Effects of influent immigration and environmental factors on bacterial assembly of activated sludge microbial communities

Hydrological characteristics strongly dominate the spatiotemporal variation of bacterioplankton sub-communities in the Yangtze River Estuary

Seasonal variations in river discharge in estuarine ecosystems drive dynamic interactions between freshwater and seawater, significantly impacting the structure and functionality of bacterioplankton sub-communities. Seasonal saltwater intrusion during the dry season intensifies the dynamic variations in water quality and salinity between the northern and southern branches of the Yangtze River Estuary, further complicating the ecological processes governing bacterioplankton communities. Nevertheless, the mechanisms underlying these processes and their effects on distinct bacterioplankton sub-communities remain insufficiently explored. In this study, the composition, functions, and assembly mechanisms of bacterioplankton communities in the Yangtze River Estuary during different hydrological periods were examined using molecular technique and various statistical analysis methods. The results showed that rare sub-communities exhibited the highest α-diversity, abundant and transient sub-communities primarily contributed to the diversity differences across hydrological periods. Saltwater intrusion into the northern branch altered bacterioplankton community and weakened the distance-decay pattern of the transient and rare sub-communities. Additionally, stochastic processes governed the assembly of rare sub-communities, and saltwater intrusion disrupted their migration and dispersal patterns. In contrast, abundant and transient sub-communities maintain their stability by adjusting their ecological strategies in response to salinity changes. Functional analysis indicated that external nutrient inputs and hydrodynamic changes in the wet season promoted community functional diversity and activity, while abundant sub-communities in the dry season were more effective at occupying resources and performing specific functions related to carbon cycling. These findings highlight the relationships between bacterioplankton sub-communities and environmental changes in estuarine ecosystems, underscoring their key roles in biogeochemical cycling.

Microbial community structure and functional characteristics in a membrane bioreactor used for real rural wastewater treatment

Membrane bioreactors (MBRs) have been widely used in the field of wastewater treatment because of their small footprint and high treatment efficiency. In this research, 10 rural wastewater treatment sites in China that employ the MBR process were systematically studied. Specifically, treatment of actual domestic wastewater using MBRs was examined by high-throughput 16S rRNA gene sequencing to explore the microbial community composition and perform function prediction. The data of water quality parameters revealed high removal rates of chemical oxygen demand and NH4+-N in all the sites. Proteobacteria were absolutely dominant in all the sites. Thauera, Nitrospira, Ferribacterium, and Dechloromonas were the main functional genera responsible for nitrogen and phosphorus removal at the tested sites. Nitrospira includes conventional nitrite-oxidizing bacteria and complete ammonia-oxidizing bacteria. Among them, 26 genes related to nitrogen metabolism were retrieved according to gene prediction, which verified the good NH4+-N removal efficiency at the tested sites. This study focuses on the analysis of microbial community structure and functional characteristics of MBR-based treatment systems for rural wastewater treatment, thereby providing a microbial basis for improving rural wastewater treatment processes.

Using machine learning to identify environmental factors that collectively determine microbial community structure of activated sludge

Activated sludge (AS) microbial communities are influenced by various environmental variables. However, a comprehensive analysis of how these variables jointly and nonlinearly shape the AS microbial community remains challenging. In this study, we employed advanced machine learning techniques to elucidate the collective effects of environmental variables on the structure and function of AS microbial communities. Applying Dirichlet multinomial mixtures analysis to 311 global AS samples, we identified four distinct microbial community types (AS-types), each characterized by unique microbial compositions and metabolic profiles. We used 14 classical linear and nonlinear machine learning methods to select a baseline model. The extremely randomized trees demonstrated optimal performance in learning the relationship between environmental factors and AS types (with an accuracy of 71.43%). Feature selection identified critical environmental factors and their importance rankings, including latitude (Lat), longitude (Long), precipitation during sampling (Precip), solids retention time (SRT), effluent total nitrogen (Effluent TN), average temperature during sampling month (Avg Temp), mixed liquor temperature (Mixed Temp), influent biochemical oxygen demand (Influent BOD), and annual precipitation (Annual Precip). Significantly, Lat, Long, Precip, Avg Temp, and Annual Precip, influenced metabolic variations among AS types. These findings emphasize the pivotal role of environmental variables in shaping microbial community structures and enhancing metabolic pathways within activated sludge. Our study encourages the application of machine learning techniques to design artificial activated sludge microbial communities for specific environmental purposes.

Microbial core communities in activated sludge plants are strongly affected by immigration and geography

BACKGROUND

The microbiota in wastewater treatment plants (WWTPs) and incoming wastewater is critical for the treatment process, the preservation of natural ecosystems and human health, and for the recovery of resources and achievement of sustainability goals. Both core species and conditionally rare and abundant taxa (CRAT) are considered process-critical but little is known about identity as well as true functional and ecological importance. Here, we present a comprehensive investigation of the microbiota of 84 municipal activated sludge (AS) plants with nutrient removal treating ~ 70% of all wastewater within a confined geographical area, Denmark (43,000 km2). With the use of an ecosystem-specific database (MiDAS 5.2), species-level classification allowed us to investigate the core and CRAT species, whether they were active, and important factors determining their presence.

RESULTS

We established a comprehensive catalog of species with names or placeholder names showing each plant contained approx. 2,500 different species. Core and CRAT represented in total 258 species, constituting around 50% of all reads in every plant. However, not all core and CRAT could be regarded as process-critical as growth rate calculations revealed that 43% did not grow in the AS plants and were present only because of continuous immigration from the influent. Analyses of regional microbiota differences and distance decay patterns revealed a stronger effect for species than genera, demonstrating that geography had a clear effect on the AS microbiota, even across a limited geographical area such as Denmark (43,000 km2).

CONCLUSIONS

The study is the first comprehensive investigation of WWTPs in a confined geographical area providing new insights in our understanding of activated sludge microbiology by introducing a concept of combining immigration and growth calculation with identifying core and CRAT to reveal the true ecosystem-critical organisms. Additionally, the clear biogeographical pattern on this scale highlights the need for more region-level studies to find regional process-critical taxa (core and CRAT), especially at species and amplicon sequence variant (ASV) level.

Archaeal communities change responding to anthropogenic and natural treatments of freeze-thawed soils

The coverage of accumulated snow plays a significant role in inducing changes in both microbial activity and environmental factors within freeze-thaw soil systems. This study aimed to analyze the impact of snow cover on the dynamics of archeal communities in freeze-thaw soil. Furthermore, it seeks to investigate the role of fertilization in freeze-thaw soil. Four treatments were established based on snow cover and fertilization:No snow and no fertilizer (CK-N), snow cover without fertilizer (X-N), fertilizer without snow cover (T-N), and both fertilizer and snow cover (T-X). The research findings indicated that after snow cover treatment, the carbon, nitrogen, and phosphorus content in freeze-thaw soil exhibit periodic fluctuations. Snow covered effectively altered the community composition of bacteria and archaea in the soil, with a greater impact on archaeal communities than on bacterial communities. Snow covered improves the stability of archaeal communities in freeze-thaw soil. Additionally, the arrival of snow also enhanced the correlation between archaea and environmental factors, with the key archaeal phyla involved being Nanoarchaeota and Crenarchaeota. Further research showed that the application of organic fertilizers also had some impact on freeze-thaw soil, but this impact was smaller compared to snow cover. In summary, the arrival of snow could alter the archaeal community and protect nutrient elements in freeze-thaw soil, reducing their loss, and its effect is more pronounced compared to the application of organic fertilizers.

Microbial communities assembly in wastewater treatment plants in China

Community assembly processes determine community structure. Deterministic processes are essential for optimizing activated sludge (AS) bioreactor performance. However, the debate regarding the relative importance of determinism versus stochasticity remains contentious, and the influencing factors are indistinct. This study used large-scale 16S rRNA gene data derived from 252 AS samples collected from 28 cities across China to explore the mechanism of AS community assembly. Results showed that the northern communities possessed lower spatial turnover and more significant dispersal limitation than those in the south, whereas the latter had more substantial deterministic processes than the former (14.46 % v.s. 9.12 %). Meanwhile, the communities in the south exhibited lower network complexity and stability. We utilized a structural equation model to explore the drivers of deterministic processes. Results revealed that low network complexity (r = -0.56, P < 0.05) and high quorum sensing bacteria abundance (r = 0.25, P < 0.001) promoted deterministic assembly, which clarifies why determinism was stronger in southern communities than northern ones. Furthermore, total phosphorus and hydraulic retention time were found to be the primary abiotic drivers. These findings provide evidence to understand the community deterministic assembly, which is crucial for resolving community structure and improving bioreactor performance.

Temporal assembly patterns of microbial communities in three parallel bioreactors treating low-concentration coking wastewater with differing carbon source concentrations

Carbon source is an important factor of biological treatment systems, the effects of which on their temporal community assembly patterns are not sufficiently understood currently. In this study, the temporal dynamics and driving mechanisms of the communities in three parallel bioreactors for low-concentration coking wastewater (CWW) treatment with differing carbon source concentrations (S0 with no glucose addition, S1 with 200 mg/L glucose addition and S2 with 400 mg/L glucose addition) were comprehensively studied. High-throughput sequencing and bioinformatics analyses including network analysis and Infer Community Assembly Mechanisms by Phylogenetic bin-based null model (iCAMP) were used. The communities of three systems showed turnover rates of 0.0029∼0.0034 every 15 days. Network analysis results showed that the S0 network showed higher positive correlation proportion (71.43%) and clustering coefficient (0.33), suggesting that carbon source shortage in S0 promoted interactions and cooperation of microbes. The neutral community model analysis showed that the immigration rate increased from 0.5247 in S0 to 0.6478 in S2. The iCAMP analysis results showed that drift (45.89%) and homogeneous selection (31.68%) dominated in driving the assembly of all the investigated microbial communities. The contribution of homogeneous selection increased with the increase of carbon source concentrations, from 27.92% in S0 to 36.08% in S2. The OTUs participating in aerobic respiration and tricarboxylic acid (TCA) cycle were abundant among the bins mainly affected by deterministic processes, while those related to the metabolism of refractory organic pollutants in CWW such as alkanes, benzenes and phenols were abundant in the bins dominated by stochastic processes.

Predicting microbial community compositions in wastewater treatment plants using artificial neural networks

BACKGROUND

Activated sludge (AS) of wastewater treatment plants (WWTPs) is one of the world's largest artificial microbial ecosystems and the microbial community of the AS system is closely related to WWTPs' performance. However, how to predict its community structure is still unclear.

RESULTS

Here, we used artificial neural networks (ANN) to predict the microbial compositions of AS systems collected from WWTPs located worldwide. The predictive accuracy R²_1:1 of the Shannon-Wiener index reached 60.42%, and the average R²_1:1 of amplicon sequence variants (ASVs) appearing in at least 10% of samples and core taxa were 35.09% and 42.99%, respectively. We also found that the predictability of ASVs was significantly positively correlated with their relative abundance and occurrence frequency, but significantly negatively correlated with potential migration rate. The typical functional groups such as nitrifiers, denitrifiers, polyphosphate-accumulating organisms (PAOs), glycogen-accumulating organisms (GAOs), and filamentous organisms in AS systems could also be well recovered using ANN models, with R²_1:1 ranging from 32.62% to 56.81%. Furthermore, we found that whether industry wastewater source contained in inflow (IndConInf) had good predictive abilities, although its correlation with ASVs in the Mantel test analysis was weak, which suggested important factors that cannot be identified using traditional methods may be highlighted by the ANN model.

CONCLUSIONS

We demonstrated that the microbial compositions and major functional groups of AS systems are predictable using our approach, and IndConInf has a significant impact on the prediction. Our results provide a better understanding of the factors affecting AS communities through the prediction of the microbial community of AS systems, which could lead to insights for improved operating parameters and control of community structure. Video Abstract.

Exploring the mechanism of Self-Consistent balance between microbiota and high efficiency in wastewater treatment

Sewage treatment mediated by microbial organisms is a promising green trend. However, the complex balance between microbiota stability and highly efficient wastewater treatment requires investigation. This study successfully improved the effectiveness of sewage treatment by resetting the microbial community structure in the activated sludge. Truepera, Methylophaga, unclassified_Fodinicurvataceae, and unclassified_Actinomanarales were the dominant genera, while salinity and NH₃-N content were identified as the key environmental factors governing the microbial structure. By optimizing the microflora structure driven by environmental factors, the key minor genera were activated and coordinated with the aforementioned genera, thereby promoting wastewater treatment. Finally, the chemical oxygen demand, NH₃-N, and total phosphorus removal rates were improved to 86.8 ± 1.9%, 82.4 ± 4.1%, and 94.8 ± 3.8%, respectively. It provides a new insight to improve the wastewater treatment through setting microbiota by environmental factor driven.

A novel simultaneous partial nitrification, anammox, denitrification and fermentation process: Enhancing nitrogen removal and sludge reduction in a single reactor

This study verified the feasibility of simultaneous partial nitrification, anammox, denitrification and fermentation process under intermittent aeration in a single reactor, and explored the impact of dissolved oxygen (DO) on the synergy between fermentation and nitrogen removal. An advanced nitrogen removal efficiency of 92.8 % and a low observed sludge yield of 0.0268-0.1474 kgMLSS/kgCOD were achieved. In-situ test showed that nitrate and ammonium decreased synchronously in the absence of organic matter, indicating the possibility of simultaneous partial denitrification, anammox and fermentation. Additionally, the abundance of functional genes for acetate production was 66,894 hits, while the key genes relevant to methanogenesis were only 348 hits, which suggested that fermentation might stop at the acid-producing stage and promote partial denitrification-anammox reaction, achieving simultaneous sludge reduction and advanced nitrogen removal performance. When DO increased from 0.1-0.3 to 0.4-0.6 mg/L, the nitrogen removal efficiency was increased (63.9 %→92.8 %) while sludge reduction was negatively affected.

Deciphering the antibiotic resistome and microbial community in municipal wastewater treatment plants at different elevations in eastern and western China

Antibiotic resistance genes (ARGs) as emerging environmental contaminants pose severe global risks to public health and ecosystems. Municipal wastewater treatment plants (WWTPs) are crucial transmitters for the dissemination and propagation of ARGs into receiving water bodies via mobile genetic elements (MGEs). However, the comprehensive and deep deciphering of the diversity, abundance, and potential hosts of ARGs in two distinct altitudinal WWTPs is scarce. In this work, we revealed the elevational distribution characteristics of the resistance genes and microbial community of six WWTPs from two distinct geographical zones: a low-elevation (LE) region (Shandong, 10-22 m above sea level) and a high-elevation (HE) region (Gansu, 1,520-1,708 m above sea level). Significant elevational variations in the diversity and relative abundance of resistance genes were observed. Wastewater treatment could significantly reduce the concentrations of ARGs and MGEs by about 1-2 and 2-3 orders of magnitude, respectively. However, above 69.95% of resistance genes were enriched in effluent. In particular, 24 ARG subtype, 3 MGE subtypes, and 59 bacterial genera were persistent in all samples. More potential hosts for ARGs in LE region and more abundant human gut microbiota in HE region were identified. This work provides helpful information for controlling the spread of ARGs for their management and assessment, thereby mitigating the risks of ARGs in WWTPs.

Variations in antibiotic resistance genes and microbial community in sludges passing through biological nutrient removal and anaerobic digestion processes in municipal wastewater treatment plants

Antimicrobial resistance (AMR) represents a relentless, silent pandemic. Contributing to this are wastewater treatment plants (WWTPs), a potential source of antibiotic resistance genes' (ARGs) transmission to the environment, threatening public health. The presence of ARGs in pathogenic bacteria and their release into the environment by WWTPs threatens the public health. The current study investigated changes in ARGs' abundance in biological nutrient removal (BNR) processes and anaerobic digestion (AD) reactors of two WWTPs. Also, microbial community structure, which is known to shape the distribution and abundance of ARGs, was also analyzed. The relative abundance of eight ARGs (tetX, tetA, tetM, TEM, sul1, sul2, ermB and qnrD) was quantified as ARGs' copies/16 S rRNA gene copies using quantitative polymerase chain reaction (qPCR). Microbial community composition was assessed by 16 S rRNA microbiome sequencing analysis. TetX was prevalent among the eight ARGs, followed by TEM and sul1. However, its abundance was decreased in the AD sludges compared to BNR sludges. Proteobacteria was the major bacterial phylum found in all the sludge samples, while Arcobacter, 12up and Acidovorax were the predominant genera. Acinetobacter and Flavobacterium were significantly more abundant in the BNR sludges, while 12up and Aeromonas were predominant in AD sludges. Principal component analysis (PCA) revealed a clear difference in dominant ARGs and bacteria between the sludges in the processes of BNR and AD of the two WWTPs. Clinically relevant bacterial genera, Klebsiella and Enterococcus, found in both the BNR and AD sludges, were significantly correlated with the tetX gene. Throughout this study, the relationship between microbial communities and specific ARGs was revealed, illustrating that the composition of the microbial community could play a vital role in the abundance of ARGs. These results will better inform future studies aimed at controlling the spread of ARGs and their potential hosts from WWTPs.

Anaerobic membrane bioreactor for carbon-neutral treatment of industrial wastewater containing N, N-dimethylformamide: Evaluation of electricity, bio-energy production and carbon emission

The feasibility of anaerobic membrane bioreactor (AnMBR) for the treatment of N, N-dimethylformamide (DMF)-containing wastewater was theoretically compared with the conventional activated sludge (CAS) process in this study. The electricity consumption and expenditure, bio-energy production and CO₂ emission were investigated using the operational results of a lab-scale AnMBR operated in a long-term operation. The AnMBR was capable of producing bio-methane from wastewater and generated 3.45 kWh/m³ of electricity as recovered bio-energy while the CAS just generated 1.17 kWh/m³ of electricity from the post-treatment of excessive sludge disposal. The large quantity of bio-methane recovered by the AnMBR can also be sold as sustainable bioresource for the use of household natural gas with a theoretical profit gain of 29,821 US$/year, while that of the CAS was unprofitable. The AnMBR was also demonstrated to significantly reduce the carbon emission by obtaining a theoretical negative CO₂ production of -2.34 kg CO₂/m³ with the recycle of bio-energy while that for the CAS was 4.50 kg CO₂/m³. The results of this study demonstrate that the AnMBR process has promising potential for the carbon-neutral treatment of high-strength DMF-containing wastewater in the future.

A critical review of wastewater quality variation and in-sewer processes during conveyance in sewer systems

In-sewer physio-biochemical processes cause significant variations of wastewater quality during conveyance, which affects the influent to a wastewater treatment plant (WWTP) and arguably the microbial community of biological treatment units in a WWTP. In wet weather, contaminants stored in sewer deposits can be resuspended and migrate downstream or be released during combined sewer overflows to the urban water bodies, posing challenges to the treatment facilities or endangering urban water quality. Therefore, in-sewer transformation and migration of contaminants have been extensively studied. The compiled results from representative research in the past few decades showed that biochemical reactions are both cross-sectionally and longitudinally organized in the deposits and the sewage, following the redox potential as well as the sequence of macromolecule/contaminant degradation. The sewage organic contents and sewer biofilm microorganisms were found to covary but more systematic studies are required to examine the temporal stability of the feature. Besides, unique communities can be developed in the sewage phase. The enrichment of the major sewage-associated microorganisms can be explained by the availability of biodegradable organic contents in sewers. The sewer deposits, including biofilms, harbor both microorganisms and contaminants and usually can provide longer residence time for in-sewer transformation than wastewater. However, the interrelationships among contaminant transformation, microorganisms in the deposits/biofilms, and those in the sewage are largely unclear. Specifically, the formation and migration of FOG (fat, oil, and grease) deposits, generation and transport of contaminants in the sewer atmosphere (e.g., H₂S, CH₄, volatile organic compounds, bioaerosols), transport and transformation of nonconventional contaminants, such as pharmaceuticals and personal care products, and wastewater quality variation during the biofilm rehabilitation period after damages caused by rains/storms are some topics for future research. Moreover, systematic and standardized field analysis of real sewers under dynamic wastewater discharge conditions is necessary. We believe that an improved understanding of these processes would assist in sewer management and better prepare us for the challenges brought about by climate change and water shortage.

Deciphering the microbial community structures and functions of wastewater treatment at high-altitude area

Introduction: The proper operation of wastewater treatment plants is a key factor in maintaining a stable river and lake environment. Low purification efficiency in winter is a common problem in high-altitude wastewater treatment plants (WWTPs), and analysis of the microbial community involved in the sewage treatment process at high-altitude can provide valuable references for improving this problem. Methods: In this study, the bacterial communities of high- and low-altitude WWTPs were investigated using Illumina high-throughput sequencing (HTS). The interaction between microbial community and environmental variables were explored by co-occurrence correlation network. Results: At genus level, Thauera (5.2%), unclassified_Rhodocyclaceae (3.0%), Dokdonella (2.5%), and Ferribacterium (2.5%) were the dominant genera in high-altitude group. The abundance of nitrogen and phosphorus removal bacteria were higher in high-altitude group (10.2% and 1.3%, respectively) than in low-altitude group (5.4% and 0.6%, respectively). Redundancy analysis (RDA) and co-occurrence network analysis showed that altitude, ultraviolet index (UVI), pH, dissolved oxygen (DO) and total nitrogen (TN) were the dominated environmental factors (p < 0.05) affecting microbial community assembly, and these five variables explained 21.4%, 20.3%, 16.9%, 11.5%, and 8.2% of the bacterial assembly of AS communities. Discussion: The community diversity of high-altitude group was lower than that of low-altitude group, and WWTPs of high-altitude aeras had a unique microbial community structure. Low temperature and strong UVI are pivotal factors contributing to the reduced diversity of activated sludge microbial communities at high-altitudes.