Metagenomics and metatranscriptomics suggest pathways of 3-chloroaniline degradation in wastewater reactors.

Biological wastewater treatment systems are often affected by shifts in influent quality, including the input of toxic chemicals. Yet the mechanisms underlying the adaptation of activated sludge process performance are rarely studied in a controlled and replicated experimental setting, particularly when challenged with a sustained toxin input. Three replicate bench-scale bioreactors were subjected to a chemical disturbance in the form of 3-chloroaniline (3-CA) over 132 days, after an acclimation period of 58 days, while three control reactors received no 3-CA input. Ammonia oxidation was initially affected by 3-CA. Within three weeks of the experiment, microbial communities in all three treatment reactors adapted to biologically degrade 3-CA resulting in partial ammonia oxidation recovery. Combining process and microbial community data from amplicon sequencing with potential functions gleaned from assembled metagenomics and metatranscriptomics data, two putative degradation pathways for 3-CA were identified. The first pathway, determined from metagenomics data, involves a benzoate dioxygenase and subsequent meta-cleavage of the aromatic ring. The second, determined from intensive short-term sampling for gene expression data in tandem with 3-CA degradation, involves a phenol monooxygenase followed by ortho-cleavage of the aromatic ring. The relative abundances of amplicon sequence variants associated with the genera Gemmatimonas, OLB8, and Taibaiella correlated significantly with 3-CA degradation. Metagenome-assembled genome data also showed the genus OLB8 to be differentially enriched in treatment reactors, making it a strong candidate as 3-CA degrader. Using replicated reactors, this study has demonstrated the impact of a sustained stress on the activated sludge process. The unique and novel features of this study include the identification of putative pathways and potential degraders of 3-CA using long-term and short-term sampling in tandem with multiple methods in a controlled and replicated experiment.

Trait-based life-history strategies explain succession scenario for complex bacterial communities under varying disturbance.

Trait-based approaches are increasingly gaining importance in community ecology, as a way of finding general rules for the mechanisms driving changes in community structure and function under the influence of perturbations. Frameworks for life-history strategies have been successfully applied to describe changes in plant and animal communities upon disturbance. To evaluate their applicability to complex bacterial communities, we operated replicated wastewater treatment bioreactors for 35 days and subjected them to eight different disturbance frequencies of a toxic pollutant (3-chloroaniline), starting with a mixed inoculum from a full-scale treatment plant. Relevant ecosystem functions were tracked and microbial communities assessed through metagenomics and 16S rRNA gene sequencing. Combining a series of ordination, statistical and network analysis methods, we associated different life-history strategies with microbial communities across the disturbance range. These strategies were evaluated using tradeoffs in community function and genotypic potential, and changes in bacterial genus composition. We further compared our findings with other ecological studies and adopted a semi-quantitative competitors, stress-tolerants, ruderals (CSR) classification. The framework reduces complex data sets of microbial traits, functions and taxa into ecologically meaningful components to help understand the system response to disturbance and hence represents a promising tool for managing microbial communities.

Frequency of disturbance alters diversity, function, and underlying assembly mechanisms of complex bacterial communities.

Disturbance is known to affect the ecosystem structure, but predicting its outcomes remains elusive. Similarly, community diversity is believed to relate to ecosystem functions, yet the underlying mechanisms are poorly understood. Here, we tested the effect of disturbance on the structure, assembly, and ecosystem function of complex microbial communities within an engineered system. We carried out a microcosm experiment where activated sludge bioreactors operated in daily cycles were subjected to eight different frequency levels of augmentation with a toxic pollutant, from never (undisturbed) to every day (press-disturbed), for 35 days. Microbial communities were assessed by combining distance-based methods, general linear multivariate models, α-diversity indices, and null model analyses on metagenomics and 16S rRNA gene amplicon data. A stronger temporal decrease in α-diversity at the extreme, undisturbed and press-disturbed, ends of the disturbance range led to a hump-backed pattern, with the highest diversity found at intermediate levels of disturbance. Undisturbed and press-disturbed levels displayed the highest community and functional similarity across replicates, suggesting deterministic processes were dominating. The opposite was observed amongst intermediately disturbed levels, indicating stronger stochastic assembly mechanisms. Trade-offs were observed in the ecosystem function between organic carbon removal and both nitrification and biomass productivity, as well as between diversity and these functions. Hence, not every ecosystem function was favoured by higher community diversity. Our results show that the assessment of changes in diversity, along with the underlying stochastic-deterministic assembly processes, is essential to understanding the impact of disturbance in complex microbial communities.

Comparative genome analysis reveals genetic adaptation to versatile environmental conditions and importance of biofilm lifestyle in Comamonas testosteroni.

Comamonas testosteroni is an important environmental bacterium capable of degrading a variety of toxic aromatic pollutants and has been demonstrated to be a promising biocatalyst for environmental decontamination. This organism is often found to be among the primary surface colonizers in various natural and engineered ecosystems, suggesting an extraordinary capability of this organism in environmental adaptation and biofilm formation. The goal of this study was to gain genetic insights into the adaption of C. testosteroni to versatile environments and the importance of a biofilm lifestyle. Specifically, a draft genome of C. testosteroni I2 was obtained. The draft genome is 5,778,710 bp in length and comprises 110 contigs. The average G+C content was 61.88 %. A total of 5365 genes with 5263 protein-coding genes were predicted, whereas 4324 (80.60 % of total genes) protein-encoding genes were associated with predicted functions. The catabolic genes responsible for biodegradation of steroid and other aromatic compounds on draft genome were identified. Plasmid pI2 was found to encode a complete pathway for aniline degradation and a partial catabolic pathway for chloroaniline. This organism was found to be equipped with a sophisticated signaling system which helps it find ideal niches and switch between planktonic and biofilm lifestyles. A large number of putative multi-drug-resistant genes coding for abundant outer membrane transporters, chaperones, and heat shock proteins for the protection of cellular function were identified in the genome of strain I2. In addition, the genome of strain I2 was predicted to encode several proteins involved in producing, secreting, and uptaking siderophores under iron-limiting conditions. The genome of strain I2 contains a number of genes responsible for the synthesis and secretion of exopolysaccharides, an extracellular component essential for biofilm formation. Overall, our results reveal the genomic features underlying the adaption of C. testosteroni to versatile environments and highlighting the importance of its biofilm lifestyle.

Support vector regression model of wastewater bioreactor performance using microbial community diversity indices: effect of stress and bioaugmentation.

The relationship between microbial community structure and function has been examined in detail in natural and engineered environments, but little work has been done on using microbial community information to predict function. We processed microbial community and operational data from controlled experiments with bench-scale bioreactor systems to predict reactor process performance. Four membrane-operated sequencing batch reactors treating synthetic wastewater were operated in two experiments to test the effects of (i) the toxic compound 3-chloroaniline (3-CA) and (ii) bioaugmentation targeting 3-CA degradation, on the sludge microbial community in the reactors. In the first experiment, two reactors were treated with 3-CA and two reactors were operated as controls without 3-CA input. In the second experiment, all four reactors were additionally bioaugmented with a Pseudomonas putida strain carrying a plasmid with a portion of the pathway for 3-CA degradation. Molecular data were generated from terminal restriction fragment length polymorphism (T-RFLP) analysis targeting the 16S rRNA and amoA genes from the sludge community. The electropherograms resulting from these T-RFs were used to calculate diversity indices - community richness, dynamics and evenness - for the domain Bacteria as well as for ammonia-oxidizing bacteria in each reactor over time. These diversity indices were then used to train and test a support vector regression (SVR) model to predict reactor performance based on input microbial community indices and operational data. Considering the diversity indices over time and across replicate reactors as discrete values, it was found that, although bioaugmentation with a bacterial strain harboring a subset of genes involved in the degradation of 3-CA did not bring about 3-CA degradation, it significantly affected the community as measured through all three diversity indices in both the general bacterial community and the ammonia-oxidizer community (α = 0.5). The impact of bioaugmentation was also seen qualitatively in the variation of community richness and evenness over time in each reactor, with overall community richness falling in the case of bioaugmented reactors subjected to 3-CA and community evenness remaining lower and more stable in the bioaugmented reactors as opposed to the unbioaugmented reactors. Using diversity indices, 3-CA input, bioaugmentation and time as input variables, the SVR model successfully predicted reactor performance in terms of the removal of broad-range contaminants like COD, ammonia and nitrate as well as specific contaminants like 3-CA. This work was the first to demonstrate that (i) bioaugmentation, even when unsuccessful, can produce a change in community structure and (ii) microbial community information can be used to reliably predict process performance. However, T-RFLP may not result in the most accurate representation of the microbial community itself, and a much more powerful prediction tool can potentially be developed using more sophisticated molecular methods.

Partial bioaugmentation to remove 3-chloroaniline slows bacterial species turnover rate in bioreactors.

Bioaugmentation is a potentially powerful tool to direct community structure and metabolic capacities in bioreactors. Yet the outcome of bioaugmentation studies is usually unpredictable and effects on microbial community dynamics are poorly understood. We asked the question whether bioaugmentation could prevent a diversity shift induced by a model toxin, 3-chloroaniline (3-CA), regardless of whether 3-CA was degraded. Four replicate membrane bioreactors (MBRs) operating in parallel were amended with Pseudomonas putida UWC3 (pWDL7::rfp), a strain that carries the upper pathway genes necessary for partial degradation of 3-CA on its plasmid. Two MBRs served as controls and two MBRs were exposed to 3-CA for 71 days. Despite the selective pressure imposed by 3-CA, there was little or no 3-CA removal and neither the 16S rRNA gene of the augmented strain UWC3 nor the plasmid pWDL7::rfp proliferated in any of the reactors. Yet both host strain and plasmid were maintained at reduced levels (~10(4) host strain cells ml(-1)) in all reactors compared to the initial inoculum (~10(7) cells ml(-1); 1% of active cells). Additionally, the microbial community dynamics were evaluated for each MBR via terminal restriction fragment length polymorphism (T-RFLP) analysis (n = 15 per reactor) that targeted a portion of the 16S rRNA gene. Analysis comprised of a suite of multivariate statistics coupled with a theoretical microbial ecological approach, 'Island Biogeography', using a bacterial species time relationship (STR), within each MBR. Control MBRs had a wider range in w values than the treatment MBRs, which is attributed to the lack of a toxin selecting for biota that can withstand its toxic nature. Bioaugmentation alone strongly slowed the bacterial species turnover rate (as revealed by very low w scaling components), compared to non-bioaugmented reactors from a previous study, but did not protect the microbial community from a diversity shift caused by the toxin. Nonmetric multidimensional scaling (NMDS) analysis revealed that treatment MBRs diverged away from the control MBRs after the first 11 days, whereas control MBRs remained clustered. Individual reactors were analyzed by multi-response permutation procedures (MRPP) and a significant difference was found between each control MBR and the treatment MBRs. The study suggests that newly introduced strains can gain a foothold in established microbial communities even at low cell concentrations (about 1% of introduced concentration within the first week) regardless of selective pressure, whereas community dynamics are more affected by the presence of a selector toxin.

Phytoplankton, not allochthonous carbon, sustains herbivorous zooplankton production.

Terrestrial organic matter inputs have long been thought to play an important role in aquatic food web dynamics. Results from recent whole lake (13)C addition experiments suggest terrestrial particulate organic carbon (t-POC) inputs account for a disproportionate portion of zooplankton production. For example, several studies concluded that although t-POC only represented approximately 20% of the flux of particulate carbon available to herbivorous zooplankton, this food source accounted for approximately 50% of the C incorporated by zooplankton. We tested the direct dietary impact of t-POC (from the leaves of riparian vegetation) and various phytoplankton on Daphnia magna somatic growth, reproduction, growth efficiency, and lipid composition. By itself, t-POC was a very poor quality resource compared to cryptophytes, diatoms, and chlorophytes, but t-POC had similar food quality compared to cyanobacteria. Small additions of high quality Cryptomonas ozolinii to t-POC-dominated diets greatly increased Daphnia growth and reproduction. When offered alone, t-POC resulted in a Daphnia growth efficiency of 5 +/- 1%, whereas 100% Cryptomonas and Scenedesmus obliquus diets resulted in growth efficiencies of 46 +/- 8% (+/- SD) and 36 +/- 3%, respectively. When offered in a 50:50 mixed diet with Cryptomonas or Scenedesmus, the t-POC fraction resulted in a partial growth efficiency of 22 +/- 9% and 15 +/- 6%, respectively. Daphnia that obtained 80% of their available food from t-POC assimilated 84% of their fatty acids from the phytoplankton component of their diet. Overall, our results suggest Daphnia selectively allocate phytoplankton-derived POC and lipids to enhance somatic growth and reproduction, while t-POC makes a minor contribution to zooplankton production.