Sparus aurata and Lates calcarifer skin microbiota under healthy and diseased conditions in UV and non-UV treated water

Abstract

Background The welfare of farmed fish is influenced by numerous environmental and management factors. Fish skin is an important site for immunity and a major route by which infections are acquired. The objective of this study was to characterize bacterial composition variability on skin of healthy, diseased, and recovered Gilthead Seabream (Sparus aurata) and Barramundi (Lates calcarifer). S. aurata, which are highly sensitive to gram-negative bacteria, were challenged with Vibrio harveyi. In addition, and to provide a wider range of infections, both fish species (S. aurata and L. calcarifer) were infected with gram-positive Streptococcus iniae, to compare the response of the highly sensitive L. calcarifer to that of the more resistant S. aurata. All experiments also compared microbial communities found on skin of fish reared in UV (a general practice used in aquaculture) and non-UV treated water tanks. Results Skin swab samples were taken from different areas of the fish (lateral lines, abdomen and gills) prior to controlled infection, and 24, 48 and 72 h, 5 days, one week and one-month post-infection. Fish skin microbial communities were determined using Illumina iSeq100 16S rDNA for bacterial sequencing. The results showed that naturally present bacterial composition is similar on all sampled fish skin sites prior to infection, but the controlled infections (T1 24 h post infection) altered the bacterial communities found on fish skin. Moreover, when the naturally occurring skin microbiota did not quickly recover, fish mortality was common following T1 (24 h post infection). We further confirmed the differences in bacterial communities found on skin and in the water of fish reared in non-UV and UV treated water under healthy and diseased conditions. Conclusions Our experimental findings shed light on the fish skin microbiota in relation to fish survival (in diseased and healthy conditions). The results can be harnessed to provide management tools for commercial fish farmers; predicting and preventing fish diseases can increase fish health, welfare, and enhance commercial fish yields.