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 x 10(8) -3.41 x 10 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. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.

ABSTRACT Microbial abundance is central to most investigations in microbial ecology, and its accurate measurement is a challenging task that has been significantly facilitated by the advent of molecular techniques over the last 20 years. Fluorescence in situ hybridization (FISH) is considered the gold standard of quantification techniques; however, it is expensive and offers low sample throughput, both of which limit its wider application. Quantitative PCR (qPCR) is an alternative that offers significantly higher throughput, and it is used extensively in molecular biology. The accuracy of qPCR can be compromised by biases in the DNA extraction and amplification steps. In this study, we compared the accuracy of these two established quantification techniques to measure the abundance of a key functional group in biological wastewater treatment systems, the ammonia-oxidizing bacteria (AOB), in samples from a time-series experiment monitoring a set of laboratory-scale reactors and a full-scale plant. For the qPCR analysis, we tested two different sets of AOB-specific primers, one targeting the 16SrRNA gene and one targeting the ammonia monooxygenase ( amoA ) gene. We found that there was a positive linear logarithmic relationship between FISH and the amoA gene-specific qPCR, where the data obtained from both techniques was equivalent at the order of magnitude level. The 16S rRNA gene-specific qPCR assay consistently underestimated AOB numbers.

Views of community assembly have traditionally been based on the contrasting perspectives of the deterministic niche paradigm and stochastic neutral models. This study sought to determine if we could use empirical interventions conceived from a niche and neutral perspective to change the diversity and evenness of the microbial community within a reactor treating wastewater and to see if there was any associated change in the removal of endocrine disrupting compounds (EDCs). The systematic removal of EDCs and micropollutants from biological treatment systems is a major challenge for environmental engineers. We manipulated pairs of bioreactors in an experiment in which "niche" (temporal variation in resource concentration and resource complexity) and "neutral" (community size and immigration) attributes were changed and the effect on the detectable diversity and the removal of steroidal estrogens was evaluated. The effects of manipulations on diversity suggested that both niche and neutral processes are important in community assembly. We found that temporal variation in environmental conditions increased diversity but resource complexity did not. Larger communities had greater diversity but attempting to increase immigration by adding soil had the opposite effect. The effects of the manipulations on EDC removal efficiency were complex. Decreases in diversity, which were associated with a decrease in evenness, were associated with an increase in EDC removal. A simple generalized neutral model (calibrated with parameters typical of wastewater treatment plants) showed that decreases in diversity should lead to the increase in abundance of some ostensibly taxa rare. We conclude that neither niche and neutral perspectives nor the effect of diversity on putative rare functions can be properly understood by naïve qualitative observations. Instead, the relative importance of the key microbial mechanisms must be determined and, ideally, expressed mathematically.

There is a growing view that the application of ecological theory has the potential to facilitate a transition from a descriptive to a predictive framework in wastewater engineering. In this study we tested the hypotheses that: (i) it is possible to engineer consistent differences between microbial communities in wastewater treatment modules; (ii) there is a positive relationship between structural complexity and genetic diversity; (iii) such interactions are modulated by the availability of energy. We developed four treatment modules of increasingly complex support material (matrix) design, and pumped a synthetic wastewater through them for 16 weeks. We then disassembled the modules and assessed the phylogenetic (general eubacteria and ammonium oxidisers, by DGGE profiling) and phenotypic (by PLFA profiling) diversity of the communities present on the support materials. We found that different genotypic and phenotypic community structures were reliably generated by the engineering of their physical environment in terms of structural complexity (as determined by particle size distribution and therefore pore size distribution). Furthermore, there was a notably consistent response of the phenotypic structure to such circumstances, and also to the presence of organic matter. However, we found no significant relationships between genetic diversity and structural complexity either for eubacterial or ammonia-oxidiser microbial groups. This work demonstrates that is it possible to engineer modules of differing microbial community composition by varying their physical complexity. This is an essential first step in testing relationships between system diversity and treatment resilience at a process level. (C) 2012 Elsevier B.V. All rights reserved.

There is a growing view that the application of ecological theory has the potential to facilitate a transition from a descriptive to a predictive framework in wastewater engineering. In this study we tested the hypotheses that: (i) it is possible to engineer consistent differences between microbial communities in wastewater treatment modules; (ii) there is a positive relationship between structural complexity and genetic diversity; (iii) such interactions are modulated by the availability of energy. We developed four treatment modules of increasingly complex support material (matrix) design, and pumped a synthetic wastewater through them for 16 weeks. We then disassembled the modules and assessed the phylogenetic (general eubacteria and ammonium oxidizers, by DGGE profiling) and phenotypic (by PLFA profiling) diversity of the communities present on the support materials. We found that different genotypic and phenotypic community structures were reliably generated by the engineering of their physical environment in terms of structural complexity (as determined by particle size distribution and therefore pore size distribution). Furthermore, there was a notably consistent response of the phenotypic structure to such circumstances, and also to the presence of organic matter. However, we found no significant relationships between genetic diversity and structural complexity either for eubacterial or ammonia-oxidiser microbial groups. This work demonstrates that is it possible to engineer modules of differing microbial community composition by varying their physical complexity. This is an essential first step in testing relationships between system diversity and treatment resilience at a process level.

Biological treatment processes are “complex systems” where many different kinds of microbes grow and interact in a dynamic manner. Understanding the relationship between microbial diversity and bioreactor performance could facilitate the optimisation of bioreactor design and enable the solution of bioreactor-related problems. However, systematic studies of the effects of operating variables on microbial diversity and reactor performance are rare. In this study, we determined the effects of different operating conditions and system configurations on the performance of laboratory-scale activated sludge reactors and microbial diversity, based on experiments designed using the factorial design approach. We found that the overall system performance and the diversity of the microbial communities in the reactors were affected by changes in the operating parameters. However, the relationship between diversity and performance was sometimes counterintuitive, as increases in system performance were not always associated with increased community diversity. Reactor configuration and addition of soil had the biggest effects on reactor performance, while the effects of organic loading rates and feed composition were less marked. Of all these parameters, reactor configuration was the only one that had a consistent effect on reactor community diversity.

This study investigated the formation of the microbial communities in two horizontal subsurface-flow laboratory-scale constructed wetlands, one planted and the other one unplanted. The abundance of the predominant functional groups (Archaea, Bacteria and sulphate-reducing bacteria) was determined using fluorescence in situ hybridization and the diversity and community structure of those functional groups were analysed using denaturing gradient gel electrophoresis. The numbers of Archaea, Bacteria and sulphate-reducing bacteria were indistinguishable in both reactors (P=0.99, 0.80 and 0.55, respectively). The microbial communities in both wetlands were typically no more similar than if they had been randomly assembled from a common source community. Plants did not appear to exert a strong effect on the structure of the microbial communities in the horizontal subsurface-flow constructed wetlands (HSCWs) studied in this investigation.

The microbial mechanisms of carbon removal in subsurface flow wetlands were studied, in one wetland with plants and one without plants. Particular emphasis was given to the influence of plants in the treatment process. Wetlands without plants showed higher carbon removal than those with plants, 63% and 51%, respectively (p<0.05). Molecular analysis of the bacterial diversity, growth rates and specific microbial activities showed that the two wetlands were different, especially towards the outlet of the two systems. Sulphate reducers and methanogens were found in both wetlands, and they are thought to be the main removers of soluble organic carbon in these two systems.