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Updated: Dec 4, 2025

Characterization of a Pathogenic Escherichia coli Strain Derived from Oreochromis spp. Farms Using Whole-Genome Sequencing
Published on: December 23, 2022
High-quality genome sequence assembly of R.A73 Enterococcus faecium isolated from freshwater fish mucus
Rim El Jeni1,2, Kais Ghedira3, Monia El Bour1
1Laboratory of Microbiology and Pathology of Aquatic Organisms, Institut National des Sciences et Technologies de la Mer (INSTM), Tunis, Tunisia.
Background:
Whole-genome sequencing using high throughput technologies has revolutionized and speeded up the scientific investigation of bacterial genetics, biochemistry, and molecular biology. Lactic acid bacteria (LABs) have been extensively used in fermentation and more recently as probiotics in food products that promote health. Genome sequencing and functional genomics investigations of LABs varieties provide rapid and important information about their diversity and their evolution, revealing a significant molecular basis. This study investigated the whole genome sequences of the Enterococcus faecium strain (HG937697), isolated from the mucus of freshwater fish in Tunisian dams. Genomic DNA was extracted using the Quick-GDNA kit and sequenced using the Illumina HiSeq2500 system. Sequences quality assessment was performed using FastQC software. The complete genome annotation was carried out with the Rapid Annotation using Subsystem Technology (RAST) web server then NCBI PGAAP.
Results:
The Enterococcus faecium R.A73 assembled in 28 contigs consisting of 2,935,283 bps. The genome annotation revealed 2884 genes in total including 2834 coding sequences and 50 RNAs containing 3 rRNAs (one rRNA 16 s, one rRNA 23 s and one rRNA 5 s) and 47 tRNAs. Twenty-two genes implicated in bacteriocin production are identified within the Enterococcus faecium R.A73 strain.
Conclusion:
Data obtained provide insights to further investigate the effective strategy for testing this Enterococcus faecium R.A73 strain in the industrial manufacturing process. Studying their metabolism with bioinformatics tools represents the future challenge and contribution to improving the utilization of the multi-purpose bacteria in food.

