Insight into the nitrogen accumulation in urban center river from functional genes and bacterial community

Alteration of bacterial community composition in the sediments of an urban artificial river caused by sewage discharge

Background

Urbanization has an ecological and evolutionary effect on urban microorganisms. Microorganisms are fundamental to ecosystem functions, such as global biogeochemical cycles, biodegradation and biotransformation of pollutants, and restoration and maintenance of ecosystems. Changes in microbial communities can disrupt these essential processes, leading to imbalances within ecosystems. Studying the impact of human activities on urban microbes is critical to protecting the environment, human health, and overall urban sustainability.

Methods

In this study, bacterial communities in the sediments of an urban artificial river were profiled by sequencing the 16S rRNA V3-V4 region. The samples collected from the eastern side of the Jiusha River were designated as the JHE group and were marked by persistent urban sewage discharges. The samples collected on the western side of the Jiusha River were categorized as the JHW group for comparative analysis.

Results

The calculated alpha diversity indices indicated that the bacterial community in the JHW group exhibited greater species diversity and evenness than that of the JHE group. Proteobacteria was the most dominant phylum between the two groups, followed by Bacteroidota. The relative abundance of Proteobacteria and Bacteroidota accumulated in the JHE group was higher than in the JHW group. Therefore, the estimated biomarkers in the JHE group were divided evenly between Proteobacteria and Bacteroidota, whereas the biomarkers in the JHW group mainly belonged to Proteobacteria. The Sulfuricurvum, MND1, and Thiobacillus genus were the major contributors to differences between the two groups. In contrast to JHW, JHE exhibited higher enzyme abundances related to hydrolases, oxidoreductases, and transferases, along with a prevalence of pathways associated with carbohydrate, energy, and amino acid metabolisms. Our study highlights the impact of human-induced water pollution on microorganisms in urban environments.

A review of the formation conditions and assessment methods of black and odorous water

Black and odorous water is an extreme pollution phenomenon. This article reviews the formation process, formation conditions, and evaluation methods of black and odorous water. The results indicate that N, P, and TOC are the key nutrients inducing black and odorous water while S, Fe, and Mn are key elements forming blackening and odorizing pollutants. In addition, Cyanobacteria, Proteobacteria, Firmicutes, Verrucomicrobia, Planctomycetes, and Actinobacteria participate in the biogeochemistry cycles of key elements and play important roles in the blackening and odorizing process of water. The black and odorous thresholds that need further verification are as follows: 1.0 g/L of organic matrix, 2.0-8.0 mg/L of NH3-N, 0.6-1.2 mg/L of TP, 0.05 mg/L of Fe2+, 0.3 mg/L of Mn2+, 1.2-2.0 mg/L of DO, and -50 to 50 mV of the ORP. In order to propose a universal assessment method, it is suggested that NH3-N, DO, COD, BOD, and TP serve as the assessment indicators, and the levels of pollutions are I (not black odor), II (mild black odor), III (moderate black odor), IV (severe black odor), and inferior IV (extremely black odor).

The investigation of the physiochemical factors and bacterial communities indicates a low-toxic infectious risk of the Qiujiang River in Shanghai, China

The overall water quality of urban rivers is closely related to the community structure and the physiochemical factors in them. In this study, the bacterial communities and physiochemical factors of the Qiujiang River, an important urban river in Shanghai, were explored. Water samples were collected from nine sites of the Qiujiang River on November 16, 2020. The water quality and bacterial diversity were studied through physicochemical detection, microbial culture and identification, luminescence bacteria method, and 16S rRNA Illumina MiSeq high-throughput sequencing technology. The water pollution of the Qiujiang River was quite serious with three water quality evaluation indexes, including Cd²⁺, Pb²⁺, and NH₄⁺-N, exceeding the Class V standard set by the Environmental Quality Standards for Surface Water (China, GB3838-2002), while the luminescent bacteria test indicated low toxicity of nine sampling sites. Through 16S rRNA sequencing, a total of 45 phyla, 124 classes, and 963 genera were identified, in which Proteobacteria, Gammaproteobacteria, and Limnohabitans were the most abundant phylum, class, and genus, respectively. The Spearman correlation heatmap and redundancy analysis showed that the bacterial communities in the Qiujiang River were correlated with pH; the concentrations of K⁺, and NH₄⁺-N, and the Limnohabitans were significantly correlated with the concentrations of K⁺, and NH₄⁺-N in the Zhongyuan Road bridge segment. In addition, opportunistic pathogens Enterobacter cloacae complex and Klebsiella pneumoniae in the samples collected in the Zhongyuan Road bridge segment and Huangpu River segment, respectively, were successfully cultured. The Qiujiang River was a heavily polluted urban river. The bacterial community structure and diversity were greatly affected by the physiochemical factors of the Qiujiang River, and it displayed low toxicity while a relatively high infectious risk of intestinal and lung infectious diseases.

Unique microbiome in organic matter-polluted urban rivers

Approximately half of the global annual production of wastewater is released untreated into aquatic environments, which results in worldwide organic matter pollution in urban rivers, especially in highly populated developing countries. Nonetheless, information on microbial community assembly and assembly-driving processes in organic matter-polluted urban rivers remains elusive. In this study, a field study based on water and sediment samples collected from 200 organic matter-polluted urban rivers of 82 cities in China and Indonesia is combined with laboratory water-sediment column experiments. Our findings demonstrate a unique microbiome in these urban rivers. Among the community assembly-regulating factors, both organic matter and geographic conditions play major roles in determining prokaryotic and eukaryotic community assemblies, especially regarding the critical role of organic matter in regulating taxonomic composition. Using a dissimilarity-overlap approach, we found universality in the dynamics of water and sediment community assembly in organic matter-polluted urban rivers, which is distinctively different from patterns in eutrophic and oligotrophic waters. The prokaryotic and eukaryotic communities are dominated by deterministic and stochastic processes, respectively. Interestingly, water prokaryotic communities showed a three-phase cyclic succession of the community assembly process before, during, and after organic matter pollution. Our study provides the first large-scale and comprehensive insight into the prokaryotic and eukaryotic community assembly in organic matter-polluted urban rivers and supports their future sustainable management.

Deciphering the nitrate sources and processes in the Ganga river using dual isotopes of nitrate and Bayesian mixing model

The dual isotopes of dissolved NO₃- (n = 43) has been used to delineate the nitrate sources and N-cycling processes in the Ganga river. The proportional contribution of nitrate from different sources has been estimated using the Bayesian mixing model. The seasonal NO₃- concentration in the lower stretch of the river Ganga varied between 4.1 and 64.1 μM with higher concentration during monsoon and post-monsoon season and lower concentration during the pre-monsoon and winter season. The temporal variation in the isotopic values ranged between +0.0 and +9.6‰ for δ¹⁵N_NO3- and -1.2 to +11.0‰ for δ¹⁸O_NO3-. The spatial NO₃- concentration during the post-monsoon season varied between 23.2 and 57.7 μM, with higher values from the middle and lower values from the lower stretch of the river Ganga. The isotopic ratio during the post-monsoon season varied between -1.0 and +11.3‰ for δ¹⁵N_NO3- and -4.6 to +5.2‰ for δ¹⁸O_NO3-. The temporal dataset from the lower stretch of the river Ganga showed the dominance of nitrate derived from the nitrification of soil organic matter (SOM) (average ∼53.4%). The nitrate contribution from synthetic fertilizers was observed to be higher during the post-monsoon season (34.7 ± 23.4%) compared to that in the monsoon (25.5 ± 19.5%) and pre-monsoon (22.2 ± 19.6%) season. No significant seasonal variations were observed in the nitrate input from manure/sewage (∼13.9%). Spatial samples collected during the post-monsoon season showed higher contribution of synthetic fertilizer in the lower stretch (34.6 ± 22.7%) compared to the middle stretch (21.1 ± 18.2%), which indicates greater influence of the agricultural activity in the lower stretch. The dual isotope study of dissolved NO₃- established that the nitrate in the Ganga river water is mostly derived from the nitrification of incoming organic compounds and is subsequently removed via assimilatory nitrate uptake. The study also emphasises significant nitrification and assimilatory nitrate removal processes operating in the mixing zone of the Ganga river and Hooghly estuary.

Quantitative characterization and genetic diversity associated with N-cycle pathways in urban rivers with different remediation techniques

The nitrate reduction contributions of denitrification, anaerobic ammonium oxidation (anammox) and dissimilatory nitrate reduction to ammonium (DNRA) remain largely unknown especially in the context of river remediation. In this research, the quantitative differentiation of these three nitrate-reduction processes with different remediation conditions was done by the joint use of microbial analysis and nitrogen isotope-tracing. The experiments were done in simulated river systems with 100-day operations. The results of isotope-tracing showed that the respective N-removal contribution of denitrification was 85.88%-92.46% and 83.49%-84.73% in urban river with aeration and addition of Ca(NO₃)₂, whereas anammox became the same important (contribution of 49.35%-57.85%) with denitrification for nitrogen removal at a high C/N (Chemical oxygen demand/total nitrogen) ratio of 20. Besides, DNRA only occurred at a C/N ratio of 10 with high-level ammonium accumulation (11.20 ± 0.61 mg/L). Microbial analyses indicated that Ca(NO₃)₂ injection could promote not only the relative abundance of Proteobacteria (from 47.66% to 59.52%) but also the abundance of hzsB (from (4.66 ± 0.40) × 10⁴ copies·g^-1 to (2.66 ± 0.12) × 10⁵ copies·g^-1). Moreover, Ca(NO₃)₂ injection showed significantly positive correlation with Candidatus Jettenia of hzsB and Thiobacillus of all the denitrification functional genes including narG, norB, nosZ and nirS. The C/N ratio showed significantly positive correlation with Azoarcus of nirS (r = 0.941, p < 0.01) and Alloactinosynnema of hzsB (r = 0.941, p < 0.01). It was worth noting that Thiobacillus dominated in N-transformation processes, which underlined the need for the coupling of N transformation with other elements such as sulfur for better understanding and manipulating N cycling in urban rivers.

Sediments alleviate the inhibition effects of antibiotics on denitrification: Functional gene, microbial community, and antibiotic resistance gene analysis

Both antibiotics and sediments can affect the denitrification in aquatic systems. However, little is known how antibiotics influence the denitrification in the presence of sediments. Here, the effects of antibiotics (sulfamethoxazole, tetracycline and ofloxacin) on denitrification in the absence and presence of sediments were investigated. The influencing mechanisms were revealed by quantifying the denitrification functional genes (DNGs), 16S-seq of bacteria, and antibiotic resistance genes (ARGs). The results showed that the presence of antibiotics inhibited NO₃-N reduction by decreasing the abundances of narG, nirK, nosZ, total DNGs, and denitrifying bacteria. However, the inhibition effect was alleviated by sediments, which promoted the growth of bacteria and decreased the selective pressure of antibiotics as the vector of bacteria and antibiotics, thus increasing the abundances of denitrifying bacteria and all the DNGs. Partial least-squares path model disclosed that antibiotics had negative effects on bacteria, ARGs and DNGs, while sediments had negative effects on ARGs but positive effects on bacteria and DNGs. The network analysis further revealed the close relation of the genera Bacillus, Acinetobacter, and Enterobacter with the ARGs and DNGs. The findings are helpful to understand the denitrification in antibiotic-polluted natural waters.