A Single-Granule-Level Approach Reveals Ecological Heterogeneity in an Upflow Anaerobic Sludge Blanket Reactor

Individual methanogenic granules are whole-ecosystem replicates with reproducible responses to environmental cues

BACKGROUND

In this study, individual methanogenic (anaerobic), granular biofilms were used as true community replicates to assess whole-microbial-community responses to environmental cues. The aggregates were sourced from a lab-scale, engineered, biological wastewater treatment system, were size-separated, and the largest granules were individually subjected to controlled environmental cues in micro-batch reactors (μBRs).

RESULTS

Individual granules were identical with respect to the structure of the active community based on cDNA analysis. Additionally, it was observed that the active microbial community of individual granules, at the depth of 16S rRNA gene sequencing, produced reproducible responses to environmental changes in pH, temperature, substrate, and trace-metal supplementation. We identified resilient and susceptible taxa associated with each environmental condition tested, as well as selected specialists, whose niche preferences span the entire trophic chain required for the complete anaerobic degradation of organic matter.

CONCLUSIONS

We found that single anaerobic granules can be considered highly-replicated whole-ecosystems with potential usefulness for the field of microbial ecology. Additionally, they act as the smallest whole-community unit within the meta-community of an engineered bioreactor. When subjected to various environmental cues, anaerobic granules responded reproducibly allowing for rare or unique opportunities for high-throughput studies testing whole-community responses to a wide range of environmental conditions.

Nondestructive and three-dimensional visualization by identifying elements using synchrotron radiation microscale X-ray CT reveals microbial and cavity distributions in anaerobic granular sludge

We developed a nondestructive three-dimensional microbial visualization method utilizing synchrotron radiation X-ray microscale computed tomography to better understand the relationship between microorganisms and their surrounding habitats. The method was tested and optimized using a mixture of axenic Escherichia coli and Comamonas testosteroni. The osmium-thiocarbohydrazide-osmium method was used to stain all the microbial cells, and gold in situ hybridization was used to detect specific phylogenetic microbial groups. The stained samples were embedded in epoxy resin for microtomographic analysis. Differences in X-ray absorbances were calculated by subtracting the pre-L3-edge images from the post-L3-edge images to visualize the osmium and gold signals. Although we successfully detected cells stained with osmium, those labeled with gold were not detected, probably because of the insufficient density of gold atoms in the microbial cells. We then applied the developed technique to anaerobic granules and visualized the distribution of microbial cells and extracellular polymeric substances. Empty spaces were highlighted to determine the cavity distribution in granules. Numerous independent cavities of different sizes were identified in the granules. The developed method can be applied to various environmental samples for deeper insights into microbial life in their habitats.

IMPORTANCE

Microorganisms inhabit diverse environments and often form biofilms. One factor that affects their community structure is the surrounding physical environment. The arrangement of residential space within the formed biofilm plays a crucial role in the supply and transportation of substances, as well as the discharge of metabolites. Conventional approaches, such as scanning electron microscopy and confocal laser scanning microscopy combined with fluorescence in situ hybridization, have limitations as they provide information primarily from the biofilm surface and cross-sections. In this study, we developed a method for detecting microorganisms in biofilms using synchrotron radiation X-ray microscale computer tomography. The developed method allows nondestructive three-dimensional observation of biofilms at a single-cell resolution (voxel size of approximately 200 nm), facilitating an understanding of the relationship between microorganisms and their physical habitats.

Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches

In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.

Development of an internal two-stage upflow anaerobic reactor integrating biostimulation strategies to enhance the degradation of aromatic compounds in wastewater from purified terephthalic acid and dimethyl terephthalate manufacturing processes

In this study, we aimed to establish high-rate biological treatment of purified terephthalic acid (PTA) and dimethyl terephthalate (DMT) wastewater that minimizes the inhibitory effects of high concentration benzoate and acetate. To achieve this, we developed a novel bioreactor system and biostimulation strategy. An internal two-stage upflow anaerobic (ITUA) reactor was operated with (i) a packed bed containing green tuff medium underlying (ii) a compartment seeded with anaerobic granular sludge. Ethylene glycol was amended to stimulate syntrophic interactions. Continuous operation of the system for 1,026 days achieve an organic removal rate of 11.0 ± 0.6 kg COD/m3/d. The abundance of aromatic degraders significantly increased during operation. Thus, we successfully developed a high-rate treatment system to treat wastewater from the PTA/DMT manufacturing processes by activating syntrophs in an ITUA reactor.

Current status and future developments of assessing microbiome composition and dynamics in anaerobic digestion systems using metagenomic approaches

The metagenomic approach stands as a powerful technique for examining the composition of microbial communities and their involvement in various anaerobic digestion (AD) systems. Understanding the structure, function, and dynamics of microbial communities becomes pivotal for optimizing the biogas process, enhancing its stability and improving overall performance. Currently, taxonomic profiling of biogas-producing communities relies mainly on high-throughput 16S rRNA sequencing, offering insights into the bacterial and archaeal structures of AD assemblages and their correlations with fed substrates and process parameters. To delve even deeper, shotgun and genome-centric metagenomic approaches are employed to recover individual genomes from the metagenome. This provides a nuanced understanding of collective functionalities, interspecies interactions, and microbial associations with abiotic factors. The application of OMICs in AD systems holds the potential to revolutionize the field, leading to more efficient and sustainable waste management practices particularly through the implementation of precision anaerobic digestion systems. As ongoing research in this area progresses, anticipations are high for further exciting developments in the future. This review serves to explore the current landscape of metagenomic analyses, with focus on advancing our comprehension and critically evaluating biases and recommendations in the analysis of microbial communities in anaerobic digesters. Its objective is to explore how contemporary metagenomic approaches can be effectively applied to enhance our understanding and contribute to the refinement of the AD process. This marks a substantial stride towards achieving a more comprehensive understanding of anaerobic digestion systems.

Unifying concepts in methanogenic, aerobic, and anammox sludge granulation

The retention of dense and well-functioning microbial biomass is crucial for effective pollutant removal in several biological wastewater treatment technologies. High solids retention is often achieved through aggregation of microbial communities into dense, spherical aggregates known as granules, which were initially discovered in the 1980s. These granules have since been widely applied in upflow anaerobic digesters for waste-to-energy conversions. Furthermore, granular biomass has been applied in aerobic wastewater treatment and anaerobic ammonium oxidation (anammox) technologies. The mechanisms underpinning the formation of methanogenic, aerobic, and anammox granules are the subject of ongoing research. Although each granule type has been extensively studied in isolation, there has been a lack of comparative studies among these granulation processes. It is likely that there are some unifying concepts that are shared by all three sludge types. Identifying these unifying concepts could allow a unified theory of granulation to be formed. Here, we review the granulation mechanisms of methanogenic, aerobic, and anammox granular sludge, highlighting several common concepts, such as the role of extracellular polymeric substances, cations, and operational parameters like upflow velocity and shear force. We have then identified some unique features of each granule type, such as different internal structures, microbial compositions, and quorum sensing systems. Finally, we propose that future research should prioritize aspects of microbial ecology, such as community assembly or interspecies interactions in individual granules during their formation and growth.

Insights into the composition and assembly mechanism of microbial communities on intertidal microsand grains

Introduction

Marine microorganisms are essential in marine ecosystems and have always been of interest. Currently, most marine microbial communities are studied at the bulk scale (millimeters to centimeters), and the composition, function and underlying assembly mechanism of microbial communities at the microscale (sub-100 micrometers) are unclear.

Methods

The microbial communities on microsand grains (40-100 µm, n = 150) from marine sediment were investigated and compared with those on macrosand grains (400-1000 µm, n = 60) and bulk sediments (n = 5) using amplicon sequencing technology.

Results

The results revealed a significant difference between microsand grains and macrosand grains. Microsand grains had lower numbers of operational taxonomic units (OTUs(97%)) and predicted functional genes than macrosand grains and bulk-scale samples. Microsand grains also showed greater intersample differences in the community composition and predicted functional genes than macrosand grains, suggesting a high level of heterogeneity of microbial communities at the microscale. Analyses based on ecological models indicated that stochastic processes dominated the assembly of microbial communities on sand grains. Consistently, cooccurrence network analyses showed that most microbial cooccurrence associations on sand grains were highly unstable. Metagenomic sequencing and further genome-scale metabolic modeling revealed that only a small number (1.3%) of microbe pairs showed high cooperative potential.

Discussion

This study explored the microbial community of marine sediments at the sub-100 µm scale, broadening the knowledge of the structure and assembly mechanism of marine microbial communities.

Micron-scale biogeography reveals conservative intra anammox bacteria spatial co-associations

Micron-scale resolution can help to reliably identify true taxon-taxon interactions in complex microbial communities. Despite widespread recognition of the critical role of metabolic interactions in anaerobic ammonium oxidation (anammox) system performance, no studies have examined microbial interactions at the micron-scale in anammox consortia. To fill this gap, we extensively sampled (totally 242 samples) the consortia of a lab-scale anammox reactor at different length scales, including bulk-scale (∼cm), macro-scale (300-500 µm) and micron-scale (70-100 µm). We firstly observed evident micron-scale heterogeneity in anammox consortia, with the relative abundance of anammox bacteria fluctuated greatly across individual clusters (2.0%-79.3%), indicating that the biotic interactions play a significant role in the assembly of anammox communities under well-controlled and well-mixed condition. Importantly, by mapping the spatial associations in anammox consortia at micron-scale, we demonstrated that the conserved co-associations for anammox bacteria were restricted to three different Brocadia species over time, and their co-associations with heterotrophs were random, implying that there was no statistically significant symbiotic interaction between anammox bacteria and other heterotrophic populations. Further metagenomic binning revealed that the quorum sensing with secondary messenger c-di-GMP potentially holding on the conservative metabolic cooperation among Brocadia species. These results shed new light on the social behavior of the anammox community. Overall, delineating of biological structures at micron-scale opens a new way of monitoring the microbial spatial structure and interactions, paving the way for improved community engineering of biotreatment systems.

High-rate cotreatment of purified terephthalate and dimethyl terephthalate manufacturing wastewater by a mesophilic upflow anaerobic sludge blanket reactor and the microbial ecology relevant to aromatic compound degradation

Polyethylene terephthalate (PET) is produced worldwide, mainly as material for plastic drink bottles. PET is produced by polymerization of purified terephthalate (PTA) or dimethyl terephthalate (DMT) with ethylene glycol. During the synthetic manufacturing processes of PTA and DMT, high organic loading wastewater is produced, which is typically treated separately by anaerobic wastewater treatment technologies. Given the high demand for PET, manufacturing plants are expanding globally, which will result in an increase in the amounts of PTA and DMT wastewater in need of treatment. In terms of effective treatment, the cotreatment of PTA and DMT wastewater has several advantages, including lower area and energy requirements. In this study, we examined the performance of an upflow anaerobic sludge blanket (UASB) reactor in cotreating PTA and DMT wastewater with high organic loading, evaluating its removal characteristics after 518 days of continuous operation. In addition, we performed a microbiome analysis of the UASB granular sludge to uncover the microbial interactions and metabolic functions within the reactor. By continuous operation, we achieved an organic removal rate of 6.6 kg m^-3 day^-1. In addition, we confirmed that aromatic compounds in the complex wastewater from the PTA and DMT manufacturing processes are biodegradable in the following order: benzoate > orthophthalate > terephthalate > isophthalate > p-toluic acid. 16S rRNA gene-based network analysis shows that anaerobic Woesearchaeales belonging to phylum Nanoarchaeota has a positive correlation with Methanoregula, Candidatus Methanofastidiosum, and Methanosarcina, suggesting a symbiotic relationship with methanogens in granular sludge. Shotgun metagenomic analysis revealed that terephthalate, isophthalate/orthophthalate, and benzoate were degraded by different members of Pelotomaculaceae and Syntrophorhabdaceae. According to the genomic information, we propose two new possible routes for orthophthalate degradation by the Syntrophorhabdaceae organism.

Ecogenomics Reveals Microbial Metabolic Networks in a Psychrophilic Methanogenic Bioreactor Treating Soy Sauce Production Wastewater

An ecogenomic analysis of the methanogenic microbial community in a laboratory-scale up-flow anaerobic sludge blanket (UASB) reactor treating soy sauce-processing wastewater revealed a synergistic metabolic network. Granular sludge samples were collected from the UASB reactor operated under psychrophilic (20°C) conditions with a COD removal rate >75%. A 16S rRNA gene amplicon sequencing-based microbial community analysis classified the major microbial taxa as Methanothrix, Methanobacterium, Pelotomaculaceae, Syntrophomonadaceae, Solidesulfovibrio, and members of the phyla Synergistota and Bacteroidota. Draft genomes of dominant microbial populations were recovered by metagenomic shotgun sequencing. Metagenomic- and metatranscriptomic-assisted metabolic reconstructions indicated that Synergistota- and Bacteroidota-related organisms play major roles in the degradation of amino acids. A metagenomic bin of the uncultured Bacteroidales 4484-276 clade encodes genes for proteins that may function in the catabolism of phenylalanine and tyrosine under microaerobic conditions. Syntrophomonadaceae and Pelotomaculaceae oxidize fatty acid byproducts presumably derived from the degradation of amino acids in syntrophic association with aceticlastic and hydrogenotrophic methanogen populations. Solidesulfovibrio organisms are responsible for the reduction of sulfite and may support the activity of hydrogenotrophic methanogens and other microbial populations by providing hydrogen and ammonia using nitrogen fixation-related proteins. Overall, functionally diverse anaerobic organisms unite to form a metabolic network that performs the complete degradation of amino acids in the psychrophilic methanogenic microbiota.

Mapping the biological activities of filamentous oxygenic photogranules

Oxygenic photogranules have been suggested as alternatives to activated sludge in wastewater treatment. Challenging for modeling photogranule-based processes is the heterogeneity of photogranule morphologies, resulting in different activities by photogranule type. The measurement of microscale-activities of filamentous photogranules is particularly difficult because of their labile interfaces. We present here an experimental and modeling approach to quantify phototrophic O₂ production, heterotrophic O₂ consumption, and O₂ diffusion in filamentous photogranules. We used planar optodes for the acquisition of spatio-temporal oxygen distributions combined with two-dimensional mathematical modeling. Light penetration into the photogranule was the factor controlling photogranule activities. The spatial distribution of heterotrophs and phototrophs had less impact. The photosynthetic response of filaments to light was detectable within seconds, emphasizing the need to analyze dynamics of light exposure of individual photogranules in photobioreactors. Studying other recurring photogranule morphologies will eventually enable the description of photogranule-based processes as the interplay of interacting photogranule populations.

Growth and Break-Up of Methanogenic Granules Suggests Mechanisms for Biofilm and Community Development

Methanogenic sludge granules are densely packed, small, spherical biofilms found in anaerobic digesters used to treat industrial wastewaters, where they underpin efficient organic waste conversion and biogas production. Each granule theoretically houses representative microorganisms from all of the trophic groups implicated in the successive and interdependent reactions of the anaerobic digestion (AD) process. Information on exactly how methanogenic granules develop, and their eventual fate will be important for precision management of environmental biotechnologies. Granules from a full-scale bioreactor were size-separated into small (0.6-1 mm), medium (1-1.4 mm), and large (1.4-1.8 mm) size fractions. Twelve laboratory-scale bioreactors were operated using either small, medium, or large granules, or unfractionated sludge. After >50 days of operation, the granule size distribution in each of the small, medium, and large bioreactor sets had diversified beyond-to both bigger and smaller than-the size fraction used for inoculation. Interestingly, extra-small (XS; <0.6 mm) granules were observed, and retained in all of the bioreactors, suggesting the continuous nature of granulation, and/or the breakage of larger granules into XS bits. Moreover, evidence suggested that even granules with small diameters could break. "New" granules from each emerging size were analyzed by studying community structure based on high-throughput 16S rRNA gene sequencing. Methanobacterium, Aminobacterium, Propionibacteriaceae, and Desulfovibrio represented the majority of the community in new granules. H2-using, and not acetoclastic, methanogens appeared more important, and were associated with abundant syntrophic bacteria. Multivariate integration (MINT) analyses identified distinct discriminant taxa responsible for shaping the microbial communities in different-sized granules.

Chemically Stressed Bacterial Communities in Anaerobic Digesters Exhibit Resilience and Ecological Flexibility

Anaerobic digestion is a technology known for its potential in terms of methane production. During the digestion process, multiple metabolites of high value are synthesized. However, recent works have demonstrated the high robustness and resilience of the involved microbiomes; these attributes make it difficult to manipulate them in such a way that a specific metabolite is predominantly produced. Therefore, an exact understanding of the manipulability of anaerobic microbiomes may open up a treasure box for bio-based industries. In the present work, the effect of nalidixic acid, γ-aminobutyric acid (GABA), and sodium phosphate on the microbiome of digested sewage sludge from a water treatment plant fed with glucose was investigated. Despite of the induced process perturbations, high stability was observed at the phylum level. However, strong variations were observed at the genus level, especially for the genera Trichococcus, Candidatus Caldatribacterium, and Phascolarctobacterium. Ecological interactions were analyzed based on the Lotka–Volterra model for Trichococcus, Rikenellaceae DMER64, Sedimentibacter, Candidatus Cloacimonas, Smithella, Cloacimonadaceae W5 and Longilinea. These genera dynamically shifted among positive, negative or no correlation, depending on the applied stressor, which indicates a surprisingly dynamic behavior. Globally, the presented work suggests a massive resilience and stability of the methanogenic communities coupled with a surprising flexibility of the particular microbial key players involved in the process.

Molecular and microbial insights towards understanding the anaerobic digestion of the wastewater from hydrothermal liquefaction of sewage sludge facilitated by granular activated carbon (GAC)

Hydrothermal liquefaction of sewage sludge to produce bio-oil and hydro-char unavoidably results in the production of high-strength organic wastewater (HTLWW). However, anaerobic digestion (AD) of HTLWW generally has low conversion efficiency due to the presence of complex and refractory organics. The present study showed that granular activated carbon (GAC) promoted the AD of HTLWW in continuous experiments, resulting in the higher methane yield (259 mL/g COD) compared to control experiment (202 mL/g COD). It was found that GAC increased the activities of both aceticlastic and hydrogenotrophic methanogens. The molecular transformation of organics in HTLWW was further analyzed. It was shown GAC promoted the degradation of soluble microbial by-products, fulvic- and humic-like substances as revealed by 3-dimensional fluorescence excitation-emission matrix (3D-EEM) analysis. Gas chromatography mass spectrometry (GC-MS) analysis showed that GAC resulted in the higher degradation of N-heterocyclic compounds, acids and aromatic compounds and less production of new organic species. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) analysis also showed that GAC promoted the degradation of nitrogenous organics. In addition, it was shown that GAC improved the removal of less oxidized, higher nitrogen content, and higher double bond equivalent (DBE) organic compounds. Microbial analysis showed that GAC not only increased the microbial concentration, but also enriched more syntrophic bacteria (e.g., Syntrophorhabdus and Synergistes), which were capable of degrading a wide range of different organics including nitrogenous and aromatic organics. Furthermore, profound effects on the methanogens and the enrichment of Methanothrix instead of Methanosarcina were observed. Overall, the present study revealed the molecular transformation and microbial mechanism in the AD of HTLWW with the presence of GAC.

High-throughput DNA sequencing technologies for water and wastewater analysis

Conventional microbiological water monitoring uses culture-dependent techniques to screen indicator microbial species such as Escherichia coli and fecal coliforms. With high-throughput, second-generation sequencing technologies becoming less expensive, water quality monitoring programs can now leverage the massively parallel nature of second-generation sequencing technologies for batch sample processing to simultaneously obtain compositional and functional information of culturable and as yet uncultured microbial organisms. This review provides an introduction to the technical capabilities and considerations necessary for the use of second-generation sequencing technologies, specifically 16S rDNA amplicon and whole-metagenome sequencing, to investigate the composition and functional potential of microbiomes found in water and wastewater systems.

Metagenomic approaches: effective tools for monitoring the structure and functionality of microbiomes in anaerobic digestion systems

Microbial metagenome analysis has proven its usefulness to investigate the microbiomes present in technical engineered ecosystems such as anaerobic digestion systems. The analysis of the total microbial genomic DNA allows the detailed determination of both the microbial community structure and its functionality. In addition, it enables to study the response of the microbiome to alterations in technical process parameters. Strategies of functional microbial networks to face abiotic stressors, e.g., resistance, resilience, and reorganization, can be evaluated with respect to overall process optimization. The objective of this paper is to review the main metagenomic tools used for effective studies on anaerobic digestion systems in monitoring the dynamic of the microbiomes, as well as the factors that have been identified so far as limiting the metagenomic studies in this ecosystems.

How sample heterogeneity can obscure the signal of microbial interactions

Microbial community data are commonly subjected to computational tools such as correlation networks, null models, and dynamic models, with the goal of identifying the ecological processes structuring microbial communities. A major assumption of these methods is that the signs and magnitudes of species interactions and vital rates can be reliably parsed from observational data on species' (relative) abundances. However, we contend that this assumption is violated when sample units contain any underlying spatial structure. Here, we show how three phenomena-Simpson's paradox, context-dependence, and nonlinear averaging-can lead to erroneous conclusions about population parameters and species interactions when samples contain heterogeneous mixtures of populations or communities. At the root of this issue is the fundamental mismatch between the spatial scales of species interactions (micrometers) and those of typical microbial community samples (millimeters to centimetres). These issues can be overcome by measuring and accounting for spatial heterogeneity at very small scales, which will lead to more reliable inference of the ecological mechanisms structuring natural microbial communities.

Molecular microbial ecology of stable versus failing rice straw anaerobic digesters

Waste rice straw (RS) is generated in massive quantities around the world and is often burned, creating greenhouse gas and air quality problems. Anaerobic digestion (AD) may be a better option for RS management, but RS is presumed to be comparatively refractory under anaerobic conditions without pre-treatment or co-substrates. However, this presumption assumes frequent reactor feeding regimes but less frequent feeding may be better for RS due to slow hydrolysis rates. Here, we assess how feeding frequency (FF) and organic loading rate (OLR) impacts microbial communities and biogas production in RS AD reactors. Using 16S rDNA amplicon sequencing and bioinformatics, microbial communities from five bench-scale bioreactors were characterized. At low OLR (1.0 g VS l-1  day-1 ), infrequently fed units (once every 21 days) had higher specific biogas yields than more frequent feeding (five in 7 days), although microbial community diversities were statistically similar (P > 0.05; ANOVA with Tukey comparison). In contrast, an increase in OLR to 2.0 g VS l-1  day-1 significantly changed Archaeal and fermenting Eubacterial sub-communities and the least frequency fed reactors failed. 'Stable' reactors were dominated by Methanobacterium, Methanosarcina and diverse Bacteroidetes, whereas 'failed' reactors saw shifts towards Clostridia and Christensenellaceae among fermenters and reduced methanogen abundances. Overall, OLR impacted RS AD microbial communities more than FF. However, combining infrequent feeding and lower OLRs may be better for RS AD because of higher specific yields.

Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process

BACKGROUND

Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters.

RESULTS

This study quantified microbial immigration from an upstream full-scale anaerobic reactor to downstream activated sludge reactors. A mass balance was applied to 16S rRNA gene amplicon sequencing data to calculate the net growth rates of individual populations in the activated sludge reactors. Among the 1178 observed operational taxonomic units (OTUs), 582 had a positive growth rate, including all the populations with abundance > 0.1%. These active populations collectively accounted for 99% of the total sequences in activated sludge. The remaining 596 OTUs with a growth rate ≤ 0 were classified as inactive populations. All the abundant populations in the upstream anaerobic reactor were inactive in the activated sludge process, indicating a negligible immigration impact. We used a supervised learning regressor to predict environmental parameters based on community composition and compared the prediction accuracy based on either the entire community or the active populations. Temperature was the most predictable parameter, and the prediction accuracy was improved when only active populations were used to train the regressor.

CONCLUSIONS

Calculating growth rate of individual microbial populations in the downstream system provides an effective approach to determine microbial activity and quantify immigration impact. For the studied biological process, a marginal immigration impact was observed, likely due to the significant differences in the growth environments between the upstream and downstream processes. Excluding inactive populations as a result of immigration further enhanced the prediction of key environmental parameters affecting process performance.

Influence of organic loading rate on purified terephthalic acid wastewater treatment in a temperature staged anaerobic treatment (TSAT) system: Performance and metagenomic characteristics

In this study, a temperature staged anaerobic treatment (TSAT) system featured by thermophilic reactor (R1)-mesophilic reactor (R2) co-digestion was introduced to treat PTA wastewater. The process was successively conducted at three organic loading rates (OLRs): 3.34, 4.45, 6.68 kg COD/(m³·d), respectively (OLRs were R1 basis). The results indicated that TSAT system was highly efficient in PTA wastewater treatment at OLR lower than 4.45 kg COD/(m³·d). Miseq sequencing analysis demonstrated that R1 and R2 were predominated by hydrogenotrophic Methanolinea and acetotrophic Methanosaeta, separately. In addition, TA06, Caldisericia and Acetothermia associated groups were highly abundant in R1, whereas Chlorobiaceae and Syntrophobacteraceae were largely observed in R2. Tax4Fun analysis suggested that the important functional capabilities were significantly different between R1 and R2 (P < 0.05). The pathways related to aromatic compounds degradation mainly occurred in mesophilic stage, while the biosynthesis and metabolism pathways were more favored in thermophilic stage.

Co-occurrence network analysis reveals thermodynamics-driven microbial interactions in methanogenic bioreactors

Methanogenic bioreactors have been applied to treat purified terephthalic acid (PTA) wastewater containing complex aromatic compounds, such as terephthalic acid, para-toluic acid and benzoic acid. This study characterized the interaction of microbial populations in 42 samples obtained from 10 PTA-degrading methanogenic bioreactors. Approximately, 54 dominant populations (11 methanogens, 8 syntrophs and 35 functionally unknown clades) that represented 73.9% of total 16S rRNA gene iTag sequence reads were identified. Co-occurrence analysis based on the abundance of dominant OTUs showed two non-overlapping networks centred around aromatic compound- (group AR: Syntrophorhabdaceae, Syntrophus and Pelotomaculum) and fatty acid- (group FA: Smithella and Syntrophobacter) degrading syntrophs. Group AR syntrophs have no direct correlation with hydrogenotrophic methanogens, while those from group FA do. As degradation of aromatic compounds has a wider thermodynamic window than fatty acids, Group AR syntrophs may be less influenced by fluctuations in hydrogenotrophic methanogen abundance or may non-specifically interact with diverse methanogens. In both groups, network analysis reveals full-scale- and lab-scale-specific uncultivated taxa that may mediate interactions between syntrophs and methanogens, suggesting that those uncultivated taxa may support the degradation of aromatic compounds through uncharted ecophysiological traits. These observations suggest that organisms from multiple niches orchestrate their metabolic capacity in multiple interaction networks to effectively degrade PTA wastewater.

Microbial community composition and diversity in rice straw digestion bioreactors with and without dairy manure

Anaerobic digestion (AD) uses a range of substrates to generate biogas, including energy crops such as globally abundant rice straw (RS). Unfortunately, RS is high in lignocellulosic material and has high to C:N ratios (~80:1), which makes it (alone) a comparatively poor substrate for AD. Co-digestion with dairy manure (DM) has been promoted as a method for balancing C:N ratios to improve RS AD whilst also treating another farm waste and co-producing a potentially useful fertiliser. However, past co-digestion studies have not directly compared RS AD microbial communities with and without DM additions, which has made it hard to assess all impacts of DM addition to RS AD processes. Here, four RS:DM ratios were contrasted in identical semi-continuous-fed AD bioreactors, and 100% RS was found to produce the highest specific methane yields (112 mL CH4/g VS/day; VS, volatile solids), which is over double yields achieved in the reactor with the highest DM content (30:70 RS:DM by mass; 48 mL CH4/g VS/day). To underpin these data, microbial communities were sequenced and characterised across the four reactors. Dominant operational taxonomic units (OTUs) in the 100% RS unit were Bacteroidetes/Firmicutes, whereas the 30:70 RS:DM unit was dominated by Proteobacteria/Spirochaetes, suggesting major microbial community shifts occur with DM additions. However, community richness was lowest with 100% RS (despite higher specific yields), suggesting particular OTUs may be more important to yields than microbial diversity. Further, ambient VFA and VS levels were significantly higher when no DM was added, suggesting DM-amended reactors may cope better with higher organic loading rates (OLR). Results show that RS AD without DM addition is feasible, although co-digestion with DM will probably allow higher OLRs, resulting in great RS throughput in farm AD units.

Role of acid/alkali-treatment in primary sludge anaerobic fermentation: Insights into microbial community structure, functional shifts and metabolic output by high-throughput sequencing

This study aimed to investigate the effect of acid- or alkali-treatment on volatile fatty acids (VFAs) production and microbiological mechanism during primary sludge anaerobic fermentation. Seven fermentation experiments were conducted at different pH (3-12). Results showed that the optimal pH was 10 for accumulation of VFAs. High-throughput sequencing results indicated that acid and alkali treatment could inhibit Erysipelotrichaceae_UCG-004 and norank_p_Aminicenantes, instead of promoting Pseudomonas and Tissierella at acidic and alkaline condition, respectively. Besides, molecular ecological networks (MENs) analysis and multivariate canonical correspondence analysis (CCA) revealed that the microbial community interactions are significant different between acid and alkali treatment groups, and acetic acid was the most vital factor in the distinct bacterial community assemblages. Predictive functional profiling using marker gene sequences found that amino acid transport and metabolism was the most abundant metabolic type with 8.43-9.41%, and acid- and alkali-treatment did not benefit Stickland reaction.

Establishment of thermophilic anaerobic terephthalic acid degradation system through one-step temperature increase startup strategy - Revealed by Illumina Miseq Sequencing

Over recent years, thermophilic digestion was constantly focused owing to its various advantage over mesophilic digestion. Notably, the startup approach of thermophilic digester needs to be seriously considered as unsuitable startup ways may result in system inefficiency. In this study, one-step temperature increase startup strategy from 37 °C to 55 °C was applied to establish a thermophilic anaerobic system treating terephthalic acid (TA) contained wastewater, meanwhile, the archaeal and bacterial community compositions at steady periods of 37 °C and 55 °C during the experimental process was also compared using Illumina Miseq Sequencing. The process operation demonstrated that the thermophilic TA degradation system was successfully established at 55 °C with over 95% COD reduction. For archaea community, the elevation of operational temperature from 37 °C to 55 °C accordingly increase the enrichment of hydrogenotrophic methanogens but decrease the abundance of the acetotrophic ones. While for bacterial community, the taxonomic analysis suggested that Syntrophorhabdus (27.40%) was the dominant genus promoting the efficient TA degradation under mesophilic condition, whereas OPB95 (24.99%) and TA06 (14.01%) related populations were largely observed and probably take some crucial role in TA degradation under thermophilic condition.