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.     

Benchmarking of 16S rRNA gene databases using known strain sequences

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.     

16S rRNA sequences reveal uncultured inhabitants of a well-studied thermal community

Abstract Molecular methods are beginning to reveal inhabitants of natural microbial communities which have nerver before been cultured. Our approach involves selective cloning of naturally occurring 16S rRNA sequences as cDNA, and comparison of these sequences to a database which includes 16S rRNA sequences of isolated community members. We provide here an overview of the method and its potential for community analysis. A 16S rRNA sequence retrieved from the well-studied hot spring cyanobacterial mat in Octopus Spring (Yellowstone National Park) is shown as an example of one contributed by an uncultured member of the community.     

16S rRNA sequences reveal uncultured inhabitants of a well-studied thermal community

Molecular methods are beginning to reveal inhabitants of natural microbial communities which have never before been cultured. Our approach involves selective cloning of naturally occurring 16S rRNA sequences as cDNA, and comparison of these sequences to a database which includes 16S rRNA sequences of isolated community members. We provide here an overview of the method and its potential for community analysis. A 16S rRNA sequence retrieved from the well-studied hot spring cyanobacterial mat in Octopus Spring (Yellowstone National Park) is shown as an example of one contributed by an uncultured member of the community.     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

基于16S rRNA基因测序分析微生物群落多样性

微生物群落多样性的研究对于挖掘微生物资源,探索微生物群落功能,阐明微生物群落与生境间的关系具有重要意义。随着宏基因组概念的提出以及测序技术的快速发展,16S rRNA基因测序在微生物群落多样性的研究中已被广泛应用。文中系统地介绍了16S rRNA基因测序分析流程中的四个重要环节,包括测序平台与扩增区的选择、测序数据预处理以及多样性分析方法,就其面临的问题与挑战进行了探讨并对未来的研究方向进行了展望,以期为微生物群落多样性相关研究提供参考。     

Development of a 16S rRNA gene-based prototype microarray for the detection of selected actinomycetes genera

Actinomycetes are known for their secondary metabolites, which have been successfully used as drugs in human and veterinary medicines. However, information on the distribution of this group of Gram-positive bacteria in diverse ecosystems and a comprehension of their activities in ecosystem processes are still scarce. We have developed a 16S rRNA-based taxonomic microarray that targets key actinomycetes at the genus level. In total, 113 actinomycete 16S rRNA probes, corresponding to 55 of the 202 described genera, were designed. The microarray accuracy was evaluated by comparing signal intensities with probe/target-weighted mismatch values and the Gibbs energy of the probe/target duplex formation by hybridizing 17 non-actinomycete and 29 actinomycete strains/clones with the probe set. The validation proved that the probe set was specific, with only 1.3% of false results. The incomplete coverage of actinomycetes by a genus-specific probe was caused by the limited number of 16S rRNA gene sequences in databases or insufficient 16S rRNA gene polymorphism. The microarray enabled discrimination between actinomycete communities from three forest soil samples collected at one site. Cloning and sequencing of 16S rRNA genes from one of the soil samples confirmed the microarray results. We propose that this newly constructed microarray will be a valuable tool for genus-level comparisons of actinomycete communities in various ecological conditions.     

PCR-generated artefact from 16S rRNA gene-specific primers

Artefacts consisting of concatenated oligonucleotide primer sequences were generated during sub-optimally performing polymerase chain reaction amplification of bacterial 16S rRNA genes using a commonly employed primer pair. These artefacts were observed during amplification for terminal restriction fragment length polymorphism analyses of complex microbial communities, and after amplification from DNA from a microbial culture. Similar repetitive motifs were found in gene sequences deposited in GenBank. The artefact can be avoided by using different primers for the amplification reaction.     

Evaluating Bias of Illumina-Based Bacterial 16S rRNA Gene Profiles

Massively parallel sequencing of 16S rRNA genes enables the comparison of terrestrial, aquatic, and host-associated microbial communities with sufficient sequencing depth for robust assessments of both alpha and beta diversity. Establishing standardized protocols for the analysis of microbial communities is dependent on increasing the reproducibility of PCR-based molecular surveys by minimizing sources of methodological bias. In this study, we tested the effects of template concentration, pooling of PCR amplicons, and sample preparation/interlane sequencing on the reproducibility associated with paired-end Illumina sequencing of bacterial 16S rRNA genes. Using DNA extracts from soil and fecal samples as templates, we sequenced pooled amplicons and individual reactions for both high (5- to 10-ng) and low (0.1-ng) template concentrations. In addition, all experimental manipulations were repeated on two separate days and sequenced on two different Illumina MiSeq lanes. Although within-sample sequence profiles were highly consistent, template concentration had a significant impact on sample profile variability for most samples. Pooling of multiple PCR amplicons, sample preparation, and interlane variability did not influence sample sequence data significantly. This systematic analysis underlines the importance of optimizing template concentration in order to minimize variability in microbial-community surveys and indicates that the practice of pooling multiple PCR amplicons prior to sequencing contributes proportionally less to reducing bias in 16S rRNA gene surveys with next-generation sequencing.     

菌群16S rRNA基因测序的聚类分析方法研究进展

16S核糖体RNA（16S rRNA）基因测序是微生物分析的重要手段。16S rRNA基因测序的原始数据复杂,存在许多误差,分析前一般需要先进行序列质量控制,即对数据进行去噪、去冗余和去嵌合,最终将质量控制后的数据分为可操作分类单元（OTU）或ASV,在OTU或ASV基础上再进行菌群的各种分析。经过多年改进,聚类方法逐渐以UPARSE、DADA2、Deblur和UNOISE3等为主流,OTU聚类已经不能满足研究的需求,而ASV聚类使得菌群分析更加准确。本文除了综述聚类方法的研究进展外,还介绍了USEARCH、MOTHUR和QIIME等多种16S基因测序分析工具软件的相关研究进展。

     

PCR primers to amplify 16S rRNA genes from cyanobacteria.

We developed and tested a set of oligonucleotide primers for the specific amplification of 16S rRNA gene segments from cyanobacteria and plastids by PCR. PCR products were recovered from all cultures of cyanobacteria and diatoms that were checked but not from other bacteria and archaea. Gene segments selectively retrieved from cyanobacteria and diatoms in unialgal but nonaxenic cultures and from cyanobionts in lichens could be directly sequenced. In the context of growing sequence databases, this procedure allows rapid and phylogenetically meaningful identification without pure cultures or molecular cloning. We demonstrate the use of this specific PCR in combination with denaturing gradient gel electrophoresis to probe the diversity of oxygenic phototrophic microorganisms in cultures, lichens, and complex microbial communities.     

Bacterial diversity based on 16S rRNA and gyrB genes at Yinshan mine, China

The diversity of bacterial communities at three sites impacted by acid mine drainage (AMD) from the Yinshan Mine in China was studied using comparative sequence analysis of two molecular markers, the 16S rRNA and gyrB genes. The phylogenetic analyses retrieved sequences from six classes of bacteria, Nitrospira, Alphaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Acidobacteria, and Actinobacteria, as well as sequences related to the plastid of the cyanobacterium Cyanidium acidocaldarium and also some unknown bacteria. The results of phylogenetic analyses based on gyrB and 16S rRNA were compared. This confirmed that gyrB gene analysis may be a useful tool, in addition to the comparative sequence analysis of the 16S rRNA gene, for the analysis of microbial community compositions. Moreover, the Mantel test showed that the geochemical characteristics, especially the pH value and the concentration of iron, strongly influenced the composition of the microbial communities.     

Single base alterations upstream of the E. coli 16S rRNA coding region result in temperature-sensitive 16S rRNA expression

We have isolated three new temperature-sensitive mutants of 16S rRNA, using the U1192 spectinomycin resistance as a selectable marker. These differ from our previously characterized ts mutants in that they map in the upstream leader region of the rRNA precursor (at positions -13, -30 and -59). The relative distribution of plasmid and chromosome-derived 16S rRNA is similar between 30S subunits, 70S ribosomes and polysomes at the permissive and restrictive temperatures. Processing of the 5' end of the RNA does not appear to be affected by the mutations. Second-site suppressors were found, and all of these except one (which is within 16S rRNA) were also due to point mutations in the upstream leader.     

Study of bacterial communities in Antarctic coastal waters by a combination of 16S rRNA and 16S rDNA sequencing

An ecological study on distribution of Antarctic bacterial communities was determined by 16S-based phylogenetic analyses of clone libraries derived from RNA and DNA extracted from two different marine areas and compared between each other. Superficial seawater samples were collected from four stations in Ross Sea, three of them located in Rod Bay and one in Evans Cove; for each station two clone libraries (16S rDNA and 16S rRNA) were prepared and evident divergences between DNA and RNA libraries of each site were obtained. Of all phylotypes 93.6% were found in RNA libraries; in contrast, only 31 phylotypes (70.5%) were retrieved from total microbial community (DNA libraries). DNA and RNA sequences related to gamma-Proteobacteria and Bacteroidetes groups, typical for Antarctic sea-ice bacterial communities, were detected in analysed sites. 16S rDNA and rRNA libraries derived from the two different areas were enriched by picophytoplanktonic 16S sequences of plastid and mitochondrion origins, reflecting that the algal blooms occurred during sampling (Antarctic summer 2003). The finding in Rod Bay libraries of high percentage of DNA clones apparently affiliated with beta-Proteobacteria typical for activated sludges and well water could be explained by the presence of a sewage depuration system at this site. Obtained results clearly demonstrate that combination of 16S rDNA and 16S rRNA gene sequencing is preferred approach to have a more reliable vision on the composition of microbial communities.     

Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering

MOTIVATION: With the advancements of next-generation sequencing technology, it is now possible to study samples directly obtained from the environment. Particularly, 16S rRNA gene sequences have been frequently used to profile the diversity of organisms in a sample. However, such studies are still taxed to determine both the number of operational taxonomic units (OTUs) and their relative abundance in a sample. RESULTS: To address these challenges, we propose an unsupervised Bayesian clustering method termed Clustering 16S rRNA for OTU Prediction (CROP). CROP can find clusters based on the natural organization of data without setting a hard cut-off threshold (3%/5%) as required by hierarchical clustering methods. By applying our method to several datasets, we demonstrate that CROP is robust against sequencing errors and that it produces more accurate results than conventional hierarchical clustering methods. Availability and Implementation: Source code freely available at the following URL: http://code.google.com/p/crop-tingchenlab/, implemented in C++ and supported on Linux and MS Windows.     

Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers

The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.     

A novel method for determining microflora composition using dynamic phylogenetic analysis of 16S ribosomal RNA deep sequencing data

Deep sequencing of the 16S rRNA gene provides a comprehensive view of bacterial communities in a particular environment and has expanded our ability to study the impact of the microflora on human health and disease. Current analysis methods rely on comparisons of the sequences generated with an expanding but limited set of annotated 16S rRNA sequences or phylogenic clustering of sequences based on arbitrary similarity cutoffs. We describe a novel approach to characterize bacterial composition using deep sequencing of 16S rRNA gene. Our method defines operational taxonomic units based on phylogenetic tree reconstruction and dynamic clustering of sequences using solely sequencing data. These OTUs can be used to identify differences in bacteria abundance between environments. This approach can perform better than previous phylogenetic methods and will significantly improve our understanding of the microfloral role on human diseases by providing a comprehensive analysis of the microbial composition from various bacterial communities.     

Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes

rRNA-based studies, which have become the most common method for assessing microbial communities, rely upon faithful amplification of the corresponding genes from the original DNA sample. We report here an analysis and reevaluation of commonly used primers for amplifying the DNA between positions 27 and 1492 of bacterial 16S rRNA genes (numbered according to the Escherichia coli rRNA). We propose a formulation for a forward primer (27f) that includes three sequences not usually present. We compare our proposed formulation to two common alternatives by using linear amplification-providing an assessment that is independent of a reverse primer-and in combination with the 1492 reverse primer (1492r) under the PCR conditions appropriate for making community rRNA gene clone libraries. For analyses of DNA from human vaginal samples, our formulation was better at maintaining the original rRNA gene ratio of Lactobacillus spp. to Gardnerella spp., particularly under stringent amplification conditions. Because our 27f formulation remains relatively simple, having seven distinct primer sequences, there is minimal loss of overall amplification efficiency and specificity.     

Molecular diversity of 16S rRNA and gyrB genes in copper mines

The molecular diversities of the microbial communities from four sites impacted by acid mine drainage (AMD) at Dexing Copper Mine in Jiangxi province of China were studied using 16S rRNA sequences and gyrB sequences. Of the four sampled sites, each habitat exhibited distinct geochemical characteristics and the sites were linked geographically allowing us to correlate microbial community structure to geochemical characteristics. In the present study, we examined the molecular diversity of 16S rRNA and gyrB genes from water at these sites using a PCR-based cloning approach. We found that the microbial community appears to be composed primarily of Proteobacteria, Acidobacteria, Actinobacteria, Nitrospira, Firmicutes, Chlorella and unknown phylotypes. Of clones affiliated with Nitrospira, Leptospirillum ferrooxidans, Leptospirillum ferriphilum and Leptospirillum group III were all detected. Principal-component analysis (PCA) revealed that the distribution of the microbial communities was influenced greatly by geochemical characteristics. The overall PCA profiles showed that the sites with similar geochemical characteristics had more similar microbial community structures. Moreover, our results also indicated that gyrB sequence analysis may be very useful for differentiating very closely related species in the study of microbial communities. H. Yin and L. Cao contributed equally to this work.