Microbial Resource Management: The Road To Go for Environmental Biotechnology

Prioritising gully remediation in a Great Barrier Reef catchment: An approach using two independent methods of assessing erosion activity in 22,300 gullies

The strategic reduction and remediation of degraded land is a global environmental priority. This is a particular priority in the Great Barrier Reef catchment area, Australia, where gully erosion a significant contributor to land degradation and water quality deterioration. Urgent action through the prioritisation and remediation of gully erosion sites is imperative to safeguard this UNESCO World Heritage site. In this study, we analyze a comprehensive dataset of 22,311 mapped gullies within a 3480 km2 portion of the lower Burdekin Basin, northeast Australia. Utilizing high-resolution lidar datasets, two independent methods - Minimum Contemporary Estimate (MCE) and Lifetime Average Estimate (LAE) - were developed to derive relative erosion rates. These methods, employing different data processing approaches and addressing different timeframes across the gully lifetime, yield erosion rates varying by up to several orders of magnitude. Despite some expected divergence, both methods exhibit strong, positive correlations with each other and additional validation data. There is a 43% agreement between the methods for the highest yielding 2% of gullies, although 80.5% of high-yielding gullies identified by either method are located within a 1 km proximity of each other. Importantly, distributions from both methods independently reveal that ∼80% of total volume of gully erosion in the study area is produced from only 20% of all gullies. Moreover, the top 2% of gullies generate 30% of the sediment loss and the majority of gullies do not significantly contribute to the overall catchment sediment yield. These results underscore the opportunity to achieve significant environmental outcomes through targeted gully management by prioritising a small cohort of high yielding gullies. Further insights and implications for management frameworks are discussed in the context of the characteristics of this cohort. Overall, this research provides a basis for informed decision-making in addressing gully erosion and advancing environmental conservation efforts.

Bois noir management in vineyard: a review on effective and promising control strategies

Among grapevine yellows, Bois noir (BN), associated with 'Candidatus Phytoplasma solani', represents the biggest threat in the main wine-growing areas worldwide, causing significant losses in berry quality and yields. BN epidemiology involves multiple plant hosts and several insect vectors, making considerably complex the development of effective management strategies. Since application of insecticides on the grapevine canopy is not effective to manage vectors, BN management includes an integrated approach based on treatments to the canopy to make the plant more resistant to the pathogen and/or inhibit the vector feeding, and actions on reservoir plants to reduce possibilities that the vector reaches the grapevine and transmit the phytoplasma. Innovative sustainable strategies developed in the last twenty years to improve the BN management are reviewed and discussed.

Economic microbiology: exploring microbes as agents in economic systems

Microbial communities exhibit striking parallels with economic markets, resembling intricate ecosystems where microorganisms engage in resource exchange akin to human market transactions. This dynamic network of resource swapping mirrors economic trade in human markets, with microbes specializing in metabolic functions much like businesses specializing in goods and services. Cooperation and competition are central dynamics in microbial communities, with alliances forming for mutual benefit and species vying for dominance, similar to businesses seeking market share. The human microbiome, comprising trillions of microorganisms within and on our bodies, is not only a marker of socioeconomic status but also a critical factor contributing to persistent health inequalities. Social and economic factors shape the composition of the gut microbiota, impacting healthcare access and quality of life. Moreover, these microbes exert indirect influence over human decisions by affecting neurotransmitter production, influencing mood, behavior, and choices related to diet and emotions. Human activities significantly impact microbial communities, from dietary choices and antibiotic use to environmental changes, disrupting these ecosystems. Beyond their natural roles, humans harness microbial communities for various applications, manipulating their interactions and resource exchanges to achieve specific goals in fields like medicine, agriculture, and environmental science. In conclusion, the concept of microbial communities as biological markets offers valuable insights into their intricate functioning and adaptability. It underscores the profound interplay between microbial ecosystems and human health and behavior, with far-reaching implications for multiple disciplines. To paraphrase Alfred Marshall, "the Mecca of the economist lies in economic microbiology."

Plants and endophytes interaction: a "secret wedlock" for sustainable biosynthesis of pharmaceutically important secondary metabolites

Many plants possess immense pharmacological properties because of the presence of various therapeutic bioactive secondary metabolites that are of great importance in many pharmaceutical industries. Therefore, to strike a balance between meeting industry demands and conserving natural habitats, medicinal plants are being cultivated on a large scale. However, to enhance the yield and simultaneously manage the various pest infestations, agrochemicals are being routinely used that have a detrimental impact on the whole ecosystem, ranging from biodiversity loss to water pollution, soil degradation, nutrient imbalance and enormous health hazards to both consumers and agricultural workers. To address the challenges, biological eco-friendly alternatives are being looked upon with high hopes where endophytes pitch in as key players due to their tight association with the host plants. The intricate interplay between plants and endophytic microorganisms has emerged as a captivating subject of scientific investigation, with profound implications for the sustainable biosynthesis of pharmaceutically important secondary metabolites. This review delves into the hidden world of the "secret wedlock" between plants and endophytes, elucidating their multifaceted interactions that underpin the synthesis of bioactive compounds with medicinal significance in their plant hosts. Here, we briefly review endophytic diversity association with medicinal plants and highlight the potential role of core endomicrobiome. We also propose that successful implementation of in situ microbiome manipulation through high-end techniques can pave the way towards a more sustainable and pharmaceutically enriched future.

The Pareto principle: To what extent does it apply to resource acquisition in stable microbial communities and thereby steer their geno-/ecotype compositions and interactions between their members?

The Pareto principle, or 20:80 rule, describes resource distribution in stable communities whereby 20% of community members acquire 80% of a key resource. In this Burning Question, we ask to what extent the Pareto principle applies to the acquisition of limiting resources in stable microbial communities; how it may contribute to our understanding of microbial interactions, microbial community exploration of evolutionary space, and microbial community dysbiosis; and whether it can serve as a benchmark of microbial community stability and functional optimality?

Micro-aeration: an attractive strategy to facilitate anaerobic digestion

Micro-aeration can facilitate anaerobic digestion (AD) by regulating microbial communities and promoting the growth of facultative taxa, thereby increasing methane yield and stabilizing the AD process. Additionally, micro-aeration contributes to hydrogen sulfide stripping by oxidization to produce molecular sulfur or sulfuric acid. Although micro-aeration can positively affect AD, it must be strictly regulated to maintain an overall anaerobic environment that permits anaerobic microorganisms to thrive. Even so, obligate anaerobes, especially methanogens, could suffer from oxidative stress during micro-aeration. This review describes the applications of micro-aeration in AD and examines the cutting-edge advances in how methanogens survive under oxygen stress. Moreover, barriers and corresponding solutions are proposed to move micro-aeration technology closer to application at scale.

Pollution and edaphic factors shape bacterial community structure and functionality in historically contaminated soils

Studies about biodegradation potential in soils often refer to artificially contaminated and simplified systems, overlooking the complexity associated with contaminated sites in a real context. This work aims to provide a holistic view on microbiome assembly and functional diversity in the model site SIN Brescia-Caffaro (Italy), characterized by historical and uneven contamination by organic and inorganic compounds. Here, physical and chemical analyses and microbiota characterization were applied on one-hundred-twenty-seven soil samples to unravel the environmental factors driving bacterial community assembly and biodegradation potential in three former agricultural fields. Chemical analyses showed a patchy distribution of metals, metalloids and polychlorinated biphenyls (PCB) and allowed soil categorization according to depth and area of collections. Likewise, the bacterial community structure, described by molecular fingerprinting and 16S rRNA gene analyses, was significantly different according to collection site and depth. Pollutant concentrations (i.e., hexachloro-biphenyls, arsenic and mercury), nitrogen content and parameters related to soil texture were identified as main drivers of microbiota assembly, being significantly correlated to bacterial community composition. Moreover, bacteria putatively involved in the aerobic degradation of PCBs were enriched over the total bacterial community in topsoils, where the highest activity was recorded using fluorescein hydrolysis as proxy. Metataxonomic analyses revealed the presence of bacteria having metabolic pathways related to PCB degradation and tolerance to heavy metals and metalloids in the topsoil samples collected in all areas. Overall, the provided dissection of soil microbiota structure and its degradation potential in the SIN Brescia-Caffaro can contribute to target specific areas for rhizoremediation implementation. Metagenomics studies could be implemented in the future to understand if specific degradative pathways are present in historically polluted sites characterized by the co-occurrence of multiple classes of contaminants.

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.

Engineering microbial technologies for environmental sustainability: choices to make

Microbial technologies have provided solutions to key challenges in our daily lives for over a century. In the debate about the ongoing climate change and the need for planetary sustainability, microbial ecology and microbial technologies are rarely considered. Nonetheless, they can bring forward vital solutions to decrease and even prevent long-term effects of climate change. The key to the success of microbial technologies is an effective, target-oriented microbiome management. Here, we highlight how microbial technologies can play a key role in both natural, i.e. soils and aquatic ecosystems, and semi-natural or even entirely human-made, engineered ecosystems, e.g. (waste) water treatment and bodily systems. First, we set forward fundamental guidelines for effective soil microbial resource management, especially with respect to nutrient loss and greenhouse gas abatement. Next, we focus on closing the water circle, integrating resource recovery. We also address the essential interaction of the human and animal host with their respective microbiomes. Finally, we set forward some key future potentials, such as microbial protein and the need to overcome microphobia for microbial products and services. Overall, we conclude that by relying on the wisdom of the past, we can tackle the challenges of our current era through microbial technologies.

Microbial Community Successional Changes in a Full-Scale Mesophilic Anaerobic Digester from the Start-Up to the Steady-State Conditions

Anaerobic digestion is a widely used technology for sewage sludge stabilization and biogas production. Although the structure and composition of the microbial communities responsible for the process in full-scale anaerobic digesters have been investigated, little is known about the microbial successional dynamics during the start-up phase and the response to variations occurring in such systems under real operating conditions. In this study, bacterial and archaeal population dynamics of a full-scale mesophilic digester treating activated sludge were investigated for the first time from the start-up, performed without adding external inoculum, to steady-state operation. High-throughput 16S rRNA gene sequencing was used to describe the microbiome evolution. The large majority of the reads were affiliated to fermentative bacteria. Bacteroidetes increased over time, reaching 22% of the total sequences. Furthermore, Methanosaeta represented the most abundant methanogenic component. The specific quantitative data generated by real-time PCR indicated an enrichment of bacteria and methanogens once the steady state was reached. The analysis allowed evaluation of the microbial components more susceptible to the shift from aerobic to anaerobic conditions and estimation of the microbial components growing or declining in the system. Additionally, activated sludge was investigated to evaluate the microbial core selected by the WWTP operative conditions.

Over-feeding the gut microbiome: A scoping review on health implications and therapeutic perspectives

The human gut microbiome has gained increasing attention over the past two decades. Several findings have shown that this complex and dynamic microbial ecosystem can contribute to the maintenance of host health or, when subject to imbalances, to the pathogenesis of various enteric and non-enteric diseases. This scoping review summarizes the current knowledge on how the gut microbiota and microbially-derived compounds affect host metabolism, especially in the context of obesity and related disorders. Examples of microbiome-based targeted intervention strategies that aim to restore and maintain an eubiotic layout are then discussed. Adjuvant therapeutic interventions to alleviate obesity and associated comorbidities are traditionally based on diet modulation and the supplementation of prebiotics, probiotics and synbiotics. However, these approaches have shown only moderate ability to induce sustained changes in the gut microbial ecosystem, making the development of innovative and tailored microbiome-based intervention strategies of utmost importance in clinical practice. In this regard, the administration of next-generation probiotics and engineered microbiomes has shown promising results, together with more radical intervention strategies based on the replacement of the dysbiotic ecosystem by means of fecal microbiota transplantation from healthy donors or with the introduction of synthetic communities specifically designed to achieve the desired therapeutic outcome. Finally, we provide a perspective for future translational investigations through the implementation of bioinformatics approaches, including machine and deep learning, to predict health risks and therapeutic outcomes.

Tracking de novo protein synthesis in the activated sludge microbiome using BONCAT-FACS

In order to ensure stable performance of engineered biotechnologies that rely on mixed microbial community systems, it is important to identify process-specific microbial traits and study their in-situ activity and responses to changing environmental conditions and system operational parameters. We used BioOrthogonal Non-Canonical Amino acid Tagging (BONCAT) in combination with Fluorescence-Activated Cell Sorting (FACS) and 16S rRNA gene amplicon sequencing to identify translationally active cells in activated sludge. We found that only a subset of the activated sludge microbiome is translationally active during the aerobic treatment phase of a full-scale sequencing batch reactor designed to enhance biological phosphorus removal from municipal wastewater. Relative abundance of amplicon sequence variants was not a reliable predictor of species activity. BONCAT-positive and -negative cells revealed a broad range of population-wide and taxa-specific translational heterogeneity. BONCAT-FACS in combination with amplicon sequencing can provide new insights into the ecophysiology of highly dynamic microbiomes in activated sludge systems.

Activity-Based Cell Sorting Reveals Resistance of Functionally Degenerate Nitrospira during a Press Disturbance in Nitrifying Activated Sludge

Managing and engineering activated sludge wastewater treatment microbiomes for low-energy nitrogen removal requires process control strategies to stop the oxidation of ammonium at nitrite. Our ability to out-select nitrite-oxidizing bacteria (NOB) from activated sludge is challenged by their metabolic and physiological diversity, warranting measurements of their in situ physiology and activity under selective growth pressures. Here, we examined the stability of nitrite oxidation in activated sludge during a press disturbance induced by treating a portion of return activated sludge with a sidestream flow containing free ammonia (FA) at 200 mg NH₃-N/liter. The nitrite accumulation ratio peaked at 42% by day 40 in the experimental bioreactor with the press disturbance, while it did not increase in the control bioreactor. A subsequent decrease in nitrite accumulation within the experimental bioreactor coincided with shifts in dominant Nitrospira 16S rRNA amplicon sequence variants (ASVs). We applied bioorthogonal noncanonical amino acid tagging (BONCAT) coupled with fluorescence-activated cell sorting (FACS) to investigate changes in the translational activity of NOB populations throughout batch exposure to FA. BONCAT-FACS confirmed that the single Nitrospira ASV washed out of the experimental bioreactor had reduced translational activity following exposure to FA, whereas the two Nitrospira ASVs that emerged after process acclimation were not impacted by FA. Thus, the coexistence of functionally degenerate and physiologically resistant Nitrospira populations provided resilience to the nitrite-oxidizing function during the press disturbance. These results highlight how BONCAT-FACS can resolve ecological niche differentiation within activated sludge and inform strategies to engineer and control microbiome function.

IMPORTANCE Nitrogen removal from activated sludge wastewater treatment systems is an energy-intensive process due to the large aeration requirement for nitrification. This energy footprint could be minimized with engineering control strategies that wash out nitrite-oxidizing bacteria (NOB) to limit oxygen demands. However, NOB populations can have a high degree of physiological diversity, and it is currently difficult to decipher the behavior of individual taxa during applied selective pressures. Here, we utilized a new substrate analog probing approach to measure the activity of NOB at the cellular translational level in the face of a press disturbance applied to the activated sludge process. Substrate analog probing corroborated the time series reactor sampling, showing that coexisting and functionally degenerate Nitrospira populations provided resilience to the nitrite oxidation process. Taken together, these results highlight how substrate analog approaches can illuminate in situ ecophysiologies within shared niches, and can inform strategies to improve microbiome engineering and management.

Substrate Pre-loading Influences Initial Colonization of GAC Biofilter Biofilms

Microbial community composition and stability affect pollutant removal for biological/granular activated carbon (BAC/GAC) processes. Here, we pre-loaded the organic carbon substrates sucrose, lactose, and Lysogeny Broth (LB) medium onto new GAC prior to use and then tested whether this substrate pre-loading promoted development of biofilms with high coverage that remained stable for prolonged operational periods. Temporal dynamics of the biomass and microbial community on the GAC were monitored via flow cytometry (FCM) and sequencing, respectively, in both batch and continuous-flow experiments. In comparison with the non-loaded GAC (control), the initial biofilm biomass on substrate-loaded GAC was 3–114 times higher, but the initial richness was considerably lower (only accounting for 13–28% of the control). The initial community compositions were significantly different between batch and continuous-flow column experiments, even when loaded with the same substrates. In the continuous-flow column experiments, both biomass and microbial community composition became remarkably similar to the control filters after 64 days of operation. From these findings, we conclude that substrate-loaded GAC could enhance initial colonization, affecting both biomass and microbial community composition. However, the biomass and composition did not remain stable during long-term operation due to continuous dispersal and competition from influent bacteria.

Microbial invasions in sludge anaerobic digesters

Among processes that control microbial community assembly, microbial invasion has received little attention until recently, especially in the field of anaerobic digestion. However, knowledge of the principles regulating the taxonomic and functional stability of microbial communities is key to truly develop better predictive models and effective management strategies for the anaerobic digestion process. To date, available studies focus on microbial invasions in digesters feed with activated sludge from municipal wastewater treatment plants. Herein, this review summarizes the importance of invasions for anaerobic digestion management, the ecological theories about microbial invasions, the traits of activated sludge microorganisms entering the digesters, and the resident communities of anaerobic reactors that are relevant for invasions and the current knowledge about the success and impacts of invasions, and discusses the research needs on this topic. The initial data indicate that the impact of invasions is low and only a small percentage of the mostly aerobic microorganisms present in the activated sludge feed are able to become stablished in the anaerobic digesters. However, there are still numerous unknowns about microbial invasions in anaerobic digestion including the influence of anaerobic feedstocks or process perturbances that new approaches on microbial ecology could unveil. KEY POINTS: • Microbial invasions are key processes to develop better strategies for digesters management. • Knowledge on pathogen invasions can improve anaerobic digestion microbial safety. • To date, the number of successful invasions on anaerobic digesters from activated sludge organisms is low. • Feed organisms detected in digesters are mostly inactive residual populations. • Need to expand the range of invaders and operational scenarios studied.

Microbial Resource Management for Ex Situ Biomethanation of Hydrogen at Alkaline pH

Biomethanation is a promising solution to convert H₂ (produced from surplus electricity) and CO₂ to CH₄ by using hydrogenotrophic methanogens. In ex situ biomethanation with mixed cultures, homoacetogens and methanogens compete for H₂/CO₂. We enriched a hydrogenotrophic microbiota on CO₂ and H₂ as sole carbon and energy sources, respectively, to investigate these competing reactions. The microbial community structure and dynamics of bacteria and methanogenic archaea were evaluated through 16S rRNA and mcrA gene amplicon sequencing, respectively. Hydrogenotrophic methanogens and homoacetogens were enriched, as acetate was concomitantly produced alongside CH₄. By controlling the media composition, especially changing the reducing agent, the formation of acetate was lowered and grid quality CH₄ (≥97%) was obtained. Formate was identified as an intermediate that was produced and consumed during the bioprocess. Stirring intensities ≥ 1000 rpm were detrimental, probably due to shear force stress. The predominating methanogens belonged to the genera Methanobacterium and Methanoculleus. The bacterial community was dominated by Lutispora. The methanogenic community was stable, whereas the bacterial community was more dynamic. Our results suggest that hydrogenotrophic communities can be steered towards the selective production of CH₄ from H₂/CO₂ by adapting the media composition, the reducing agent and the stirring intensity.

New insights from the biogas microbiome by comprehensive genome-resolved metagenomics of nearly 1600 species originating from multiple anaerobic digesters

BACKGROUND

Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository.

RESULTS

Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain.

CONCLUSIONS

The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

Guiding Mineralization Co-Culture Discovery Using Bayesian Optimization

Many disciplines rely on testing combinations of compounds, materials, proteins, or bacterial species to drive scientific discovery. It is time-consuming and expensive to determine experimentally, via trial-and-error or random selection approaches, which of the many possible combinations will lead to desirable outcomes. Hence, there is a pressing need for more rational and efficient experimental design approaches to reduce experimental effort. In this work, we demonstrate the potential of machine learning methods for the in silico selection of promising co-culture combinations in the application of bioaugmentation. We use the example of pollutant removal in drinking water treatment plants, which can be achieved using co-cultures of a specialized pollutant degrader with combinations of bacterial isolates. To reduce the experimental effort needed to discover high-performing combinations, we propose a data-driven experimental design. Based on a dataset of mineralization performance for all pairs of 13 bacterial species co-cultured with MSH1, we built a Gaussian process regression model to predict the Gompertz mineralization parameters of the co-cultures of two and three species, based on the single-strain parameters. We subsequently used this model in a Bayesian optimization scheme to suggest potentially high-performing combinations of bacteria. We achieved good performance with this approach, both for predicting mineralization parameters and for selecting effective co-cultures, despite the limited dataset. As a novel application of Bayesian optimization in bioremediation, this experimental design approach has promising applications for highlighting co-culture combinations for in vitro testing in various settings, to lessen the experimental burden and perform more targeted screenings.

Common principles and best practices for engineering microbiomes

Despite broad scientific interest in harnessing the power of Earth's microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue that structuring research and technology developments around a design-build-test-learn (DBTL) cycle will advance microbiome engineering and spur new discoveries of the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyse microbiome function. These approaches can be used to harness microbiomes for broad applications related to medicine, agriculture, energy and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. We anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture and enabling the bioeconomy.

Process Disturbances in Agricultural Biogas Production—Causes, Mechanisms and Effects on the Biogas Microbiome: A Review

Disturbances of the anaerobic digestion process reduce the economic and environmental performance of biogas systems. A better understanding of the highly complex process is of crucial importance in order to avoid disturbances. This review defines process disturbances as significant changes in the functionality within the microbial community leading to unacceptable and severe decreases in biogas production and requiring an active counteraction to be overcome. The main types of process disturbances in agricultural biogas production are classified as unfavorable process temperatures, fluctuations in the availability of macro- and micronutrients (feedstock variability), overload of the microbial degradation potential, process-related accumulation of inhibiting metabolites such as hydrogen (H2), ammonium/ammonia (NH4+/NH3) or hydrogen sulphide (H2S) and inhibition by other organic and inorganic toxicants. Causes, mechanisms and effects on the biogas microbiome are discussed. The need for a knowledge-based microbiome management to ensure a stable and efficient production of biogas with low susceptibility to disturbances is derived and an outlook on potential future process monitoring and control by means of microbial indicators is provided.

Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data

Detecting disturbances in microbial communities is an important aspect of managing natural and engineered microbial communities. Here, we implemented a custom-built continuous staining device in combination with real-time flow cytometry (RT-FCM) data acquisition, which, combined with advanced FCM fingerprinting methods, presents a powerful new approach to track and quantify disturbances in aquatic microbial communities. Through this new approach we were able to resolve various natural community and single-species microbial contaminations in a flow-through drinking water reactor. Next to conventional FCM metrics, we applied metrics from a recently developed fingerprinting technique in order to gain additional insight into the microbial dynamics during these contamination events. Importantly, we found that multiple community FCM metrics based on different statistical approaches were required to fully characterize all contaminations. Furthermore we found that for accurate cell concentration measurements and accurate inference from the FCM metrics (coefficient of variation ≤ 5%), at least 1000 cells should be measured, which makes the achievable temporal resolution a function of the prevalent bacterial concentration in the system-of-interest. The integrated RT-FCM acquisition and analysis approach presented herein provides a considerable improvement in the temporal resolution by which microbial disturbances can be observed and simultaneously provides a multi-faceted toolset to characterize such disturbances.

Metataxonomy and functionality of wood-tar degrading microbial consortia

Wood-tar is a liquid material obtained by wood gasification process, and comprises several polycyclic aromatic hydrocarbons (PAH). Tar biodegradation is a very challenging task, due to its toxicity and to its complex chemistry. The 'microbial resource management' concerns the use of environmental microbial communities potentially able to provide us services. We applied this concept in tar biodegradation. Tar composed by several PAH (including phenanthrene, acenaphthylene and fluorene) was subjected to a biodegradation process in triplicate microcosms spiked with a microbial community collected from PAH-rich soils. In 20 days, 98.9% of tar was mineralized or adsorbed to floccules, while negative controls showed poor PAH reduction. The dynamics of fungal and bacterial communities was assessed through Automated Ribosomal Intergenic Spacer Analysis (ARISA), 454 pyrosequencing of the fungal ITS and of the bacterial 16S rRNA. Quantification of the degrading bacterial communities was performed via quantitative Real Time PCR of the 16S rRNA genes and of the cathecol 2,3-dioxygenase genes. Results showed the importance of fungal tar-degrading populations in the first period of incubation, followed by a complex bacterial dynamical growth ruled by co-feeding behaviors.

Hydrogen-Fueled Microbial Pathways in Biogas Upgrading Systems Revealed by Genome-Centric Metagenomics

Biogas upgrading via carbon dioxide hydrogenation is an emerging technology for electrofuel production. The biomethanation efficiency is strongly dependent on a balanced microbial consortium, whose high- resolution characterization along with their functional potential and interactions are pivotal for process optimization. The present work is the first genome-centric metagenomic study on mesophilic and thermophilic biogas upgrading reactors aiming to define the metabolic profile of more than 200 uncultivated microbes involved in hydrogen assisted methanogenesis. The outcomes from predictive functional analyses were correlated with microbial abundance variations to clarify the effect of process parameters on the community. The operational temperature significantly influenced the microbial richness of the reactors, while the H2 addition distinctively alternated the abundance of the taxa. Two different Methanoculleus species (one mesophilic and one thermophilic) were identified as the main responsible ones for methane metabolism. Finally, it was demonstrated that the addition of H2 exerted a selective pressure on the concerted or syntrophic interactions of specific microbes functionally related to carbon fixation, propionate and butanoate metabolisms. Novel bacteria were identified as candidate syntrophic acetate oxidizers (e.g., Tepidanaerobacter sp. DTU063), while the addition of H2 favored the proliferation of potential homoacetogens (e.g., Clostridia sp. DTU183). Population genomes encoding genes of Wood-Ljungdahl pathway were mainly thermophilic, while propionate degraders were mostly identified at mesophilic conditions. Finally, putative syntrophic interactions were identified between microbes that have either versatile metabolic abilities or are obligate/facultative syntrophs.

The active microbial community more accurately reflects the anaerobic digestion process: 16S rRNA (gene) sequencing as a predictive tool

BACKGROUND

Amplicon sequencing methods targeting the 16S rRNA gene have been used extensively to investigate microbial community composition and dynamics in anaerobic digestion. These methods successfully characterize amplicons but do not distinguish micro-organisms that are actually responsible for the process. In this research, the archaeal and bacterial community of 48 full-scale anaerobic digestion plants were evaluated on DNA (total community) and RNA (active community) level via 16S rRNA (gene) amplicon sequencing.

RESULTS

A significantly higher diversity on DNA compared with the RNA level was observed for archaea, but not for bacteria. Beta diversity analysis showed a significant difference in community composition between the DNA and RNA of both bacteria and archaea. This related with 25.5 and 42.3% of total OTUs for bacteria and archaea, respectively, that showed a significant difference in their DNA and RNA profiles. Similar operational parameters affected the bacterial and archaeal community, yet the differentiating effect between DNA and RNA was much stronger for archaea. Co-occurrence networks and functional prediction profiling confirmed the clear differentiation between DNA and RNA profiles.

CONCLUSIONS

In conclusion, a clear difference in active (RNA) and total (DNA) community profiles was observed, implying the need for a combined approach to estimate community stability in anaerobic digestion.

A year of monitoring 20 mesophilic full-scale bioreactors reveals the existence of stable but different core microbiomes in bio-waste and wastewater anaerobic digestion systems

BACKGROUND

Anaerobic digestion (AD) is a microbe-driven process of biomass decomposition to CH₄ and CO₂. In addition to renewable and cost-effective energy production, AD has emerged in the European Union as an environmentally friendly model of bio-waste valorisation and nutrient recycling. Nevertheless, due to the high diversity of uncharacterised microbes, a typical AD microbiome is still considered as "dark matter".

RESULTS

Using the high-throughput sequencing of small rRNA gene, and a monthly monitoring of the physicochemical parameters for 20 different mesophilic full-scale bioreactors over 1 year, we generated a detailed view of AD microbial ecology towards a better understanding of factors that influence and shape these communities. By studying the broadly distributed OTUs present in over 80% of analysed samples, we identified putatively important core bacteria and archaea to the AD process that accounted for over 70% of the whole microbial community relative abundances. AD reactors localised at the wastewater treatment plants were shown to operate with distinct core microbiomes than the agricultural and bio-waste treating biogas units. We also showed that both the core microbiomes were composed of low (with average community abundance ≤ 1%) and highly abundant microbial populations; the vast majority of which remains yet uncharacterised, e.g. abundant candidate Cloacimonetes. Using non-metric multidimensional scaling, we observed microorganisms grouping into clusters that well reflected the origin of the samples, e.g. wastewater versus agricultural and bio-waste treating biogas units. The calculated diversity patterns differed markedly between the different community clusters, mainly due to the presence of highly diverse and dynamic transient species. Core microbial communities appeared relatively stable over the monitoring period.

CONCLUSIONS

In this study, we characterised microbial communities in different AD systems that were monitored over a 1-year period. Evidences were shown to support the concept of a core community driving the AD process, whereas the vast majority of dominant microorganisms remain yet to be characterised.

Design of waste stabilization pond systems: A review

A better design instruction for waste stabilization ponds is needed due to their growing application for wastewater purification, increasingly strict environmental regulations, and the fact that most of previous design manuals are outdated. To critically review model-based designs of typical pond treatment systems, this paper analyzed more than 150 articles, books, and reports from 1956 to 2016. The models developed in these publications ranged from simple rules and equations to more complex first-order and mechanistic models. From a case study on all four approaches, it appeared that rules of thumb is no longer a proper tool for pond designs due to its low design specification and very high output variability and uncertainty. On the other hand, at the beginning phase of design process or in case of low pressure over land and moderate water quality required, regression equations can be useful to form an idea for pond dimensions. More importantly, mechanistic models proved their capacity of generating more precise and comprehensive designs but still need to overcome their lack of calibration and validation, and overparameterization. In another case study, an essential but often overlooked role of uncertainty analysis in pond designs was investigated via a comparison between deterministic and uncertainty-based approaches. Unlike applying a safety factor representing all uncertainty sources, probabilistic designs quantify the uncertainty of model outputs by including prior uncertainty of inputs and parameters, which generates more scientifically reliable outcomes for decision makers. Based on these findings, we advise engineers and designers to shift from the conventional approaches to more innovative and economic tools which are suitable for dealing with large variations of natural biological systems.

Microbial biotechnology and circular economy in wastewater treatment

Microbial biotechnology is essential for the development of circular economy in wastewater treatment by integrating energy production and resource recovery into the production of clean water. A comprehensive knowledge about identity, physiology, ecology, and population dynamics of process‐critical microorganisms will improve process stability, reduce CO2 footprints, optimize recovery and bioenergy production, and help finding new approaches and solutions. Examples of research needs and perspectives are provided, demonstrating the great importance of microbial biotechnology.

Bacterial interactions and implications for oil biodegradation process in mangrove sediments

Mangrove sediment harbors a unique microbiome and is a hospitable environment for a diverse group of bacteria capable of oil biodegradation. Our goal was to understand bacterial community dynamics from mangrove sediments contaminated with heavy-oil and to evaluate patterns potentially associated with oil biodegradation is such environments. We tested the previously proposed hypothesis of a two-phase pattern of petroleum biodegradation, under which key events in the degradation process take place in the first three weeks after contamination. Two sample sites with different oil pollution histories were compared through T-RFLP analyses and using a pragmatic approach based on the Microbial Resource Management Framework. Our data corroborated the already reported two-phase pattern of oil biodegradation, although the original proposed explanation related to the biophysical properties of the soil is questioned, opening the possibility to consider other plausible hypotheses of microbial interactions as the main drivers of this pattern.

Regional synchrony in full-scale activated sludge bioreactors due to deterministic microbial community assembly

Seasonal community structure and regionally synchronous population dynamics have been observed in natural microbial ecosystems, but have not been well documented in wastewater treatment bioreactors. Few studies of community dynamics in full-scale activated sludge systems facing similar meteorological conditions have been done to compare the importance of deterministic and neutral community assembly mechanisms. We subjected weekly activated sludge samples from six regional full-scale bioreactors at four wastewater treatment plants obtained over 1 year to Illumina sequencing of 16S ribosomal RNA genes, resulting in a library of over 17 million sequences. All samples derived from reactors treating primarily municipal wastewater. Despite variation in operational characteristics and location, communities displayed temporal synchrony at the individual operational taxonomic unit (OTU), broad phylogenetic affiliation and community-wide scale. Bioreactor communities were dominated by 134 abundant and highly regionally synchronized OTU populations that accounted for over 50% of the total reads. Non-core OTUs displayed abundance-dependent population synchrony. Alpha diversity varied by reactor, but showed a highly reproducible and synchronous seasonal fluctuation. Community similarity was dominated by seasonal changes, but individual reactors maintained minor stable differences after 1 year. Finally, the impacts of mass migration driven by direct biomass transfers between reactors was investigated, but had no significant effect on community similarity or diversity in the sink community. Our results show that population dynamics in activated sludge bioreactors are consistent with niche-driven assembly guided by seasonal temperature fluctuations.

The full-scale anaerobic digestion microbiome is represented by specific marker populations

Anaerobic digestion is a well-established microbial-based technology for the treatment of organic waste streams and subsequent biogas recovery. A robust and versatile microbial community to ensure overall stability of the process is essential. Four full-scale anaerobic digestion plants were followed for one year to link operational characteristics with microbial community composition and structure. Similarities between digesters, community dynamics and co-occurrence between bacteria and archaea within each digester were analysed. Free ammonia concentration (>200 mg N L^-1) and conductivity (>30 mS cm^-1) hindered acetoclastic methanogenesis by Methanosaetaceae. Thus, methanogenesis was pushed to the hydrogenotrophic pathway carried out by Methanobacteriales and Methanomicrobiales. Firmicutes dominated the overall bacterial community in each of the digesters (>50%), however, principal coordinate analysis of Bray-Curtis indices showed that each of the four digesters hosted a unique microbial community. The uniqueness of this community was related to two phylotypes belonging to the Syntrophomonas genus (Phy32 and Phy34) and to one unclassified bacterium (Phy2), which could both be considered marker populations in the community. A clear differentiation in co-occurrence of methanogens with several bacteria was observed between the different digesters. Our results demonstrated that full-scale anaerobic digestion plants show constant dynamics and co-occurrence patterns in function of time, but are unique in terms of composition, related to the presence of marker populations.

Unraveling the microbiome of a thermophilic biogas plant by metagenome and metatranscriptome analysis complemented by characterization of bacterial and archaeal isolates

BACKGROUND

One of the most promising technologies to sustainably produce energy and to mitigate greenhouse gas emissions from combustion of fossil energy carriers is the anaerobic digestion and biomethanation of organic raw material and waste towards biogas by highly diverse microbial consortia. In this context, the microbial systems ecology of thermophilic industrial-scale biogas plants is poorly understood.

RESULTS

The microbial community structure of an exemplary thermophilic biogas plant was analyzed by a comprehensive approach comprising the analysis of the microbial metagenome and metatranscriptome complemented by the cultivation of hydrolytic and acido-/acetogenic Bacteria as well as methanogenic Archaea. Analysis of metagenome-derived 16S rRNA gene sequences revealed that the bacterial genera Defluviitoga (5.5 %), Halocella (3.5 %), Clostridium sensu stricto (1.9 %), Clostridium cluster III (1.5 %), and Tepidimicrobium (0.7 %) were most abundant. Among the Archaea, Methanoculleus (2.8 %) and Methanothermobacter (0.8 %) were predominant. As revealed by a metatranscriptomic 16S rRNA analysis, Defluviitoga (9.2 %), Clostridium cluster III (4.8 %), and Tepidanaerobacter (1.1 %) as well as Methanoculleus (5.7 %) mainly contributed to these sequence tags indicating their metabolic activity, whereas Hallocella (1.8 %), Tepidimicrobium (0.5 %), and Methanothermobacter (<0.1 %) were transcriptionally less active. By applying 11 different cultivation strategies, 52 taxonomically different microbial isolates representing the classes Clostridia, Bacilli, Thermotogae, Methanomicrobia and Methanobacteria were obtained. Genome analyses of isolates support the finding that, besides Clostridium thermocellum and Clostridium stercorarium, Defluviitoga tunisiensis participated in the hydrolysis of hemicellulose producing ethanol, acetate, and H2/CO2. The latter three metabolites are substrates for hydrogentrophic and acetoclastic archaeal methanogenesis.

CONCLUSIONS

Obtained results showed that high abundance of microorganisms as deduced from metagenome analysis does not necessarily indicate high transcriptional or metabolic activity, and vice versa. Additionally, it appeared that the microbiome of the investigated thermophilic biogas plant comprised a huge number of up to now unknown and insufficiently characterized species.

Reorganisation of a mesophilic biogas microbiome as response to a stepwise increase of ammonium nitrogen induced by poultry manure supply

An anaerobic digestion experiment was investigated to evaluate the impact of increasing amounts of ammonium nitrogen due to poultry manure addition on the reactor performance, especially on the microbiome response. The microbial community structure was assessed by using a 16S rRNA gene approach, which was further correlated with the prevalent environmental conditions by using statistical analyses. The addition of 50% poultry manure led to a process disturbance indicated by a high VFA content (almost 10 g(HAc-Eq) L(-1)) in combination with elevated concentrations of ammonium nitrogen (5.9 g NH4(+)-N kg(FM)(-1)) and free ammonia (0.5 g NH3 kg(FM)(-1)). Simultaneously the microbiome, changed from a Bacteroidetes-dominated to a Clostridiales-dominated community accompanied by a shift from the acetoclastic to the hydrogenotrophic pathway. The "new" microbial community was functional redundant as the overall process rates were similar to the former one. A further increase of poultry manure resulted in a complete process failure.

A mesophilic anaerobic digester for treating food waste: process stability and microbial community analysis using pyrosequencing

Background

Anaerobic digesters become unstable when operated at a high organi c loading rate (OLR). Investigating the microbial community response to OLR disturbance is helpful for achieving efficient and stable process operation. However, previous studies have only focused on community succession during different process stages. How does community succession influence process stability? Is this kind of succession resilient? Are any key microbial indicator closely related to process stability? Such relationships between microbial communities and process stability are poorly understood.

Results

In this study, a mesophilic anaerobic digester for treating food waste (FW) was operated to study the microbial diversity and dynamicity due to OLR disturbance. Overloading resulted in proliferation of acidogenic bacteria, and the resulting high volatile fatty acid (VFA) yield triggered an abundance of acetogenic bacteria. However, the abundance and metabolic efficiency of hydrogenotrophic methanogens decreased after disturbance, and as a consequence, methanogens and acetogenic bacteria could not efficiently complete the syntrophy. This stress induced the proliferation of homoacetogens as alternative hydrogenotrophs for converting excessive H₂ to acetate. However, the susceptible Methanothrix species also failed to degrade the excessive acetate. This metabolic imbalance finally led to process deterioration. After process recovery, the digester gradually returned to its original operational conditions, reached close to its original performance, and the microbial community profile achieved a new steady-state. Interestingly, the abundance of Syntrophomonas and Treponema increased during the deteriorative stage and rebounded after disturbance, suggesting they were resilient groups.

Conclusions

Acidogenic bacteria showed high functional redundancy, rapidly adapted to the increased OLR, and shaped new microbial community profiles. The genera Syntrophomonas and Treponema were resilient groups. This observation provides insight into the key microbial indicator that are closely related to process stability. Moreover, the succession of methanogens during the disturbance phase was unsuitable for the metabolic function needed at high OLR. This contradiction resulted in process deterioration. Thus, methanogenesis is the main step that interferes with the stable operation of digesters at high OLR. Further studies on identifying and breeding high-efficiency methanogens may be helpful for breaking the technical bottleneck of process instability and achieving stable operation under high OLR.

Management of Microbial Communities through Transient Disturbances Enhances the Functional Resilience of Nitrifying Gas-Biofilters to Future Disturbances

Microbial communities have a key role for the performance of engineered ecosystems such as waste gas biofilters. Maintaining constant performance despite fluctuating environmental conditions is of prime interest, but it is highly challenging because the mechanisms that drive the response of microbial communities to disturbances still have to be disentangled. Here we demonstrate that the bioprocess performance and stability can be improved and reinforced in the face of disturbances, through a rationally predefined strategy of microbial resource management (MRM). This strategy was experimentally validated in replicated pilot-scale nitrifying gas-biofilters, for the two steps of nitrification. The associated biological mechanisms were unraveled through analysis of functions, abundances and community compositions for the major actors of nitrification in these biofilters, that is, ammonia-oxidizing bacteria (AOB) and Nitrobacter-like nitrite-oxidizers (NOB). Our MRM strategy, based on the application of successive, transient perturbations of increasing intensity, enabled to steer the nitrifier community in a favorable way through the selection of more resistant AOB and NOB sharing functional gene sequences close to those of, respectively, Nitrosomonas eutropha and Nitrobacter hamburgensis that are well adapted to high N load. The induced community shifts resulted in significant enhancement of nitrification resilience capacity following the intense perturbation.

Presence does not imply activity: DNA and RNA patterns differ in response to salt perturbation in anaerobic digestion

BACKGROUND

The microbial community in anaerobic digestion is mainly monitored by means of DNA-based methods. This may lead to incorrect interpretation of the community parameters, because microbial abundance does not necessarily reflect activity. In this research, the difference between microbial community response on DNA (total community) and RNA (active community) based on the 16S rRNA (gene) with respect to salt concentration and response time was evaluated.

RESULTS

The application of higher NaCl concentrations resulted in a decrease in methane production. A stronger and faster response to salt concentration was observed on RNA level. This was reflected in terms of microbial community composition and organization, as richness, evenness, and overall diversity were differentially impacted. A higher divergence of community structure was observed on RNA level as well, indicating that total community composition depends on deterministic processes, while the active community is determined by stochastic processes. Methanosaeta was identified as the most abundant methanogen on DNA level, but its relative abundance decreased on RNA level, related to salt perturbation.

CONCLUSIONS

This research demonstrated the need for RNA-based community screening to obtain reliable information on actual community parameters and to identify key species that determine process stability.

In-Situ Remediation Approaches for the Management of Contaminated Sites: A Comprehensive Overview

Though several in-situ treatment methods exist to remediate polluted sites, selecting an appropriate site-specific remediation technology is challenging and is critical for successful clean up of polluted sites. Hence, a comprehensive overview of all the available remediation technologies to date is necessary to choose the right technology for an anticipated pollutant. This review has critically evaluated the (i) technological profile of existing in-situ remediation approaches for priority and emerging pollutants, (ii) recent innovative technologies for on-site pollutant remediation, and (iii) current challenges as well as future prospects for developing innovative approaches to enhance the efficacy of remediation at contaminated sites.

Metaproteomics of complex microbial communities in biogas plants

Production of biogas from agricultural biomass or organic wastes is an important source of renewable energy. Although thousands of biogas plants (BGPs) are operating in Germany, there is still a significant potential to improve yields, e.g. from fibrous substrates. In addition, process stability should be optimized. Besides evaluating technical measures, improving our understanding of microbial communities involved into the biogas process is considered as key issue to achieve both goals. Microscopic and genetic approaches to analyse community composition provide valuable experimental data, but fail to detect presence of enzymes and overall metabolic activity of microbial communities. Therefore, metaproteomics can significantly contribute to elucidate critical steps in the conversion of biomass to methane as it delivers combined functional and phylogenetic data. Although metaproteomics analyses are challenged by sample impurities, sample complexity and redundant protein identification, and are still limited by the availability of genome sequences, recent studies have shown promising results. In the following, the workflow and potential pitfalls for metaproteomics of samples from full-scale BGP are discussed. In addition, the value of metaproteomics to contribute to the further advancement of microbial ecology is evaluated. Finally, synergistic effects expected when metaproteomics is combined with advanced imaging techniques, metagenomics, metatranscriptomics and metabolomics are addressed.

The activated sludge ecosystem contains a core community of abundant organisms

Understanding the microbial ecology of a system requires that the observed population dynamics can be linked to their metabolic functions. However, functional characterization is laborious and the choice of organisms should be prioritized to those that are frequently abundant (core) or transiently abundant, which are therefore putatively make the greatest contribution to carbon turnover in the system. We analyzed the microbial communities in 13 Danish wastewater treatment plants with nutrient removal in consecutive years and a single plant periodically over 6 years, using Illumina sequencing of 16S ribosomal RNA amplicons of the V4 region. The plants contained a core community of 63 abundant genus-level operational taxonomic units (OTUs) that made up 68% of the total reads. A core community consisting of abundant OTUs was also observed within the incoming wastewater to three plants. The net growth rate for individual OTUs was quantified using mass balance, and it was found that 10% of the total reads in the activated sludge were from slow or non-growing OTUs, and that their measured abundance was primarily because of immigration with the wastewater. Transiently abundant organisms were also identified. Among them the genus Nitrotoga (class Betaproteobacteria) was the most abundant putative nitrite oxidizer in a number of activated sludge plants, which challenges previous assumptions that Nitrospira (phylum Nitrospirae) are the primary nitrite-oxidizers in activated sludge systems with nutrient removal.

Community shifts in a well-operating agricultural biogas plant: how process variations are handled by the microbiome

This study provides a comprehensive, long-term microbiological study of a continuously operated, mesophilic, agricultural biogas plant fed with whole-crop silages of maize and rye, cattle manure and cattle slurry. The microbial community structure was accessed by high-throughput 16S rRNA gene amplicon sequencing. For the characterisation of the microbial dynamics, the community profiling method terminal restriction fragment length polymorphism (TRFLP) in combination with a cloning-sequencing approach as well as a LC-MS/MS approach for protein identification were applied. Our results revealed that the anaerobic digestion is a highly sensitive process: small variations in the process performance induce fluctuations in the microbial community composition and activity. In this context, it could be proven that certain microbial species were better adapted to changing process condition such as temperature (interspecies competition) and that there is a physiological compensation between different microorganisms so that the reactor efficiency was not adversely affected despite of structural and functional changes within the microbial community.

Deciphering microbial community robustness through synthetic ecology and molecular systems synecology

Microbial ecosystems exhibit specific robustness attributes arising from the assembly and interaction networks of diverse, heterogeneous communities challenged by fluctuating environmental conditions. Synthetic ecology provides new insights into key biodiversity-stability relationships and robustness determinants of host-associated or environmental microbiomes. Driven by the advances of meta-omics technologies and bioinformatics, community-centered approaches (defined as molecular systems synecology) combined with the development of dynamic and mechanistic mathematical models make it possible to decipher and predict the outcomes of microbial ecosystems under disturbances. Beyond discriminating the normal operating range and natural, intrinsic dynamics of microbial processes from systems-level responses to environmental forcing, predictive modeling is poised to be integrated within prescriptive analytical frameworks and thus provide guidance in decision-making and proactive microbial resource management.

Thermophilic and cellulolytic consortium isolated from composting plants improves anaerobic digestion of cellulosic biomass: Toward a microbial resource management approach

A cellulolytic consortium was isolated from a composting plant in order to boost the initial hydrolysis step encountered in anaerobic digestion. Improvement of the cellulose degradation, as well as biogas production, was observed for the cultures inoculated with the exogenous consortium. Metagenomics analyses pointed out a weak richness (related to the number of OTUs) of the exogenous consortium induced by the selective pressure (cellulose as sole carbon source) met during the initial isolation steps. Main microbial strains determined were strictly anaerobic and belong to the Clostridia class. During cellulose anaerobic degradation, pH drop induced a strong modification of the microbial population. Despite the fact that richness and evenness were very weak, the exogenous consortium was able to adapt and to maintain the cellulolytic degradation potential. This important result point out the fact that simplified microbial communities could be used in order to increase the robustness of mixed cultures involved in environmental biotechnology.

The impact of biochars on sorption and biodegradation of polycyclic aromatic hydrocarbons in soils--a review

Amending polycyclic aromatic hydrocarbon (PAH)-contaminated soils with biochar may be cheaper and environmentally friendly than other forms of organic materials. This has led to numerous studies on the use of biochar to either bind or stimulate the microbial degradation of organic compounds in soils. However, very little or no attention have been paid to the fact that biochars can give simultaneous impact on PAH fate processes, such as volatilization, sorption and biodegradation. In this review, we raised and considered the following questions: How does biochar affect microbes and microbial activities in the soil? What are the effects of adding biochar on sorption of PAHs? What are the effects of adding biochar on degradation of PAHs? What are the factors that we can manipulate in the laboratory to enhance the capability of biochars to degrade PAHs? A triphasic concept of how biochar can give simultaneous impact on PAH fate processes in soils was proposed, which involves rapid PAH sorption into biochar, subsequent desorption and modification of soil physicochemical properties by biochar, which in turn stimulates microbial degradation of the desorbed PAHs. It is anticipated that biochar can give simultaneous impact on PAH fate processes in soils.

Dynamic variation of the microbial community structure during the long-time mono-fermentation of maize and sugar beet silage

This study investigated the development of the microbial community during a long-term (337 days) anaerobic digestion of maize and sugar beet silage, two feedstocks that significantly differ in their chemical composition. For the characterization of the microbial dynamics, the community profiling method terminal restriction fragment length polymorphism (TRFLP) in combination with a cloning-sequencing approach was applied.

Our results revealed a specific adaptation of the microbial community to the supplied feedstocks. Based on the high amount of complex compounds, the anaerobic conversion rate of maize silage was slightly lower compared with the sugar beet silage. It was demonstrated that members from the phylum Bacteroidetes are mainly involved in the degradation of low molecular weight substances such as sugar, ethanol and acetate, the main compounds of the sugar beet silage. It was further shown that species of the genus Methanosaeta are highly sensitive against sudden stress situations such as a strong decrease in the ammonium nitrogen (NH₄⁺-N) concentration or a drop of the pH value. In both cases, a functional compensation by members of the genera Methanoculleus and/or Methanosarcina was detected. However, the overall biomass conversion of both feedstocks proceeded efficiently as a steady state between acid production and consumption was recorded, which further resulted in an equal biogas yield.