Abstract

The Vibrio genus inhabit estuarine and marine ecosystem throughout the world and can cause severe infections in humans and animals. Previous studies have demonstrated the dynamics of Vibrio at both community and population levels and assessed the close relationship between environmental factors and Vibrio diversity and abundance, such as temperature, salinity, and dissolved oxygen. It is also generally believed that aquaculture is the fastest-growing food sector, which is also applying great environmental impacts on microbial communities in aquatic ecosystems. However, our understanding of the spatiotemporal quantification of Vibrio throughout the four seasons in the aquaculture zone and response to environmental factors remains poor. To explore the spatiotemporal distribution and abundance of the Vibrio community with their related environmental factors and detect the relationships among them, we collected 10 seawater sites spanning four seasons across the whole year in Dongshan Bay for investigating the Vibrio community dynamics. Marked differences in diversity and abundance of the Vibrio community were observed between seasons, which were mainly driven by temperature, dissolved oxygen, nitrate, and nitrite. qPCR analysis showed that Vibrio abundance was most abundant in the summer (5.37 × 106 copies/L), compared with the autumn (4.58 × 106 copies/L), spring (1.18 × 106 copies/L), and winter (1.55 × 104 copies/L). A total of 22 Vibrio operational taxonomic units (OTUs) and 28 species were identified by universal bacteria 16S rRNA gene and cultivation methods, with Vibrio fortis the dominant in these aquaculture areas. To summarize, our present study is one of the few studies to research the occurrence of Vibrio in marine aquaculture of South China, and the results indicate that Vibrio are widely distributed in aquaculture environment and that a further risk assessment is needed to be conducted.

Highlights

  • More than 47% of the global fish production are harvested from aquaculture, and China is the world’s largest producer of aquaculture-based foods, representing ca. 60% of global production; and marine aquaculture accounts for about 6% of our total domestic food supply (Food and Agriculture Organization of the United Nations [FAO], and The State of World Fisheries and Aquaculture [WFA], 2016)

  • Our clustering analysis of the normalized environmental parameters using the average cluster method indicated that the environmental variable clustering was strongly affected by seasonal pattern, with values taken in winter and spring distinctly different from those of the other two seasons (Supplementary Figure S1)

  • Our results suggest that a specific phylogenetic group, that is, Vibrio, can exhibit a clear spatial distribution pattern within the season, which is consistent with evidence by Dowle et al (2015) and Zeng et al (2019), who reported that total bacterial diversity changed with distance away from aquaculture zones

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Summary

Introduction

More than 47% of the global fish production are harvested from aquaculture, and China is the world’s largest producer of aquaculture-based foods, representing ca. 60% of global production; and marine aquaculture accounts for about 6% of our total domestic food supply (Food and Agriculture Organization of the United Nations [FAO], and The State of World Fisheries and Aquaculture [WFA], 2016). The genus Vibrio is a group of gram-negative rods belonging to the Gammaproteobacteria with facultative fermentative metabolisms. This genus is highly heterogeneous and has abundant members of native microbial assemblages in a great variety of aquatic environment (Thompson et al, 2004; Zhang X.H. et al, 2018). Most earlier studies on the Vibrio diversity are carried out by cultivation-dependent approaches (Baffone et al, 2006; Hsieh et al, 2008; Nigro et al, 2011; Amin et al, 2016; Kopprio et al, 2017; Wong et al, 2019). Due to the rapid development of high-throughput sequencing (HTS) technology, it offers potential solution to overcome the limitation of traditional cultivation-dependent approach

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