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