ArticlePloS one2023
The selection of software and database for metagenomics sequence analysis impacts the outcome of microbial profiling and pathogen detection.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gut Microbiota Alterations Associated With Colonization by Multidrug-Resistant Organisms in ICU Patients: First Systematic Review and Meta-Analysis.MicrobiologyOpen · 2026Pooled it
- Reference Database Selection Influences Both Taxonomic Annotation and Ecological Inference in Arbuscular Mycorrhizal Fungal Communities.Journal of fungi (Basel, Switzerland) · 2026Article
- Benchmarking the impact of reference genome selection on taxonomic profiling accuracy.BMC genomics · 2026Article
- Exploring sagebrush leaf microbial metagenomes from deep, host-derived sequencing.Microbiology spectrum · 2026Article
- Insights Into Sequences of Viral and Bacterial Origin in the Metatranscriptome of Centaurea cyanus L. Susceptible and Resistant to Acetolactate Synthase (ALS)-Inhibiting Herbicides.Environmental microbiology reports · 2026Article
- HYMET: a hybrid metagenomic pipeline for accurate and efficient taxonomic classification.GigaScience · 2026Article
- Assessing sequencing-based pathogen surveillance of a recreational swimming area in Oslo, Norway.Access microbiology · 2026Article
- Integrative analysis across metagenomic taxonomic classifiers: A case study of the gut microbiome in aging and longevity in the Integrative Longevity Omics Study.PLoS computational biology · 2026Article
- Advances and emerging technologies in the diagnosis of viral infections in pigs: Progress, challenges, and One Health perspectives.Veterinary world · 2025Review
- Comparative evaluation of MG-RAST, MEGAN6 and Kraken2 for whole metagenome analysis of saffron corms for bacterial community structure and function.Molecular genetics and genomics : MGG · 2025Article
- Computational Metagenomics: State of the Art.International journal of molecular sciences · 2025Review
- Article
- Wastewater Metavirome Diversity: Exploring Replicate Inconsistencies and Bioinformatic Tool Disparities.International journal of environmental research and public health · 2025Article
- Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification.mSystems · 2025Article
- Aerospace Mutagenized Tea Tree Increases Rhizospheric Microorganisms, Enhances Nutrient Conversion Capacity and Promotes Growth.Plants (Basel, Switzerland) · 2025Article
- Impact of simulation and reference catalogues on the evaluation of taxonomic profiling pipelines.Microbial genomics · 2025Article
- Effect of microbial diversity and their functions on soil nutrient cycling in the rhizosphere zone of Dahongpao mother tree and cutting Dahongpao.Frontiers in plant science · 2025Article
- Taxonize-gb: A tool for filtering GenBank non-redundant databases based on taxonomy.bioRxiv : the preprint server for biology · 2024Article
- Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes.Frontiers in microbiology · 2024Article
Corrections and comments
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Shotgun metagenomic sequencing analysis is widely used for microbial profiling of biological specimens and pathogen detection. However, very little is known about the technical biases caused by the choice of analysis software and databases on the biological specimen. In this study, we evaluated different direct read shotgun metagenomics taxonomic profiling software to characterize the microbial compositions of simulated mice gut microbiome samples and of biological samples collected from wild rodents across multiple taxonomic levels. Using ten of the most widely used metagenomics software and four different databases, we demonstrated that obtaining an accurate species-level microbial profile using the current direct read metagenomics profiling software is still a challenging task. We also showed that the discrepancies in results when different databases and software were used could lead to significant variations in the distinct microbial taxa classified, in the characterizations of the microbial communities, and in the differentially abundant taxa identified. Differences in database contents and read profiling algorithms are the main contributors for these discrepancies. The inclusion of host genomes and of genomes of the interested taxa in the databases is important for increasing the accuracy of profiling. Our analysis also showed that software included in this study differed in their ability to detect the presence of Leptospira, a major zoonotic pathogen of one health importance, especially at the species level resolution. We concluded that using different databases and software combinations can result in confounding biological conclusions in microbial profiling. Our study warrants that software and database selection must be based on the purpose of the study.
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