Inter-kingdom interactions and stability of methanogens revealed by machine-learning guided multi-omics analysis of industrial-scale biogas plants

Viral auxiliary roles in hydrolytic and biosynthetic metabolism regulate prokaryotic microbial interactions in anaerobic digestion

Anaerobic digestion (AD) viruses have gained recognition as significant regulators of microbial interactions within AD communities, yet their ecological roles remain largely unexplored. In this study, we investigated the ecological roles of AD viruses in regulating microbial interactions among syntrophic hosts. We recovered 3921 diverse viral sequences from four full-scale anaerobic digesters and confirmed their widespread presence across 127 global metagenomic sampling sites (with >95 % sequence similarity), underscoring the ubiquity of prokaryotic viruses in AD-related systems. Through the construction of virus-prokaryote interactions (66.8 % validated at the transcriptional level) and analysis of viral-host transcriptional abundances, we identified significant associations between AD viruses and key processes, including hydrolysis, acidogenesis, and methanogenesis. Notably, polyvalent viruses were found to interact with both hydrolytic and fermentative communities. We further characterized viral auxiliary metabolism, hydrolytic substrate spectra, and microbial auxotrophy, showing that viruses not only could enhance the breakdown of complex substrates (e.g., cellulose, chitin, peptidoglycan) but also potentially supported the biosynthesis of essential nutrients (e.g., cysteine, methionine, heme, and cobalamin). These activities were proposed to regulate resource fluxes through alternating lysogenic and lytic cycles. Phylogenetic analysis of viral gene and horizontal gene transfer (HGT) identification suggest that AD viruses employ promiscuous infection on syntrophic hosts, potentially as an adaptive evolutionary strategy in the AD ecosystem. This study provides new insights into the ecological roles of AD viruses, highlighting their potential impact on the stability and functionality of AD systems.

Metagenomic Exploration Uncovers Several Novel 'Candidatus' Species Involved in Acetate Metabolism in High-Ammonia Thermophilic Biogas Processes

Biogas reactors operating at elevated ammonia levels are commonly susceptible to process disturbances, further augmented at thermophilic temperatures. The major cause is assumed to be linked to inhibition followed by an imbalance between different functional microbial groups, centred around the last two steps of the anaerobic digestion, involving acetogens, syntrophic acetate oxidisers (SAOB) and methanogens. Acetogens are key contributors to reactor efficiency, acting as the crucial link between the hydrolysis and fermentation steps and the final methanogenesis step. Their major product is acetate, at high ammonia levels further converted by SAOB and hydrogenotrophic methanogens to biogas. Even though these functionally different processes are well recognised, less is known about the responsible organism at elevated temperature and ammonia conditions. The main aim of this study was to garner insights into the penultimate stages in three thermophilic reactors (52°C) operated under high ammonia levels (FAN 0.7-1.0 g/L; TAN 3.6-4.4 g/L). The primary objective was to identify potential acetogens and SAOBs. Metagenomic data from the three reactors were analysed for the reductive acetyl-CoA pathway (Wood-Ljungdahl Pathway) and glycine synthase reductase pathway. The results revealed a lack of true acetogens but uncovered three potential SAOB candidates that harbour the WLP, 'Candidatus Thermodarwinisyntropha acetovorans', 'Candidatus Thermosyntrophaceticus schinkii', 'Candidatus Thermotepidanaerobacter aceticum', and a potential lipid-degrader 'Candidatus Thermosyntrophomonas ammoiaca'.

Harnessing microbial division of labor for biomanufacturing: a review of laboratory and formal modeling approaches

Bioprocess industries aim to meet the increasing demand for product complexity by designing enhanced cellular and metabolic capabilities for the host. Monocultures, standard biomanufacturing workhorses, are often restricted in their capability to meet these demands, and the solution often involves the genetic modification of the host. Synthetic microbial communities are a promising alternative to monocultures because they exhibit division of labor, enabling efficient resource utilization and pathway modularity. This specialization minimizes metabolic burden and enhances robustness to perturbations, providing a competitive advantage. Despite this potential, their utilization in biotechnological or bioprocessing applications remains limited. The recent emergence of new and innovative community design tools and strategies, particularly those harnessing the division of labor, holds promise to change this outlook. Understanding the microbial interactions governing natural microbial communities can be used to identify complementary partners, informing synthetic community design. Therefore, we particularly consider engineering division of labor in synthetic microbial communities as a viable solution to accelerate progress in the field. This review presents the current understanding of how microbial interactions enable division of labor and how this information can be used to design synthetic microbial communities to perform tasks otherwise unfeasible to individual organisms. We then evaluate laboratory and formal modeling approaches specifically developed to: elucidate microbial community physiology, guide experimental design, and improve our understanding of complex community interactions assisting synthetic community design. By synthesizing these insights, we aim to present a comprehensive framework that advances the use of microbial communities in biomanufacturing applications.

A Novel Sulfatase for Acesulfame Degradation in Wastewater Treatment Plants as Evidenced from Shinella Strains

The artificial sweetener acesulfame is a persistent pollutant in wastewater worldwide. So far, only a few bacterial isolates were recently found to degrade acesulfame efficiently. In Bosea and Chelatococcus strains, a Mn2+-dependent metallo-β-lactamase-type sulfatase and an amidase signature family enzyme catalyze acesulfame hydrolysis via acetoacetamide-N-sulfonate to acetoacetate. Here, we describe a new acesulfame sulfatase in Shinella strains isolated from wastewater treatment plants in Germany. Their genomes do not encode the Mn2+-dependent sulfatase. Instead, a formylglycine-dependent sulfatase gene was found, together with the acetoacetamide-N-sulfonate amidase gene on a plasmid shared by all known acesulfame-degrading Shinella strains. Heterologous expression, proteomics, and size exclusion chromatography corroborated the physiological function of the Shinella sulfatase in acesulfame hydrolysis. Since both acesulfame sulfatase types are absent in other bacterial genomes or metagenome-assembled genomes, we surveyed 73 tera base pairs of wastewater-associated metagenome raw data sets. Bosea/Chelatococcus sulfatase gene signatures were regularly found from 2013, particularly in North America, Europe, and East Asia, whereas Shinella sulfatase gene signatures were first detected in 2020. Moreover, signatures for the Shinella sulfatase and amidase genes co-occur only in six data sets from China, Finland, and Mexico, suggesting that the Shinella genes were enriched or introduced quite recently in wastewater treatment facilities.

Feedstock-dependent antibiotic resistance gene patterns and expression profiles in industrial scale biogas plants revealed by meta-omics technology

This study investigated antimicrobial resistance in the anaerobic digesters of two industrial-scale biogas plants processing agricultural biomass and municipal wastewater sludge. A combination of deep sequencing and genome-centric workflow was implemented for metagenomic and metatranscriptomics data analysis to comprehensively examine potential antimicrobial resistance in microbial communities. Anaerobic microbes were found to harbour numerous antibiotic resistance genes (ARGs), with 58.85% of the metagenome-assembled genomes (MAGs) harbouring antibiotic resistance. A moderately positive correlation was observed between the abundance and expression of ARGs. ARGs were located primarily on bacterial chromosomes. A higher expression of resistance genes was observed on plasmids than on chromosomes. Risk index assessment suggests that most ARGs identified posed a significant risk to human health. However, potentially pathogenic bacteria showed lower ARG expression than non-pathogenic ones, indicating that anaerobic treatment is effective against pathogenic microbes. Resistomes at the gene category level were associated with various antibiotic resistance categories, including multidrug resistance, beta-lactams, glycopeptides, peptides, and macrolide-lincosamide-streptogramin (MLS). Differential expression analysis revealed specific genes associated with potential pathogenicity, emphasizing the importance of active gene expression in assessing the risks associated with ARGs.

Mechanistic understanding of acclimation and energy metabolism of acetoclastic methanogens under different substrate to microorganism ratios

Mechanistic understanding of acetoclastic methanogenesis is pivotal for optimizing anaerobic digestion for efficient methane production. In this study, two different operational modes, continuous flow reactor (CFR) and sequencing batch reactor (SBR), accompanied with solids retention times (SRT) of 10 days (SBR10d and CFR10d) and 25 days (SBR25d and CFR25d) were implemented to elucidate their impacts on microbial communities and energy metabolism of methanogens in acetate-fed systems. Microbial community analysis revealed that the relative abundance of Methanosarcina (16.0%-46.0%) surpassed Methanothrix (3.7%-22.9%) in each reactor. SBRs had the potential to enrich both Methanothrix and Methanosarcina. Compared to SBRs, CFRs had lower total relative abundance of methanogens. Methanosarcina exhibited a superior enrichment in reactors with 10-day SRT, while Methanothrix preferred to be acclimated in reactors with 25-day SRT. The operational mode and SRT were also observed to affect the distribution of acetate-utilizing bacteria, including Pseudomonas, Desulfocurvus, Mesotoga, and Thauera. Regarding enzymes involved in energy metabolism, Ech and Vho/Vht demonstrated higher relative abundances at 10-day SRT compared to 25-day SRT, whereas Fpo and MtrA-H showed higher relative abundances in SBRs than those in CFRs. The relative abundance of genes encoding ATPase harbored by Methanothrix was higher than Methanosarcina at 25-day SRT. Additionally, the relative abundance of V/A-type ATPase (typically for methanogens) was observed higher in SBRs compared to CFRs, while the F-type ATPase (typically for bacteria) exhibited higher relative abundance in CFRs than that in SBRs.

Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology

Due to the complex nature of microbiome data, the field of microbial ecology has many current and potential uses for machine learning (ML) modeling. With the increased use of predictive ML models across many disciplines, including microbial ecology, there is extensive published information on the specific ML algorithms available and how those algorithms have been applied. Thus, our goal is not to summarize the breadth of ML models available or compare their performances. Rather, our goal is to provide more concrete and actionable information to guide microbial ecologists in how to select, run, and interpret ML algorithms to predict the taxa or genes associated with particular sample categories or environmental gradients of interest. Such microbial data often have unique characteristics that require careful consideration of how to apply ML models and how to interpret the associated results. This review is intended for practicing microbial ecologists who may be unfamiliar with some of the intricacies of ML models. We provide examples and discuss common opportunities and pitfalls specific to applying ML models to the types of data sets most frequently collected by microbial ecologists.

Carbon/nitrogen flows and associated microbial communities in full-scale foodwaste treatment plants

Microorganisms play key roles in the conversion of organic matter in foodwaste. However, both the microbially-mediated element (carbon/C and nitrogen/N) flows and associated microbial communities in foodwaste treatment plants (FWTPs) remain unclear. This study collected samples of different foodwaste treatment units from five full-scale FWTPs to analyze the C/N flows and microbial communities in foodwaste treatment processes. Results showed that 39.8-45.0% of organic carbon in foodwaste was converted into biogas. Hydrolytic acidogenic bacteria (e.g., Lactobacillus and Limosilactobacillus) and eukaryota (e.g., Cafeteriaceae, Saccharomycetales, and Agaricomycetes) were more abundant in feedstock and pretreatment units. Redundancy analyses showed that acidogens were major players in the transformation of foodwaste organic matter. Populations of W27 and Tepidanaerobacter were major contributors to the difference in conversion of C/N in these FWTPs. This study could support foodwaste treatment efficiencies improvement by providing insights into C/N flows and associated microbiota in FWTPs.

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics

The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters. Microbial communities were analyzed regarding their taxonomic composition, functional potential, as well as functions expressed on the proteome level. Different abundances of genes and enzymes related to the biogas process could be mostly attributed to different process parameters. Individual MAGs exhibiting different abundances in the digesters were studied in detail, and their roles in the hydrolysis, acidogenesis and acetogenesis steps of anaerobic digestion could be assigned. Methanoculleus thermohydrogenotrophicum was an active hydrogenotrophic methanogen in all three digesters, whereas Methanothermobacter wolfeii was more prevalent at higher process temperatures. Further analysis focused on MAGs, which were abundant in all digesters, indicating their potential to ensure biogas process stability. The most prevalent MAG belonged to the class Limnochordia; this MAG was ubiquitous in all three digesters and exhibited activity in numerous pathways related to different steps of AD.