The generic term “Gill disease” refers to a wide range of disorders that affect the gills and severely impact salmonid aquaculture systems worldwide. In rainbow trout freshwater aquaculture, various etiological agents causing gill diseases have been described, particularly Flavobacterium and Amoeba species, but research studies suggest a more complex and multifactorial aetiology. Here, a cohort of rainbow trout affected by gill disease is monitored both through standard laboratory techniques and 16S rRNA Next-Generation Sequencing (NGS) analysis during a natural disease outbreak and subsequent antibiotic treatment with Oxytetracycline. NGS results show a clear clustering of the samples between pre- and post-treatment based on the microbial community of the gills. Interestingly, the three main pathogenic bacteria species in rainbow trout (Yersinia ruckeri, Flavobacterium psychrophilum, and Flavobacterium branchiophilum) appear to be weak descriptors of the diversity between pre-treatment and post-treatment groups. In this study, the dynamics of the gill microbiome during the outbreak and subsequent treatment are far more complex than previously reported in the literature, and environmental factors seem of the utmost importance in determining gill disease. These findings present a potential novel perspective on the diagnosis and management of gill diseases, showing the limitations of conventional laboratory methodologies in elucidating the complexity of this disease in rainbow trout. To the authors’ knowledge, this work is the first to describe the microbiome of rainbow trout gills during a natural outbreak and subsequent antibiotic treatment. The results of this study suggest that NGS can play a critical role in the analysis and comprehension of gill pathology. Using NGS in future research is highly recommended to gain deeper insights into such diseases correlating gill’s microbiome with other possible cofactors and establish strong prevention guidelines.
Novel insights on microbiome dynamics during a gill disease outbreak in farmed rainbow trout (Oncorhynchus mykiss)
Orioles M.;Marroni F.;Radovic S.;Galeotti M.;
2024-01-01
Abstract
The generic term “Gill disease” refers to a wide range of disorders that affect the gills and severely impact salmonid aquaculture systems worldwide. In rainbow trout freshwater aquaculture, various etiological agents causing gill diseases have been described, particularly Flavobacterium and Amoeba species, but research studies suggest a more complex and multifactorial aetiology. Here, a cohort of rainbow trout affected by gill disease is monitored both through standard laboratory techniques and 16S rRNA Next-Generation Sequencing (NGS) analysis during a natural disease outbreak and subsequent antibiotic treatment with Oxytetracycline. NGS results show a clear clustering of the samples between pre- and post-treatment based on the microbial community of the gills. Interestingly, the three main pathogenic bacteria species in rainbow trout (Yersinia ruckeri, Flavobacterium psychrophilum, and Flavobacterium branchiophilum) appear to be weak descriptors of the diversity between pre-treatment and post-treatment groups. In this study, the dynamics of the gill microbiome during the outbreak and subsequent treatment are far more complex than previously reported in the literature, and environmental factors seem of the utmost importance in determining gill disease. These findings present a potential novel perspective on the diagnosis and management of gill diseases, showing the limitations of conventional laboratory methodologies in elucidating the complexity of this disease in rainbow trout. To the authors’ knowledge, this work is the first to describe the microbiome of rainbow trout gills during a natural outbreak and subsequent antibiotic treatment. The results of this study suggest that NGS can play a critical role in the analysis and comprehension of gill pathology. Using NGS in future research is highly recommended to gain deeper insights into such diseases correlating gill’s microbiome with other possible cofactors and establish strong prevention guidelines.File | Dimensione | Formato | |
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