ArticleFrontiers in microbiology2025
A species-level identification pipeline for human gut microbiota based on the V3-V4 regions of 16S rRNA.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence at the gut-oral microbiota frontier: mapping machine learning tools for gastric cancer risk prediction.Biomedical engineering online · 2025Pooled it
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- Hydroelectric Dam May Impact the Microbiome of an Endangered Northern Map Turtle (Graptemys geographica) Population.Current microbiology · 2026Article
- Network pharmacology, molecular docking, and in vivo experiments reveal the effects of Polygonati Rhizoma on periodontitis.Scientific reports · 2026Article
- Differences in the Biliary Microbiome Between Biliary Tract Cancer and Benign Biliary Disease.Microorganisms · 2026Article
- Pasture diversity and regenerative management shape ruminant gut microbiome dynamics within a real multi-year farming system.Frontiers in microbiology · 2026Article
- Beneficial bacteria-based bioformulations as potential biocontrol and biocleaning solutions for stone heritage conservation.World journal of microbiology & biotechnology · 2025Article
- Species-level enterosignatures predict clinical phenotypes in chronic hepatitis B and causal triangulation of gut-metabolite-CHB interactions.Frontiers in microbiology · 2025Article
- Species-level taxonomic characterization of gut microbiota in HIV-infected individuals.Frontiers in microbiology · 2025Article
- Alterations in gut microbiota and metabolomic profiles in acute stroke: insights into brain-gut axis dysregulation.Frontiers in microbiology · 2025Article
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12 authors.
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Abstract
16S rRNA gene sequencing is pivotal for identifying bacterial species in microbiome studies, especially using the V3-V4 hypervariable regions. A fixed 98.5% similarity threshold is often applied for species-level identification, but this approach can cause misclassification due to varying thresholds among species. To address this, our study integrated data from SILVA, NCBI, and LPSN databases, extracting V3-V4 region sequences and supplementing them with 16S rRNA sequences from 1,082 human gut samples. This resulted in a non-redundant amplicon sequence variants (ASVs) database specific to the V3-V4 regions (positions 341-806). Utilizing this database, we identified flexible classification thresholds for 674 families, 3,661 genera, and 15,735 species, finding clear thresholds for 87.09% of families and 98.38% of genera. For the 896 most common human gut species, we established precise taxonomic thresholds. To leverage these findings, we developed the asvtax pipeline, which applies flexible thresholds for more accurate taxonomic classification, notably improving the identification of new ASVs. The asvtax pipeline not only enhances the precision of species-level classification but also provides a robust framework for analyzing complex microbial communities, facilitating more reliable ecological and functional interpretations in microbiome research.
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