Dynamics of microbial diversity profiles in waters of different qualities. Approximation to an ecological quality indicator

Wastewater discharges alter microbial community composition in surface waters of the canadian prairies

Microbial communities are an important component of freshwater biodiversity that is threatened by anthropogenic impacts. Wastewater discharges pose a particular concern by being major sources of anthropogenic contaminants and microorganisms that may influence the composition of natural microbial communities. Nevertheless, the effects of wastewater treatment plant (WWTP) effluents on microbial communities remain largely unexplored. In this study, the effects of wastewater discharges on microbial communities from five different WWTPs in Southern Saskatchewan were investigated using rRNA gene metabarcoding. In parallel, nutrient levels and the presence of environmentally relevant organic pollutants were analyzed. Higher nutrient loads and pollutant concentrations resulted in significant changes in microbial community composition. The greatest changes were observed in Wascana Creek (Regina), which was found to be heavily polluted by wastewater discharges. Several taxa occurred in greater relative abundance in the wastewater-influenced stream segments, indicating anthropogenic pollution and eutrophication, especially taxa belonging to Proteobacteria, Bacteroidota, and Chlorophyta. Strong decreases were measured within the taxa Ciliphora, Diatomea, Dinoflagellata, Nematozoa, Ochrophyta, Protalveolata, and Rotifera. Across all sample types, a significant decline in sulfur bacteria was measured, implying changes in functional biodiversity. In addition, downstream of the Regina WWTP, an increase in cyanotoxins was detected which was correlated with a significant change in cyanobacterial community composition. Overall, these data suggest a causal relationship between anthropogenic pollution and changes in microbial communities, possibly reflecting an impairment of ecosystem health.

Next-Generation High-Throughput Sequencing to Evaluate Bacterial Communities in Freshwater Ecosystem in Hydroelectric Reservoirs

The quality of aquatic ecosystems is a major public health concern. The assessment and management of a freshwater system and the ecological monitoring of microorganisms that are present in it can provide indicators of the environment and water quality to protect human and animal health. with bacteria is. It is a major challenge to monitor the microbiological bacterial contamination status of surface water associated with anthropogenic activities within rivers and freshwater reservoirs. Understanding the composition of aquatic microbial communities can be beneficial for the early detection of pathogens, improving our knowledge of their ecological niches, and characterizing the assemblages of microbiota responsible for the degradation of contaminants and microbial substrates. The present study aimed to characterize the bacterial microbiota of water samples collected alongside the Madeira River and its small tributaries in rural areas near the Santo Antonio Energia hydroelectric power plant (SAE) reservoir in the municipality of Porto Velho, Rondonia state, Western Brazil. An Illumina 16s rRNA metagenomic approach was employed and the physicochemical characteristics of the water sample were assessed. We hypothesized that both water metagenomics and physicochemical parameters would vary across sampling sites. The most abundant genera found in the study were Acinetobacter, Deinococcus, and Pseudomonas. PERMANOVA and ANCOM analysis revealed that collection points sampled at the G4 location presented a significantly different microbiome compared to any other group, with the Chlamidomonadaceae family and Enhydrobacter genus being significantly more abundant. Our findings support the use of metagenomics to assess water quality standards for the protection of human and animal health in this microgeographic region.

Predicting bend-induced heterogeneity in sediment microbial communities by integrating bacteria-based index of biotic integrity and supervised learning algorithms

Prioritizing the relationship between heterogeneity of sediment habitats and river bends is critical when planning and reconstructing urban rivers. However, the exact relationship between ecological heterogeneity and river bends remains ambiguous. Therefore, this research proposed a new approach to quantify and predict bend-induced ecological heterogeneity, incorporating the bacteria-based index of biotic integrity (Ba-IBI), path model, and random forest regression model. The developed Ba-IBI quantified heterogeneity in sediment microbial communities, ranging from low (1.40) to high (3.97). A path model was developed and validated in order to further investigate the relative contributions of environmental factors to the Ba-IBI. The established path model, which was considered acceptable with a CMIN/df = 1.949 < 4, suggested that primary environmental factors affecting the sediment bacterial communities were flow velocity and ammonium concentration in sediment. To further characterize the relationship between environmental factors and the Ba-IBI, a function was constructed using the random forest regression model that predicts the responses of sediment bacterial communities to environmental factors with R² = 0.6126. The proposed approach and prediction tools will provide knowledge to improve natural channel design and post-project evaluations in river restoration projects.

Exploring the allochthonous pollution influence on bacterial community and co-occurrence dynamics of River Ganga water through 16S rRNA-tagged amplicon metagenome

River Ganga is one of the largest and most sacred rivers of India. This river is largely affected by anthropogenic activities causing significant increase in water pollution. The impact of drains discharging polluted water on the bacterial community dynamics in the river remains unexplored. To elucidate this, the targeted 16S rRNA V3-V4 variable region amplicon sequencing and bioinformatic analysis were performed using water from upstream, drain, and downstream of river Ganga. Analysis revealed significant difference in relative abundances of bacterial communities. The increase in bacterial abundance and alpha diversity was detected in the downstream compared to the upstream. Environmental factors were found significantly different between upstream and downstream water. At the phyla level, highly abundant taxa such as Proteobacteria, Actinobacteria, Planctomycetes, Bacteroidetes, and Verrucomicrobia were observed. Bacterial genera like Prevotella, Bacteroides, Blautia, and Faecalibacterium (fecal indicator) had higher abundance in the downstream site. Network co-occurrence revealed that bacterial communities have a modular profile with reduced interaction in drain and downstream water. The network of co-occurring bacterial communities consists of 283 nodes with edge connectivity of 6900, 7074, and 5294 in upstream, drain, and downstream samples, respectively. Upstream communities exhibited the highest positive interaction followed by the drain and the downstream sites. Additionally, highly abundant pathogenic species such as Acinetobacter baumannii and Prevotella copri were also detected in all samples. This study suggests the drain to be allochthonous pollution vector that significantly contributes to bacterial community enrichment. From the results of this study, it is apparent that the lotic water may be used as the ecological reference to understand and monitor the variations in the bacterial communities and their co-occurrence dynamics in the fresh water ecosystems.

Expanding ecological assessment by integrating microorganisms into routine freshwater biomonitoring

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.

Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast

High-throughput sequencing of microbial assemblages has been proposed as an alternative methodology to the traditional ones used in marine monitoring and environmental assessment. Here, we evaluated pico- and nanoplankton diversity as ecological indicators in NW Mediterranean coastal waters by comparing their diversity in samples subjected to varying degrees of continental pressures. Using metabarcoding of the 16S and 18S rRNA genes, we explored whether alphadiversity indices, abundance of Operational Taxonomic Units and taxonomic groups (and their ratios) provide information on the ecological quality of coastal waters. Our results revealed that only eukaryotic diversity metrics and a limited number of prokaryotic and eukaryotic taxa displayed potential in assessing continental influences in our surveyed area, resulting thus in a restrained potential of microbial plankton diversity as an ecological indicator. Therefore, incorporating microbial plankton diversity in environmental assessment could not always result in a significant improvement of current marine monitoring strategies.

Groundwater microbial diversity and antibiotic resistance linked to human population density in Yucatan Peninsula, Mexico

Microbial community composition in selected karst groundwater sites in the Yucatan Peninsula, Mexico, was assessed to determine the environmental variables influencing groundwater microbial diversity. The karst aquifer system is a groundwater-dependent ecosystem and is the world’s second largest underwater karst cave system. The area’s geology allows precipitation to infiltrate into the groundwater system and prevents accumulation of surface water; as such, groundwater is the only source of fresh water on the peninsula. The sampling locations consisted of three karst sinkholes that extend through the freshwater zone into the saline water, and an abandoned drinking water well of an ocean-side resort, during the dry and rainy seasons. The analysis showed that highly diverse microbial communities are present in the Yucatan groundwater, sustained by permanently warm temperatures and high nutrient input from human activity. Proximity to densely populated areas, such as tourist resorts, is the most important factor influencing both the diversity and presence of fecal bacteria and the antibiotic resistance profile.

Development of microbial community-based index of biotic integrity to evaluate the wetland ecosystem health in Suzhou, China

The development of microbial community-based biological indicators for assessing aquatic ecological status is urgently needed in heavily impaired regions, due to the local extinction of traditional indicator macro-organisms. The aim of this study was to develop and validate a microbial community-based index of biotic integrity (MC-IBI) to assess the health of wetlands in Suzhou, China. High-throughput sequencing was used to obtain information about microbial communities in wetlands and to investigate the health of the wetlands. When constructing the index, we selected what we considered were the most important environmental factors and biological parameters, and identified sensitive and tolerant species. We then used the index to evaluate the health of the inflows and outflows of 15 wetlands in Suzhou. The results showed that, of the 30 samples collected at the 10 impacted inflow sites, 2 were classified as "poor," 5 were "commonly," 18 were sub-healthy, and 5 were healthy; at the restored outflow sites, 24 were "healthy" and 6 were "sub-healthy." The health was worst at the inflows of wetlands that received agricultural effluent, followed by those that received industrial effluent, and was best at those that received urban effluent. The results from our study show that this newly developed MC-IBI gave reasonable evaluations of the health of wetland ecosystems. This application demonstrates that the evaluation system was feasible and we suggest that evaluations that further MC-IBI evaluation approaches should be developed further in the future.

Reduction of bacterial integrity associated with dam construction: A quantitative assessment using an index of biotic integrity improved by stability analysis

Rivers are extensively regulated by damming, yet the effects of such interruption on bacterial communities have not been assessed quantitatively. To fill this gap, we proposed a bacteria-based index of biotic integrity (Ba-IBI) by using bacterial community dataset collected from the Three Gorges Reservoir and its upper reaches. Stability analysis based on bacterial resistance (RS) and resilience (RL) to external disturbance was conducted to improve the performance of the index. Four core metrics, i.e. the ratio of Bacilli, Bacteroidetes and Clostridia to Alphaproteobacteria (BBC/A), Oxalobacteraceae, Methanotrophs and Thermophiles were selected after range, responsive and redundancy tests. The improved Ba-IBI, ranging from 1.04 to 4.10, was better at distinguishing sites with or without direct dam effects compared with the unimproved one. The index values maintained high in the riverine sites while reducing in the reservoir, demonstrating the negative influence of dam construction on bacterial integrity. Based on the assessment results, 23.1%, 46.2% and 30.8% sampling sites were large, moderately and little affected by damming, respectively. A Random Forest (RF) regression model was trained and tested, offering a valid prediction of the input Ba-IBI and environmental parameters. Sensitivity analysis revealed the significant contributions of flow velocity towards the predicting process performance, indicating the importance of hydrodynamic conditions on determining the spatial variability of bacterial communities. This study provides not only a first quantitative insight for assessing bacterial response to damming, but also a guideline for applying the improved index in the dam regulation and ecological protection.

Fungal Community as a Bioindicator to Reflect Anthropogenic Activities in a River Ecosystem

The fungal community interacts with the ambient environment and can be used as a bioindicator to reflect anthropogenic activities in aquatic ecosystems. Several studies have investigated the impact of anthropogenic activities on the fungal community and found that community diversity and composition are influenced by such activities. Here we combined chemical analysis of water properties and sequencing of fungal internal transcribed spacer regions to explore the relationship between water quality indices and fungal community diversity and composition in three river ecosystem areas along a gradient of anthropogenic disturbance (i.e., less-disturbed mountainous area, wastewater-discharge urban area, and pesticide and fertilizer used agricultural area). Results revealed that the level of anthropogenic activity was strongly correlated to water quality and mycoplankton community. The increase in organic carbon and nitrogen concentrations in water improved the relative abundance of Schizosaccharomyces, which could be used as a potential biomarker to reflect pollutant and nutrient discharge. We further applied a biofilm reactor using water from the three areas as influent to investigate the differences in fungal communities in the formed biofilms. Different community compositions were observed among the three areas, with the dominant fungal phyla in the biofilms found to be more sensitive to seasonal effects than those found in water. Finally, we determined whether the fungal community could recover following water quality restoration. Our biofilm reactor assay revealed that the recovery of fungal community would occur but need a long period of time. Thus, this study highlights the importance of preserving the original natural aquatic ecosystem.

Analysis of Bacterial Community Characteristics, Abundance of Antibiotics and Antibiotic Resistance Genes Along a Pollution Gradient of Ba River in Xi'an, China

The microbial communities in freshwater have raised concerns about the ecosystem and human health. Many ecological environmental problems have been found in urban river because of the unreasonable use and long-term wastewater discharge. In this study, we explored the bacterial community composition, abundance of 14 antibiotics and 21 antibiotic resistance genes (ARGs), and water environment features in seven water samples and seven sediment samples from Ba River in Xi'an, China. Results showed Proteobacteria and Bacteroidetes were the dominant phyla in all samples, and sediment samples had a higher bacterial diversity and richness than it in water. Bacterial communities of site 5 and 6 were clustered in discrepant patterns compared to those at remaining sites from other samples. It might be influenced by nutrients, heavy metals and antibiotics. Antibiotics concentrations ranged from 1.26 to 1.61 × 10³ ng L^-1 in water samples and 1.55 to 4.05 × 10² μg kg^-1 in sediment samples. Sulfamerazine (SM1) and erythromycin (ERY) were the chief antibiotics in water samples, while the level of oxytetracycline (OTC) and cefazolin (CFZ) were higher in sediment samples. Canonical correspondence analysis showed that trimethoprim (TMP) was significantly related to Acinetobacter in W6, and that SM1 and OTC had positive correlation with Arcobacter in W5. The tetC, bla_{TEM ,} ermF and sul1 had higher pollution abundance ranging from 10^-4 to 10⁰ copies/16S rRNA gene copies in all samples. Significant correlations were observed between ARGs and matching antibiotics, suggesting that antibiotics can pose the selective pressure on ARGs in this river. In summary, these finding might provide some new data to the limited information available on the bacterial community characteristics, abundance of antibiotics and ARGs in urban river of China.

Aquatic Bacterial Communities Associated With Land Use and Environmental Factors in Agricultural Landscapes Using a Metabarcoding Approach

This study applied a 16S rRNA gene metabarcoding approach to characterize bacterial community compositional and functional attributes for surface water samples collected within, primarily, agriculturally dominated watersheds in Ontario and Québec, Canada. Compositional heterogeneity was best explained by stream order, season, and watercourse discharge. Generally, community diversity was higher at agriculturally dominated lower order streams, compared to larger stream order systems such as small to large rivers. However, during times of lower relative water flow and cumulative 2-day rainfall, modestly higher relative diversity was found in the larger watercourses. Bacterial community assemblages were more sensitive to environmental/land use changes in the smaller watercourses, relative to small-to-large river systems, where the proximity of the sampled water column to bacteria reservoirs in the sediments and adjacent terrestrial environment was greater. Stream discharge was the environmental variable most significantly correlated (all positive) with bacterial functional groups, such as C/N cycling and plant pathogens. Comparison of the community structural similarity via network analyses helped to discriminate sources of bacteria in freshwater derived from, for example, wastewater treatment plant effluent and intensity and type of agricultural land uses (e.g., intensive swine production vs. dairy dominated cash/livestock cropping systems). When using metabarcoding approaches, bacterial community composition and coexisting pattern rather than individual taxonomic lineages, were better indicators of environmental/land use conditions (e.g., upstream land use) and bacterial sources in watershed settings. Overall, monitoring changes and differences in aquatic microbial communities at regional and local watershed scales has promise for enhancing environmental footprinting and for better understanding nutrient cycling and ecological function of aquatic systems impacted by a multitude of stressors and land uses.

Integrating microbial biomass, composition and function to discern the level of anthropogenic activity in a river ecosystem

Anthropogenic activities (e.g., wastewater discharge and pesticide and fertilizer use) have considerable impact on the biotic properties of natural aquatic ecosystems, especially the microbial community and function. Microbes can respond to anthropogenic activities and are thus potential indicators of activity levels. Several reports have documented the impacts of anthropogenic activities on the variations in the microbial community, but the direct use of microbial community indices to discern anthropogenic activity levels remains limited. Here, we integrated flow cytometry, 16S rRNA sequencing, and natural organic matter metabolism determination to investigate microbial biomass, composition, and function in three areas along a gradient of anthropogenic disturbance (less-disturbed mountainous area, wastewater-discharge urban area, and pesticide and fertilizer used agricultural area) in a river ecosystem. Multiple statistical methods were used to explore the causal relationships between changes in environmental factors and microbial variation. Results showed that anthropogenic activities (e.g., wastewater discharge, pesticide and fertilizer use) facilitated bacterial production, affected dominant species distribution, and accelerated natural organic matter (NOM) metabolic rate by microbes. After screening the possible factors influencing the microbial community, we determined that cyanobacterial concentration could be a diagnostic indicator of nutrient levels. We also developed a NOM metabolic index to quantitatively reflect the holistic influence of nutrients and xenobiotics.

The impact of wastewater treatment effluent on microbial biomasses and diversities in coastal sediment microcosms of Hangzhou Bay

Disposal of wastewater treatment plant (WWTP) effluent into sea, a typical anthropogenic disturbance, may influence many environmental factors and change the coastal microbial community structure. In this study, by setting up coastal sediment microcosms perturbed by WWTP effluent, the changes of microbial community structure under different degree of disturbances were investigated. Quantitative PCR (qPCR) and terminal restriction fragment length polymorphism (T-RFLP) were used to analyzed the biomass and biodiversity. High throughput sequencing analysis was used to identify the classification of the microorganisms. Our study suggested that low ratio of WWTP effluent may stimulate dominant species, which increase the biomass but decrease the biodiversity; while high ratio of WWTP effluent may depress all species, which decrease the biomass but increase the biodiversity. In other words, the impact was dose-dependent. The changes of microbial community structure may provide a metric for water environmental assessment and pollution control.

Characterization of microbial communities in wetland mesocosms receiving caffeine-enriched wastewater

A 454 high-throughput pyrosequencing approach was used to characterize the structures of microbial communities in wetland mesocosms receiving caffeine-enriched wastewater at a concentration of 250 μg L(-1). The removal efficiencies of caffeine in the planted beds (93.0 %) were significantly (p < 0.05) higher than those in the unplanted beds (81.4 %). Bacterial diversity was decreased by 25 and 22.4 %, respectively, in both planted and unplanted mesocosms after 210-day operation. The results of taxonomic analyses suggested that chronic exposure of wetland ecosystems to caffeine could lead to moderate shifts in microbial community composition. In total, 2156 operational taxonomic units (OTUs) were generated and 20 phyla comprising 260 genera were identified. The major phylogenetic groups at phylum level included Firmicutes (39 %), Actinobacteria (25.1 %), Proteobacteria (17.1 %), Synergistetes (5.6 %), and Chloroflexi (5.5 %). Bacilli and Synergistia increased in abundance in the planted mesocosms, while for the unplanted mesocosms, Actinobacterial, Clostridia and Betaproteobacteria exhibited increased proportion under the exposure of caffeine. At genus level, Propionibacterium, Staphylococcus, Bacillus, and Streptococcus were found to be increased in abundance after caffeine treatment. As for the response of fungal community to caffeine enrichment, genus like Cladosporium, Emericellopsis, Aspergillus, and Phoma were found to be resistant to caffeine disturbance. When compared to the microbial community between planted and unplanted mesocosms, a distinct community profile for both bacteria and fungi community was observed. The presence of plants had a remarkable effect on the structure of microbial community, helping buffer against the stress associated with caffeine exposure.

Ibuprofen removal in horizontal subsurface flow constructed wetlands: treatment performance and fungal community dynamics

The treatment performance of ibuprofen (IBP)-enriched wastewater by horizontal subsurface flow constructed wetlands planted with cattail (Typha angustifolia) and unplanted control mesocosms was investigated. Removal efficiencies of IBP were significantly (p < .05) enhanced in the planted mesocosms (78.5%) compared to those in the unplanted beds (57.9%). An 18S rRNA gene high-throughput pyrosequencing approach was used to investigate the effects of IBP on the structure of the fungal community in these wetland systems. The overall diversity of the fungal community was reduced under the IBP exposure. Taxonomic analysis revealed that 62.2% of the fungal sequences were affiliated with Basidiomycota, followed by Ascomycota (37.4%) at the phylum level. Uncultured fungus (48.2%), Chaetomium sp. (14.2%), Aspergillus sp. (12.4%), Trichoderma sp. (5.7%), Cladosporium sp. (5.4%), and Emericellopsis sp. (5.2%) were identified as dominant genera. At the genus level, a distinct profile of the fungal community in the IBP-enriched mesocosms was observed as compared to the control beds, and as well specific fungal genera were enhanced in the planted beds, regardless of IBP enrichment. However, despite these differences, the composition of the fungal community (as measured by Bray-Curtis similarity) was mostly unaffected by the significant IBP enrichment. On the other hand, a consistent similarity pattern of fungal community structure in the planted mesocosms suggests that the presence of higher macrophytes in the wetland systems may well help shape the fungal community structure.

Year-Long Metagenomic Study of River Microbiomes Across Land Use and Water Quality

Select bacteria, such as Escherichia coli or coliforms, have been widely used as sentinels of low water quality; however, there are concerns regarding their predictive accuracy for the protection of human and environmental health. To develop improved monitoring systems, a greater understanding of bacterial community structure, function, and variability across time is required in the context of different pollution types, such as agricultural and urban contamination. Here, we present a year-long survey of free-living bacterial DNA collected from seven sites along rivers in three watersheds with varying land use in Southwestern Canada. This is the first study to examine the bacterial metagenome in flowing freshwater (lotic) environments over such a time span, providing an opportunity to describe bacterial community variability as a function of land use and environmental conditions. Characteristics of the metagenomic data, such as sequence composition and average genome size (AGS), vary with sampling site, environmental conditions, and water chemistry. For example, AGS was correlated with hours of daylight in the agricultural watershed and, across the agriculturally and urban-affected sites, k-mer composition clustering corresponded to nutrient concentrations. In addition to indicating a community shift, this change in AGS has implications in terms of the normalization strategies required, and considerations surrounding such strategies in general are discussed. When comparing abundances of gene functional groups between high- and low-quality water samples collected from an agricultural area, the latter had a higher abundance of nutrient metabolism and bacteriophage groups, possibly reflecting an increase in agricultural runoff. This work presents a valuable dataset representing a year of monthly sampling across watersheds and an analysis targeted at establishing a foundational understanding of how bacterial lotic communities vary across time and land use. The results provide important context for future studies, including further analyses of watershed ecosystem health, and the identification and development of biomarkers for improved water quality monitoring systems.

Bacterial communities of Beijing surface waters as revealed by 454 pyrosequencing of the 16S rRNA gene

As a better understanding of Beijing surface water ecosystems can provide clues for environmental management and public health, here, we report a study of the bacterial communities of five Beijing surface waters conducted using 454 pyrosequencing of 16S ribosomal RNA (rRNA) genes. We expected to observe a core bacterial community among the surface waters and differences in bacterial community abundance over the different locations of sampling. In this study, we obtained a total of 60,810 trimmed reads from the five samples after the removal of unqualified reads. Bacterial sequences from the five samples were classified into taxonomic classes using the default settings of the mothur platform. Our results provided insight into the bacterial community composition of surface waters and revealed that there was a core microbial community in the microbial populations of surface samples at different geographic locations, with 13 phyla and 40 genera in common. Our findings also revealed the differences in bacterial communities among five surface water samples obtained at different locations.