Microbial community composition in urban riverbank sediments: response to municipal effluents over spatial gradient

Nowadays, the further development of urbanization and industrialization have caused an extreme shortage of water resources and led to the contamination of the major base flow of rivers in many regions by municipal and industrial wastewater effluent (Rice et al. 2013). Currently, China owns the world's largest municipal wastewater sector in terms of municipal wastewater treatment plants (WWTPs) (about 4,000) number and treatment capacity (7.4 × 10¹⁰ m³/year) (Lu et al. 2019). Although with the implementation of stringent discharge limits and remarkable achievements in wastewater treatment, the treated effluent still contains large nutrients and toxic pollutants. These pollutants release into natural water, which has non-negligible adverse impacts on the aquatic ecosystem. Numerous studies have indicated that the parameters of treated effluent are still above the limit, which can cause eutrophication (Berehanu et al. 2015) and ecotoxicity problems. The problems can change the diversity and richness of microbial communities (Chonova et al. 2016; Qiu et al. 2021), and further have negative consequences for global biogeochemical cycling (Grob et al. 2013).

Microorganisms are vital to biogeochemical cycles. Once environmental conditions change, microorganisms are extremely sensitive and respond quickly to changes (Wu et al. 2019; Wang et al. 2020a), thus can be a reliable indicator for monitoring the quality of rivers and sediment. Riverbanks, part of riverine systems, are scoured by river water, periodically submerged, and provide habitat for wildlife and microorganisms (Meier et al. 2005; Buckley et al. 2012). The nutrients, metals, and other harmful contaminants in rivers can be deposited and sorbed on riverbank sediments, thereby affecting the quality and microbial community in sediments (Johnston & Leff 2015; Lynch et al. 2018). Zhang et al. (2014a) found pollutant-resistant genera in the sea sediment of an industrial area. Johnston & Leff (2015) revealed that bacterial community compositions were strongly influenced by polycyclic aromatic hydrocarbon (PAH) concentrations in highly PAH-contaminated sites. A study reported that river water characterized by high sulphate concentrations can facilitate the existence of bacteria involved in sulphur cycles in river sediments (Martínez-Santos et al. 2018). Under long-term pollution, some microbial populations will prevail over others to change the structure and function of the community (Lors et al. 2010; Machado et al. 2012).

Up to now, many studies about the responses and variations of microbial communities in various environmental conditions were performed, like constructed wetlands (Zhang et al. 2021), WWTP effluents (Yu et al. 2020), activated sludge (Thomsen et al. 2010), and reservoir (Shi et al. 2020). While the study on microbial community in urban riverbank sediments influenced by municipal effluents has attracted the attention of researchers in recent years. In this study, we examined the sediments along the riverbank of the Macha River. Until now, these studies carried out on the Macha River mainly focused on the occurrence of organic matter (OM) (Zhang et al. 2014b). This study first focuses on the compositions of sediment bacterial communities along the riverbank of the Macha River.

The overall goal of this study is to describe the compositions of sediment bacterial communities in the municipal effluent-affected urban riverbank over the spatial gradient. The specific objectives include the following aspects: (1) measure the physiochemical parameters of sediments; (2) evaluate the bacterial community diversity and variation among sampling sites; and (3) assess the impact of environmental heterogeneity caused by anthropogenic activities on the biogeographic distribution of bacterial communities. The purpose of this study is to provide a further understanding of microbial ecology in contaminated riverbank sediments.

The Macha River (13.6 km long), an important flood diversion channel in the lower reaches of the Chu River, is located to the north of the Yangtze River, as well as is the main water source and sewage receiving water body of Luhe District, Nanjing, China. The effluents that come from industrial and domestic wastewater have been treated before discharging into the Macha River. According to the discharge standard of pollutants for municipal wastewater treatment plants in China (GB18918-2002), the residual effluent can still have adverse consequences for riverbank sediment quality.

Sediments were air-dried and ground to 100 mesh. Total nitrogen (TN) was determined by the semi-micro Kjeldahl method (Ran et al. 2016). Ammonia nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃^—N) were determined after 50 mL of KCl extraction using a spectrophotometer (UV-1800PC) (Mulvaney 1996). OM was measured by a colorimetric method developed by Bartlett and Ross (Bartlett & Ross 1988). Effective sulphur (ES) was quantified using ion chromatography (Dionex Ion Chromatograph Model ICS-1100, Dionex Corp., Sunnyvale, California) (Li et al. 2009). Electrical conductivity (EC) and sediment pH were measured in the dissolved solution with a ratio of sediment to ultrapure water (18.2 MΩ cm) of 1:5 (w/v) using an electric conductometer (CM-230) and a pH meter (PHS-3C), respectively. The above-mentioned measurements were performed in triplicate to count the mean value and standard deviation.

On arrival at the laboratory, the DNA samples of fresh sediment samples were extracted using Power soil™ DNA Isolation kit (Mobio Laboratories, Carlsbad, CA, USA) and carried out as described in Kowalchuk et al. (2003). The integrity of extracted DNA was checked on 1% agarose gel electrophoresis and placed at −80 °C until use. The primer pairs 338F (ACTCCTACGGGAGGCAGCAG) and 806R (GGACTACHVGGGTWTCTAAT) were used to amplify the V4 regions of bacterial 16S rRNA genes (Zhang et al. 2018), and the polymerase chain reaction (PCR) conditions were as follows: 3 min at 95 °C; 30 cycles for 30 s at 95 °C; 30 s at 55 °C, and a final extension of 72 °C for 45 s. Subsequently, the PCR products were sequenced by Guheinfo (Hangzhou, China). All 16S rRNA sequences were analyzed by QIIME for quality filtration, then the filtered sequences were clustered into bacterial operational taxonomic units (OTUs) with a 97% similarity cutoff by Mothur software. Sequences obtained in this study are deposited in National Omics Data Encyclopedia (NODE) database with the accession number OEP002636.

Rarefaction and Shannon–Winner curves were calculated by Mothur according to the clustered OTUs, which also could be utilized to determine the alpha diversity, like Chao 1, Shannon, Simpson, PD-Whole-Tree, and Good's coverage. Significant differences in the variance of parameters were evaluated with analysis of variance (ANOVA) or Kruskal–Wallis tests. The similarity between the sediment samples was measured by principle coordinate analysis (PcoA) based on Bray–Curtis distances. The heatmap was conducted by R software to reveal the composition of the community structure. Pearson correlation analysis for the relationships between physiochemical parameters and dominant genera was performed using SPSS software. Redundancy analysis (RDA) was used to reflect the relationship between environmental parameters and bacterial communities by means of the R software package.

The physicochemical properties of sediments over spatial gradient are summarized in Table 1. The TN ranged from 0.03 to 0.11%, and high contents were observed in the SU1, SM2, and SD1 sites. Meanwhile, the concentrations of NH₄⁺-N and NO₃^－-N in the above three sites were relatively high; sites SU1 and SD1 had the highest NO₃^－-N (0.69 ± 0.04 mg/kg) and NH₄⁺-N (85.9 ± 2.23 mg/kg) concentrations, respectively. The nitrogen level in sediments of Macha River is much lower than that of the Jialu River (Zhengzhou, China) with a TN of 0.21 ± 0.12%, NH₄⁺-N of 173.5 ± 105.4 mg/kg, and NO₃^－-N of 0.96 ± 0.26 mg/kg, which has been severely polluted by a variety of contaminant sources such as industrial and domestic wastewater, trade wastes, and untreated or lightly treated sewage wastes (Fu et al. 2014). As for the OM and ES, sites SM2 (OM = 2.16%, ES = 119.9 mg/kg) and SD1 (OM = 2.22%, ES = 62.7 mg/kg) had higher values than SU1 (OM = 1.37%, ES = 59.8 mg/kg), which may be attributed to the different sources of contamination at these sites. SU1 was mainly subjected to the effluent from a fish farm that discharged uneaten feed and fish excreta into the nearby river, and then led to the high concentrations of TN, NH4⁺-N, and NO₃^—N in the sediments, which is consistent with previous studies (Zivic et al. 2010; Huang et al. 2012). The EC in sediment of SM2 was 180.5 μS/cm and much higher than the average value of 116 μS/cm of all samples, and similarly, the interstitial water at SM2 had the highest TDS of 126.5 mg/L. This means the site had higher ionic concentrations, which may be due to strong anthropogenic activity (Das 2005). In addition, low concentrations of contaminants were observed in the rest sites SU2, SM1, and SW1, indicating the low pollution degree in these sites. That is because these three sites are relatively farther away from the origin points of effluent discharge and subjected to lower influence by effluents (Martínez-Santos et al. 2018). Macha River is the main flood diversion channel in the middle and lower reaches of the Chu River, the hydrodynamic process of seasonal flood could influence the physiochemical parameters of riverbank sediments by flushing the riverbank and transporting part of sediments to downstream (Tang et al. 2019). In addition, the pH of sediments was basically alkalescence (7.18–7.67), the temperature of interstitial water was in the range of 20.8–21.4 °C, and the salinity of interstitial water was 0.1 ppt. These basic parameters showed no obvious difference among sites.

In general, the physicochemical properties of sediments are impacted by complex interactions including periodic inundation, river hydrology, and anthropogenic pollution (Johnston & Leff 2015; Martínez-Santos et al. 2018).

At the genus level, a large proportion of OTUs was related to the known nitrifiers and denitrifiers (Figure 8). Nitrospira belongs to nitrifiers, and Anaeromyxobacter, GOUTA19, Gallionella, Dechloromonas, Geobacter, and Flavobacterium belong to denitrifiers. The genus Nitrospira, a kind of nitrite-oxidizing bacteria, was associated with nitrogen transformations (r = 0.814; p < 0.05) (Table 3). Previous study has shown that Nitrospira bacteria were capable of complete nitrification, i.e., the oxidation of ammonium and nitrite to nitrate directly (Daims et al. 2015). A high abundance of Nitrospira was found at sites SU1 and SU2 (Figure 8), and both sites were evidently influenced by the effluent from a fish farm, where nitrogen fertilizers were used to feed fish. This result matches a study that abundant Nitrospira was found in agricultural soil amended with nitrogen fertilizers (Li et al. 2019a). Qiu et al. (2021) found that NH₄⁺-N was negatively correlated with genus Nitrospira. Correlation analysis (Table 3) indicated that the genus Nitrospira was strongly and positively correlated with NO₃⁻-N (r = 0.814, p < 0.05), and which also demonstrated that Nitrospira might play an important role in ammonium removal. The genera 4-29 and Nitrospira were from the same order Nitrospirales. As shown in Table 3, the abundance of 4-29 was significantly positively correlated with ES (r = 0.856, p < 0.05), indicating that the presence of 4-29 may be related to the sulphur cycle.

It is well known that Geobacter is the clade of iron-reducing bacteria and is widely distributed in riverbank sediments. In the present study, according to the Pearson correlations analysis, the genus Geobacter was more positively related to NH₄⁺-N (r = 0.910, p < 0.01). Recently, more studies were reported that Geobacter could oxidize OM, participate in sulfite reduction and mediate the reduction of ammonium oxidation (Li et al. 2018, 2019b).

The genera GOUTA19 and Gallionella have been proven as a kind of microbes related to autotrophic denitrification (Wang et al. 2020b; Mai et al. 2021). GOUTA19 (from the family Thermodesulfovibrionaceae) has been observed in diverse conditions previously, such as alfalfa-rice rotation systems, oil-storage cavities and groundwater contaminated with diesel/biodiesel blends (Watanabe et al. 2002; Lopes et al. 2014). As mentioned above, Thermodesulfovibrionaceae as SRB was often observed in sulphate reduction process. Previous study has indicated that GOUTA19 might be responsible for the anaerobic biodegradation of benzene and naphthalene under iron and sulphate reduction (Müller et al. 2017). The high abundance of GOUTA19 (Figure 8) and the highest concentration of ES at site SM2 (Table 1), suggest the importance of sulphate to SRB in the sediments. In addition, a high abundance of GOUTA19 was observed at sites SU1 and SU2, which may be due to the relatively high concentrations of NO₃⁻-N. Studies have indicated that NO₃⁻-N not only serves as the essential nutrient for microbial physiological activities, but also acts as efficient electron acceptors which can oxidize sulfide to sulphate for the growth of SRB (Wang et al. 2018; Whw et al. 2019).

Dechloromonas as denitrifying bacteria can degrade various mono-aromatic compounds anaerobically. For example, Dechloromonas can mineralize benzene to carbon dioxide (CO₂) under anaerobic conditions with nitrate as an electron acceptor (Coates et al. 2001). A recent article has reported the ability of Dechloromonas to Sb(V) reduction and removal in the sediments (Yang et al. 2021). The abundance of Dechloromonas and Gallionella in sediment samples was significantly positively correlated with the NH₄⁺-N concentrations, and the corresponding r values were 0.821 (p < 0.05) and 0.943 (p < 0.01), respectively. Thus, the sites SM1 and SW1 with the lowest NH₄⁺-N concentrations did not detect the presence of Gallionella (Figure 8). Studies have indicated that ammonium or nitrate were nitrogen sources of Gallionella (Hallbeck et al. 1993). A lack of NH₄⁺-N would limit the growth of Gallionella.

Summing up the above, the contaminants discharged from different anthropogenic activities were the crucial factors shaping the bacterial community.

In conclusion, urban rivers are of prime importance to human survival and industrial development and are simultaneously subjected to human waste. The untreated and treated effluents containing nutrients and contaminants present negative consequences on river water and sediment quality and further shape the bacterial community compositions of aquatic ecosystems. We selected seven sites and measured the environmental variables, and the results displayed that the sediments immediately downstream of effluents were more influenced by wastewater, with higher bacterial abundance and biodiversity. Environmental factors, including NO₃⁻-N, NH₄⁺-N, ES, and OM are important in shaping the bacterial community. Nitrifiers (e.g., Nitrospira) and denitrifiers (e.g., Anaeromyxobacter) at the genus level seem to be predominant bacteria at those sites impacted by effluents, while the genus Serratia was the most dominant bacteria at the sites non-impacted by effluents. In sediment sites, the physiochemical parameters and bacterial community structures were spatially different and were closely related to the different effluents they received.

Preparation of sediment samples and DNA extraction were performed by Y.G. and Z.L. Microbial community analysis was performed by L.H. and J.F. The manuscript was written by J.F. and Y.L.. The corresponding author was Y.L.

This study was supported by the Fundamental Research Funds for the Central Universities (226-2023-00077), National Natural Science Foundation of China (91851110), and Foundation for Outstanding Young Scientific and Technological Innovation Teams of Colleges and Universities in Hubei Province (T2022053).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.