ArticleHeliyon2016
Significant loss of sensitivity and specificity in the taxonomic classification occurs when short 16S rRNA gene sequences are used.
Article in Heliyon, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- Associations of vaginal microbiota with the onset, severity, and type of symptoms of genitourinary syndrome of menopause in women.Frontiers in cellular and infection microbiology · 2024Trial
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- Vibrio proteolyticus DCF12.2 postbiotic modulates intestinal metabolic and immune pathways in zebrafish.Applied microbiology and biotechnology · 2026Article
- [Comparative analysis of microbial communities in different oral ecological niches of preschool children].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2026Article
- Oral Administration ofAnimals : an open access journal from MDPI · 2026Article
- Gut Microbiota and Nutritional Profiles of Colon Cancer Patients Undergoing Chemotherapy: A Longitudinal Pilot Study.Nutrients · 2026Article
- Multi-omics provides functional insights and underscores practical challenges in assessing the composition and performance of a nitrifying microbial consortium.Applied and environmental microbiology · 2026Article
- Profiling the bacteriome of a diet fed in meal or pelleted form, delivered as dry, wet/dry, or liquid feed and its impact on the fecal and intestinal bacteriome of grow-finisher pigs.Journal of animal science · 2026Article
- Characterization of fecal bacterial microbiomes according to fecal color, consistency, and sample type in piglets before and after weaning.Frontiers in veterinary science · 2026Article
- Short Read Lengths Recover Ecological Patterns in 16S rRNA Gene Amplicon Data.Molecular ecology resources · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- Unveiling the impact of 16S rRNA gene intergenomic variation on primer design and gut microbiome profiling.Frontiers in microbiology · 2025Article
- Enriching the future of public health microbiology with hybridization bait capture.Clinical microbiology reviews · 2024Review
- SpeciateIT and vSpeciateDB: novel, fast, and accurate per sequence 16S rRNA gene taxonomic classification of vaginal microbiota.BMC bioinformatics · 2024Article
- A comparison between full-length 16S rRNA Oxford nanopore sequencing and Illumina V3-V4 16S rRNA sequencing in head and neck cancer tissues.Archives of microbiology · 2024Article
- Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data.Genome biology and evolution · 2024Article
- SpeciateIT and vSpeciateDB: Novel, fast and accurate per sequence 16S rRNA gene taxonomic classification of vaginal microbiota.bioRxiv : the preprint server for biology · 2024Article
- Nanopore-based metagenomics analysis reveals microbial presence in amniotic fluid: A prospective study.Heliyon · 2024Article
- Microbial Community Profiling Protocol with Full-length 16S rRNA Sequences and Emu.Current protocols · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
The classification performance of Kraken was evaluated in terms of sensitivity and specificity when using short and long 16S rRNA sequences. A total of 440,738 sequences from bacteria with complete taxonomic classifications were downloaded from the high quality ribosomal RNA database SILVA. Amplicons produced (86,371 sequences; 1450 bp) by virtual PCR with primers covering the V1-V9 region of the 16S-rRNA gene were used as reference. Virtual PCŔs of internal fragments V3-V4, V4-V5 and V3-V5 were performed. A total of 81,523, 82,334 and 82,998 amplicons were obtained for regions V3-V4, V4-V5 and V3-V5 respectively. Differences in depth of taxonomic classification were detected among the internal fragments. For instance, sensitivity and specificity of sequences classified up to subspecies level were higher when the largest internal fraction (V3-V5) was used (54.0 and 74.6% respectively), compared to V3-V4 (45.1 and 66.7%) and V4-V5 (41.8 and 64.6%) fragments. Similar pattern was detected for sequences classified up to more superficial taxonomic categories (i.e. family, order, class…). Results also demonstrate that internal fragments lost specificity and some could be misclassified at the deepest taxonomic levels (i.e. species or subspecies). It is concluded that the larger V3-V5 fragment could be considered for massive high throughput sequencing reducing the loss of sensitivity and sensibility.
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