonomic units (OTUs). Although many methods have been proposed for OTU inferences, a major challenge is the balance between inference accuracy and computational efficiency, where inference accuracy is often sacrificed to accommodate the need to analyze large numbers of sequences. Inspired by the hierarchical clustering method and a modified greedy network clustering algorithm, we propose a novel multi-seeds based heuristic clustering method, named MSClust, for OTU inference. MSClust first adaptively selects multi-seeds instead of one seed for each candidate cluster, and the reads are then processed using a greedy clustering strategy. Through many numerical examples, we demonstrate that MSClust enjoys less memory usage, and better biological accuracy compared to existing heuristic clustering methods while preserving efficiency and scalability.     

Designation of Streptomycete 16S and 23S rRNA-based target regions for oligonucleotide probes

The 16S and 23S rRNA of various Streptomyces species were partially sequenced and screened for the presence of stretches that could define all members of the genus, groups of species, or individual species. Nucleotide 929 (Streptomyces ambofaciens nomenclature [J.L. Pernodet, M.T. Alegre, F. Boccard, and M. Guerineau, Gene 79:33-46, 1989]) is a nucleotide highly unique to Streptomyces species which, in combination with flanking regions, allowed the designation of a genus-specific probe. Regions 158 through 203 of the 16S rRNA and 1518 through 1645 of the 23S rRNA (helix 54 [Pernodet et al., Gene 79:33-46, 1989]) have a high potential to define species, whereas the degree of variation in regions 982 through 998 and 1102 through 1122 of the 16S rRNA is less pronounced but characteristic for at least certain species. Alone or in combination with each other, these regions may serve as target sites for synthetic oligonucleotide probes and primers to be used in the determination of pure cultures and in the characterization of community structures. The specificity of several probes is demonstrated by dot blot hybridization.     

Novel primers for 16S rRNA-based archaeal community analyses in environmental samples

Next generation sequencing technologies for in depth analyses of complex microbial communities rely on rational primer design based on up-to-date reference databases. Most of the 16S rRNA-gene based analyses of environmental Archaea community composition use PCR primers developed from small data sets several years ago, making an update long overdue. Here we present a new set of archaeal primers targeting the 16S rRNA gene designed from 8500 aligned archaeal sequences in the SILVA database. The primers 340F-1000R showed a high archaeal specificity (< 1% bacteria amplification) covering 93 and 97% of available sequences for Crenarchaeota and Euryarchaeota respectively. In silico tests of the primers revealed at least 38% higher coverage for Archaea compared to other commonly used primers. Empirical tests with clone libraries confirmed the high specificity of the primer pair to Archaea in three biomes: surface waters in the Arctic Ocean, the pelagic zone of a temperate lake and a methanogenic bioreactor. The clone libraries featured both Euryarchaeota and Crenarchaeota in variable proportions and revealed dramatic differences in the archaeal community composition and minimal phylogenetic overlap between samples.     

Designation of Streptomycete 16S and 23S rRNA-based target regions for oligonucleotide probes.

The 16S and 23S rRNA of various Streptomyces species were partially sequenced and screened for the presence of stretches that could define all members of the genus, groups of species, or individual species. Nucleotide 929 (Streptomyces ambofaciens nomenclature [J.L. Pernodet, M.T. Alegre, F. Boccard, and M. Guerineau, Gene 79:33-46, 1989]) is a nucleotide highly unique to Streptomyces species which, in combination with flanking regions, allowed the designation of a genus-specific probe. Regions 158 through 203 of the 16S rRNA and 1518 through 1645 of the 23S rRNA (helix 54 [Pernodet et al., Gene 79:33-46, 1989]) have a high potential to define species, whereas the degree of variation in regions 982 through 998 and 1102 through 1122 of the 16S rRNA is less pronounced but characteristic for at least certain species. Alone or in combination with each other, these regions may serve as target sites for synthetic oligonucleotide probes and primers to be used in the determination of pure cultures and in the characterization of community structures. The specificity of several probes is demonstrated by dot blot hybridization.     

Retrieval of nearly complete 16S rRNA gene sequences from environmental DNA following 16S rRNA-based community fingerprinting

16S rRNA-based fingerprinting techniques allow rapid analyses of overall bacterial community structure but suffer from a lack of phylogenetic information hitherto retrievable from the short 16S rRNA gene sequences obtained from excised bands. An approach is presented that allows nearly complete 16S rRNA gene sequences to be retrieved for abundant components of the bacterial community as obtained by the community fingerprint, i.e. those reflected by major fingerprint bands. This was achieved by designing a pair of highly specific primers derived from the sequence of an excised band. Combined with universal 16S rRNA primers, these specific primers were applied directly to environmental DNA serving as template. This procedure allowed the generation of a nearly complete 16S rRNA gene sequence of the target taxon by specific polymerase chain reaction (PCR) followed by cycle sequencing down to a relative abundance of at least 1.5% of the environmental DNA. The procedure was exemplified for an epsilonproteobacterium related to Thiomicrospira denitrificans occurring in the central Baltic Sea. This approach is based only on PCR without any cloning step involved. It allows focussing on specific target taxa and is thus rather efficient. This approach should be applicable in general to 16S rRNA or 16S rRNA gene-based fingerprinting techniques and their respective environmental DNA.     

Development and validation of a prototype 16S rRNA-based taxonomic microarray for Alphaproteobacteria

The microarray approach has been proposed for high throughput analysis of the microbial community by providing snapshots of the microbial diversity under different environmental conditions. For this purpose, a prototype of a 16S rRNA-based taxonomic microarray was developed and evaluated for assessing bacterial community diversity. The prototype microarray is composed of 122 probes that target bacteria at various taxonomic levels from phyla to species (mostly Alphaproteobacteria). The prototype microarray was first validated using bacteria in pure culture. Differences in the sequences of probes and potential target DNAs were quantified as weighted mismatches (WMM) in order to evaluate hybridization reliability. As a general feature, probes having a WMM > 2 with target DNA displayed only 2.8% false positives. The prototype microarray was subsequently tested with an environmental sample, which consisted of an Agrobacterium-related polymerase chain reaction amplicon from a maize rhizosphere bacterial community. Microarray results were compared to results obtained by cloning-sequencing with the same DNA. Microarray analysis enabled the detection of all 16S rRNA gene sequences found by cloning-sequencing. Sequences representing only 1.7% of the clone library were detected. In conclusion, this prototype 16S rRNA-based taxonomic microarray appears to be a promising tool for the analysis of Alphaproteobacteria in complex ecosystems.     

16S rRNA-based analysis of microbiota from the cecum of broiler chickens.

The microbiota of the intestinal tract of chickens plays an important role in inhibiting the establishment of intestinal pathogens. Earlier culturing and microscopic examinations indicated that only a fraction of the bacteria in the cecum of chickens could be grown in the laboratory. Therefore, a survey of cecal bacteria was done by retrieval of 16S rRNA gene sequences from DNA isolated from the cecal content and the cecal mucosa. The ribosomal gene sequences were amplified with universal primers and cloned or subjected to temporal temperature gradient gel electrophoresis (TTGE). Partial 16S rRNA gene sequences were determined from the clones and from the major bands in TTGE gels. A total of 1,656 partial 16S rRNA gene sequences were obtained and compared to sequences in the GenBank. The comparison indicated that 243 different sequences were present in the samples. Overall, sequences representing 50 phylogenetic groups or subgroups of bacteria were found, but approximately 89% of the sequences represented just four phylogenetic groups (Clostridium leptum, Sporomusa sp., Clostridium coccoides, and enterics). Sequences of members of the Bacteroides group, the Bifidobacterium infantis subgroup, and of Pseudomonas sp. each accounted for less than 2% of the total. Sequences related to those from the Escherichia sp. subgroup and from Lactobacillus, Pseudomonas, and Bifidobacterium spp. were generally between 98 and 100% identical to sequences already deposited in the GenBank. Sequences most closely related to those of the other bacteria were generally 97% or less identical to those in the databases and therefore might be from currently unknown species. TTGE and random cloning indicated that certain phylogenetic subgroups were common to all birds analyzed, but sequence data from random cloning also provided evidence for qualitative and quantitative differences among the cecal microbiota of individual birds reared under very similar conditions.     

Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies

The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.     

Extensive set of 16S rRNA-based probes for detection of bacteria in human feces

For the detection of six groups of anaerobic bacteria in human feces, we designed seven new 16S rRNA-based oligonucleotide probes. This set of probes extends the current set of probes and gives more data on the composition of the human gut flora. Probes were designed for Phascolarctobacterium and relatives (Phasco741), Veillonella (Veil223), Eubacterium hallii and relatives (Ehal1469), Lachnospira and relatives (Lach571), and Eubacterium cylindroides and relatives (Ecyl387), and two probes were designed for Ruminococcus and relatives (Rbro730 and Rfla729). The hybridization conditions for the new probes were optimized for fluorescent in situ hybridization, and the probes were validated against a set of reference organisms. The probes were applied to fecal samples of 11 volunteers to enumerate their target bacterial groups. The Phasco741 and Veil223 probes both detected average numbers below 1% of the total number of bacteria as determined with the bacterial kingdom-specific Bact338 probe. The Ecyl387 probe detected about 1.4%, the Lach571 and Ehal1469 probes detected 3.8 and 3.6%, respectively, and a combination of the Rbro730 and Rfla729 probes detected 10.3%. A set of 15 probes consisting of probes previously described and those presented here were evaluated in hybridization with the fecal samples of the same volunteers. Together, the group-specific probes detected 90% of the total bacterial cells.     

Endophytic Pseudomonasspp. populations of pathogen-infected potato plants analysed by 16S rDNA- and 16S rRNA-based denaturating gradient gel electrophoresis

The diversity of abundant and metabolically active pseudomonads in potato plants was analysed using a culture-independent approach. The effect of two plant varieties, Agria and Bionta, as well as the presence of a plant pathogen Erwinia carotovora ssp. atroseptica on this bacterial group was tested. A combination of Pseudomonas-specific PCR, DGGE analysis, cloning and sequencing of partial 16S rDNA genes was performed using DNA and RNA extracted from potato stem tissue. Sequence analysis revealed a high species diversity, with the most prominent ones being Pseudomonas stutzeri and Pseudomonas gingeri. Some species showed high rRNA contents indicating high metabolic activity. Both, highly abundant and metabolically active Pseudomonaspopulations were more affected by the plant genotype than by the presence of E. carotovora.     

Application and validation of DNA microarrays for the 16S rRNA-based analysis of marine bacterioplankton

An oligonucleotide probe-based DNA microarray was evaluated for its ability to detect 16S rRNA targets in marine bacterioplankton samples without prior amplification by polymerase chain reaction (PCR). The results obtained were compared with those of quantitative fluorescence in situ hybridization (FISH). For extraction and direct labelling of total RNA, a fast and efficient protocol based on commercially available kits was established. A set of redundant and hierarchically structured probes was applied, and specificity of hybridization was assessed by additional control oligonucleotides comprising single central mismatches. The protocol was initially tested by microarray analysis of bacterial pure cultures. Complete discrimination of all control oligonucleotides was achieved, indicating a high degree of hybridization specificity. In a co-culture, abundant members were detected by microarray analysis, but signal ratios of positive probes did not correlate well with quantitative data from FISH experiments. A marine picoplankton sample from the German Bight was analysed. Bacterial populations with relative abundances of at least 5% were detected by hybridizing 0.1 microg of total RNA extracted from a sample of 375 ml equivalent to 4.1 x 10(8) cells. Our results demonstrate that major populations of marine bacterioplankton can be identified by microarray analysis in a fast and reliable way, even in relatively low volumes of sea water.     

基于组合探针识别的大规模细菌分类16 S rRNA基因芯片设计

随着16 S rRNA序列资源的不断丰富,以及寡核苷酸微阵列基因芯片技术的不断进步,检测复杂微生物菌落中的微生物种群构成成为可能．现有的序列特异性探针设计算法缺乏足够的覆盖度、灵活性以及效率,不能满足大规模细菌检测基因芯片的设计要求．很多组特异性探针设计算法的思路多局限于针对某个目标序列组设计唯一的组特异性探针．在很多应用场合,设计单个探针检测组内所有目标序列的目标是很难达到的．因此,设计多个探针通过组合方式进行检测是很有必要的．每个探针能特异性地检测组内一部分目标序列,通过组合就能提高覆盖率．然而,在所有可能的探针组合中找到一个优化的探针组合是很耗时的．提出了一个可行的基于相对熵和遗传算法的组合探针设计算法．