Depth induced assembly discrepancy of multitrophic microbial communities affect microbial nitrogen transformation processes in river cross-sections

Temporal profiling of sediment microbial communities in the Three Gorges Reservoir Area discovered time-dissimilarity patterns and multiple stable states

Microbial communities play vital roles in cycling nutrients and maintaining water quality in aquatic ecosystems. To better understand the dynamics of microbial communities and to pave way to effective ecological remediation, it's essential to reveal the temporal patterns of the communities and to identify their states. However, research exploring the dynamic changes of microbial communities needs a large amount of time-series data, which could be an extravagant requirement for a single study. In this research, we overcame this challenge by conducting a meta-analysis of years of accumulations of 16S rRNA high-throughput sequencing data from the Three Gorges Reservoir Area (TGRA), an ecological and environmental hotspot. For better understanding the microbial communities time-dissimilarity dynamics, three microbial communities time-dissimilarity patterns were hypothesized, and the linear pattern in the TGRA was validated. In addition, to explore the stability of microbial communities in the TGRA, two alternative stable states were revealed, and their differences in community richness, alpha diversity indices, community composition, ecological network topological properties, and metabolic functions were demonstrated. In short, two states of microbial communities showed distinct richness and alpha diversity indices, and the communities in one state were more dominated by Halomonas and Nitrosopumilaceae genera, facilitating nitrogen cycling metabolic processes; whilst the main genera of the other state were Bathyarchaeia and Methanosaeta, which favored methane-related metabolism. Moreover, different studies and environmental differences between mainstream and tributaries were attributed as the potential inducing factors of the state division. Our study provides a comprehensive insight into the dynamics and stability of microbial communities in the TGRA, and a reference for future studies on microbial community dynamics.

Characteristics of groundwater microbial communities' structure under the impact of elevated nitrate concentrations in north China plain

In groundwater environments, the interaction between microbial communities and the hydrogeochemical parameters have been investigated extensively in the past years. However, little is known whether the maximum contamination level (MCL) is a threshold value that dictates the microbial composition. In this study, we analyzed 10 groundwater samples for their nitrate, nitrite, COD and sulfate concentrations, and characterized their microbial compositions using 16 S rRNA based high-throughput sequencing methods. All the 10 samples had oxygen demands higher than the corresponding MCL of China (10 mg L^-1); moreover, 4 out of 10 samples also had nitrate concentrations higher than the corresponding MCL, which indicated that the groundwater quality was negatively impacted by anthropogenic activities. Comparing the microbial composition of groundwater that had higher-than-MCL nitrate concentrations to those that had lower-than-MCL nitrate concentrations, no significant differences were detected in communities' richness and diversity. However, the non-metric multi-dimensional analysis suggested that the 4 groundwater samples whose nitrate concentration exceed MCL are distinctly different from those of the rest 6 samples, indicating that MCL does have a significant impact on microbial structures. Pearson's correlation analysis suggested that none of the four analyzed hydrochemical parameters had significant impact on microbial communities' richness and diversity; however, at the genus level, the correlation results suggested that JG30-KM-CM45, Sphingomonas and Rhodococcus are closely correlated with nitrate concentration. The findings of this study deepened our understanding with respect to the relationships between the environmental quality indices and the microbial compositions of groundwater.