ArticlemSystems2023
Informed interpretation of metagenomic data by StrainPhlAn enables strain retention analyses of the upper airway microbiome.
Article in mSystems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Gut microbiome in type 2 diabetes: insights from metagenomics, multi-omics, and diet-microbe interactions.Gut microbes · 2026Review
- The Unified Human Virome Database: A toolkit for expanded human virome analysis.bioRxiv : the preprint server for biology · 2026Article
- Microbial Ecological Signatures Predict Pathogen Emergence and Multidrug Resistance in Cystic Fibrosis Airways up to a Year in Advance.medRxiv : the preprint server for health sciences · 2026Article
- A model, mixed-species urinary catheter biofilm derived from spinal cord injury patients.Biofilm · 2025Article
- Optimizing synthetic cystic fibrosis sputum media for growth of non-typeable Haemophilus influenzae.Access microbiology · 2025Article
- Infection and the microbiome in bronchiectasis.European respiratory review : an official journal of the European Respiratory Society · 2024Review
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Authors and funding
9 authors.
Funding
Abstract
importanceThe usage of 16S rRNA gene sequencing has become the state-of-the-art method for the characterization of the microbiota in health and respiratory disease. The method is reliable for low biomass samples due to prior amplification of the 16S rRNA gene but has limitations as species and certainly strain identification is not possible. However, the usage of metagenomic tools for the analyses of microbiome data from low biomass samples is not straight forward, and careful optimization is needed. In this work, we show that by validating StrainPhlAn 3 results with the data from bacterial cultures, the strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA being present when parameters are carefully optimized to fit low biomass microbiomes. This work further proposes that strain retention analyses are feasible, at least for more abundant species. This will help to better understand the longitudinal dynamics of the upper respiratory microbiome during health and disease.
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