Comparison of two approaches for the classification of 16S rRNA gene sequences

Chatellier, Sonia; Mugnier, Nathalie; Allard, F; Bonnaud, Bertrand; Collin, Valérie; Belkum, Alex van; Veyrieras, Jean‐Baptiste; Emler, Stefan

doi:10.1099/jmm.0.074377-0

Cited by 12 publications

(8 citation statements)

References 21 publications

(23 reference statements)

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“…The low power of 16S rRNA can be attributed to the paucity of informative sites compared with mtDNA COI. Cawthorn and co-workers using the 16S rRNA were also not able to distinguish 53 commercial fish species 31 . However, species identification based on mtDNA COI was unambiguous, our results suggest that COI sequence provides sufficient genetic variability for all studied species especially sampled populations of C. zillii and S. melanotheron .…”

Section: Discussionmentioning

confidence: 93%

“…Our results show that mtDNA COI has a higher degree of DNA variability than mt 16S rRNA and importantly, is widely used for fish identification 30 . Furthermore, recent studies have revealed that the 16S rRNA failed to distinguish closely related species due to their lower genetic variability 31 . We find that using the ML tree and the genetic pairwise distance matrix, the 16S rRNA failed to distinguish conspecific species in the sampled Tilapia populations, as shown by low bootstrap values in the phylogenetic tree.…”

Section: Discussionmentioning

confidence: 99%

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DNA barcoding of Clarias gariepinus, Coptodon zillii and Sarotherodon melanotheron from Southwestern Nigeria

2016

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DNA barcoding has been adopted as a gold standard rapid, precise and unifying identification system for animal species and provides a database of genetic sequences that can be used as a tool for universal species identification. In this study, we employed mitochondrial genes 16S rRNA (16S) and cytochrome oxidase subunit I (COI) for the identification of some Nigerian freshwater catfish and Tilapia species. Approximately 655 bp were amplified from the 5′ region of the mitochondrial cytochrome C oxidase subunit I (COI) gene whereas 570 bp were amplified for the 16S rRNA gene. Nucleotide divergences among sequences were estimated based on Kimura 2-parameter distances and the genetic relationships were assessed by constructing phylogenetic trees using the neighbour-joining (NJ) and maximum likelihood (ML) methods. Analyses of consensus barcode sequences for each species, and alignment of individual sequences from within a given species revealed highly consistent barcodes (99% similarity on average), which could be compared with deposited sequences in public databases. The nucleotide distance between species belonging to different genera based on COI ranged from 0.17% between Sarotherodon melanotheron and Coptodon zillii to 0.49% between Clarias gariepinus and C. zillii, indicating that S. melanotheron and C. zillii are closely related. Based on the data obtained, the utility of COI gene was confirmed in accurate identification of three fish species from Southwest Nigeria.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

DNA barcoding of Clarias gariepinus, Coptodon zillii and Sarotherodon melanotheron from Southwestern Nigeria

2016

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“…flexneri was additionally detected from a pure culture of E. coli . Thus, the 16S rRNA gene sequencing has poor discriminatory power to separate closely related species . The sequence analysis targeting additional genetic markers such as 23S rRNA genes may provide better resolution .…”

Section: Discussionmentioning

confidence: 99%

Rapid bacterial identification by direct PCR amplification of 16S rRNA genes using the MinION™ nanopore sequencer

et al. 2019

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Rapid identification of bacterial pathogens is crucial for appropriate and adequate antibiotic treatment, which significantly improves patient outcomes. 16S ribosomal RNA (rRNA) gene amplicon sequencing has proven to be a powerful strategy for diagnosing bacterial infections. We have recently established a sequencing method and bioinformatics pipeline for 16S rRNA gene analysis utilizing the Oxford Nanopore Technologies MinION™ sequencer. In combination with our taxonomy annotation analysis pipeline, the system enabled the molecular detection of bacterial DNA in a reasonable time frame for diagnostic purposes. However, purification of bacterial DNA from specimens remains a rate‐limiting step in the workflow. To further accelerate the process of sample preparation, we adopted a direct PCR strategy that amplifies 16S rRNA genes from bacterial cell suspensions without DNA purification. Our results indicate that differences in cell wall morphology significantly affect direct PCR efficiency and sequencing data. Notably, mechanical cell disruption preceding direct PCR was indispensable for obtaining an accurate representation of the specimen bacterial composition. Furthermore, 16S rRNA gene analysis of mock polymicrobial samples indicated that primer sequence optimization is required to avoid preferential detection of particular taxa and to cover a broad range of bacterial species. This study establishes a relatively simple workflow for rapid bacterial identification via MinION™ sequencing, which reduces the turnaround time from sample to result, and provides a reliable method that may be applicable to clinical settings.

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“…DNA sequence-based bacterial identification has relied almost exclusively on partial or complete 16S ribosomal RNA gene sequencing [38][39][40][41][42]. In spite of the ubiquitous use of 16S sequence data, the limitations of this approach are well established [43]. One of the first problems identified with this technique was the difficulty of primer design, necessitating attempts at creation of 'universal' primers, ideally capable of amplifying a portion of the 16S rRNA gene from any bacterial isolate [44].…”

Section: Comparison Of Identification Methodsmentioning

confidence: 99%

“…In practice, multiple primer pairs may sometimes need to be trialled to obtain successful amplification from any given isolate. Another issue relates to the limited resolution of the identification information provided by 16S rRNA gene sequencing [43]. The original rationale for the choice of the 16S rRNA gene for use in bacterial identification is based on the need for a balance between sequence conservation versus sequence diversity.…”

Section: Comparison Of Identification Methodsmentioning

confidence: 99%

Discovery of thermophilic Bacillales using reduced-representation genotyping for identification

Talamantes-Becerra

Carling²,

Kilian³

et al. 2020

BMC Microbiol

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Background: This study demonstrates the use of reduced-representation genotyping to provide preliminary identifications for thermophilic bacterial isolates. The approach combines restriction enzyme digestion and PCR with next-generation sequencing to provide thousands of short-read sequences from across the bacterial genomes. Isolates were obtained from compost, hot water systems, and artesian bores of the Great Artesian Basin. Genomic DNA was double-digested with two combinations of restriction enzymes followed by PCR amplification, using a commercial provider of DArTseq™, Diversity Arrays Technology Pty Ltd. (Canberra, Australia). The resulting fragments which formed a reduced-representation of approximately 2.3% of the genome were sequenced. The sequence tags obtained were aligned against all available RefSeq bacterial genome assemblies by BLASTn to identify the nearest reference genome. Results: Based on the preliminary identifications, a total of 99 bacterial isolates were identified to species level, from which 8 isolates were selected for whole-genome sequencing to assess the identification results. Novel species and strains were discovered within this set of isolates. The preliminary identifications obtained by reduced-representation genotyping, as well as identifications obtained by BLASTn alignment of the 16S rRNA gene sequence, were compared with those derived from the whole-genome sequence data, using the same RefSeq sequence database for the three methods. Identifications obtained with reduced-representation sequencing agreed with the identifications provided by whole-genome sequencing in 100% of cases. The identifications produced by BLASTn alignment of 16S rRNA gene sequence to the same database differed from those provided by whole-genome sequencing in 37.5% of cases, and produced ambiguous identifications in 50% of cases. Conclusions: Previously, this method has been successfully demonstrated for use in bacterial identification for medical microbiology. This study demonstrates the first successful use of DArTseq™ for preliminary identification of thermophilic bacterial isolates, providing results in complete agreement with those obtained from whole-genome sequencing of the same isolates. The growing database of bacterial genome sequences provides an excellent resource for alignment of reduced-representation sequence data for identification purposes, and as the available sequenced genomes continue to grow, the technique will become more effective.

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Comparison of two approaches for the classification of 16S rRNA gene sequences

Cited by 12 publications

References 21 publications

DNA barcoding of Clarias gariepinus, Coptodon zillii and Sarotherodon melanotheron from Southwestern Nigeria

DNA barcoding of Clarias gariepinus, Coptodon zillii and Sarotherodon melanotheron from Southwestern Nigeria

Rapid bacterial identification by direct PCR amplification of 16S rRNA genes using the MinION™ nanopore sequencer

Discovery of thermophilic Bacillales using reduced-representation genotyping for identification

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