School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand.
School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand.
Environ Pollut. 2020 Aug;263(Pt A):114438. doi: 10.1016/j.envpol.2020.114438. Epub 2020 Apr 3.
Marine coastal contamination caused by human activity is a major issue worldwide. The implementation of effective pollution monitoring programs, especially in coastal areas, is important and urgent. The use of biological, physiological, or biochemical measurements to monitor the impacts of pollution has garnered increasing interest, particularly for the development of new non-invasive tools to assess water pollution. Fish skin mucus is in direct contact with the marine environment, making it a favourable microenvironment for the formation of biofilm bacterial communities. In this study, we developed a non-invasive technique, sampling fish skin mucus to determine and analyse bacterial community composition using next-generation sequencing. We hypothesised that bacterial communities associated with the skin mucus of a common harbour benthic blennioid triplefin fish, Forsterygion capito, would reflect conditions of different marine environments. We detected clear differences in bacterial community alpha-diversity between contaminated and reference sites. Beta-diversity analysis also revealed differences in the bacterial community structure of the skin mucus of fish inhabiting different geographical areas. The relative abundance of different bacterial orders varied among sites, as determined by linear discriminant analysis (LDA) and effect size (LEfSe) analyses. The observed variation in bacterial community compositions correlated more strongly with variation in hydrocarbons than to various metal concentrations. Using advanced DNA sequencing technologies, we have developed a novel non-invasive, low-cost and effective tool to monitor the impacts of pollution through analysis of the bacterial communities associated with fish skin mucus.
人类活动导致的海洋沿海污染是一个全球性的主要问题。实施有效的污染监测计划，特别是在沿海地区，是重要和紧迫的。使用生物、生理或生化测量来监测污染的影响已经引起了越来越多的关注，特别是对于开发新的非侵入性工具来评估水污染。鱼类皮肤黏液与海洋环境直接接触，使其成为形成生物膜细菌群落的有利微环境。在这项研究中，我们开发了一种非侵入性技术，通过下一代测序从鱼类皮肤黏液中采样，以确定和分析细菌群落组成。我们假设与常见的港湾底栖三鳍鱼（Forsterygion capito）皮肤黏液相关的细菌群落将反映不同海洋环境的条件。我们检测到污染和参照点之间的细菌群落 α 多样性有明显差异。β 多样性分析还揭示了不同地理区域鱼类皮肤黏液中细菌群落结构的差异。通过线性判别分析（LDA）和效应大小（LEfSe）分析，确定不同细菌门的相对丰度在不同地点存在差异。观察到的细菌群落组成变化与碳氢化合物的变化比各种金属浓度的变化更密切相关。我们使用先进的 DNA 测序技术，开发了一种新的非侵入性、低成本和有效的工具，通过分析与鱼类皮肤黏液相关的细菌群落来监测污染的影响。
