Machine learning approach identifies water sample source based on microbial abundance.

Water quality can change along a river system due to differences in adjacent land use patterns and discharge sources. These variations can induce rapid responses of the aquatic microbial community, which may be an indicator of water quality characteristics. In the current study, we used a random forest model to predict water sample sources from three different river ecosystems along a gradient of anthropogenic disturbance (i.e., less disturbed mountainous area, wastewater discharged urban area, and pesticide and fertilizer applied agricultural area) based on environmental physicochemical indices (PCIs), microbiological indices (MBIs), and their combination. Results showed that among the PCI-based models, using conventional water quality indices as inputs provided markedly better prediction of water sample source than using pharmaceutical and personal care products (PPCPs), and much better prediction than using polycyclic aromatic hydrocarbons (PAHs) and substituted PAHs (SPAHs). Among the MBI-based models, using the abundances of the top 30 bacteria combined with pathogenic antibiotic resistant bacteria (PARB) as inputs achieved the lowest median out-of-bag error rate (9.9%) and increased median kappa coefficient (0.8694), while adding fungal inputs reduced the kappa coefficient. The model based on the top 30 bacteria still showed an advantage compared with models based on PCIs or the combination of PCIs and MBIs. With improvement in sequencing technology and increase in data availability in the future, the proposed method provides an economical, rapid, and reliable way in which to identify water sample sources based on abundance data of microbial communities.

[Universality and Potential Application of Mn(â ¡) Oxidation Triggered by Microbial Interspecies Interactions].

Mn(Ⅱ)-oxidizing microorganisms can catalytically increase the oxidation rate of divalent manganese by several orders of magnitude, and affect the valence state and fate of elemental manganese. In addition to Mn(Ⅱ)-oxidization by a single microbial strain, our previous studies revealed that interspecies interactions between two bacterial strains (Sphingopyxis sp. QXT-31 and Arthrobacter sp. QXT-31) could trigger the Mn(Ⅱ)-oxidizing activities of Arthrobacter sp. QXT-31. In order to further explore its universality, mechanism, and potential engineering applications, research was conducted on three other Sphingopyxis strains using culture-dependent experiments, comparative genomic analysis, and transcriptome analysis. The results showed that one Sphingopyxis strain could also trigger the Mn(Ⅱ)-oxidizing activity of Arthrobacter sp. QXT-31, which could be regarded as a hint for the prevalence of Mn(Ⅱ) oxidation triggered by microbial interspecies interactions in the natural environment. Furthermore, the upregulation of the antibiotic synthesis pathway in Sphingopyxis was observed just before the Mn(Ⅱ)-oxidizing activity of Arthrobacter sp. QXT-31 was triggered, thus suggesting its possible involvement in stimulating the Mn(Ⅱ)-oxidizing activity of Arthrobacter sp. QXT-31. Finally, we demonstrated that using microbial interspecies interactions to enhance the oxidative removal of Mn(Ⅱ) in a manganese removal reactor is potentially feasible.

Use of convertible flow cells to simulate the impacts of anthropogenic activities on river biofilm bacterial communities.

Bacterial attachment to surfaces and the development of biofilms are crucial processes during the self-purification of polluted rivers. Biofilm bacterial communities also are a potential indicator of the human impact on an aquatic system. Here, we used indoor reactors with 7.7cm3 transparent convertible flow cells to observe the formation of biofilms in river water from different land-use areas (i.e., an undisturbed mountainous area, a wastewater-discharge urban area, and a pesticide-fertilizer applied agricultural area). We then compared the bacterial biomass, composition, and function among the formed biofilms and explored whether the biofilm bacterial communities formed in polluted river water (urban area) could shift to those formed in unpolluted water (mountainous area) after simulating water-body remediation. After 60d of indoor biofilm cultivation, the biofilms formed with the three types of influent were markedly different. Anthropogenic activities (e.g., wastewater discharge and pesticide-fertilizer use) facilitated biofilm bacterial production and the metabolic rate and altered the composition and metabolic patterns of the biofilm bacterial communities. After switching from an urban water to mountainous water influent in the same reactor, the biofilm bacterial communities that initially formed in the polluted discharge did not shift to that formed in unpolluted water. This result indicated that even after water remediation, the composition of the river biofilm bacterial community would not recover to a community like that observed under non-polluted conditions. Our study highlights possible issues related to current pollution-remediation routines and emphasizes the importance of sustainable anthropogenic activities within river basins.

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.

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.

Influence of microbial community diversity and function on pollutant removal in ecological wastewater treatment.

Traditional wastewater treatments based on activated sludge often encounter the problems of bulking and foaming, as well as malodor. To solve these problems, new treatment technologies have emerged in recent decades, including the ecological wastewater treatment process, which introduces selected local plants into the treatment system. With a focus on the underlying mechanisms of the ecological treatment process, we explored the microbial community biomass, composition, and function in the treatment system to understand the microbial growth in this system and its role in pollutant removal. Flow cytometry analysis revealed that ecological treatment significantly decreased influent bacterial quantity, with around 80% removal. 16S rRNA gene sequencing showed that the ecological treatment also altered the bacterial community structure of the wastewater, leading to a significant change in Comamonadaceae in the effluent. In the internal ecological system, because most of microbes aggregate in the plant rhizosphere and the sludge under plant roots, we selected two plant species (Nerium oleander and Arundo donax) to study the characteristics of rhizosphere and sludge microbes. Metagenomic results showed that the microbial community composition and function differed between the two species, and the microbial communities of A. donax were more sensitive to seasonal effects. Combined with their greater biomass and abundance of metabolic genes, microbes associated with N. oleander showed a greater contribution to pollutant removal. Further, the biodegradation pathways of some micropollutants, e.g., atrazine, were estimated.

Removal of malachite green dye from wastewater by different organic acid-modified natural adsorbent: kinetics, equilibriums, mechanisms, practical application, and disposal of dye-loaded adsorbent.

Natural adsorbent (Cinnamomum camphora sawdust) modified by organic acid (oxalic acid, citric acid, and tartaric acid) was investigated as a potential adsorbent for the removal of hazardous malachite green (MG) dye in aqueous media in a batch process. The extent of MG adsorption onto modified sawdust increased with increasing organic acid concentrations, pH, contact time, and temperature but decreased with increasing adsorbent dosage and ionic strength. Kinetic study indicated that the pseudo-second-order kinetic model could best describe the adsorption kinetics of MG. Equilibrium data were found to fit well with the Langmuir model, and the maximum adsorption capacity of the three kinds of organic acid-modified sawdust was 280.3, 222.8, and 157.5 mg/g, respectively. Thermodynamic parameters suggested that the sorption of MG was an endothermic process. The adsorption mechanism, the application of adsorbents in practical wastewater, the prediction of single-stage batch adsorption system, and the disposal of depleted adsorbents were also discussed.