Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities

Residence Time Structures Microbial Communities Through Niche Partitioning

Much of life on Earth is at the mercy of currents and flow. Residence time (τ) estimates how long organisms and resources remain in a system based on the ratio of volume (V) to flow rate (Q). Short τ should promote immigration but limit species establishment, while long τ should favour species that survive on limited resources. Theory suggests these opposing forces shape the abundance, diversity and function of flowing systems. We experimentally tested how residence time affects a lake microbial community by exposing chemostats to a τ gradient spanning seven orders of magnitude. Microbial abundance, richness and evenness increased non-linearly with τ, while functions like productivity and resource consumption declined. Taxa formed distinct clusters of short- and long-τ specialists consistent with niche partitioning. Our findings demonstrate that residence time drives biodiversity and community function in flowing habitats that are commonly found in environmental, engineered and host-associated ecosystems.

Read-Across of Biotransformation Potential between Activated Sludge and the Terrestrial Environment: Toward Making It Practical and Plausible

Recent emphasis on the development of safe-and-sustainable-by-design chemicals highlights the need for methods facilitating the early assessment of persistence. Activated sludge experiments have been proposed as a time- and resource-efficient way to predict half-lives in simulation studies. Here, this persistence "read-across" approach was developed to be more broadly and robustly applicable. We evaluated 21 previously used reference plant protection products (PPPs) for their broader applicability in calibrating regression and classification models for predicting half-lives in soil (DT50OECD307) and water-sediment systems (DT50OECD308) based on their half-life in sludge and the organic carbon-water partition coefficient KOC as predictors. The calibrated regression models showed satisfactory predictions of DT50OECD307 for another 22 test PPPs. Performance was less satisfying for the prediction of DT50OECD308 for 46 active pharmaceutical ingredients (APIs), suggesting a need for expanding the set of calibration substances and more experimental KOC values. The classification models mostly correctly classified persistent and non-persistent test compounds for both PPPs and APIs, which is relevant for early-stage screening of persistence. Transformation products of the reference compounds in activated sludge samples were consistent with the reported degradation pathways in soil, particularly with respect to major aerobic, enzyme-catalyzed transformation reactions. Overall, "reading across" biotransformation in environmental compartments such as soils or sediments from experiments with activated sludge outperformed three widely used in silico approaches for estimating half-lives and hence has immediate potential to support early assessment of biodegradability when aiming to develop chemicals that are safe and sustainable by design.

What is the Difference between Conventional Drinking Water, Potable Reuse Water, and Nonpotable Reuse Water? A Microbiome Perspective

As water reuse applications expand, there is a need for more comprehensive means to assess water quality. Microbiome analysis could provide the ability to supplement fecal indicators and pathogen profiling toward defining a "healthy" drinking water microbiota while also providing insight into the impact of treatment and distribution. Here, we utilized 16S rRNA gene amplicon sequencing to identify signature features in the composition of microbiota across a wide spectrum of water types (potable conventional, potable reuse, and nonpotable reuse). A clear distinction was found in the composition of microbiota as a function of intended water use (e.g., potable vs nonpotable) across a very broad range of U.S. water systems at both the point of compliance (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.71) and point of use (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.41). Core and discriminatory analysis further served in identifying distinct differences between potable and nonpotable water microbiomes. Taxa were identified at both the phylum (Desulfobacterota, Patescibacteria, and Myxococcota) and genus (Aeromonas and NS11.12_marine_group) levels that effectively discriminated between potable and nonpotable waters, with the most discriminatory taxa being core/abundant in nonpotable waters (with few exceptions, such as Ralstonia being abundant in potable conventional waters). The approach and findings open the door to the possibility of microbial community signature profiling as a water quality monitoring approach for assessing efficacy of treatments and suitability of water for intended use/reuse application.

Disentangling abiotic and biotic effects of treated wastewater on stream biofilm resistomes enables the discovery of a new planctomycete beta-lactamase

BACKGROUND

Environmental reservoirs of antibiotic resistance pose a threat to human and animal health. Aquatic biofilms impacted by wastewater effluent (WW) are known environmental reservoirs for antibiotic resistance; however, the relative importance of biotic factors and abiotic factors from WW on the abundance of antibiotic resistance genes (ARGs) within aquatic biofilms remains unclear. Additionally, experimental evidence is limited within complex aquatic microbial communities as to whether genes bearing low sequence similarity to validated reference ARGs are functional as ARGs.

RESULTS

To disentangle the effects of abiotic and biotic factors on ARG abundances, natural biofilms were previously grown in flume systems with different proportions of stream water and either ultrafiltered or non-ultrafiltered WW. In this study, we conducted deep shotgun metagenomic sequencing of 75 biofilm, stream, and WW samples from these flume systems and compared the taxonomic and functional microbiome and resistome composition. Statistical analysis revealed an alignment of the resistome and microbiome composition and a significant association with experimental treatment. Several ARG classes exhibited an increase in normalized metagenomic abundances in biofilms grown with increasing percentages of non-ultrafiltered WW. In contrast, sulfonamide and extended-spectrum beta-lactamase ARGs showed greater abundances in biofilms grown in ultrafiltered WW compared to non-ultrafiltered WW. Overall, our results pointed toward the dominance of biotic factors over abiotic factors in determining ARG abundances in WW-impacted stream biofilms and suggested gene family-specific mechanisms for ARGs that exhibited divergent abundance patterns. To investigate one of these specific ARG families experimentally, we biochemically characterized a new beta-lactamase from the Planctomycetota (Phycisphaeraceae). This beta-lactamase displayed activity in the cleavage of cephalosporin analog despite sharing a low sequence identity with known ARGs.

CONCLUSIONS

This discovery of a functional planctomycete beta-lactamase ARG is noteworthy, not only because it was the first beta-lactamase to be biochemically characterized from this phylum, but also because it was not detected by standard homology-based ARG tools. In summary, this study conducted a metagenomic analysis of the relative importance of biotic and abiotic factors in the context of WW discharge and their impact on both known and new ARGs in aquatic biofilms. Video Abstract.

Contaminants of emerging concern reduction and microbial community characterization across a three-barrier advanced water treatment system

This research investigated the removal of contaminants of emerging concern (CECs) and characterized the microbial community across an advanced water treatment (AWT) train consisting of Coagulation/Flocculation/Clarification/Granular Media Filtration (CFCGMF), Ozone-Biological Activated Carbon Filtration (O3/BAC), Granular Activated Carbon filtration, Ultraviolet Disinfection, and Cartridge Filtration (GAC/UV/CF). The AWT train successfully met the goals of CECs and bulk organics removal. The microbial community at each treatment step of the AWT train was characterized using 16S rRNA sequencing on the Illumina MiSeq platform generated from DNA extracted from liquid and solid (treatment media) samples taken along the treatment train. Differences in the microbial community structure were observed. The dominant operational taxonomic units (OTU) decreased along the treatment train, but the treatment steps did impact the microbial community composition downstream of each unit process. These results provide insights into microbial ecology in advanced water treatment systems, which are influenced and shaped by each treatment step, the microbial community interactions, and their potential metabolic contribution to CECs degradation.

Different Microeukaryotic Trophic Groups Show Different Latitudinal Spatial Scale Dependences in Assembly Processes across the Continental Shelves of China

The relative role of stochasticity versus determinism is critically dependent on the spatial scale over which communities are studied. However, only a few studies have attempted to reveal how spatial scales influence the balance of different assembly processes. In this study, we investigated the latitudinal spatial scale dependences in assembly processes of microeukaryotic communities in surface water and sediment along the continental shelves of China. It was hypothesized that different microeukaryotic trophic groups (i.e., autotroph, heterotroph, mixotroph, and parasite) showed different latitudinal scale dependences in their assembly processes. Our results disclosed that the relative importance of different assembly processes depended on a latitudinal space scale for planktonic microeukaryotes. In surface water, as latitudinal difference increased, the relative contributions of homogenous selection and homogenizing dispersal decreased for the entire community, while those of heterogeneous selection and drift increased. The planktonic autotrophic and heterotrophic groups shifted from stochasticity-dominated processes to heterogeneous selection as latitudinal differences surpassed thresholds of 8° and 16°, respectively. For mixotrophic and parasitic groups, however, the assembly processes were always dominated by drift across different spatial scales. The balance of different assembly processes for the autotrophic group was mainly driven by temperature, whereas that of the heterotrophic group was driven by salinity and geographical distance. In sediment, neither the entire microeukaryotic community nor the four trophic groups showed remarkable spatial scale dependences in assembly processes; they were always overwhelmingly dominated by the drift. This work provides a deeper understanding of the distribution mechanisms of microeukaryotes along the continental shelves of China from the perspective of trophic groups.

Predicting and improving the microbial removal of organic micropollutants during wastewater treatment: A review

Organic micropollutants (OMPs) consist of widely used chemicals such as pharmaceuticals and pesticides that can persist in surface and groundwaters at low concentrations (ng/L to μg/L) for a long time. The presence of OMPs in water can disrupt aquatic ecosystems and threaten the quality of drinking water sources. Wastewater treatment plants (WWTPs) rely on microorganisms to remove major nutrients from water, but their effectiveness at removing OMPs varies. Low removal efficiency might be the result of low concentrations, inherent stable chemical structures of OMPs, or suboptimal conditions in WWTPs. In this review, we discuss these factors, with special emphasis on the ongoing adaptation of microorganisms to degrade OMPs. Finally, recommendations are drawn to improve the prediction of OMP removal in WWTPs and to optimize the design of new microbial treatment strategies. OMP removal seems to be concentration-, compound-, and process-dependent, which poses a great complexity to develop accurate prediction models and effective microbial processes targeting all OMPs.

Scientific concepts and methods for moving persistence assessments into the 21st century

The evaluation of a chemical substance's persistence is key to understanding its environmental fate, exposure concentration, and, ultimately, environmental risk. Traditional biodegradation test methods were developed many years ago for soluble, nonvolatile, single-constituent test substances, which do not represent the wide range of manufactured chemical substances. In addition, the Organisation for Economic Co-operation and Development (OECD) screening and simulation test methods do not fully reflect the environmental conditions into which substances are released and, therefore, estimates of chemical degradation half-lives can be very uncertain and may misrepresent real environmental processes. In this paper, we address the challenges and limitations facing current test methods and the scientific advances that are helping to both understand and provide solutions to them. Some of these advancements include the following: (1) robust methods that provide a deeper understanding of microbial composition, diversity, and abundance to ensure consistency and/or interpret variability between tests; (2) benchmarking tools and reference substances that aid in persistence evaluations through comparison against substances with well-quantified degradation profiles; (3) analytical methods that allow quantification for parent and metabolites at environmentally relevant concentrations, and inform on test substance bioavailability, biochemical pathways, rates of primary versus overall degradation, and rates of metabolite formation and decay; (4) modeling tools that predict the likelihood of microbial biotransformation, as well as biochemical pathways; and (5) modeling approaches that allow for derivation of more generally applicable biotransformation rate constants, by accounting for physical and/or chemical processes and test system design when evaluating test data. We also identify that, while such advancements could improve the certainty and accuracy of persistence assessments, the mechanisms and processes by which they are translated into regulatory practice and development of new OECD test guidelines need improving and accelerating. Where uncertainty remains, holistic weight of evidence approaches may be required to accurately assess the persistence of chemicals. Integr Environ Assess Manag 2022;18:1454-1487. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Co-Occurrence Relationship and Stochastic Processes Affect Sedimentary Archaeal and Bacterial Community Assembly in Estuarine-Coastal Margins

Sedimentary microorganisms play crucial roles in maintaining the functional stability of aquatic ecosystems. However, their taxonomic composition and assembly processes are not well known in estuarine−coastal margins because of their complex environment. We investigated microbial communities, co-occurrence relationships, and underlying mechanisms in 33 surface sediment samples collected in the Jiulong River Estuary and the Taiwan Strait to reveal their composition dynamics. The abundance, diversity, and composition of microorganisms demonstrated obvious spatial variables. Methanobacterium and Methanosarcina, as well as Candidatus_Nitrosopumilus and Nitrososphaeraceae were the main methanogenic and ammonia-oxidizing archaea, with an average abundance of more than 5.91% and 4.27%, respectively. Along with a salinity gradient increase, the relative abundance of methanogenic archaea (from 42.9% to 16.6%) contrasted with the trend of ammonia-oxidizing archaea (from 6.04% to 18.7%). The number of methanogenic archaea gradually decreased with increasing geographic distance (p < 0.05), whereas ammonia-oxidizing archaea showed no significant change (p > 0.05). In co-occurrence patterns, closer inter-taxa connections were observed among archaea−archaea and bacteria−bacteria than in archaea−bacteria, which indicated that coexistence within the same kingdom was greater than interaction between different kingdoms in shaping the community structure along the salinity gradient. Furthermore, null model analyses of the microbial community showed that undominated was the most prominent process, explaining over 44.9% of community variation, followed by heterogeneous selection and dispersal limitation, which contributed to 27.7% and 16.3%, respectively. We demonstrated that stochasticity, rather than determinism, regulates community assembly. These results further highlight that intra-kingdom co-occurrence and stochastic processes shape the structure and assembly of microbial communities in estuarine−coastal margins.

Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture

BACKGROUND

The ability to quantitatively predict ecophysiological functions of microbial communities provides an important step to engineer microbiota for desired functions related to specific biochemical conversions. Here, we present the quantitative prediction of medium-chain carboxylate production in two continuous anaerobic bioreactors from 16S rRNA gene dynamics in enriched communities.

RESULTS

By progressively shortening the hydraulic retention time (HRT) from 8 to 2 days with different temporal schemes in two bioreactors operated for 211 days, we achieved higher productivities and yields of the target products n-caproate and n-caprylate. The datasets generated from each bioreactor were applied independently for training and testing machine learning algorithms using 16S rRNA genes to predict n-caproate and n-caprylate productivities. Our dataset consisted of 14 and 40 samples from HRT of 8 and 2 days, respectively. Because of the size and balance of our dataset, we compared linear regression, support vector machine and random forest regression algorithms using the original and balanced datasets generated using synthetic minority oversampling. Further, we performed cross-validation to estimate model stability. The random forest regression was the best algorithm producing more consistent results with median of error rates below 8%. More than 90% accuracy in the prediction of n-caproate and n-caprylate productivities was achieved. Four inferred bioindicators belonging to the genera Olsenella, Lactobacillus, Syntrophococcus and Clostridium IV suggest their relevance to the higher carboxylate productivity at shorter HRT. The recovery of metagenome-assembled genomes of these bioindicators confirmed their genetic potential to perform key steps of medium-chain carboxylate production.

CONCLUSIONS

Shortening the hydraulic retention time of the continuous bioreactor systems allows to shape the communities with desired chain elongation functions. Using machine learning, we demonstrated that 16S rRNA amplicon sequencing data can be used to predict bioreactor process performance quantitatively and accurately. Characterizing and harnessing bioindicators holds promise to manage reactor microbiota towards selection of the target processes. Our mathematical framework is transferrable to other ecosystem processes and microbial systems where community dynamics is linked to key functions. The general methodology used here can be adapted to data types of other functional categories such as genes, transcripts, proteins or metabolites. Video Abstract.

Toward Characterizing the Genetic Basis of Trace Organic Contaminant Biotransformation in Activated Sludge: The Role of Multicopper Oxidases as a Case Study

Activated sludge treatment leverages the ability of microbes to uptake and (co)-metabolize chemicals and has shown promise in eliminating trace organic contaminants (TrOCs) during wastewater treatment. However, targeted interventions to optimize the process are limited as the fundamental drivers of the observed reactions remain elusive. In this work, we present a comprehensive workflow for the identification and characterization of key enzymes involved in TrOCs biotransformation pathways in complex microbial communities. To demonstrate the applicability of the workflow, we investigated the role of the enzymatic group of multicopper oxidases (MCOs) as one putatively relevant driver of TrOCs biotransformation. To this end, we analyzed activated sludge metatranscriptomic data and selected, synthesized, and heterologously expressed three phylogenetically distinct MCO-encoding genes expressed in communities with different TrOCs oxidation potentials. Following the purification of the encoded enzymes, we screened their activities against different substrates. We saw that MCOs exhibit significant activities against selected TrOCs in the presence of the mediator compound 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid and, in some cases, also in the presence of the wastewater contaminant 4'-hydroxy-benzotriazole. In the first case, we identified oxidation products previously reported from activated sludge communities and concluded that in the presence of appropriate mediators, bacterial MCOs could contribute to the biological removal of TrOCs. Similar investigations of other key enzyme systems may significantly advance our understanding of TrOCs biodegradation and assist the rational design of biology-based water treatment strategies in the future.

Mapping soil microbial residence time at the global scale

Soil microbes are the fundamental engine for carbon (C) cycling. Microbial residence time (MRT) therefore determines the mineralization of soil organic C, releasing C as heterotrophic respiration and contributing substantially to the C efflux in terrestrial ecosystems. We took use of a comprehensive dataset (2627 data points) and calculated the MRT based on the basal respiration and microbial biomass C. Large variations in MRT were found among biomes, with the largest MRT in boreal forests and grasslands and smallest in natural wetlands. Biogeographic patterns of MRT were found along climate variables (temperature and precipitation), vegetation variables (root C density and net primary productivity), and edaphic factors (soil texture, pH, topsoil porosity, soil C, and total nitrogen). Among environmental factors, edaphic properties dominate the MRT variations. We further mapped the MRT at the global scale with an empirical model. The simulated and observed MRT were highly consistent at plot- (R² = .86), site- (R²  = .88), and biome- (R²  = .99) levels. The global average of MRT was estimated to be 38 (±5) days. A clear latitudinal biogeographic pattern was found for MRT with lower values in tropical regions and higher values in the Arctic. The biome- and global-level estimates of MRT serve as valuable data for parameterizing and benchmarking microbial models.

Microbial river-to-sea continuum: gradients in benthic and planktonic diversity, osmoregulation and nutrient cycling

BACKGROUND

Coastal aquatic ecosystems include chemically distinct, but highly interconnected environments. Across a freshwater-to-marine transect, aquatic communities are exposed to large variations in salinity and nutrient availability as tidal cycles create periodic fluctuations in local conditions. These factors are predicted to strongly influence the resident microbial community structure and functioning, and alter the structure of aquatic food webs and biogeochemical cycles. Nevertheless, little is known about the spatial distribution of metabolic properties across salinity gradients, and no study has simultaneously surveyed the sediment and water environments. Here, we determined patterns and drivers of benthic and planktonic prokaryotic and microeukaryotic community assembly across a river and tidal lagoon system by collecting sediments and planktonic biomass at nine shallow subtidal sites in the summer. Genomic and transcriptomic analyses, alongside a suite of complementary geochemical data, were used to determine patterns in the distribution of taxa, mechanisms of salt tolerance, and nutrient cycling.

RESULTS

Taxonomic and metabolic profiles related to salt tolerance and nutrient cycling of the aquatic microbiome were found to decrease in similarity with increasing salinity, and distinct trends in diversity were observed between the water column and sediment. Non-saline and saline communities adopted divergent strategies for osmoregulation, with an increase in osmoregulation-related transcript expression as salinity increased in the water column due to lineage-specific adaptations to salt tolerance. Results indicated a transition from phosphate limitation in freshwater habitats to nutrient-rich conditions in the brackish zone, where distinct carbon, nitrogen and sulfur cycling processes dominated. Phosphorus acquisition-related activity was highest in the freshwater zone, along with dissimilatory nitrate reduction to ammonium in freshwater sediment. Activity associated with denitrification, sulfur metabolism and photosynthesis were instead highest in the brackish zone, where photosynthesis was dominated by distinct microeukaryotes in water (Cryptophyta) and sediment (diatoms). Despite microeukaryotes and archaea being rare relative to bacteria, results indicate that they contributed more to photosynthesis and ammonia oxidation, respectively.

CONCLUSIONS

Our study demonstrates clear freshwater-saline and sediment-water ecosystem boundaries in an interconnected coastal aquatic system and provides a framework for understanding the relative importance of salinity, planktonic-versus-benthic habitats and nutrient availability in shaping aquatic microbial metabolic processes, particularly in tidal lagoon systems. Video abstract.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Association between Aquatic Micropollutant Dissipation and River Sediment Bacterial Communities

Assessment of micropollutant biodegradation is essential to determine the persistence of potentially hazardous chemicals in aquatic ecosystems. We studied the dissipation half-lives of 10 micropollutants in sediment-water incubations (based on the OECD 308 standard) with sediment from two European rivers sampled upstream and downstream of wastewater treatment plant (WWTP) discharge. Dissipation half-lives (DT50s) were highly variable between the tested compounds, ranging from 1.5 to 772 days. Sediment from one river sampled downstream from the WWTP showed the fastest dissipation of all micropollutants after sediment RNA normalization. By characterizing sediment bacteria using 16S rRNA sequences, bacterial community composition of a sediment was associated with its capacity for dissipating micropollutants. Bacterial amplicon sequence variants of the genera Ralstonia, Pseudomonas, Hyphomicrobium, and Novosphingobium, which are known degraders of contaminants, were significantly more abundant in the sediment incubations where fast dissipation was observed. Our study illuminates the limitations of the OECD 308 standard to account for variation of dissipation rates of micropollutants due to differences in bacterial community composition. This limitation is problematic particularly for those compounds with DT50s close to regulatory persistence criteria. Thus, it is essential to consider bacterial community composition as a source of variability in regulatory biodegradation and persistence assessments.

Substratum-associated microbiota

Highlights of new, interesting, and emerging research findings on substratum-associated microbiota covered from a survey of 2019 literature from primarily freshwaters provide insight into research trends of interest to the Water Environment Federation and others interested in benthic, aquatic environments. Coverage of topics on bottom-associated or attached algae and cyanobacteria, though not comprehensive, includes new methods, taxa new-to-science, nutrient dynamics, auto- and heterotrophic interactions, grazers, bioassessment, herbicides and other pollutants, metal contaminants, and nuisance, and bloom-forming and harmful algae. Coverage of bacteria, also not comprehensive, focuses on the ecology of benthic biofilms and microbial communities, along with the ecology of microbes like Caulobacter crescentus, Rhodobacter, and other freshwater microbial species. Bacterial topics covered also include metagenomics and metatranscriptomics, toxins and pollutants, bacterial pathogens and bacteriophages, and bacterial physiology. Readers may use this literature review to learn about or renew their interest in the recent advances and discoveries regarding substratum-associated microbiota. PRACTITIONER POINTS: This review of literature from 2019 on substratum-associated microbiota presents highlights of findings on algae, cyanobacteria, and bacteria from primarily freshwaters. Coverage of algae and cyanobacteria includes findings on new methods, taxa new to science, nutrient dynamics, auto- and heterotrophic interactions, grazers, bioassessment, herbicides and other pollutants, metal contaminants, and nuisance, bloom-forming and harmful algae. Coverage of bacteria includes findings on ecology of benthic biofilms and microbial communities, the ecology of microbes, metagenomics and metatranscriptomics, toxins and pollutants, bacterial pathogens and bacteriophages, and bacterial physiology. Highlights of new, noteworthy and emerging topics build on those from 2018 and will be of relevance to the Water Environment Federation and others interested in benthic, aquatic environments.

Comparison of Small Molecule Biotransformation Half-Lives between Activated Sludge and Soil: Opportunities for Read-Across?

Compartment-specific degradation half-lives are essential pieces of information in the regulatory risk assessment of synthetic chemicals. However, their measurement according to regulatory testing guidelines is laborious and costly. Despite the obvious ecological and economic benefits of knowing environmental degradability as early as possible, its consideration in the early phases of rational chemical design is therefore challenging. Here, we explore the possibility to use half-lives determined in highly time- and work-efficient biotransformation experiments with activated sludge and mixtures of chemicals to predict soil half-lives from regulatory simulation studies. We experimentally determined half-lives for 52 structurally diverse agrochemical active ingredients in batch reactors with three concentrations of the same activated sludge. We then developed bi- and multivariate models for predicting half-lives in soil by regressing the experimentally determined half-lives in activated sludge against average soil half-lives of the same chemicals extracted from regulatory data. The models differed in how we accounted for sorption-related bioavailability differences in soil and activated sludge. The best-performing models exhibited good coefficients of determination (R² of around 0.8) and low average errors (<factor of 3 in half-life predictions) and were robust in cross-validation. From a practical perspective, these results suggest that it may indeed be possible to read across from half-lives determined in highly efficient biotransformation experiments in activated sludge to soil half-lives, which are obtained from much more work- and resource-intense regulatory studies, and that these predictions are clearly superior to predictions based on the output of BIOWIN, a publicly available quantitative structure-biodegradation relationship (QSBR) model. From a theoretical perspective, these results suggest that soil and activated sludge microbial communities, although certainly different in terms of taxonomic composition, may be functionally similar with respect to the enzymatic transformation of environmentally relevant concentrations of a diverse range of chemical compounds.

Unveiling microbial structures during raw microalgae digestion and co-digestion with primary sludge to produce biogas using semi-continuous AnMBR systems

Methane production from microalgae can be enhanced through anaerobic co-digestion with carbon-rich substrates and thus mitigate the inhibition risk associated with its low C:N ratio. Acclimated microbial communities for microalgae disruption can be used as a source of natural enzymes in bioenergy production. However, co-substrates with a certain microbial diversity such as primary sludge might shift the microbial structure. Substrates were generated in a Water Resource Recovery Facility (WRRF) and combined as follows: Scenedesmus or Chlorella digestion and microalgae co-digestion with primary sludge. The study was performed using two lab-scale Anaerobic Membrane Bioreactors (AnMBR). During three years, different feedstocks scenarios for methane production were evaluated with a special focus on the microbial diversity of the AnMBR. 57% of the population was shared between the different feedstock scenarios, revealing the importance of Anaerolineaceae members besides Smithella and Methanosaeta genera. The addition of primary sludge enhanced the microbial diversity of the system during both Chlorella and Scenedesmus co-digestion and promoted different microbial structures. Aceticlastic methanogen Methanosaeta was dominant in all the feedstock scenarios. A more remarkable role of syntrophic fatty acid degraders (Smithella, Syntrophobacteraceae) was observed during co-digestion when only microalgae were digested. However, no significant changes were observed in the microbial composition during anaerobic microalgae digestion when feeding only Chlorella or Scenedesmus. This is the first work revealing the composition of complex communities for semi-continuous bioenergy production from WRRF streams. The stability and maintenance of a microbial core over-time in semi-continuous AnMBRs is here shown supporting their future application in full-scale systems for raw microalgae digestion or co-digestion.

Relating Metatranscriptomic Profiles to the Micropollutant Biotransformation Potential of Complex Microbial Communities

Biotransformation of chemical contaminants is of importance in various natural and engineered systems. However, in complex microbial communities and with chemical contaminants at low concentrations, our current understanding of biotransformation at the level of enzyme-chemical interactions is limited. Here, we explored an approach to identify associations between micropollutant biotransformation and specific gene products in complex microbial communities, using association mining between chemical and metatranscriptomic data obtained from experiments with activated sludge grown at different solid retention times. We successfully demonstrate proportional relationships between the measured rate constants and associated gene transcripts for nitrification as a major community function, but also for the biotransformation of two nitrile-containing micropollutants (bromoxynil and acetamiprid) and transcripts of nitrile hydratases, a class of enzymes that we experimentally confirmed to produce the detected amide transformation products. As these results suggest that metatranscriptomic information can indeed be quantitatively correlated with low abundant community functions such as micropollutant biotransformation in complex microbial communities, we proceeded to explore the potential of association mining to highlight enzymes likely involved in catalyzing less well-understood micropollutant biotransformation reactions. Specifically, we use the cases of nitrile hydration and oxidative biotransformation reactions to show that the consideration of additional experimental evidence (such as information on biotransformation pathways) increases the likelihood of detecting plausible novel enzyme-chemical relationships. Finally, we identify a cluster of mono- and dioxygenase fourth-level enzyme classes that most strongly correlate with oxidative micropollutant biotransformation reactions in activated sludge.

Investigation of the process stability of different anammox configurations and assessment of the simulation validity of various anammox-based kinetic models

Over the last 30 years, the successful implementation of the anammox process has attracted research interest from all over the world. Various reactor configurations were investigated for the anammox process. However, the construction of the anammox process is a delicate topic in regards to the high sensitivity of the biological reaction. To better understand the effects of configurations on the anammox performance, process-kinetic models and activity kinetic models were critically overviewed, respectively. A significant difference in the denitrification capabilities was observed even with similar dominated functional species of anammox with different configurations. Although the kinetic analysis gained insight into the feasibility of both batch and continuous processes, most models were often applied to match the kinetic data in an unsuitable manner. The validity assessment illustrated that the Grau second-order model and Stover–Kincannon model were the most appropriate and shareable reactor-kinetic models for different anammox configurations. This review plays an important role in the anammox process performance assessment and augmentation of the process control.

Over the last 30 years, the successful implementation of the anammox process has attracted research interest from all over the world.

Gene Transmission in the One Health Microbiosphere and the Channels of Antimicrobial Resistance

Antibiotic resistance is a field in which the concept of One Health can best be illustrated. One Health is based on the definition of communication spaces among diverse environments. Antibiotic resistance is encoded by genes, however, these genes are propagated in mobile genetic elements (MGEs), circulating among bacterial species and clones that are integrated into the multiple microbiotas of humans, animals, food, sewage, soil, and water environments, the One Health microbiosphere. The dynamics and evolution of antibiotic resistance depend on the communication networks linking all these ecological, biological, and genetic entities. These communications occur by environmental overlapping and merging, a critical issue in countries with poor sanitation, but also favored by the homogenizing power of globalization. The overwhelming increase in the population of highly uniform food animals has contributed to the parallel increase in the absolute size of their microbiotas, consequently enhancing the possibility of microbiome merging between humans and animals. Microbial communities coalescence might lead to shared microbiomes in which the spread of antibiotic resistance (of human, animal, or environmental origin) is facilitated. Intermicrobiome communication is exerted by shuttle bacterial species (or clones within species) belonging to generalist taxa, able to multiply in the microbiomes of various hosts, including humans, animals, and plants. Their integration into local genetic exchange communities fosters antibiotic resistance gene flow, following the channels of accessory genome exchange among bacterial species. These channels delineate a topology of gene circulation, including dense clusters of species with frequent historical and recent exchanges. The ecological compatibility of these species, sharing the same niches and environments, determines the exchange possibilities. In summary, the fertility of the One Health approach to antibiotic resistance depends on the progress of understanding multihierarchical systems, encompassing communications among environments (macro/microaggregates), among microbiotas (communities), among bacterial species (clones), and communications among MGEs.

Multi-omics analysis reveals niche and fitness differences in typical denitrification microbial aggregations

Suspended floc and fixed biofilm are two commonly applied strategies for heterotrophic denitrification in wastewater treatment. These two strategies use different carbon sources and reside within different ecological niches for microbial aggregation, which were hypothesized to show distinct microbial structures and metabolic fitness. We surveyed three floc reactors and three biofilm reactors for denitrification and determined if there were distinct microbial aggregations. Multiple molecular omics approaches were used to determine the microbial community composition, co-occurrence network and metabolic pathways. Proteobacteria was the dominating and most active phylum among all samples. Carbon source played an important role in shaping the microbial community composition while the distribution of functional protein was largely influenced by salinity. We found that the topological network features had different ecological patterns and that the microorganisms in the biofilm reactors had more nodes but less interactions than those in floc reactors. The large niche differences in the biofilm reactors explained the observed high microbial diversity, functional redundancy and resulting high system stability. We also observed a lower proportion of denitrifiers and higher resistance to oxygen and salinity perturbation in the biofilm reactors than the floc reactors. Our findings support our hypothesis that niche differences caused a distinct microbial structure and increased microbial ecology distribution, which has the potential to improve system efficiency and stability.

Exploring the effects of operational mode and microbial interactions on bacterial community assembly in a one-stage partial-nitritation anammox reactor using integrated multi-omics

BACKGROUND

The metabolic capacities of anammox bacteria and associated microbial community interactions in partial-nitritation anammox (PNA) reactors have received considerable attention for their crucial roles in energy-efficient nitrogen removal from wastewater. However, a comprehensive understanding of how abiotic and biotic factors shape bacterial community assembly in PNA reactors is not well reported.

RESULTS

Here, we used integrated multi-omics (i.e., high-throughput 16S rRNA gene, metagenomic, metatranscriptomic, and metaproteomic sequencing) to reveal how abiotic and biotic factors shape the bacterial community assembly in a lab-scale one-stage PNA reactor treating synthetic wastewater. Analysis results of amplicon sequences (16S rRNA gene) from a time-series revealed distinct relative abundance patterns of the key autotrophic bacteria, i.e., anammox bacteria and ammonia-oxidizing bacteria (AOB), and the associated heterotrophic populations in the seed sludge and the sludge at the new stable state after deterioration. Using shotgun metagenomic sequences of anammox sludge, we recovered 58 metagenome-assembled genomes (MAGs), including 3 MAGs of anammox bacteria and 3 MAGs of AOB. The integrated metagenomic, metatranscriptomic, and metaproteomic data revealed that nitrogen metabolism is the most active process in the studied PNA reactor. The abundant heterotrophs contribute to the reduction of nitrate to nitrite/ammonium for autotrophic bacteria (anammox bacteria and AOB). Genomic and transcriptomic data revealed that the preference for electron donors of the dominant heterotrophs in different bacterial assemblages (seed and new stable state) varied along with the shift in anammox bacteria that have different metabolic features in terms of EPS composition. Notably, the most abundant heterotrophic bacteria in the reactor were more auxotrophic than the less abundant heterotrophs, regarding the syntheses of amino acids and vitamins. In addition, one of the abundant bacteria observed in the bacterial community exhibited highly transcribed secretion systems (type VI).

CONCLUSIONS

These findings provide the first insight that the bacterial communities in the PNA reactor are defined by not only abiotic factors (operating mode) but also metabolic interactions, such as nitrogen metabolism, exchange of electron donors, and auxotrophies.