Australian Institute of Marine Science, Townsville, QLD, Australia.
College of Science and Engineering, James Cook University, Townsville, QLD, Australia.
Microbiome. 2019 Jun 21;7(1):94. doi: 10.1186/s40168-019-0705-7.
Coral reefs are facing unprecedented pressure on local and global scales. Sensitive and rapid markers for ecosystem stress are urgently needed to underpin effective management and restoration strategies. Although the fundamental contribution of microbes to the stability and functioning of coral reefs is widely recognised, it remains unclear how different reef microbiomes respond to environmental perturbations and whether microbiomes are sensitive enough to predict environmental anomalies that can lead to ecosystem stress. However, the lack of coral reef microbial baselines hinders our ability to study the link between shifts in microbiomes and ecosystem stress. In this study, we established a comprehensive microbial reference database for selected Great Barrier Reef sites to assess the diagnostic value of multiple free-living and host-associated reef microbiomes to infer the environmental state of coral reef ecosystems.
A comprehensive microbial reference database, originating from multiple coral reef microbiomes (i.e. seawater, sediment, corals, sponges and macroalgae), was generated by 16S rRNA gene sequencing for 381 samples collected over the course of 16 months. By coupling this database to environmental parameters, we showed that the seawater microbiome has the greatest diagnostic value to infer shifts in the surrounding reef environment. In fact, 56% of the observed compositional variation in the microbiome was explained by environmental parameters, and temporal successions in the seawater microbiome were characterised by uniform community assembly patterns. Host-associated microbiomes, in contrast, were five-times less responsive to the environment and their community assembly patterns were generally less uniform. By applying a suite of indicator value and machine learning approaches, we further showed that seawater microbial community data provide an accurate prediction of temperature and eutrophication state (i.e. chlorophyll concentration and turbidity).
Our results reveal that free-living microbial communities have a high potential to infer environmental parameters due to their environmental sensitivity and predictability. This highlights the diagnostic value of microorganisms and illustrates how long-term coral reef monitoring initiatives could be enhanced by incorporating assessments of microbial communities in seawater. We therefore recommend timely integration of microbial sampling into current coral reef monitoring initiatives.
珊瑚礁正面临着前所未有的地方和全球范围内的压力。迫切需要敏感和快速的生态系统压力标志物,以支持有效的管理和恢复策略。尽管微生物对珊瑚礁的稳定性和功能的基本贡献已被广泛认可,但仍不清楚不同的珊瑚礁微生物组对环境扰动的反应如何,以及微生物组是否足够敏感,以预测可能导致生态系统压力的环境异常。然而,珊瑚礁微生物基线的缺乏阻碍了我们研究微生物组变化与生态系统压力之间联系的能力。在这项研究中,我们为选定的大堡礁地点建立了一个全面的微生物参考数据库,以评估多种自由生活和宿主相关的珊瑚礁微生物组推断珊瑚礁生态系统环境状态的诊断价值。
通过对 16 个月内采集的 381 个样本进行 16S rRNA 基因测序,生成了一个源自多种珊瑚礁微生物组(即海水、沉积物、珊瑚、海绵和大型藻类)的综合微生物参考数据库。通过将该数据库与环境参数相结合,我们表明海水微生物组具有最大的诊断价值,可以推断周围珊瑚礁环境的变化。事实上,微生物组观察到的组成变化中有 56%可以用环境参数来解释,并且海水微生物组的时间演替特征是一致的群落组装模式。相比之下,宿主相关微生物组对环境的响应要低五倍,其群落组装模式通常不太一致。通过应用一系列指示值和机器学习方法,我们进一步表明,海水微生物群落数据可以准确预测温度和富营养化状态(即叶绿素浓度和浊度)。
我们的结果表明,由于自由生活微生物群落对环境的敏感性和可预测性,它们具有推断环境参数的高潜力。这突出了微生物的诊断价值,并说明了如何通过将海水微生物群落的评估纳入当前的珊瑚礁监测计划,来增强长期的珊瑚礁监测计划。因此,我们建议及时将微生物采样纳入当前的珊瑚礁监测计划中。