Spatiotemporal variation of bacterial communities in three cascade reservoirs in a southern city of China

Reservoirs are important water sources of urban drinking water supply. Bacteria play an important role in the removal of organics in reservoirs, but some of them can pose a health risk to consumers. Knowledge of bacterial community composition in drinking water sources can favour the drinking water security safeguards. This study investigated the monthly composition and diversity of bacterial communities in three cascade reservoirs using high-throughput Illumina HiSeq sequencing over one hydrological year. The diversity and structure of the bacterial community showed distinct spatiotemporal variation. Mycobacterium , Acinetobacter , Sphingomonas , Sphingobacterium and Pseudomonas were the genera resistant to chlorine. In addition, Acinetobacter , Arcobacter , Mycobacterium , Pseudomonas and Staphylococcus were the main potential pathogenic genera. The bacterial community diversity and the average relative abundance of potential pathogenic genera detected in the wet season were higher than those in the dry season. Water temperature was found to be the main factor for the temporal variation. The spatial variation of bacterial community diversity and the average relative abundance of potential pathogenic genera were related to water current and the degree of water pollution, respectively. The results of this study can conduce the bene ﬁ cial management of drinking water treatment processes.


GRAPHICAL ABSTRACT INTRODUCTION
Reservoirs are important water sources of urban drinking water supply in China (Yang et al. ), especially for the southern city (subtropical area) in the present study, whose source water is almost completely from cascade reservoirs.  (Chen et al. ). However, it is regrettable that most of those studies only involved one drinking water source and/or were conducted once, which did not reflect the spatiotemporal variation of the bacterial community. Only a few studies investigated the potential pathogenic bacteria, which not only pose a threat to human health, but may also cause pipe corrosion if they enter the distribution system. Moreover, even though the influence factors on composition and diversity of bacterial In this study, a series of water samples were collected on a monthly basis from a group of three cascade reservoirs in a southern city in China over the course of a whole hydrological year. The bacterial communities, potential pathogenic bacteria and their relationships with water characteristics were investigated. Furthermore, the spatiotemporal variations in community diversity, potential pathogenic bacteria and the influencing factors were determined. The results of this study can contribute to the drinking water security safeguards, and can provide a reference for other cascade reservoirs used as drinking water sources in the subtropical area.

Sample collection and physico-chemical analysis
The three cascade reservoirs (YT, SZ and SY) are the major drinking water sources for a southern city of China (subtropical area), and they provide a daily raw water supply of 3,600,000 m 3 for drinking water treatment plants and serve almost seven million people. Their raw water originates from the Dongjiang River, which is a branch of the Pearl River.
The raw water flows into three cascade reservoirs (YT-SZ-SY) through pumps and pipelines (Figure 1). Their basic information is provided in Table S1. In this study, 36 water samples were collected from the water intakes for the water  permanganate method, COD Mn ) were analyzed according to standard protocols (APHA ).

Molecular analyses
DNA was extracted using the cetyl trimethyl ammonium bromide (CTAB) method (Shan et al. ), and then the purity and concentration of DNA were determined by agarose gel electrophoresis. Appropriate samples were placed in a centrifuge tube and diluted with sterile water to 1 ng/μL.
Using the diluted genomic DNA as the template, specific primers with Barcode, Phusion ® high-fidelity polymerase chain reaction (PCR) Master Mix with GC Buffer from New England Biolabs, and high-efficiency high-fidelity enzyme were used for the PCR according to the selection of sequencing region to ensure the efficiency and accuracy of amplification. The primers used to identify bacterial diversity were those in the 16S V4 region (515F and 806R). In addition, PCR products were determined by 2% agarose gel electrophoresis. According to the concentration of PCR products, the samples were mixed with equal amount. After the samples were thoroughly mixed, the PCR products were detected by 2% agarose gel electrophoresis, and the products were recovered by the gel recovery kit provided by Qiagen. Lastly, the TruSeq ® DNA PCR-free Sample Preparation Kit was used for library construction. The constructed library was quantified by Qubit and Q-PCR.
After the library was qualified, HiSeq2500 PE250 was used for computer sequencing.

Sequence processing and data analysis
According to Barcode sequence and PCR amplified primer sequence, the sample data were separated from the computer data. After cutting Barcode sequence and primer sequence, FLASH was used to splice reads of each sample

Bacterial community diversity
In this study, based on 16S rRNA sequencing analysis by Furthermore, as shown in Figure 2, the means for these parameters of the three water sample groups followed a spatial trend in the order of YT > SZ > SY. All the results indicated spatiotemporal variation occurred in the three cascade reservoirs.

Bacterial community composition
In this study, 20-34 bacterial phyla, 43-76 bacterial classes, 80-142 bacterial orders, 140-253 bacterial families and 179-419 bacterial genera were identified in the 36 water samples (Table S3). Figure    Acinetobacter were present in water samples YT5 and SY4, while Acinetobacter was also abundant in water sample SY5. Dechloromonas, a member of Betaproteobacteria, only predominated in water sample YT2. In addition, Sphingomonas, which is affiliated to Alphaproteobacteria, was numerous in water sample SZ5.

Chryseobacterium and Sphingobacterium pertain to
Bacteroidetes were plentiful in water sample SY5, and Chryseobacterium was also in a relatively high proportion in water sample SY4. Acinetobacter, Sphingomonas, Sphingobacterium and Pseudomonas are resistant to chlorine (Sun et al. ), and their relatively high abundance may create difficulty in achieving drinking water safety criterion. Furthermore, it is noted that Acinetobacter, Pseudomonas and Arcobacter are potential pathogenic bacteria.

Potential pathogenic bacteria
In order to further assess the potential pathogenic risk in the three cascade reservoirs, the potential pathogenic bacteria were analyzed by comparing the genera with the known potential pathogenic genera (WHO ; Ye & Zhang ). Twenty potential pathogenic genera were found (Table S4, Table S5 and Table S6). Although potential pathogenic genera were in low abundances, most of them prevailed in all the water samples. Acinetobacter, Arcobacter, Mycobacterium, Pseudomonas and Staphylococcus, whose relative abundances were more than 1% in at least one sample, were the main potential pathogenic genera.
Besides Acinetobacter and Pseudomonas, Mycobacterium is also resistant to chlorine (Simões & Simões ; Lin et al. ). In particular, the average relative abundances of potential pathogenic genera detected in the wet season (6.89% of YT, 5.65% of SZ and 10.69% of SY) were higher than those in the dry season (4.34% of YT, 3.10% of SZ and 2.54% of SY) ( Figure S2). The average relative abundances of potential pathogenic genera detected in the three cascade reservoirs followed an apparent spatial trend in the order of SY (6.62%) > YT (5.61%) > SZ (4.37%) ( Figure S3).

Relationship between the bacterial community and
water characteristics SPSS 19.0 software was used to analyze Pearson's correlation of the bacterial community indices, the relative abundance of Proteobacteria and the sum of relative abundance of potential pathogenic genera with the water characteristics (shown in Table S7). As shown in Table 1, water temperature showed prominent positive correlation with OTUs (P < 0.01), Shannon (P < 0.05), Chao1 (P < 0.01), Proteobacteria (P < 0.05) and potential pathogenic genera (P < 0.05). There were also significant positive relationships between potential pathogenic genera and turbidity and COD Mn (both P < 0.05).

Temporal variations
The average bacterial community diversity and relative abundance of Proteobacteria and potential pathogenic genera showed obvious temporal variation, with a higher average diversity and relative abundance in the wet season compared to the dry season (Table S2, Figure 3 and Figure S2). Such temporal variation was thought related to the water temperature in the reservoirs because a higher temperature within a certain range is favourable for microbial growth. It has been reported that bacterial community composition experienced notable alternation with a shift of wet and dry seasons in subtropical water bodies (Araújo & Leal ; Yu et al. ). In the studied city, the wet season covers April to September, during which water temperature in the reservoirs was 27.56 ± 1.06 C (Table S7). The dry season runs from October to March the following year, during which water temperature in the reservoirs was 21.61 ± 3.25 C (Table S7). Detailed examination revealed that the values of OTUs, Shannon and Chao1, and the relative abundance of Proteobacteria and the sum of relative abundance of potential pathogenic genera correlated positively with water temperature (Table 1). In the practices of the drinking water plants with the three reservoirs as the water sources, sequential chlorination and chlorine dioxide disinfection have been used to deal with the risk of microbial outbreaks in the wet season (Qie & Zhang ).
The sum of relative abundance of potential pathogenic genera was also observed to be correlated with turbidity (Table 1). It might be because turbidity can provide a habitat and shielding for potential pathogenic bacteria. Previous studies have shown turbidity is closely related to potential pathogenic bacteria abundance in waters (Huey & Meyer ), and the abundances of particle-associated and freeliving microbial communities were reportedly proportional to turbidity (Dang & Lovell ). Turbidity is hence listed as a microbiological indicator in the Safe Drinking Water Act in United States (United States Environmental Protection Agency ). In the present study, the average turbidity in the wet season was higher than that in the dry season in the three reservoirs. This trend was consistent with the temporal variation of potential pathogenic genera.  operation showed that the turbidity in the finished water remained below 0.1 NTU, and the total plate count was almost undetected (no more than 10 colony forming units/ mL) (Zhang & Liu ).

Spatial variations
For the bacterial communtiy composition, Proteobacteria was the most dominant bacterial phylum in most of the water samples collected from the three reservoirs (Figure 3).
This is a common observation in many drinking water sources, such as reservoir water ( (Table S7). Reservoir YT, as a diversion reservoir, receives water from the Dongjiang River, whose water quality conformed to the requirement of

Potential pathogenic bacteria
Potential pathogenic bacteria were analyzed in detail to assess whether control measures in the drinking treatment plants were adequate and whether more safeguards should be taken to guarantee drinking water safety. In this study, even though not in high abundances, 20 potential pathogenic genera were detected in the three reservoirs (Table S4, Table S5 and Table S6). The main potential pathogenic genera included Acinetobacter, Arcobacter, Mycobacterium, Pseudomonas and Staphylococcus, and detected. The bacterial community diversity and the average relative abundance of potential pathogenic genera were higher in the wet season than in the dry season, and water temperature was the major factor leading to the temporal variation. They also showed distinct spatial variations in the three cascade reservoirs. The spatial variation of bacterial community diversity was found to be related to water current, and the potential pathogenic genera was influenced by the degree of water pollution.
Water turbidity and COD Mn were found to be the dominant factors relating to the average relative abundance of potential pathogenic genera.
In order to secure the bacterial safety of drinking water, necessary measures, such as the removal of turbidity and COD Mn , should be carried out as soon as possible. There should also be further studies on inactivation of potential pathogenic bacteria.