Dataset Information

Taxonomic resolution of the ribosomal RNA operon in bacteria: implications for its use with long-read sequencing.

ABSTRACT: DNA barcoding through the use of amplified regions of the ribosomal operon, such as the 16S gene, is a routine method to gain an overview of the microbial taxonomic diversity within a sample without the need to isolate and culture the microbes present. However, bacterial cells usually have multiple copies of this ribosomal operon, and choosing the 'wrong' copy could provide a misleading species classification. While this presents less of a problem for well-characterized organisms with large sequence databases to interrogate, it is a significant challenge for lesser known organisms with unknown copy number and diversity. Using the entire length of the ribosomal operon, which encompasses the 16S, 23S, 5S and internal transcribed spacer regions, should provide greater taxonomic resolution but has not been well explored. Here, we use publicly available reference genomes and explore the theoretical boundaries when using concatenated genes and the full-length ribosomal operons, which has been made possible by the development and uptake of long-read sequencing technologies. We quantify the issues of both copy choice and operon length in a phylogenetic context to demonstrate that longer regions improve the phylogenetic signal while maintaining taxonomic accuracy.

SUBMITTER: de Oliveira Martins L

PROVIDER: S-EPMC7671355 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Taxonomic resolution of the ribosomal RNA operon in bacteria: implications for its use with long-read sequencing.

de Oliveira Martins Leonardo L Page Andrew J AJ Mather Alison E AE Charles Ian G IG

NAR genomics and bioinformatics 20191114 1

DNA barcoding through the use of amplified regions of the ribosomal operon, such as the 16S gene, is a routine method to gain an overview of the microbial taxonomic diversity within a sample without the need to isolate and culture the microbes present. However, bacterial cells usually have multiple copies of this ribosomal operon, and choosing the 'wrong' copy could provide a misleading species classification. While this presents less of a problem for well-characterized organisms with large sequ ...[more]

PMID: 33575567

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Project description:We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3' transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5' ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread. Importance: We precisely mapped the 5' and 3' ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are complex, with internal promoters and terminators generating multiple transcription units and allowing differential gene expression within these operons. We discovered extensive antisense transcription that results from more than 500 operons, which fully overlap or extensively overlap adjacent divergent or convergent operons. The genomic regions corresponding to these antisense transcripts are highly conserved in E. coli (including Shigella species), although it remains to be proven whether or not they are functional. Our observations of features unearthed by single-nucleotide transcriptome mapping suggest that deeper layers of transcriptional regulation in bacteria are likely to be revealed in the future.

Project description:BackgroundLong-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.ResultsOur results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.ConclusionsOur critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Dataset Information

Taxonomic resolution of the ribosomal RNA operon in bacteria: implications for its use with long-read sequencing.

Publications

Taxonomic resolution of the ribosomal RNA operon in bacteria: implications for its use with long-read sequencing.

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