Deterministic processes drive the microbial assembly during the recovery of an anaerobic digester after a severe ammonia shock

Environmental instability reduces shock resistance by enriching specialist taxa with distinct two component regulatory systems

Different microbial communities are impacted disproportionately by environmental disturbances. The degree to which a community can remain unchanged under a disturbance is referred to as resistance1. However, the contributing ecological factors, which infer a community's resistance are unknown. In this study, the impact of historical environmental stability on ecological phenomena and microbial community resistance to shocks was investigated. Three separate methanogenic bioreactor consortia, which were subjected to varying degrees of historical environmental stability, and displayed different levels of resistance to an organic loading rate (OLR) shock were sampled. Their community composition was assessed using high throughput sequencing of 16S rRNA genes and assembly based metagenomics. The effect environmental instability on ecological phenomena such as microbial community assembly, microbial niche breadth and the rare biosphere were assessed in the context of each reactor's demonstrated resistance to an OLR shock. Additionally, metagenome assembled genomes were analysed for functional effects of prolonged stability/instability. The system which was subjected to more environmental instability experienced more temporal variation in community beta diversity and a proliferation of specialists, with more abundant two component regulatory systems. This community was more susceptible to deterministic community assembly and demonstrated a lower degree of resistance, indicating that microbial communities experiencing longer term environmental instability (e.g. variations in pH or temperature) are less able to resist a large disturbance.

Bioenergetically constrained dynamical microbial interactions govern the performance and stability of methane-producing bioreactors

Biogas generation from organic waste by anaerobic bioreactors as renewable energy largely depends on microbial community and species interplays involved. This microbial networking is complex and time-dependent, influencing community succession and reactor performance, but remains unexplored due to the challenges in quantifying dynamics. We employed empirical dynamic modeling to analyze daily networking from a newly established bioreactor converting sucrose to biogas. Over time, microbial interactions within the three trophic (fermentative, syntrophic, and methanogenic) groups varied substantially more than between groups. Notably, versatile syntrophic bacteria like Syntrophorhabdus exhibited stronger interaction strength (0.14 ± 0.22) to hydrogen-dependent methylotrophic Methanomassiliicoccus than strictly syntrophic bacteria associated with butyrate (0.01 ± 0.01 for Syntrophomonas) and propionate (0.00 ± 0.01 for Syntrophobacter). The time-varying interaction networks were closely linked to the system performance dynamics, particularly concerning hydrogen concentrations. As community succession progressed, the stability of interaction network increased through time, accompanied by increased complexity and higher interaction strength. Causal analyses revealed intricate feedback involving catabolic energetics, community structure, and microbial interactions. These feedback mechanisms played a crucial role in regulating anaerobic degradation processes, thereby offering strategies for manipulating microbial interactions to enhance bioreactor stability and efficiency.

A comprehensive dataset for assessing the impact of ammonium salts and zeolite on anaerobic digestion performance, microbial dynamics, and metabolomic profiles

This article presents comprehensive data derived from lab-scale batch anaerobic digesters that were subjected to inhibition by various sources of ammonia. To counter this inhibition, zeolite was introduced into selected digesters. The provided dataset offers a detailed depiction of degradation performance dynamics over time, as well as insights into both microbial and metabolic changes during the inhibition. In detail, 10 conditions were tested in triplicate. In a first series of 15 bioreactors ammonia was introduced to achieve a TAN concentration of 8 g/L, utilizing NH3 solution, NH4Cl salt, (NH4)2CO3 salt, or (NH4)2PO4 salt as inhibitors. A control condition without ammonia was also set up. A second series of 15 bioreactors was set up exactly as the first one, with the addition of zeolite at a concentration of 15 g/L. The data provided includes information on operational conditions, degradation performance measurements throughout the entire process (using biogas production and composition, dissolved organic and inorganic carbon, volatile fatty acids, pH, free and total ammonia nitrogen, apparent isotopic fractionation of biogas as indicators), microbial community analysis using 16S rRNA gene sequencing (50 samples analysed), and metabolomic analysis through liquid chromatography-mass spectrometry (LC-MS) (108 samples analysed). Sequencing data were generated by using IonTorrent PGM sequencer. The sequencing data have been deposited with links to project PRJEB52324, in ENA database from EBI (https://www.ebi.ac.uk/ena/browser/view/PRJEB52324). Sample accession numbers go from SAMEA14277573 to SAMEA14277621. The metabolomic data were generated using an LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific, MA, US). The metabolomic data have been deposited to the EMBL-EBI MetaboLights database with the identifier MTBLS7859 (https://www.ebi.ac.uk/metabolights/MTBLS7859). This data can be used as a source for comparisons with other studies focusing on the inhibition of anaerobic digestion by ammonia, particularly in the context of exploring microbial or metabolomic dynamics during inhibition. Additionally it provides a multi-omic dataset (metataxonomic and metabolomic) with detailed associated metadata describing anaerobic digesters. The dataset is directly is associated to the research article titled "Inhibition of anaerobic digestion by various ammonia sources resulted in subtle differences in metabolite dynamics." [1].

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.

Monitoring of cellulose-rich biowaste co-digestion with 3D fluorescence spectroscopy and mass spectrometry-based metabolomics

Anaerobic digestion (AD) is a promising waste management strategy that reduces landfilling while generating biogas. Anaerobic co-digestion involves mixing two or more substrates to enhance the nutrient balance required for microorganism growth and thus improve the degradation. Monitoring AD is crucial for comprehending the biological process, optimizing process stability, and achieving efficient biogas production. In this work, we have used three dimensional excitation emission fluorescence spectroscopy and mass spectrometry metabolomics, two complementary techniques, to monitor the anaerobic co-digestion (AcoD) of cellulose, ash wood or oak wood with food waste. The two approaches were compared together and to the biogas production records. Results of this experiment demonstrated the complementarity of both analytical techniques with the measurement of the biogas production since 3D fluorescence spectroscopy and MS metabolomics revealed the earlier molecular changes occurring in the bioreactors, mainly associated with the hydrolysis step, whereas the biogas production data reflected the biological activity in the last step of the digestion. Moreover, in all cases, the three data sets effectively delineated the differences among the substrates. While the two wood substrates were poorly degradable as they were richer in aromatic compounds, cellulose was highly degradable and was characterized by the production of several glycolipids. Then, the three tested AcoDs resulted in a similar 3D EEM fluorescence and metabolomics profiles, close to the one observed for the AD of food waste alone, indicating that the incorporation of the food waste drove the molecular degradation events in the AcoDs. Substrate-specific differences were appreciated from the biogas production data. The overall results of this research are expected to provide insight into the design of guidelines for monitoring AcoD.

Exploring the mechanism of Self-Consistent balance between microbiota and high efficiency in wastewater treatment

Sewage treatment mediated by microbial organisms is a promising green trend. However, the complex balance between microbiota stability and highly efficient wastewater treatment requires investigation. This study successfully improved the effectiveness of sewage treatment by resetting the microbial community structure in the activated sludge. Truepera, Methylophaga, unclassified_Fodinicurvataceae, and unclassified_Actinomanarales were the dominant genera, while salinity and NH₃-N content were identified as the key environmental factors governing the microbial structure. By optimizing the microflora structure driven by environmental factors, the key minor genera were activated and coordinated with the aforementioned genera, thereby promoting wastewater treatment. Finally, the chemical oxygen demand, NH₃-N, and total phosphorus removal rates were improved to 86.8 ± 1.9%, 82.4 ± 4.1%, and 94.8 ± 3.8%, respectively. It provides a new insight to improve the wastewater treatment through setting microbiota by environmental factor driven.