Perú is the fifth most important rainbow trout farming country in the world, with Puno being the main regional exporter. The cultivation of fish from imported eggs, different culture conditions, as well as environmental variations can alter the diversity of the bacterial community causing the predominance of certain pathogens during some periods of the year. DNA metabarcoding is a tool that offers important advantages for rapid monitoring of bacterial communities, including the identification and tracking of those that are not easy to cultivate in the laboratory.
In this sense, the present study sought to identify pathogenic bacteria present in water bodies from three rainbow trout farms in three localities (Arapa, Lagunillas and Yunguyo) located in the Lake Titicaca basin (Puno). Water samples were collected and filtered (1 L) at different times of the year (rain in March and dry in September). For the identification of bacterial species, the analysis of the hypervariable region V1-V3 of gene RNAr 16S, was performed. The ASVs were obtained using QIIME2 pipeline with DADA2 package. The taxonomic assignment of the ASVs was performed using the sklearn classification method based on the latest SILVA r16S database. Rarefaction was performed to 10.000 reads. MEGAN metagenomic analysis platform allows the analysis of ASVs by performing the distribution at taxonomic levels, and taxonomic clustering analysis was performed (at the family level) using the Neighbor-Joining method. Pathogenic bacterial families were identified in the different sampling localities such as: Yersiniaceae in Yunguyo, Pseudomonadaceae in Lagunillas (during March), and Rickettsiaceae in Arapa (during rainy season and both seasons). This method is recommended for monitoring pathogens in fish farms, in order to contribute in improving cultures of rainbow trout.
Acknowledgment: This work was funded by PpR-2019 and 2022, Meta 03 Desarrollo Tecnológico, IMARPE, Ministerio de la Producción