Balance of neutral and deterministic components in the dynamics of activated sludge floc assembly

Microbial community assembly in engineered bioreactors

Microbial community assembly (MCA) processes that shape microbial communities in environments are being used to analyze engineered bioreactors such as activated sludge systems and anaerobic digesters. The goal of studying MCA is to be able to understand and predict the effect of design and operation procedures on bioreactor microbial composition and function. Ultimately, this can lead to bioreactors that are more efficient, resilient, or resistant to perturbations. This review summarizes the ecological theories underpinning MCA, evaluates MCA analysis methods, analyzes how these MCA-based methods are applied to engineered bioreactors, and extracts lessons from case studies. Furthermore, we suggest future directions in MCA research in engineered bioreactor systems. The review aims to provide insights and guidance to the growing number of environmental engineers who wish to design and understand bioreactors through the lens of MCA.

The cost of adaptability: resource availability constrains functional stability under pulsed disturbances

Global change exposes ecosystems to changes in the frequency, magnitude, and concomitancy of disturbances, which impact the composition and functioning of these systems. Here, we experimentally evaluate the effects of salinity disturbances and eutrophication on bacterial communities from coastal ecosystems. The functional stability of these communities is critically important for maintaining water quality, productivity, and ecosystem services, such as fishery yields. Microbial functional stability can be maintained via resistance and resilience, which are reflected in genomic traits such as genome size and codon usage bias and may be linked to metabolic costs. However, little is known about the mechanisms that select these traits under varying nutrient regimes. To study the impact of pulsed disturbances on community assembly and functioning depending on metabolic costs, we performed a 41-day pulse disturbance experiment across two levels of resource availability. Our setup triggered stochastic community re-assembly processes in all treatments. In contrast, we observed consistent and resource availability-dependent patterns of superordinate community functioning and structural patterns, such as functional resistance in response to disturbances, genomic trait distributions, and species diversity. Predicted genomic traits reflected the selection for taxa possessing resistant- and resilience-related traits, particularly under high nutrient availability. Our findings are a step toward unraveling the compositional and genomic underpinnings of functional resistance in microbial communities after exposure to consecutive pulse disturbances. Our work demonstrates how resource availability alleviates metabolic constraints on resistance and resilience, and this has important consequences for predicting water quality and ecosystem productivity of environments exposed to global change.

IMPORTANCE

Understanding the communities' responses to disturbances is a prerequisite to predicting ecosystem dynamics and, thus, highly relevant considering global change. Microbial communities play key roles in numerous ecosystem functions and services, and the large diversity, rapid growth, and phenotypic plasticity of microorganisms are thought to allow high resistance and resilience. While potential metabolic costs associated with adaptations to fluctuating environments have been debated, little evidence supports trade-offs between resource availability, resistance, and resilience. Here, we experimentally assessed the compositional and functional responses of an aquatic microbial model community to disturbances and systematically manipulated resource availability. Our results demonstrate that the capacity to tolerate environmental fluctuations is constrained by resource availability and reflected in the selection of genomic traits.

Resistance of aerobic granular sludge microbiomes to periodic loss of biomass

Granular sludge is a biofilm process used for wastewater treatment which is currently being implemented worldwide. It is important to understand how disturbances affect the microbial community and performance of reactors. Here, two acetate-fed replicate reactors were inoculated with acclimatized sludge and the reactor performance, and the granular sludge microbial community succession were studied for 149 days. During this time, the microbial community was challenged by periodically removing half of the reactor biomass, subsequently increasing the food-to-microorganism (F/M) ratio. Diversity analysis together with null models show that overall, the microbial communities were resistant to the disturbances, observing some minor effects on polyphosphate-accumulating and denitrifying microbial communities and their associated reactor functions. Community turnover was driven by drift and random granule loss, and stochasticity was the governing ecological process for community assembly. These results evidence the aerobic granular sludge process as a robust system for wastewater treatment.

Ecological Insights Into Community Interactions, Assembly Processes and Function in the Denitrifying Phosphorus Removal Activated Sludge Driven by Phosphorus Sources

The microbial characteristics in the wastewater treatment plants (WWTPs) strongly affect their optimal performance and functional stability. However, a cognitive gap remains regarding the characteristics of the microbial community driven by phosphorus sources, especially co-occurrence patterns and community assembly based on phylogenetic group. In this study, 59 denitrifying phosphorus removal (DPR) activated sludge samples were cultivated with phosphorus sources. The results suggested that homogeneous selection accounted for the largest proportion that ranged from 35.82 to 64.48%. Deterministic processes dominated in 12 microbial groups (bins): Candidatus_Accumulibacter and Pseudomonas in these bins belonged to phosphate-accumulating organisms (PAOs). Network analysis revealed that species interactions were intensive in cyclic nucleoside phosphate-influenced microbiota. Function prediction indicated that cyclic nucleoside phosphates increased the activity of enzymes related to denitrification and phosphorus metabolism and increased the α-diversity of microorganism but decreased the diversity of metabolic function. Based on these results, it was assumed that cyclic nucleoside phosphates, rather than inorganic phosphates, are the most available phosphorus source for majority microorganisms in DPR activated sludge. The study revealed the important role of phosphorus source in the construction and assembly of microbial communities and provided new insights about pollutant removal from WWTPs.

Transient-rare Bacterial Taxa Are Assembled Neutrally across Temporal Scales

Despite the importance of microbial communities in ecosystem functions, the mechanisms underlying the assembly of rare taxa over time are poorly understood. It remains largely unknown whether rare taxa exhibit similar assembly processes to common taxa in local communities. We herein retrieved the 16S rRNA sequences of bacteria collected bimonthly for 2 years from the Pohang wastewater treatment plant. The transient-rare taxa showed different abundance distributions from the common taxa. Transient-rare taxon assemblages also exhibited higher temporal variations than common taxon assemblages, suggesting the distinct ecological patterns of the two assemblages. A multivariate analysis revealed that environmental parameters accounted for 25.3 and 61.6% of temporal variations in the transient-rare and common taxon assemblages, respectively. The fitting of all observed taxa to a neutral community model revealed that 96.4% of the transient-rare taxa (relative abundance, 71.4%) and 73.3% of the common taxa (relative abundance, 45.6%) followed the model, suggesting that stochastic mechanisms were more important than deterministic ones in the assembly of the transient-rare taxa. Collectively, the present results indicate that the transient-rare bacterial taxa at the Pohang wastewater treatment plant differed from the common taxa in ecological patterns, suggesting that dispersal is a key process in their assembly.

Long-run bacteria-phage coexistence dynamics under natural habitat conditions in an environmental biotechnology system

Bacterial viruses are widespread and abundant across natural and engineered habitats. They influence ecosystem functioning through interactions with their hosts. Laboratory studies of phage-host pairs have advanced our understanding of phenotypic and genetic diversification in bacteria and phages. However, the dynamics of phage-host interactions have been seldom recorded in complex natural environments. We conducted an observational metagenomic study of the dynamics of interaction between Gordonia and their phages using a three-year data series of samples collected from a full-scale wastewater treatment plant. The aim was to obtain a comprehensive picture of the coevolution dynamics in naturally evolving populations at relatively high time resolution. Coevolution was followed by monitoring changes over time in the CRISPR loci of Gordonia metagenome-assembled genome, and reciprocal changes in the viral genome. Genome-wide analysis indicated low strain variability of Gordonia, and almost clonal conservation of the trailer end of the CRISPR loci. Incorporation of newer spacers gave rise to multiple coexisting bacterial populations. The host population carrying a shorter CRISPR locus that contain only ancestral spacers, which has not acquired newer spacers against the coexisting phages, accounted for more than half of the total host abundance in the majority of samples. Phages genome co-evolved by introducing directional changes, with no preference for mutations within the protospacer and PAM regions. Metagenomic reconstruction of time-resolved variants of host and viral genomes revealed how the complexity at the population level has important consequences for bacteria-phage coexistence.

The environment drives microbial trait variability in aquatic habitats

A prerequisite to improve the predictability of microbial community dynamics is to understand the mechanisms of microbial assembly. To study factors that contribute to microbial community assembly, we examined the temporal dynamics of genes in five aquatic metagenome time-series, originating from marine offshore or coastal sites and one lake. With this trait-based approach we expected to find gene-specific patterns of temporal allele variability that depended on the seasonal metacommunity size of carrier-taxa and the variability of the milieu and the substrates to which the resulting proteins were exposed. In more detail, we hypothesized that a larger seasonal metacommunity size would result in increased temporal variability of functional units (i.e., gene alleles), as shown previously for taxonomic units. We further hypothesized that multicopy genes would feature higher temporal variability than single-copy genes, as gene multiplication can result from high variability in substrate quality and quantity. Finally, we hypothesized that direct exposure of proteins to the extracellular environment would result in increased temporal variability of the respective gene compared to intracellular proteins that are less exposed to environmental fluctuations. The first two hypotheses were confirmed in all data sets, while significant effects of the subcellular location of gene products was only seen in three of the five time-series. The gene with the highest allele variability throughout all data sets was an iron transporter, also representing a target for phage infection. Previous work has emphasized the role of phage-prokaryote interactions as a major driver of microbial diversity. Our finding therefore points to a potentially important role of iron transporter-mediated phage infections for the assembly and maintenance of diversity in aquatic prokaryotes.

Effects of forced taxonomic transitions on metabolic composition and function in microbial microcosms

Surveys of microbial systems indicate that in many situations taxonomy and function may constitute largely independent ('decoupled') axes of variation. However, this decoupling is rarely explicitly tested experimentally, partly because it is hard to directly induce taxonomic variation without affecting functional composition. Here we experimentally evaluate this paradigm using microcosms resembling lake sediments and subjected to two different levels of salinity (0 and 19) and otherwise similar environmental conditions. We used DNA sequencing for taxonomic and functional profiling of bacteria and archaea and physicochemical measurements to monitor metabolic function, over 13 months. We found that the taxonomic composition of the saline systems gradually but strongly diverged from the fresh systems. In contrast, the metabolic composition (in terms of proportions of various genes) remained nearly identical across treatments and over time. Oxygen consumption rates and methane concentrations were substantially lower in the saline treatment, however, their similarity either increased (for oxygen) or did not change significantly (for methane) between the first and last sampling time, indicating that the lower metabolic activity in the saline treatments was directly and immediately caused by salinity rather than the gradual taxonomic divergence. Our experiment demonstrates that strong taxonomic shifts need not directly affect metabolic rates.

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes

BACKGROUND

Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene that may not truly represent in situ functions.

RESULTS

Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs). We found that the AS MAGs have obvious plant-specific features and that few proteins are shared by different WWTPs, especially for WWTPs located in geographically distant areas. Further, we developed a novel machine learning approach that can distinguish between AS MAGs and MAGs from other environments based on the clusters of orthologous groups of proteins with an accuracy of 96%. With the aid of machine learning, we also identified some functional features (e.g., functions related to aerobic metabolism, nutrient sensing/acquisition, and biofilm formation) that are likely vital for AS bacteria to adapt themselves in wastewater treatment bioreactors.

CONCLUSIONS

Our work reveals that, although the bacterial species in different municipal WWTPs could be different, they may have similar deterministic functional features that allow them to adapt to the AS systems. Also, we provide valuable genome resources and a novel approach for future investigation and better understanding of the microbiome of AS and other ecosystems. Video Abtract.

Effect of temperature on opportunistic pathogen gene markers and microbial communities in long-term stored roof-harvested rainwater

Roof-harvested rainwater (RHRW) has received increasing attention in recent years as an alternative water source for domestic use, yet its biological stability during storage is not fully understood. This study investigated the effects of temperature (4 °C, 20 °C and 30 °C) on the microbiological characteristics of RHRW over a storage period of 60 days by targeting different microbial groups including total bacteria and fecal indictor Escherichia coli, bacterial opportunistic pathogen genera and species (Legionella spp, Legionella pneumophila, Mycobacterium spp, Mycobacterium avium, Pseudomonas aeruginosa), and two amoebas (Acanthamoeba and Vermamoeba vermiformis). The rainwater chemistry demonstrated no obvious change during storage. The highest biomass was observed in RHRW stored at 30 °C, as measured by heterotrophic bacterial counts, adenosine triphosphate, and 16S rRNA gene numbers. Gene markers of E. coli, Legionella spp., P. aeruginosa, and V. vermiformis were detected in fresh RHRW and can persist during RHRW storage; whereas P. aeruginosa was the only species demonstrated significant regrowth at higher storage temperatures (P < 0.05). Acanthamoeba spp. was only detected in RHRW after 50 days of storage at three investigated temperatures, highlighting increased health risks in long-term stored RHRW. Bacterial community compositions were significantly different in RHRW stored at different temperatures, with increased variations among triplicate storage bottles noted at higher temperatures along with storage time. The results provide insights into RHRW storage practices in terms of mitigating microbial contamination risks.

Quantifying the contribution of microbial immigration in engineered water systems

Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.

Nexus of Stochastic and Deterministic Processes on Microbial Community Assembly in Biological Systems

Microbial community assembly in engineered biological systems is often simultaneously influenced by stochastic and deterministic processes, and the nexus of these two mechanisms remains to be further investigated. Here, three lab-scale activated sludge reactors were seeded with identical inoculum and operated in parallel under eight different sludge retention time (SRT) by sequentially reducing the SRT from 15 days to 1 day. Using 16S rRNA gene amplicon sequencing data, the microbial populations at the start-up (15-day SRT) and SRT-driven (≤10-day SRT) phases were observed to be noticeably different. Clustering results demonstrated ecological succession at the start-up phase with no consistent successional steps among the three reactors, suggesting that stochastic processes played an important role in the community assembly during primary succession. At the SRT-driven phase, the three reactors shared 31 core operational taxonomic units (OTUs). Putative primary acetate utilizers and secondary metabolizers were proposed based on K-means clustering, network and synchrony analysis. The shared core populations accounted for 65% of the total abundance, indicating that the microbial communities at the SRT-driven phase were shaped predominantly by deterministic processes. Sloan’s Neutral model and a null model analysis were performed to disentangle and quantify the relative influence of stochastic and deterministic processes on community assembly. The increased estimated migration rate in the neutral community model and the higher percentage of stochasticity in the null model implied that stochastic community assembly was intensified by strong deterministic factors. This was confirmed by the significantly different α- and β-diversity indices at SRTs shorter than 2 days and the observation that over half of the core OTUs were unshared or unsynchronized. Overall, this study provided quantitative insights into the nexus of stochastic and deterministic processes on microbial community assembly in a biological process.

Assessing the Hybrid Effects of Neutral and Niche Processes on Gut Microbiome Influenced by HIV Infection

That both stochastic neutral and deterministic niche forces are in effect in shaping the community assembly and diversity maintenance is becoming an increasingly important consensus. However, assessing the effects of disease on the balance between the two forces in the human microbiome has not been explored to the best of our knowledge. In this article, we applied a hybrid model to address this issue by analyzing the potential effect of HIV infection on the human gut microbiome and adopted a further step of multimodality testing to improve the interpretation of their model. Our study revealed that although niche process is the dominant force in shaping human gut microbial communities, niche process- and neutral process-driven taxa could coexist in the same microbiome, confirming the notion of their joint responsibility. However, we failed to detect the effect of HIV infection in changing the balance. This suggests that the rule governing community assembly and diversity maintenance may be changed by the disturbance from HIV infection-caused dysbiosis. Although we admit that the general question of disease effect on community assembly and diversity maintenance may still be an open question, our study presents the first piece of evidence to reject the significant influence of diseases.

Coupled virus - bacteria interactions and ecosystem function in an engineered microbial system

Viruses are thought to control bacterial abundance, affect community composition and influence ecosystem function in natural environments. Yet their dynamics have seldom been studied in engineered systems, or indeed in any system, for long periods of time. We measured virus abundance in a full-scale activated sludge plant every week for two years. Total bacteria and ammonia oxidising bacteria (AOB) abundances, bacterial community profiles, and a suite of environmental and operational parameters were also monitored. Mixed liquor virus abundance fluctuated over an order of magnitude (3.18 × 10⁸-3.41 × 10⁹ virus's mL^-1) and that variation was statistically significantly associated with total bacterial and AOB abundance, community composition, and effluent concentrations of COD and NH₄⁺- N and thus system function. This suggests viruses play a far more important role in the dynamics of activated sludge systems than previously realised and could be one of the key factors controlling bacterial abundance, community structure and functional stability and may cause reactors to fail. These findings are based on statistical associations, not mechanistic models. Nevertheless, viral associations with abiotic factors, such as pH, make physical sense, giving credence to these findings and highlighting the role that physical factors play in virus ecology. Further work is needed to identify and quantify specific bacteriophage and their hosts to enable us to develop mechanistic models of the ecology of viruses in wastewater treatment systems. However, since we have shown that viruses can be related to effluent quality and virus quantification is simple and cheap, practitioners would probably benefit from quantifying viruses now.

Thickness determines microbial community structure and function in nitrifying biofilms via deterministic assembly

Microbial biofilms are ubiquitous in aquatic environments where they provide important ecosystem functions. A key property believed to influence the community structure and function of biofilms is thickness. However, since biofilm thickness is inextricably linked to external factors such as water flow, temperature, development age and nutrient conditions, its importance is difficult to quantify. Here, we designed an experimental system in a wastewater treatment plant whereby nitrifying biofilms with different thicknesses (50 or 400 µm) were grown in a single reactor, and thus subjected to identical external conditions. The 50 and 400 µm biofilm communities were significantly different. This beta-diversity between biofilms of different thickness was primarily caused by deterministic factors. Turnover (species replacement) contributed more than nestedness (species loss) to the beta-diversity, i.e. the 50 µm communities were not simply a subset of the 400 µm communities. Moreover, the two communities differed in the composition of nitrogen-transforming bacteria and in nitrogen transformation rates. The study illustrates that biofilm thickness alone is a key driver for community composition and ecosystem function, which has implications for biotechnological applications and for our general understanding of biofilm ecology.

Composition and Dynamics of the Activated Sludge Microbiome during Seasonal Nitrification Failure

Wastewater treatment plants in temperate climate zones frequently undergo seasonal nitrification failure in the winter month yet maintain removal efficiency for other contaminants. We tested the hypothesis that nitrification failure can be correlated to shifts in the nitrifying microbial community. We monitored three parallel, full-scale sequencing batch reactors over the course of a year with respect to reactor performance, microbial community composition via 16S rRNA gene amplicon sequencing, and functional gene abundance using qPCR. All reactors demonstrated similar changes to their core microbiome, and only subtle variations among seasonal and transient taxa. We observed a decrease in species richness during the winter, with a slow recovery of the activated sludge community during spring. Despite the change in nitrification performance, ammonia monooxygenase gene abundances remained constant throughout the year, as did the relative sequence abundance of Nitrosomonadacae. This suggests that nitrification failure at colder temperatures might result from different reaction kinetics of nitrifying taxa, or that other organisms with strong seasonal shifts in population abundance, e.g. an uncultured lineage of Saprospiraceae, affect plant performance in the winter. This research is a comprehensive analysis of the seasonal microbial community dynamics in triplicate full-scale sequencing batch reactors and ultimately strengthens our basic understanding of the microbial ecology of activated sludge communities by revealing seasonal succession patterns of individual taxa that correlate with nutrient removal efficiency.

Neutral and selective dynamics in a synthetic microbial community

We created a synthetic microbial community to help understand how evolution and selection pressure change the species diversity of an ecosystem. Our results show that there is a clear transition between neutral and selective regimes that depends on the rate of immigration as well as the fitness differences.

Ecologists debate the relative importance of selective vs. neutral processes in understanding biodiversity. This debate is especially pertinent to microbial communities, which play crucial roles in areas such as health, disease, industry, and the environment. Here, we created a synthetic microbial community using heritable genetic barcodes and tracked community composition over repeated rounds of subculture with immigration. Consistent with theory, we find a transition exists between neutral and selective regimes, and the crossover point depends on the fraction of immigrants and the magnitude of fitness differences. Neutral models predict an increase in diversity with increased carrying capacity, while our selective model predicts a decrease in diversity. The community here lost diversity with an increase in carrying capacity, highlighting that using the correct model is essential for predicting community response to change. Together, these results emphasize the importance of including selection to obtain realistic models of even simple systems.

Function and functional redundancy in microbial systems

Microbial communities often exhibit incredible taxonomic diversity, raising questions regarding the mechanisms enabling species coexistence and the role of this diversity in community functioning. On the one hand, many coexisting but taxonomically distinct microorganisms can encode the same energy-yielding metabolic functions, and this functional redundancy contrasts with the expectation that species should occupy distinct metabolic niches. On the other hand, the identity of taxa encoding each function can vary substantially across space or time with little effect on the function, and this taxonomic variability is frequently thought to result from ecological drift between equivalent organisms. Here, we synthesize the powerful paradigm emerging from these two patterns, connecting the roles of function, functional redundancy and taxonomy in microbial systems. We conclude that both patterns are unlikely to be the result of ecological drift, but are inevitable emergent properties of open microbial systems resulting mainly from biotic interactions and environmental and spatial processes.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Stochastic Community Assembly: Does It Matter in Microbial Ecology?

Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.

Membrane biofilm communities in full-scale membrane bioreactors are not randomly assembled and consist of a core microbiome

Finding efficient biofouling control strategies requires a better understanding of the microbial ecology of membrane biofilm communities in membrane bioreactors (MBRs). Studies that characterized the membrane biofilm communities in lab-and pilot-scale MBRs are numerous, yet similar studies in full-scale MBRs are limited. Also, most of these studies have characterized the mature biofilm communities with very few studies addressing early biofilm communities. In this study, five full-scale MBRs located in Seattle (Washington, U.S.A.) were selected to address two questions concerning membrane biofilm communities (early and mature): (i) Is the assembly of biofilm communities (early and mature) the result of random immigration of species from the source community (i.e. activated sludge)? and (ii) Is there a core membrane biofilm community in full-scale MBRs? Membrane biofilm (early and mature) and activated sludge (AS) samples were collected from the five MBRs, and 16S rRNA gene sequencing was applied to investigate the bacterial communities of AS and membrane biofilms (early and mature). Alpha and beta diversity measures revealed clear differences in the bacterial community structure between the AS and biofilm (early and mature) samples in the five full-scale MBRs. These differences were mainly due to the presence of large number of unique but rare operational taxonomic units (∼13% of total reads in each MBR) in each sample. In contrast, a high percentage (∼87% of total reads in each MBR) of sequence reads was shared between AS and biofilm samples in each MBR, and these shared sequence reads mainly belong to the dominant taxa in these samples. Despite the large fraction of shared sequence reads between AS and biofilm samples, simulated biofilm communities from random sampling of the respective AS community revealed that biofilm communities differed significantly from the random assemblages (P < 0.001 for each MBR), indicating that the biofilm communities (early and mature) are unlikely to represent a random sample of the AS community. In addition to the presence of unique operational taxonomic units in each biofilm sample (early or mature), comparative analysis of operational taxonomic units and genera revealed the presence of a core biofilm community in the five full-scale MBRs. These findings provided insight into the membrane biofilm communities in full-scale MBRs. More comparative studies are needed in the future to elucidate the factors shaping the core and unique biofilm communities in full-scale MBRs.

Inferring neutral biodiversity parameters using environmental DNA data sets

The DNA present in the environment is a unique and increasingly exploited source of information for conducting fast and standardized biodiversity assessments for any type of organisms. The datasets resulting from these surveys are however rarely compared to the quantitative predictions of biodiversity models. In this study, we simulate neutral taxa-abundance datasets, and artificially noise them by simulating noise terms typical of DNA-based biodiversity surveys. The resulting noised taxa abundances are used to assess whether the two parameters of Hubbell's neutral theory of biodiversity can still be estimated. We find that parameters can be inferred provided that PCR noise on taxa abundances does not exceed a certain threshold. However, inference is seriously biased by the presence of artifactual taxa. The uneven contribution of organisms to environmental DNA owing to size differences and barcode copy number variability does not impede neutral parameter inference, provided that the number of sequence reads used for inference is smaller than the number of effectively sampled individuals. Hence, estimating neutral parameters from DNA-based taxa abundance patterns is possible but requires some caution. In studies that include empirical noise assessments, our comprehensive simulation benchmark provides objective criteria to evaluate the robustness of neutral parameter inference.

Neutral processes and species sorting in benthic microalgal community assembly: effects of tidal resuspension

Benthic microalgae (BMA) provide vital food resources for heterotrophs and stabilize sediments with their extracellular secretions. A central goal in ecology is to understand how processes such as species interactions and dispersal, contribute to observed patterns of species abundance and distribution. Our objectives were to assess the effects of sediment resuspension on microalgal community structure. We tested whether taxa-abundance distributions could be predicted using neutral community models (NCMs) and also specific hypotheses about passive migration: (i) As migration decreases in sediment patches, BMA α-diversity will decrease, and (ii) As migration decreases, BMA community dissimilarity (β-diversity) will increase. Co-occurrence indices (checkerboard score and variance ratio) were also computed to test for deterministic factors, such as competition and niche differentiation, in shaping communities. Two intertidal sites (mudflat and sand bar) differing in resuspension regime were sampled throughout the tidal cycle. Fluorometry and denaturing gradient gel electrophoresis were utilized to investigate diatom community structure. Observed taxa-abundances fit those predicted from NCMs reasonably well (R² of 0.68-0.93), although comparisons of observed local communities to artificial randomly assembled communities rejected the null hypothesis that diatom communities were assembled solely by stochastic processes. No co-occurrence tests indicated a significant role for competitive exclusion or niche partitioning in microalgal community assembly. In general, predictions about relationships between migration and species diversity were supported for local community dynamics. BMA at low tide (lowest migration) exhibited reduced α-diversity as compared to periods of immersion at both mudflat and sand bar sites. β-diversity was higher during low tide emersion on the mudflat, but did not differ temporally at the sand bar site. In between-site metacommunity comparisons, low- and high-resuspension sites exhibited distinct community compositions while the low-energy mudflats contained higher microalgal biomass and greater α-diversity. To our knowledge this is the first study to test the relevance of neutral processes in structuring marine microalgal communities. Our results demonstrate a prominent role for stochastic factors in structuring local BMA community assembly, although unidentified nonrandom processes also appear to play some role. High passive migration, in particular, appears to help maintain species diversity and structure communities in both sand and muddy habitats.

High-rate activated sludge communities have a distinctly different structure compared to low-rate sludge communities, and are less sensitive towards environmental and operational variables

High-rate activated sludge processes allow for the recovery of organics and energy from wastewaters. These systems are operated at a short sludge retention time and high sludge-specific loading rates, which results in a higher sludge yield and better digestibility than conventional, low-rate activated sludge. Little is known about the microbial ecology of high-rate systems. In this work, we address the need for a fundamental understanding of how high-rate microbial communities differ from low-rate communities. We investigated the high-rate and low-rate communities in a sewage treatment plant in relation to environmental and operational variables over a period of ten months. We demonstrated that (1) high-rate and low-rate communities are distinctly different in terms of richness, evenness and composition, (2) high-rate community dynamics are more variable and less shaped by deterministic factors compared to low-rate communities, (3) sub-communities of continuously core and transitional members are more shaped by deterministic factors than the continuously rare members, both in high-rate and low-rate communities, and (4) high-rate community members showed a co-occurrence pattern similar to that of low-rate community members, but were less likely to be correlated to environmental and operational variables. These findings provide a basis for further optimization of high-rate systems, in order to facilitate resource recovery from wastewater.

The importance of neutral and niche processes for bacterial community assembly differs between habitat generalists and specialists

The mechanisms of community assembly are a central focus in the field of microbial ecology. However, to what extent these mechanisms differ in importance by traits of groups is poorly understood. Here we quantified the importance of neutral and niche processes in community assembly for bacteria, habitat specialists and generalists in 21 plateau lakes of China. Results showed that both neutral and niche processes played a critical role in the assembly of entire bacterial communities, shaping a unique biogeographical pattern. A few habitat generalists and many specialists were identified. Interestingly, habitat specialists were only governed by niche process, with seven significant environmental variables-salinity, dissolved oxygen, water transparency, total phosphorus, ammonium-nitrogen, temperature and total nitrogen-independently explaining 40.3% of the biological variation. By contrast, habitat generalists were strongly driven by neutral process, with 50.9% of the variation of detection frequency explained in neutral community model. Only three environmental variables-salinity, total nitrogen and dissolved oxygen-significantly affected the distribution of habitat generalists, independently explaining 13.6% of the variation. Governed by different assembly mechanisms, habitat specialists and generalists presented disparate biogeographical patterns. Our result emphasizes the importance of investigating the bacterial community assembly at more refined levels than entire communities.

Shotgun Metagenomic Profiles Have a High Capacity To Discriminate Samples of Activated Sludge According to Wastewater Type

This study was conducted to investigate whether functions encoded in the metagenome could improve our ability to understand the link between microbial community structures and functions in activated sludge. By analyzing data sets from six industrial and six municipal wastewater treatment plants (WWTPs), covering different configurations, operational conditions, and geographic regions, we found that wastewater influent composition was an overriding factor shaping the metagenomic composition of the activated sludge samples. Community GC content profiles were conserved within treatment plants on a time scale of years and between treatment plants with similar influent wastewater types. Interestingly, GC contents of the represented phyla covaried with the average GC contents of the corresponding WWTP metagenome. This suggests that the factors influencing nucleotide composition act similarly across taxa and thus the variation in nucleotide contents is driven by environmental differences between WWTPs. While taxonomic richness and functional richness were correlated, shotgun metagenomics complemented taxon-based analyses in the task of classifying microbial communities involved in wastewater treatment systems. The observed taxonomic dissimilarity between full-scale WWTPs receiving influent types with varied compositions, as well as the inferred taxonomic and functional assignment of recovered genomes from each metagenome, were consistent with underlying differences in the abundance of distinctive sets of functional categories. These conclusions were robust with respect to plant configuration, operational and environmental conditions, and even differences in laboratory protocols.

IMPORTANCE

This work contributes to the elucidation of drivers of microbial community assembly in wastewater treatment systems. Our results are significant because they provide clear evidence that bacterial communities in WWTPs assemble mainly according to influent wastewater characteristics. Differences in bacterial community structures between WWTPs were consistent with differences in the abundance of distinctive sets of functional categories, which were related to the metabolic potential that would be expected according to the source of the wastewater.

Neutral community model explains the bacterial community assembly in freshwater lakes

Over the past decade, neutral theory has gained attention and recognition for its capacity to explain bacterial community structure (BCS) in addition to deterministic processes. However, no clear consensus has been drawn so far on their relative importance. In a metacommunity analysis, we explored at the regional and local scale the effects of these processes on the bacterial community assembly within the water column of 49 freshwater lakes. The BCS was assessed using terminal restriction fragment length polymorphism (T-RFLP) of the 16S rRNA genes. At the regional scales, results indicated that the neutral community model well predicted the spatial community structure (R(2) mean = 76%) compared with the deterministic factors - which explained only a small fraction of the BCS total variance (less than 14%). This suggests that the bacterial compartment was notably driven by stochastic processes, through loss and gain of taxa. At the local scale, the bacterial community appeared to be spatially structured by stochastic processes (R(2) mean = 65%) and temporally governed by the water temperature, a deterministic factor, even if some bacterial taxa were driven by neutral dynamics. Therefore, at both regional and local scales the neutral community model appeared to be relevant in explaining the bacterial assemblage structure.

Impacts of multiwalled carbon nanotubes on nutrient removal from wastewater and bacterial community structure in activated sludge

BACKGROUND

The increasing use of multiwalled carbon nanotubes (MWCNTs) will inevitably lead to the exposure of wastewater treatment facilities. However, knowledge of the impacts of MWCNTs on wastewater nutrient removal and bacterial community structure in the activated sludge process is sparse.

AIMS

To investigate the effects of MWCNTs on wastewater nutrient removal, and bacterial community structure in activated sludge.

METHODS

Three triplicate sequencing batch reactors (SBR) were exposed to wastewater which contained 0, 1, and 20 mg/L MWCNTs. MiSeq sequencing was used to investigate the bacterial community structures in activated sludge samples which were exposed to different concentrations of MWCNTs.

RESULTS

Exposure to 1 and 20 mg/L MWCNTs had no acute (1 day) impact on nutrient removal from wastewater. After long-term (180 days) exposure to 1 mg/L MWCNTs, the average total nitrogen (TN) removal efficiency was not significantly affected. TN removal efficiency decreased from 84.0% to 71.9% after long-term effects of 20 mg/L MWCNTs. After long-term exposure to 1 and 20 mg/L MWCNTs, the total phosphorus removal efficiencies decreased from 96.8% to 52.3% and from 98.2% to 34.0% respectively. Further study revealed that long-term exposure to 20 mg/L MWCNTs inhibited activities of ammonia monooxygenase and nitrite oxidoreductase. Long-term exposure to 1 and 20 mg/L MWCNTs both inhibited activities of exopolyphosphatase and polyphosphate kinase. MiSeq sequencing data indicated that 20 mg/L MWCNTs significantly decreased the diversity of bacterial community in activated sludge. Long-term exposure to 1 and 20 mg/L MWCNTs differentially decreased the abundance of nitrifying bacteria, especially ammonia-oxidizing bacteria. The abundance of PAOs was decreased after long-term exposure to 20 mg/L MWCNTs. The abundance of glycogen accumulating organisms (GAOs) was increased after long-term exposure to 1 mg/L MWCNTs.

CONCLUSION

MWCNTs have adverse effects on biological wastewater nutrient removal, and altered the diversity and structure of bacterial community in activated sludge.

The bias associated with amplicon sequencing does not affect the quantitative assessment of bacterial community dynamics

The performance of two sets of primers targeting variable regions of the 16S rRNA gene V1–V3 and V4 was compared in their ability to describe changes of bacterial diversity and temporal turnover in full-scale activated sludge. Duplicate sets of high-throughput amplicon sequencing data of the two 16S rRNA regions shared a collection of core taxa that were observed across a series of twelve monthly samples, although the relative abundance of each taxon was substantially different between regions. A case in point was the changes in the relative abundance of filamentous bacteria Thiothrix, which caused a large effect on diversity indices, but only in the V1–V3 data set. Yet the relative abundance of Thiothrix in the amplicon sequencing data from both regions correlated with the estimation of its abundance determined using fluorescence in situ hybridization. In nonmetric multidimensional analysis samples were distributed along the first ordination axis according to the sequenced region rather than according to sample identities. The dynamics of microbial communities indicated that V1–V3 and the V4 regions of the 16S rRNA gene yielded comparable patterns of: 1) the changes occurring within the communities along fixed time intervals, 2) the slow turnover of activated sludge communities and 3) the rate of species replacement calculated from the taxa–time relationships. The temperature was the only operational variable that showed significant correlation with the composition of bacterial communities over time for the sets of data obtained with both pairs of primers. In conclusion, we show that despite the bias introduced by amplicon sequencing, the variable regions V1–V3 and V4 can be confidently used for the quantitative assessment of bacterial community dynamics, and provide a proper qualitative account of general taxa in the community, especially when the data are obtained over a convenient time window rather than at a single time point.

Patterns and processes of microbial community assembly

Recent research has expanded our understanding of microbial community assembly. However, the field of community ecology is inaccessible to many microbial ecologists because of inconsistent and often confusing terminology as well as unnecessarily polarizing debates. Thus, we review recent literature on microbial community assembly, using the framework of Vellend (Q. Rev. Biol. 85:183-206, 2010) in an effort to synthesize and unify these contributions. We begin by discussing patterns in microbial biogeography and then describe four basic processes (diversification, dispersal, selection, and drift) that contribute to community assembly. We also discuss different combinations of these processes and where and when they may be most important for shaping microbial communities. The spatial and temporal scales of microbial community assembly are also discussed in relation to assembly processes. Throughout this review paper, we highlight differences between microbes and macroorganisms and generate hypotheses describing how these differences may be important for community assembly. We end by discussing the implications of microbial assembly processes for ecosystem function and biodiversity.

Bacterial community dynamics and taxa-time relationships within two activated sludge bioreactors

Background

Biological activated sludge process must be functionally stable to continuously remove contaminants while relying upon the activity of complex microbial communities. However the dynamics of these communities are as yet poorly understood. A macroecology metric used to quantify community dynamic is the taxa-time relationship (TTR). Although the TTR of animal and plant species has been well documented, knowledge is still lacking in regard to TTR of microbial communities in activated sludge bioreactors.

Aims

1) To characterize the temporal dynamics of bacterial taxa in activated sludge from two bioreactors of different scale and investigate factors affecting such dynamics; 2) to evaluate the TTRs of activated sludge microbial communities in two bioreactors of different scale.

Methods

Temporal variation of bacterial taxa in activated sludge collected from a full- and lab-scale activated sludge bioreactor was monitored over a one-year period using pyrosequencing of 16S rRNA genes. TTR was employed to quantify the bacterial taxa shifts based on the power law equation S = cT^w.

Results

The power law exponent w for the full-scale bioreactor was 0.43 (R² = 0.970), which is lower than that of the lab-scale bioreactor (w = 0.55, R² = 0.971). The exponents for the dominant phyla were generally higher than that of the rare phyla. Canonical correspondence analysis (CCA) result showed that the bacterial community variance was significantly associated with water temperature, influent (biochemical oxygen demand) BOD, bioreactor scale and dissolved oxygen (DO). Variance partitioning analyses suggested that wastewater characteristics had the greatest contribution to the bacterial community variance, explaining 20.3% of the variance of bacterial communities independently, followed by operational parameters (19.9%) and bioreactor scale (3.6%).

Conclusions

Results of this study suggest bacterial community dynamics were likely driven partly by wastewater and operational parameters and provide evidence that the TTR may be a fundamental ecological pattern in macro- and microbial systems.

Multi-scale modelling of bioreactor-separator system for wastewater treatment with two-dimensional activated sludge floc dynamics

A simple "first generation" multi-scale computational model of the formation of activated sludge flocs at micro-scale and reactor performance at macro-scale is proposed. The model couples mass balances for substrates and biomass at reactor scale with an individual-based approach for the floc morphology, shape and micro-colony development. Among the novel model processes included are the group attachment/detachment of micro-flocs to the core structure and the clustering of nitrifiers. Simulation results qualitatively describe the formation of micro-colonies of ammonia and nitrite oxidizers and the extracellular polymeric substance produced by heterotrophic microorganisms, as typically observed in fluorescence in situ hybridization images. These results are the first step towards realistic multi-scale multispecies models of the activated sludge wastewater treatment systems and a generic modelling strategy that could be extended to other engineered biological systems.

Community history affects the predictability of microbial ecosystem development

Microbial communities mediate crucial biogeochemical, biomedical and biotechnological processes, yet our understanding of their assembly, and our ability to control its outcome, remain poor. Existing evidence presents conflicting views on whether microbial ecosystem assembly is predictable, or inherently unpredictable. We address this issue using a well-controlled laboratory model system, in which source microbial communities colonize a pristine environment to form complex, nutrient-cycling ecosystems. When the source communities colonize a novel environment, final community composition and function (as measured by redox potential) are unpredictable, although a signature of the community's previous history is maintained. However, when the source communities are pre-conditioned to their new habitat, community development is more reproducible. This situation contrasts with some studies of communities of macro-organisms, where strong selection under novel environmental conditions leads to reproducible community structure, whereas communities under weaker selection show more variability. Our results suggest that the microbial rare biosphere may have an important role in the predictability of microbial community development, and that pre-conditioning may help to reduce unpredictability in the design of microbial communities for biotechnological applications.

Industrial activated sludge exhibit unique bacterial community composition at high taxonomic ranks

Biological degradation of domestic and industrial wastewater by activated sludge depends on a common process of separation of the diverse self-assembled and self-sustained microbial flocs from the treated wastewater. Previous surveys of bacterial communities indicated the presence of a common core of bacterial phyla in municipal activated sludge, an observation consistent with the concept of ecological coherence of high taxonomic ranks. The aim of this work was to test whether this critical feature brings about a common pattern of abundance distribution of high bacterial taxa in industrial and domestic activated sludge, and to relate the bacterial community structure of industrial activated sludge with relevant operational parameters. We have applied 454 pyrosequencing of 16S rRNA genes to evaluate bacterial communities in full-scale biological wastewater treatment plants sampled at different times, including seven systems treating wastewater from different industries and one plant that treats domestic wastewater, and compared our datasets with the data from municipal wastewater treatment plants obtained by three different laboratories. We observed that each industrial activated sludge system exhibited a unique bacterial community composition, which is clearly distinct from the common profile of bacterial phyla or classes observed in municipal plants. The influence of process parameters on the bacterial community structure was evaluated using constrained analysis of principal coordinates (CAP). Part of the differences in the bacterial community structure between industrial wastewater treatment systems were explained by dissolved oxygen and pH. Despite the ecological relevance of floc formation for the assembly of bacterial communities in activated sludge, the wastewater characteristics are likely to be the major determinant that drives bacterial composition at high taxonomic ranks.

Bacterial community dynamics in full-scale activated sludge bioreactors: operational and ecological factors driving community assembly and performance

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a “structure–function” paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors’ communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation.

Quantification of the relative roles of niche and neutral processes in structuring gastrointestinal microbiomes

The theoretical description of the forces that shape ecological communities focuses around two classes of models. In niche theory, deterministic interactions between species, individuals, and the environment are considered the dominant factor, whereas in neutral theory, stochastic forces, such as demographic noise, speciation, and immigration, are dominant. Species abundance distributions predicted by the two classes of theory are difficult to distinguish empirically, making it problematic to deduce ecological dynamics from typical measures of diversity and community structure. Here, we show that the fusion of species abundance data with genome-derived measures of evolutionary distance can provide a clear indication of ecological dynamics, capable of quantifying the relative roles played by niche and neutral forces. We apply this technique to six gastrointestinal microbiomes drawn from three different domesticated vertebrates, using high-resolution surveys of microbial species abundance obtained from carefully curated deep 16S rRNA hypervariable tag sequencing data. Although the species abundance patterns are seemingly well fit by the neutral theory of metacommunity assembly, we show that this theory cannot account for the evolutionary patterns in the genomic data; moreover, our analyses strongly suggest that these microbiomes have, in fact, been assembled through processes that involve a significant nonneutral (niche) contribution. Our results demonstrate that high-resolution genomics can remove the ambiguities of process inference inherent in classic ecological measures and permits quantification of the forces shaping complex microbial communities.

Bacterial community assembly and turnover within the intestines of developing zebrafish

Background

The majority of animal associated microorganisms are present in digestive tract communities. These intestinal communities arise from selective pressures of the gut habitats as well as host's genotype are regarded as an extra ‘organ’ regulate functions that have not evolved wholly on the host. They are functionally essential in providing nourishment, regulating epithelial development, and influencing immunity in the vertebrate host. As vertebrates are born free of microorganisms, what is poorly understood is how intestinal bacterial communities assemble and develop in conjunction with the development of the host.

Methodology/Principal Findings

Set within an ecological framework, we investigated the bacterial community assembly and turnover within the intestinal habitats of developing zebrafish (from larvae to adult animals). Spatial and temporal species-richness relationships and Mantel and partial Mantel tests revealed that turnover was low and that richness and composition was best predicted by time and not intestinal volume (habitat size) or changes in food diet. We also observed that bacterial communities within the zebrafish intestines were deterministically assembled (reflected by the observed low turnover) switching to stochastic assembly in the later stages of zebrafish development.

Conclusions/Significance

This study is of importance as it provides a novel insight into how intestinal bacterial communities assemble in tandem with the host's development (from early to adult stages). It is our hope that by studying intestinal microbiota of this vertebrate model with such or some more refined approaches in the future could well provide ecological insights for clinical benefit. In addition, this study also adds to our still fledgling knowledge of how spatial and temporal species-richness relationships are shaped and provides further mounting evidence that bacterial community assembly and dynamics are shaped by both deterministic and stochastic considerations.