RNAmmer: consistent and rapid annotation of ribosomal RNA genes

The publication of a complete genome sequence is usually accompanied by annotations of its genes. In contrast to protein coding genes, genes for ribosomal RNA (rRNA) are often poorly or inconsistently annotated. This makes comparative studies based on rRNA genes difficult. We have therefore created computational predictors for the major rRNA species from all kingdoms of life and compiled them into a program called RNAmmer. The program uses hidden Markov models trained on data from the 5S ribosomal RNA database and the European ribosomal RNA database project. A pre-screening step makes the method fast with little loss of sensitivity, enabling the analysis of a complete bacterial genome in less than a minute. Results from running RNAmmer on a large set of genomes indicate that the location of rRNAs can be predicted with a very high level of accuracy. Novel, unannotated rRNAs are also predicted in many genomes. The software as well as the genome analysis results are available at the CBS web server.     

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.     

C16S - a Hidden Markov Model based algorithm for taxonomic classification of 16S rRNA gene sequences

Recent advances in high throughput sequencing technologies and concurrent refinements in 16S rDNA isolation techniques have facilitated the rapid extraction and sequencing of 16S rDNA content of microbial communities. The taxonomic affiliation of these 16S rDNA fragments is subsequently obtained using either BLAST-based or word frequency based approaches. However, the classification accuracy of such methods is observed to be limited in typical metagenomic scenarios, wherein a majority of organisms are hitherto unknown. In this study, we present a 16S rDNA classification algorithm, called C16S, that uses genus-specific Hidden Markov Models for taxonomic classification of 16S rDNA sequences. Results obtained using C16S have been compared with the widely used RDP classifier. The performance of C16S algorithm was observed to be consistently higher than the RDP classifier. In some scenarios, this increase in accuracy is as high as 34%. A web-server for the C16S algorithm is available at http://metagenomics.atc.tcs.com/C16S/.     

OTU Analysis Using Metagenomic Shotgun Sequencing Data

Because of technological limitations, the primer and amplification biases in targeted sequencing of 16S rRNA genes have veiled the true microbial diversity underlying environmental samples. However, the protocol of metagenomic shotgun sequencing provides 16S rRNA gene fragment data with natural immunity against the biases raised during priming and thus the potential of uncovering the true structure of microbial community by giving more accurate predictions of operational taxonomic units (OTUs). Nonetheless, the lack of statistically rigorous comparison between 16S rRNA gene fragments and other data types makes it difficult to interpret previously reported results using 16S rRNA gene fragments. Therefore, in the present work, we established a standard analysis pipeline that would help confirm if the differences in the data are true or are just due to potential technical bias. This pipeline is built by using simulated data to find optimal mapping and OTU prediction methods. The comparison between simulated datasets revealed a relationship between 16S rRNA gene fragments and full-length 16S rRNA sequences that a 16S rRNA gene fragment having a length >150 bp provides the same accuracy as a full-length 16S rRNA sequence using our proposed pipeline, which could serve as a good starting point for experimental design and making the comparison between 16S rRNA gene fragment-based and targeted 16S rRNA sequencing-based surveys possible.     

Amplification and sequencing of variable regions in bacterial 23S ribosomal RNA genes with conserved primer sequences

Published bacterial 23S ribosomal RNA sequences were aligned, and universally conserved regions flanking highly variable regions were looked for. In strategically positioned conserved regions, six oligonucleotides suitable for polymerase chain reaction (PCR) and sequencing were designed, allowing fast sequencing of four of the most variable 23S rRNA regions. Two other primers were designed for PCR amplification of nearly complete 23S rRNA genes. All these primers successfully amplified fragments of 23S rRNA genes from seven unrelated bacteria. Four primers were used to determine 938 bp of sequence forCampylobacter jejuni subsp.jejuni. These results indicate that the oligonucleotide sequences presented here are useful for PCR amplification and sequence determination of variable 23S rRNA regions for a broad variety of eubacterial species.     

VITCOMIC2: visualization tool for the phylogenetic composition of microbial communities based on 16S rRNA gene amplicons and metagenomic shotgun sequencing

Background

The 16S rRNA gene-based amplicon sequencing analysis is widely used to determine the taxonomic composition of microbial communities. Once the taxonomic composition of each community is obtained, evolutionary relationships among taxa are inferred by a phylogenetic tree. Thus, the combined representation of taxonomic composition and phylogenetic relationships among taxa is a powerful method for understanding microbial community structure; however, applying phylogenetic tree-based representation with information on the abundance of thousands or more taxa in each community is a difficult task. For this purpose, we previously developed the tool VITCOMIC (VIsualization tool for Taxonomic COmpositions of MIcrobial Community), which is based on the genome-sequenced microbes’ phylogenetic information. Here, we introduce VITCOMIC2, which incorporates substantive improvements over VITCOMIC that were necessary to address several issues associated with 16S rRNA gene-based analysis of microbial communities.

Results

We developed VITCOMIC2 to provide (i) sequence identity searches against broad reference taxa including uncultured taxa; (ii) normalization of 16S rRNA gene copy number differences among taxa; (iii) rapid sequence identity searches by applying the graphics processing unit-based sequence identity search tool CLAST; (iv) accurate taxonomic composition inference and nearly full-length 16S rRNA gene sequence reconstructions for metagenomic shotgun sequencing; and (v) an interactive user interface for simultaneous representation of the taxonomic composition of microbial communities and phylogenetic relationships among taxa. We validated the accuracy of processes (ii) and (iv) by using metagenomic shotgun sequencing data from a mock microbial community.

Conclusions

The improvements incorporated into VITCOMIC2 enable users to acquire an intuitive understanding of microbial community composition based on the 16S rRNA gene sequence data obtained from both metagenomic shotgun and amplicon sequencing.

     

Comparison of 16S rRNA and protein-coding genes as molecular markers for assessing microbial diversity (Bacteria and Archaea) in ecosystems

PCR amplification of the rRNA gene is the most popular method for assessing microbial diversity. However, this molecular marker is often present in multiple copies in cells presenting, in addition, an intragenomic heterogeneity. In this context, housekeeping genes may be used as taxonomic markers for ecological studies. However, the efficiency of these protein-coding genes compared to 16S rRNA genes has not been tested on environmental data. For this purpose, five protein marker genes for which primer sets are available, were selected (rplB, pyrG, fusA, leuS and rpoB) and compared with 16S rRNA gene results from PCR amplification or metagenomic data from aquatic ecosystems. Analysis of the major groups found in these ecosystems, such as Actinobacteria, Bacteroides, Proteobacteria and Cyanobacteria, showed good agreement between the protein markers and the results given by 16S rRNA genes from metagenomic reads. However, with the markers it was possible to detect minor groups among the microbial assemblages, providing more details compared to 16S rRNA results from PCR amplification. In addition, the use of a set of protein markers made it possible to deduce a mean copy number of rRNA operons. This average estimate is essentially lower than the one estimated in sequenced genomes.     

Museum fish specimens and molecular taxonomy: A comparative study on DNA extraction protocols and preservation techniques

Museum fish specimens are invaluable resources for genetic studies, but extraction of high quality DNA is often problematic. In this study, hairtail fishes of the genera Trichiurus and Lepturacanthus (family: Trichiuridae) representing a wide range of preservation histories and three different methods of preservation were analyzed for mitochondrial DNA (mtDNA) extraction, amplification and sequencing of marker genes. A total of six protocols, including a commercially available kit, were compared in this study. Amplification of conserved genes such as16S rRNA and 12S rRNA were done using polymerase chain reaction with sequence analyses using automated capillary sequencing techniques. The results show that mtDNA extraction, amplification and sequencing of conserved genes could be obtained successfully from frozen (?20°C) preserved specimens (1–5 years) and also from ethanol (95%) fixed specimens (2–5 years) but not from any of the formalin (10%) fixed specimens (3–4 years). However, specimens that have been fixed for only 7 days in buffered formalin (10% formalin with phosphate buffer containing 173 mm salt) and ethanol (95%) could yield successful mtDNA extraction, amplification and sequence information of both 16S rRNA and 12S rRNA.     

Identification and characterization of metagenomic fragments from tidal flat sediment

Phylogenetic surveys based on cultivation-independent methods have revealed that tidal flat sediments are environments with extensive microbial diversity. Since most of prokaryotes in nature cannot be easily cultivated under general laboratory conditions, our knowledge on prokaryotic dwellers in tidal flat sediment is mainly based on the analysis of metagenomes. Microbial community analysis based on the 16S rRNA gene and other phylogenetic markers has been widely used to provide important information on the role of microorganisms, but it is basically an indirect means, compared with direct sequencing of metagenomic DNAs. In this study, we applied a sequence-based metagenomic approach to characterize uncultivated prokaryotes from tidal flat sediment. Two large-insert genomic libraries based on fosmid were constructed from tidal flat metagenomic DNA. A survey based on end-sequencing of selected fosmid clones resulted in the identification of clones containing 274 bacterial and 16 archaeal homologs in which majority were of proteobacterial origins. Two fosmid clones containing large metagenomic DNAs were completely sequenced using the shotgun method. Both DNA inserts contained more than 20 genes encoding putative proteins which implied their ecological roles in tidal flat sediment. Phylogenetic analyses of evolutionary conserved proteins indicate that these clones are not closely related to known prokaryotes whose genome sequence is known, and genes in tidal flat may be subjected to extensive lateral gene transfer, notably between domains Bacteria and Archaea. This is the first report demonstrating that direct sequencing of metagenomic gene library is useful in underpinning the genetic makeup and functional roles of prokaryotes in tidal flat sediments.     

Evaluation of sequence alignments and oligonucleotide probes with respect to three-dimensional structure of ribosomal RNA using ARB software package

Background  

Availability of high-resolution RNA crystal structures for the 30S and 50S ribosomal subunits and the subsequent validation of comparative secondary structure models have prompted the biologists to use three-dimensional structure of ribosomal RNA (rRNA) for evaluating sequence alignments of rRNA genes. Furthermore, the secondary and tertiary structural features of rRNA are highly useful and successfully employed in designing rRNA targeted oligonucleotide probes intended for in situ hybridization experiments. RNA3D, a program to combine sequence alignment information with three-dimensional structure of rRNA was developed. Integration into ARB software package, which is used extensively by the scientific community for phylogenetic analysis and molecular probe designing, has substantially extended the functionality of ARB software suite with 3D environment.     

FragGeneScan: predicting genes in short and error-prone reads

The advances of next-generation sequencing technology have facilitated metagenomics research that attempts to determine directly the whole collection of genetic material within an environmental sample (i.e. the metagenome). Identification of genes directly from short reads has become an important yet challenging problem in annotating metagenomes, since the assembly of metagenomes is often not available. Gene predictors developed for whole genomes (e.g. Glimmer) and recently developed for metagenomic sequences (e.g. MetaGene) show a significant decrease in performance as the sequencing error rates increase, or as reads get shorter. We have developed a novel gene prediction method FragGeneScan, which combines sequencing error models and codon usages in a hidden Markov model to improve the prediction of protein-coding region in short reads. The performance of FragGeneScan was comparable to Glimmer and MetaGene for complete genomes. But for short reads, FragGeneScan consistently outperformed MetaGene (accuracy improved ∼62% for reads of 400 bases with 1% sequencing errors, and ∼18% for short reads of 100 bases that are error free). When applied to metagenomes, FragGeneScan recovered substantially more genes than MetaGene predicted (>90% of the genes identified by homology search), and many novel genes with no homologs in current protein sequence database.     

Microbial phylogeny and diversity: Small subunit ribosomal RNA sequence analysis and beyond

Small subunit ribosomal RNA (16S rRNA) gene sequence analysis is used for the identification and classification of prokaryotes. In addition, sequencing of 16S rRNA genes amplified directly from the environment is used to estimate microbial diversity. The presence of mosaicism, intra-genomic heterogeneity and the lack of a universal threshold sequence identity value limit 16S rRNA-based phylogenetic analysis. PCR-amplification bias and cloning bias can also result in an inaccurate representation of the microbial diversity. In this review, recently reported complexities of 16S rRNA gene sequence analyses and the requirement of additional tools for microbial phylogeny and diversity analyses are discussed.     

Reconstruction of ribosomal RNA genes from metagenomic data

Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.