Mediterranean coasts are among the most urbanized in the world, and such habitat modification poses a great threat to the health and stability of marine ecosystems. To monitor the effects of ports and coastal defense structures on ecosystem health and biodiversity, we used a molecular approach to characterize marine microbial communities: metabarcoding. Water samples were collected from seven Italian coastal locations, and within each of them from three different points: inside the port, in a site with coastal defense structures, and in a natural one. Water was then filtered, and the DNA was extracted from the filters. The V4-V5 region of the 16S rRNA gene was then amplified from the extracted DNA and sequenced using high-throughput sequencing. Because of time constraints, the data analysis was performed on a dataset of raw sequencing data from a previous study. A bioinformatics pipeline was tested on this dataset to assess its functioning in future analyses. The pipeline involves the use of QIIME2 with the implement of cutadapt and DADA2 for the filtering and the denoising of the reads. The taxonomic assignment was performed using the SILVA database.
Metabarcoding: a molecular approach to explore the marine microbial community
GIRARDI, ANITA
2023/2024
Abstract
Mediterranean coasts are among the most urbanized in the world, and such habitat modification poses a great threat to the health and stability of marine ecosystems. To monitor the effects of ports and coastal defense structures on ecosystem health and biodiversity, we used a molecular approach to characterize marine microbial communities: metabarcoding. Water samples were collected from seven Italian coastal locations, and within each of them from three different points: inside the port, in a site with coastal defense structures, and in a natural one. Water was then filtered, and the DNA was extracted from the filters. The V4-V5 region of the 16S rRNA gene was then amplified from the extracted DNA and sequenced using high-throughput sequencing. Because of time constraints, the data analysis was performed on a dataset of raw sequencing data from a previous study. A bioinformatics pipeline was tested on this dataset to assess its functioning in future analyses. The pipeline involves the use of QIIME2 with the implement of cutadapt and DADA2 for the filtering and the denoising of the reads. The taxonomic assignment was performed using the SILVA database.File | Dimensione | Formato | |
---|---|---|---|
Girardi_Anita.pdf
accesso riservato
Dimensione
1.03 MB
Formato
Adobe PDF
|
1.03 MB | Adobe PDF |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/70536