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Una base de datos completa de datos biológicos derivados de aguas residuales en cinco ciudades europeas
Ágnes Becsei1, Patrick Munk2, Alessandro Fuschi3
1Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Pázmány Péter stny. 1A, 1117 Budapest, Hungary.
Este estudio presenta un gran conjunto de datos longitudinal de metagenómica de aguas residuales de cinco ciudades europeas, que permite la vigilancia de patógenos y el análisis de comunidades microbianas. Los datos accesibles y la base de datos PostgreSQL promueven la reutilización y el descubrimiento de la investigación.
Área de la Ciencia:
- Environmental microbiology
- Genomics
- Public health
Sus antecedentes:
- Sewage metagenomics is crucial for pathogen surveillance and understanding microbial communities.
- Longitudinal datasets are essential for tracking dynamic changes in microbial populations.
- Existing datasets may lack comprehensive annotations or accessibility for reuse.
Objetivo del estudio:
- To create and share a highly curated, longitudinal sewage metagenomics dataset.
- To facilitate pathogen surveillance and microbial community analysis across European cities.
- To promote data reuse and advance research through an accessible resource.
Principales métodos:
- Collected 239 sewage samples from five European cities over time.
- Performed metagenomic sequencing and analyzed taxonomic profiles and antimicrobial resistance genes.
- Utilized qPCR for specific pathogen identification and Hi-C sequencing for genomic linkage.
Principales resultados:
- Generated a comprehensive dataset including taxonomic profiles, antimicrobial resistance genes, and assembled genomes.
- Developed a publicly available PostgreSQL database for efficient data exploration and querying.
- Provided annotated metagenome-assembled genomes and associated metadata.
Conclusiones:
- The presented dataset and database offer a valuable resource for sewage metagenomics research.
- This initiative supports proactive pathogen surveillance and microbial ecology studies.
- The data facilitates efficient access and reuse, accelerating scientific discovery.
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