ArticleScientific reports2023
Determining the most accurate 16S rRNA hypervariable region for taxonomic identification from respiratory samples.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.
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Who cites it
62 citing papers in PubMed, 2 syntheses or guidelines pooled it, 91 citations in OpenAlex.
- Oral Microbiota Characteristics in Relation to Different Dietary Patterns: A Systematic Review.Nutrients · 2026Pooled it
- From culture-based to 16S sequencing approaches: oral microbiota changes in aging, frailty, and oral hypofunction - a systematic review.BMC oral health · 2026Pooled it
- Acute inorganic nitrate ingestion does not impact oral microbial composition, cognitive function, or high-intensity exercise performance in female team-sport athletes.European journal of applied physiology · 2024Trial
- Multi-omics dissection of phyllospheric microbial succession and volatile flavor compound formation in cigar tobacco during fermentation.Journal of the science of food and agriculture · 2026Article
- Microbiomics: Novel Biomarkers of Colorectal Cancer Diagnosis and Prognosis.Diagnostics (Basel, Switzerland) · 2026Review
- Exploring the oral microbiome: from traditional techniques to advanced omics and databases.Antonie van Leeuwenhoek · 2026Review
- LEMMIv2: benchmarking framework for metagenomic and 16S amplicon profilers with a catalogue of evaluated tools.Genome biology · 2026Article
- Evaluating Sequencing Strategies for Endometrial Microbiome Profiling in Endometrial Cancer: A Comparative Study of Short- and Long-Read 16S rRNA Approaches.Cancer reports (Hoboken, N.J.) · 2026Article
- From soil to sequences: mechanisms and tools unravelling plant-rhizomicrobiome interactions.World journal of microbiology & biotechnology · 2026Review
- Optimizing primer selection for microbial diversity studies in freshwater lakes: a comprehensive evaluation of 16S rRNA, 18S rRNA, and ITS gene regions.FEMS microbiology ecology · 2026Article
- Longitudinal long-read microbiome profiling in a canine model reveals how age, diet, and birth mode shape gut community dynamics.mSystems · 2026Article
- Characterization of the Endometrial Microbiota of Healthy Mares Across the Estrous Cycle.Animals : an open access journal from MDPI · 2026Article
- Intratumoral microbiome signatures in a North Central Indian colorectal cancer cohort: identification of novel prognostic biomarkers and functional pathways.Scientific reports · 2026Article
- Distinct Limosilactobacillus reuteri microcapsule models: construction and therapeutic evaluation in DSS-induced colitis mice.NPJ science of food · 2026Article
- Toward reproducible pig gut microbiome profiling through standardized methodologies.ISME communications · 2026Article
- Evaluation of lactic acid ferment lysate for the management of oily skin: impact on sebum, hydration, and microbiota.Frontiers in physiology · 2026Article
- Large-scale characterisation of the nasal microbiome redefines Staphylococcus aureus colonisation status.Nature communications · 2025Article
- Alterations of the nasal and oral microbiota in multiple sclerosis.EBioMedicine · 2025Article
- Comparative analysis of illumina and oxford nanopore sequencing platforms for 16S rRNA profiling of respiratory microbial communities.Scientific reports · 2025Article
- Effects of Athletic Nutritional Supplements on the Human Gut Microbiota: A Narrative Review.Nutrients · 2025Review
2 more citing papers are in PubMed but not listed here.
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
16S rRNA gene profiling, which contains nine hypervariable regions (V1-V9), is the gold standard for identifying taxonomic units by high-throughput sequencing. Microbiome studies combine two or more region sequences (usually V3-V4) to increase the resolving power for identifying bacterial taxa. We compare the resolving powers of V1-V2, V3-V4, V5-V7, and V7-V9 to improve microbiome analyses in sputum samples from patients with chronic respiratory diseases. DNA were isolated from 33 human sputum samples, and libraries were created using a QIASeq screening panel intended for Illumina platforms (16S/ITS; Qiagen Hilden, Germany). The analysis included a mock community as a microbial standard control (ZymoBIOMICS). We used the Deblur algorithm to identify bacterial amplicon sequence variants (ASVs) at the genus level. Alpha diversity was significantly higher for V1-V2, V3-V4, and V5-V7 compared with V7-V9, and significant compositional dissimilarities in the V1-V2 and V7-V9 analyses versus the V3-V4 and V5-V7 analyses. A cladogram confirmed these compositional differences, with the latter two being very similar in composition. The combined hypervariable regions showed significant differences when discriminating between the relative abundances of bacterial genera. The area under the curve revealed that V1-V2 had the highest resolving power for accurately identifying respiratory bacterial taxa from sputum samples. Our study confirms that 16S rRNA hypervariable regions provide significant differences for taxonomic identification in sputum. Comparing the taxa of microbial community standard control with the taxa samples, V1-V2 combination exhibits the most sensitivity and specificity. Thus, while third generation full-length 16S rRNA sequencing platforms become more available, the V1-V2 hypervariable regions can be used for taxonomic identification in sputum.
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