Suitability of partial 16S ribosomal RNA gene sequence analysis for the identification of dangerous bacterial pathogens

AIMS: In a bioterrorism event a rapid tool is needed to identify relevant dangerous bacteria. The aim of the study was to assess the usefulness of partial 16S rRNA gene sequence analysis and the suitability of diverse databases for identifying dangerous bacterial pathogens. METHODS AND RESULTS: For rapid identification purposes a 500-bp fragment of the 16S rRNA gene of 28 isolates comprising Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Francisella tularensis, Yersinia pestis, and eight genus-related and unrelated control strains was amplified and sequenced. The obtained sequence data were submitted to three public and two commercial sequence databases for species identification. The most frequent reason for incorrect identification was the lack of the respective 16S rRNA gene sequences in the database. CONCLUSIONS: Sequence analysis of a 500-bp 16S rDNA fragment allows the rapid identification of dangerous bacterial species. However, for discrimination of closely related species sequencing of the entire 16S rRNA gene, additional sequencing of the 23S rRNA gene or sequencing of the 16S-23S rRNA intergenic spacer is essential. SIGNIFICANCE AND IMPACT OF THE STUDY: This work provides comprehensive information on the suitability of partial 16S rDNA analysis and diverse databases for rapid and accurate identification of dangerous bacterial pathogens.     

16S rRNA gene sequencing on a benchtop sequencer: accuracy for identification of clinically important bacteria

Aims

Test the choice of 16S rRNA gene amplicon and data analysis method on the accuracy of identification of clinically important bacteria utilizing a benchtop sequencer.

Methods and Results

Nine 16S rRNA amplicons were tested on an Ion Torrent PGM to identify 41 strains of clinical importance. The V1–V2 region identified 40 of 41 isolates to the species level. Three data analysis methods were tested, finding that the Ribosomal Database Project's SequenceMatch outperformed BLAST and the Ion Reporter Metagenomics analysis pipeline. Lastly, 16S rRNA gene sequencing mixtures of four species through a six log range of dilution showed species were identifiable even when present as 0·1% of the mixture.

Conclusions

Sequencing the V1–V2 16S rRNA gene region, made possible by the increased read length Ion Torrent PGM sequencer's 400 base pair chemistry, may be a better choice over other commonly used regions for identifying clinically important bacteria. In addition, the SequenceMatch algorithm, freely available from the Ribosomal Database Project, is a good choice for matching filtered reads to organisms. Lastly, 16S rRNA gene sequencing's sensitivity to the presence of a bacterial species at 0·1% of a mixture suggests it has sufficient sensitivity for samples in which important bacteria may be rare.

Significance and Impact of the Study

We have validated 16S rRNA gene sequencing on a benchtop sequencer including simple mixtures of organisms; however, our results highlight deficits for clinical application in place of current identification methods.     

DNA sequence of the 16S rRNA/23S rRNA intercistronic spacer of two rDNA operons of the archaebacterium Methanococcus vannielii

The DNA sequence of the spacer (plus flanking) regions separating the 16S rRNA and 23S rRNA genes of two presumptive rDNA operons of the archaebacterium Methanococcus vannielii was determined. The spacers are 156 and 242 base pairs in size and they share a sequence homology of 49 base pairs following the 3' terminus of the 16S rRNA gene and of about 60 base pairs preceding the 5' end of the 23S rRNA gene. The 242 base pair spacer, in addition contains a sequence which can be transcribed into tRNAAla, whereas no tRNA-like secondary structure can be delineated from the 156 base pair spacer region. Almost complete sequence homology was detected between the end of the 16S rRNA gene and the 3' termini of either Escherichia coli or Halobacterium halobium 16S rRNA, whereas the putative 5' terminal 23S rRNA sequence shared partial homology with E. coli 23S rRNA and eukaryotic 5.8S rRNA.     

米尔顿姬小蜂线粒体16SrRNA与COI基因片段序列测定及分析

【背景】米尔顿姬小蜂是一种入侵我国台湾地区的植食性小蜂,能够严重影响水果的产量和食用价值。目前在我国大陆没有分布,由于其个体微小,与近似种区别较小,通过传统的形态学分类方法难以鉴定,因此有必要研究其基因片段序列,探讨分子鉴定方法。【方法】利用PCR方法扩增并测定了米尔顿姬小蜂线粒体16SrRNA和COI基因的部分序列,并对各序列的碱基组成进行了分析。然后根据COI基因部分序列,利用DNAMAN的MaximumLikelihood方法构建了米尔顿姬小蜂与膜翅目其他科的系统发育树。【结果】16SrRNA基因的PCR扩增产物为426bp,COI基因的PCR扩增产物为488bp。通过测序获得米尔顿姬小蜂16SrRNA和COI基因部分序列,序列分析表明,16SrRNA和COI基因的A＋T含量均较高,存在较强的A＋T偏向性。系统发育树显示,米尔顿姬小蜂与蚜小蜂科的Encarsiaberlesei亲缘关系最近,与姬小蜂科的Chrysocharisnautius、C．eurynota亲缘关系较远。【结论与意义】本研究为米尔顿姬小蜂的分子鉴定提供了依据。     

Variations in 16S rRNA-based microbiome profiling between pyrosequencing runs and between pyrosequencing facilities

Pyrosequencing of 16S rRNA gene amplicons on the 454 FLX Titanium platform has been widely used to analyze microbiomes in various environments. However, different results may stem from variations among sequencing runs or among sequencing facilities. This study aimed to evaluate these variations between different pyrosequencing runs by sequencing 16S rRNA gene amplicon libraries generated from three sets of rumen samples twice each on the 454 FLX Titanium system at two independent sequencing facilities. Similar relative abundances were found for predominant taxa represented by large numbers of sequence reads but not for minor taxa represented by small numbers of sequence reads. The two sequencing facilities revealed different bacterial profiles with respect to both predominant taxa and minor taxa, including the most predominant genus Prevotella, the family Lachnospiraceae, and the phylum Proteobacteria. Differences in primers used to generate amplicon libraries may be a major source of variations in microbiome profiling. Because different primers and regions of 16S rRNA genes are often used by different researchers, significant variations likely exist among studies. Quantitative interpretation for relative abundance of taxa, especially minor taxa, from prevalence of sequence reads and comparisons of results from different studies should be done with caution.     

Asaia sp., an unusual spoilage organism of fruit-flavored bottled water

A gram-negative bacillus was isolated from a batch of fruit-flavored bottled water, which had spoiled as a result of bacterial overgrowth (>10(6) CFU/ml). The spoilage organism was extremely difficult to identify phenotypically and was poorly identified as Pasturella sp. (78.7% identification profile) employing the API 20NE identification scheme, which gave the profile 5040000. Molecular identification through PCR amplification of a partial region of the 16S rRNA gene followed by direct automated sequencing of the PCR amplicon allowed identification of the organism. Due to the sequence identity (100%) between the spoilage organism and a reference strain in GenBank, the spoilage isolate was considered to be an Asaia sp., a recently described genus and member of the acetic acid bacteria. This is the first report of Asaia sp. causing spoilage of a foodstuff and highlights the benefits of molecular identification techniques based on 16S rRNA gene sequences in the identification of unusual spoilage organisms.     

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is “who is there?” This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.     

Profiling of the bacteria responsible for pyogenic liver abscess by 16S rRNA gene pyrosequencing

Pyogenic liver abscess (PLA) is a severe disease with considerable mortality and is often polymicrobial. Understanding the pathogens that cause PLA is the basis for PLA treatment. Here, we profiled the bacterial composition in PLA fluid by pyrosequencing the 16S ribosomal RNA (rRNA) gene based on next-generation sequencing (NGS) technology to identify etiological agents of PLA and to provide information of their 16S rRNA sequences for application to DNA-based techniques in the hospital. Twenty patients with PLA who underwent percutaneous catheter drainage, abscess culture, and blood culture for isolates were included. Genomic DNAs from abscess fluids were subjected to polymerase chain reaction and pyrosequencing of the 16S rRNA gene with a 454 GS Junior System. The abscess and blood cultures were positive in nine (45%) and four (20%) patients, respectively. Pyrosequencing of 16S rRNA gene showed that 90% of the PLA fluid samples contained single or multiple genera of known bacteria such as Klebsiella, Fusobacterium, Streptococcus, Bacteroides, Prevotella, Peptostreptococcus, unassigned Enterobacteriaceae, and Dialister. Klebsiella was predominantly found in the PLA fluid samples. All samples that carried unassigned bacteria had 26.8% reads on average. We demonstrated that the occurrence of PLA was associated with eight known bacterial genera as well as unassigned bacteria and that 16S rRNA gene sequencing was more useful than conventional culture methods for accurate identification of bacterial pathogens from PLA.     

Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads

Microbial communities host unparalleled taxonomic diversity. Adequate characterization of environmental and host-associated samples remains a challenge for microbiologists, despite the advent of 16S rRNA gene sequencing. In order to increase the depth of sampling for diverse bacterial communities, we developed a method for sequencing and assembling millions of paired-end reads from the 16S rRNA gene (spanning the V3 region; ～200 nucleotides) by using an Illumina genome analyzer. To confirm reproducibility and to identify a suitable computational pipeline for data analysis, sequence libraries were prepared in duplicate for both a defined mixture of DNAs from known cultured bacterial isolates (>1 million postassembly sequences) and an Arctic tundra soil sample (>6 million postassembly sequences). The Illumina 16S rRNA gene libraries represent a substantial increase in number of sequences over all extant next-generation sequencing approaches (e.g., 454 pyrosequencing), while the assembly of paired-end 125-base reads offers a methodological advantage by incorporating an initial quality control step for each 16S rRNA gene sequence. This method incorporates indexed primers to enable the characterization of multiple microbial communities in a single flow cell lane, may be modified readily to target other variable regions or genes, and demonstrates unprecedented and economical access to DNAs from organisms that exist at low relative abundances.     

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.     

BIPES,a cost-effective high-throughput method for assessing microbial diversity

Pyrosequencing of 16S rRNA (16S) variable tags has become the most popular method for assessing microbial diversity, but the method remains costly for the evaluation of large numbers of environmental samples with high sequencing depths. We developed a barcoded Illumina paired-end (PE) sequencing (BIPES) method that sequences each 16S V6 tag from both ends on the Illumina HiSeq 2000, and the PE reads are then overlapped to obtain the V6 tag. The average accuracy of Illumina single-end (SE) reads was only 97.9%, which decreased from ∼99.9% at the start of the read to less than 85% at the end of the read; nevertheless, overlapping of the PE reads significantly increased the sequencing accuracy to 99.65% by verifying the 3′ end of each SE in which the sequencing quality was degraded. After the removal of tags with two or more mismatches within the medial 40–70 bases of the reads and of tags with any primer errors, the overall base sequencing accuracy of the BIPES reads was further increased to 99.93%. The BIPES reads reflected the amounts of the various tags in the initial template, but long tags and high GC tags were underestimated. The BIPES method yields 20–50 times more 16S V6 tags than does pyrosequencing in a single-flow cell run, and each of the BIPES reads costs less than 1/40 of a pyrosequencing read. As a laborsaving and cost-effective method, BIPES can be routinely used to analyze the microbial ecology of both environmental and human microbiomes.     

米尔顿姬小蜂线粒体16S rRNA与COⅠ基因片段序列测定及分析

【背景】米尔顿姬小蜂是一种入侵我国台湾地区的植食性小蜂,能够严重影响水果的产量和食用价值。目前在我国大陆没有分布,由于其个体微小,与近似种区别较小,通过传统的形态学分类方法难以鉴定,因此有必要研究其基因片段序列,探讨分子鉴定方法。【方法】利用PCR方法扩增并测定了米尔顿姬小蜂线粒体16SrRNA和COⅠ基因的部分序列,并对各序列的碱基组成进行了分析。然后根据COⅠ基因部分序列,利用DNAMAN的Maximum Likelihood方法构建了米尔顿姬小蜂与膜翅目其他科的系统发育树。【结果】16SrRNA基因的PCR扩增产物为426bp,COⅠ基因的PCR扩增产物为488bp。通过测序获得米尔顿姬小蜂16SrRNA和COⅠ基因部分序列,序列分析表明,16SrRNA和COⅠ基因的A+T含量均较高,存在较强的A+T偏向性。系统发育树显示,米尔顿姬小蜂与蚜小蜂科的Encarsia berlesei亲缘关系最近,与姬小蜂科的Chrysocharis nautius、C.eurynota亲缘关系较远。【结论与意义】本研究为米尔顿姬小蜂的分子鉴定提供了依据。     

Use of Subtractive Hybridization To Design Habitat-Based Oligonucleotide Probes for Investigation of Natural Bacterial Communities

We describe a rapid oligonucleotide probe design strategy based on subtractive hybridization which yields probes for 16S rRNA or rRNA genes of individual members of microbial communities that are specific within the context of those communities. This strategy circumvents the need to sequence many similar or identical clones of dominant members of a community. Radioactively labeled subfragments of a cloned 16S rRNA gene sequence for which a probe is required (target) were hybridized with biotinylated total 16S ribosomal DNA (rDNA) amplified from the microbial community, and the hybrids formed were subsequently discarded. The remaining enriched fragments were used to screen a library consisting of cloned subfragments of the target sequence by colony hybridization in order to identify the variable regions of the 16S rRNA gene with the required specificity. The sequencing of random clones in one 16S rDNA library demonstrated that only those clones with 100% sequence identity with the probe fragment were detected by it. Moreover, sequencing of other, randomly selected, probe-positive clones revealed 100% sequence identity with the probe. Probes developed in this way tended to correspond to more variable regions of the 16S rRNA if the target sequences were similar to the sequences of other clones in the library and to less variable regions if the target sequences were phylogenetically isolated within the clone library. Although the absolute specificity of the latter probes, as assessed by comparison with available database sequences, was lower than the absolute specificity of the probes from the more variable regions, they were specific within the context of the environmental samples from which they were derived.     

Asaia sp., an Unusual Spoilage Organism of Fruit-Flavored Bottled Water

A gram-negative bacillus was isolated from a batch of fruit-flavored bottled water, which had spoiled as a result of bacterial overgrowth (>10⁶ CFU/ml). The spoilage organism was extremely difficult to identify phenotypically and was poorly identified as Pasturella sp. (78.7% identification profile) employing the API 20NE identification scheme, which gave the profile 5040000. Molecular identification through PCR amplification of a partial region of the 16S rRNA gene followed by direct automated sequencing of the PCR amplicon allowed identification of the organism. Due to the sequence identity (100%) between the spoilage organism and a reference strain in GenBank, the spoilage isolate was considered to be an Asaia sp., a recently described genus and member of the acetic acid bacteria. This is the first report of Asaia sp. causing spoilage of a foodstuff and highlights the benefits of molecular identification techniques based on 16S rRNA gene sequences in the identification of unusual spoilage organisms.     

Isolation of endophytic bacteria from arboreal species of the Amazon and identification by sequencing of the 16S rRNA encoding gene

Endophytic bacteria from three arboreal species native to the Amazon (Carapa guianenses, Ceiba pentandra, and Swietenia macrophylla), were isolated and identified, through partial sequencing of the 16S rRNA encoding gene. From these, 16 isolates were obtained, although, when compared to sequences deposited in GenBank, only seven had produced identifiable fragments. Bacillus, Pantoea and two non-culturable samples were identified. Results obtained through sequence analysis revealed low genetic diversity across the isolates, even when analyzing different species and plant structures. This is the first report concerning the isolation and identification of endophytic bacteria in these plant species.     

Comparison of 16S rRNA sequencing with conventional and commercial phenotypic techniques for identification of enterococci from the marine environment

AIMS: To compare accuracy of genus and species level identification of presumptive enterococci isolates from the marine environment using conventional biochemical testing, four commercial identification systems and 16S rRNA sequence analysis. METHODS AND RESULTS: Ninety-seven environmental bacterial isolates identified as presumptive enterococci on mEI media were tested using conventional and Enterococcus genus screen biochemical tests, four commercial testing systems and 16S rRNA sequencing. Conventional and Enterococcus genus screen biochemical testing, 16S rRNA sequencing and two commercial test systems achieved an accuracy of > or = 94% for Enterococcus genus confirmation. Conventional biochemical testing and 16S rRNA sequencing achieved an accuracy of > or = 90% for species level identification. CONCLUSIONS: For confirmation of Enterococcus genus from mEI media, conventional or genus screen biochemical testing, 16S rRNA sequencing and the four commercial systems were correct 79-100% of the time. For speciation to an accuracy of 90% or better, either conventional biochemical testing or 16S rRNA sequencing is required. SIGNIFICANCE AND IMPACT OF THE STUDY: Accurate identification of presumptive environmental Enterococcus isolates to genus and species level is an integral part of laboratory quality assurance and further characterization of Enterococcus species from pollution incidents. This investigation determines the ability of six different methods to correctly identify environmental isolates.     

Phylogenetic diversity of the intestinal bacterial community in the termite Reticulitermes speratus.

The phylogenetic diversity of the intestinal microflora of a lower termite, Reticulitermes speratus, was examined by a strategy which does not rely on cultivation of the resident microorganisms. Small-subunit rRNA genes (16S rDNAs) were directly amplified from the mixed-population DNA of the termite gut by the PCR and were clonally isolated. Analysis of partial 16S rDNA sequences showed the existence of well-characterized genera as well as the presence of bacterial species for which no 16S rDNA sequence data are available. Of 55 clones sequenced, 45 were phylogenetically affiliated with four of the major groups of the domain Bacteria: the Proteobacteria, the spirochete group, the Bacteroides group, and the low-G+C-content gram-positive bacteria. Within the Proteobacteria, the 16S rDNA clones showed a close relationship to those of cultivated species of enteric bacteria and sulfate-reducing bacteria, while the 16S rDNA clones in the remaining three groups showed only distant relationships to those of known organisms in these groups. Of the remaining 10 clones, among which 8 clones formed a cluster, there was only very low sequence similarity to known 16S rRNA sequences. None of these clones were affiliated with any of the major groups within the domain Bacteria. The 16S rDNA gene sequence data show that the majority of the intestinal microflora of R. speratus consists of new, uncultured species previously unknown to microbiologists.     

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology–a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.