Introduction
Urban rivers and lakes are important to human culture, welfare, and development, but they have suffered from long-term serious pollution because of the various anthropogenic activities and discharge of untreated or coarsely treated wastewater from sewage treatment plants (Gücker et al., 2011). These pose a threat to the health of aquatic ecosystems and can change the physio-chemical environment and microbial community composition (Bradley, Emma, & Kelly, 2013). Pervious researches have demonstrated that the effluent discharge can lead to high nutrients pollution (nitrate, phosphate, and ammonium) and organic matter pollution (permanganate index, chemical oxygen demand, and suspended solids), which has an adverse effect on the functions of ecological community and aquatic ecosystems (Gücker, Brauns, & Pusch, 2009; Waiser, Tumber, & Holm, 2011). As an important part of urban river ecosystems, microbial communities play an irreplaceable role in participating in the biogeochemical processes and nutrient cycling (Azam, 1998; Lawrence, Swerhone, Wassenaar, & Neu, 2005) and are the ideal variables for monitoring the ecological impact of anthropogenic activities on the functional characteristics in river water environment.
In natural ecosystems, individual organisms do not exist in isolation, but coexist with each other to form a network of ecological interactions. These complex associations mediate the influence of biodiversity on ecosystem functions (Duffy, Cardinale, Mcintyre, Thebault, & Loreau, 2007). Microorganisms (such as, bacteria and microbial eukaryotes) are the important contributors to the biodiversity and can play important roles in the food web and biogeochemical cycle (Azam & Malfatti, 2007; Buchan, Lecleir, Gulvik, & Gonzalez, 2014). Microbial community structure is not only affected by interactions between species, but also by physicochemical parameters and regional conditions (Jones et al., 2013; Yannarell & Triplett, 2005). The co-occurrence patterns revealed based on metagenomic sequencing can predict the positive and negative ecological interactions between environmental variables and various species in aquatic ecosystems (Bunse et al., 2016). Network analysis can determine the keystone species that are necessary to maintain community stability among many species. Keystone species can affect the entire microbial community through a series of pathways. For example, they can affect the community structure and function through the adjustment of some intermediate groups and effect groups. Besides, keystone species also susceptible to dynamic environment, the disappearance or change of keystone species may cause disturbance to mature communities (Steele et al., 2011).
The microbial communities are composed of abundant taxa with high abundance and rare taxa with low abundance. Among them, the types of abundant taxa are few, and most of them are rare taxa (Logares et al., 2013). Abundant taxa are conductive to the organic matter flux and biomass yield (Pedrosalio, 2012), so the study of their community diversity is of great significance for deeply understanding ecological function. The emergence of rare species is due to an unfavorable environment, but when the environment becomes favorable, its abundance increases. Studies have shown that rare taxa can accelerate the degradation of organic matter, which is of great significance to the nutrition cycle (Pester, Bittner, Deevong, Wagner, & Loy, 2010). Indigenous rare taxa in environment can control the invasion of foreign microorganisms (such as certain foreign pathogens) (Mallon et al., 2015), these results indicated that rare microorganisms also play an irreplaceable role in the ecosystem. However, due to the limitation of methods, the previous community analysis mainly focused on relatively rich taxa through microscopic observation (Yu et al., 2014). Metagenomics are the research of collective microbial genomes recovered directly from environmental samples, which is independent on culture or prior knowledge of microbial communities (Rastogi & Sani, 2011). Metagenomics investigations have been performed in various environments (e.g., the ocean, soil, phyllosphere, and sediment), can provide the functional diversity and phylogenetic of uncultured microorganisms and identify the rare taxa (Jo, 2004).
The trend of microbial succession in time has been fully confirmed, but the formation mechanism of microbial temporal succession is still unclear. The main purpose of this study is to understand the formation and maintenance mechanism of microbial diversity (including abundance and composition). On this issue, the most mainstream views are microbial community construction is subject to a combination of deterministic processes (based on niche theory, including species interactions, environmental selection, etc.) and stochastic processes (based on neutral theory, including diffusion limitation, drift, etc.) (Stegen, Lin, Konopka, & Fredrickson, 2012). The complex interrelationship networks can reflect the inherent mechanism of microbial interaction on environmental interference (Hunt & Ward, 2015). On this basis, we could also explore the topological characteristics of these networks and identify the keystone species based on statistical analysis. Although a great deal of studies has been conducted on the interactions between abundant taxa (Chen, Chen, Xing, Li, & Wu, 2010; Ger et al., 2016), few studies has investigated how rare bacterial taxa and eukaryotic phytoplankton taxa affect the community structure of microorganisms in aquatic ecosystem. So far, co-occurrence patterns of rare taxa in urban rivers still has little attention. Therefore, identified key species in our study area were divided into abundant taxa and rare taxa. In this study, metagenome sequencing based on 16S and 18S rDNA genes were used to detect the seasonal pattern of bacterial and eukaryotic phytoplankton communities in an urban river, network analysis was used to identify keystone species necessary to maintain community stability, and discussed the relationship between these keystone species and ecological functions and environmental variables. Our research will help to understand the interactions and ecological functions of microorganisms in depth, and improve the ability to predict the response of microorganisms to environmental changes.
Materials and methods