Adaptation of a microbial community to demand-oriented biological methanation

Insights into the phylogenetic and metabolic diversity of Planctomycetota in anaerobic digesters and the isolation of novel Thermoguttaceae species

Studying bacteria in anaerobic digestion (AD) is crucial for optimizing microbial processes. While abundant taxa are often studied, less abundant groups may harbour novel metabolic potential. This study fills the gap by focusing on the Planctomycetota phylum, known to encode diverse carbohydrate-active enzymes (CAZymes). Despite their common presence in diverse aerobic and anaerobic environments, their role in AD is relatively unexplored. We utilized both culture-dependent and culture-independent techniques to investigate the phylogenetic and metabolic diversity of Planctomycetota within AD reactors. Our findings revealed that among the diverse planctomycetotal operational taxonomic units present, only a few are prevalent and abundant community members. Planctomycetota share functional traits with e.g. Verrucomicrobiota exhibiting distinct CAZyme gene repertoires that indicates specialization in degrading algal polysaccharides and glycoproteins. To explore the planctomycetotal metabolic capabilities, we monitored their presence in algal-fed digesters. Additionally, we isolated a strain from mucin-based medium, revealing its genetic potential for a mixotrophic lifestyle. Based on the genomic analysis, we propose to introduce the Candidatus Luxemburgiella decessa gen. nov. sp. nov., belonging to the Thermoguttaceae family within the Pirellulales order of the Planctomycetia class. This study enhances our understanding of Planctomycetota in AD by highlighting their phylogenetic diversity and metabolic capabilities.

Impact of trace metal supplementation on anaerobic biological methanation under hydrogen and carbon dioxide starvation

Biomethanation is a crucial process occurring in natural and engineered systems which can reduce carbon dioxide to methane impacting the global carbon cycle. However, little is known about the effect of on-and-off gaseous provision and micronutrients on bioconversion. Here, anaerobic microbiomes underwent intermittent feeding with incremental starvations and selective metal supplementation to assess the impact of hydrogen and carbon dioxide availability on microbial physiology. Resilience was tested under differential cultivations in basal medium supplemented with either nickel or cobalt. Nickel-augmented cultures exhibited faster recovery upon starvation, suggesting a beneficial effect. Dominant Methanothermobacter thermautotrophicus demonstrated robust growth, genetic stability and transcriptional downregulation when starved. Conversely, bacteria were plastic and prone to genetic fluctuations, accumulating mutations on genes encoding for ABC-transporters and C-metabolism enzymes. This study pioneers cellular resilience and response to micronutrient supplementation in anaerobic carbon dioxide-fixating microbiomes, offering valuable insights into microbial activity recovery after carbon and electron donor deprivation.

Multivariate comparison of taxonomic, chemical and operational data from 80 different full-scale anaerobic digester-related systems

BACKGROUND

The holistic characterization of different microbiomes in anaerobic digestion (AD) systems can contribute to a better understanding of these systems and provide starting points for bioengineering. The present study investigates the microbiome of 80 European full-scale AD systems. Operational, chemical and taxonomic data were thoroughly collected, analysed and correlated to identify the main drivers of AD processes.

RESULTS

The present study describes chemical and operational parameters for a broad spectrum of different AD systems. With this data, Spearman correlation and differential abundance analyses were applied to narrow down the role of the individual microorganisms detected. The authors succeeded in further limiting the number of microorganisms in the core microbiome for a broad range of AD systems. Based on 16S rRNA gene amplicon sequencing, MBA03, Proteiniphilum, a member of the family Dethiobacteraceae, the genus Caldicoprobacter and the methanogen Methanosarcina were the most prevalent and abundant organisms identified in all digesters analysed. High ratios for Methanoculleus are often described for agricultural co-digesters. Therefore, it is remarkable that Methanosarcina was surprisingly high in several digesters reaching ratios up to 47.2%. The various statistical analyses revealed that the microorganisms grouped according to different patterns. A purely taxonomic correlation enabled a distinction between an acetoclastic cluster and a hydrogenotrophic one. However, in the multivariate analysis with chemical parameters, the main clusters corresponded to hydrolytic and acidogenic microorganisms, with SAOB bacteria being particularly important in the second group. Including operational parameters resulted in digester-type specific grouping of microbes. Those with separate acidification stood out among the many reactor types due to their unexpected behaviour. Despite maximizing the organic loading rate in the hydrolytic pretreatments, these stages turned into extremely robust methane production units.

CONCLUSIONS

From 80 different AD systems, one of the most holistic data sets is provided. A very distinct formation of microbial clusters was discovered, depending on whether taxonomic, chemical or operational parameters were combined. The microorganisms in the individual clusters were strongly dependent on the respective reference parameters.

Microbiome modeling: a beginner's guide

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Improved biological methanation using tubular foam-bed reactor

BACKGROUND

Power-to-gas is the pivotal link between electricity and gas infrastructure, enabling the broader integration of renewable energy. Yet, enhancements are necessary for its full potential. In the biomethanation process, transferring H2 into the liquid phase is a rate-limiting step. To address this, we developed a novel tubular foam-bed reactor (TFBR) and investigated its performance at laboratory scale.

RESULTS

A non-ionic polymeric surfactant (Pluronic® F-68) at 1.5% w/v was added to the TFBR's culture medium to generate a stabilized liquid foam structure. This increased both the gas-liquid surface area and the bubble retention time. Within the tubing, cells predominantly traveled evenly suspended in the liquid phase or were entrapped in the thin liquid film of bubbles flowing inside the tube. Phase (I) of the experiment focused primarily on mesophilic (40 °C) operation of the tubular reactor, followed by phase (II), when Pluronic® F-68 was added. In phase (II), the TFBR exhibited 6.5-fold increase in biomethane production rate (MPR) to 15.1 ( L CH 4 /L R /d) , with a CH4 concentration exceeding 90% (grid quality), suggesting improved H2 transfer. Transitioning to phase (III) with continuous operation at 55 °C, the MPR reached 29.7L CH 4 /L R /d while maintaining the grid quality CH4. Despite, reduced gas-liquid solubility and gas-liquid mass transfer at higher temperatures, the twofold increase in MPR compared to phase (II) might be attributed to other factors, i.e., higher metabolic activity of the methanogenic archaea. To assess process robustness for phase (II) conditions, a partial H2 feeding regime (12 h 100% and 12 h 10% of the nominal feeding rate) was implemented. Results demonstrated a resilient MPR of approximately 14.8L CH 4 /L R /d even with intermittent, low H2 concentration.

CONCLUSIONS

Overall, the TFBR's performance plant sets the course for an accelerated introduction of biomethanation technology for the storage of volatile renewable energy. Robust process performance, even under H2 starvation, underscores its reliability. Further steps towards an optimum operation regime and scale-up should be initiated. Additionally, the use of TFBR systems should be considered for biotechnological processes in which gas-liquid mass transfer is a limiting factor for achieving higher reaction rates.

Optimization of the Ex Situ Biomethanation of Hydrogen and Carbon Dioxide in a Novel Meandering Plug Flow Reactor: Start-Up Phase and Flexible Operation

With the increasing use of renewable energy resources for the power grid, the need for long-term storage technologies, such as power-to-gas systems, is growing. Biomethanation provides the opportunity to store energy in the form of the natural gas-equivalent biomethane. This study investigates a novel plug flow reactor that employs a helical static mixer for the biological methanation of hydrogen and carbon dioxide. In tests, the reactor achieved an average methane production rate of 2.5 LCH4LR∗d (methane production [LCH4] per liter of reactor volume [LR] per day [d]) with a maximum methane content of 94%. It demonstrated good flexibilization properties, as repeated 12 h downtimes did not negatively impact the process. The genera Methanothermobacter and Methanobacterium were predominant during the initial phase, along with volatile organic acid-producing, hydrogenotrophic, and proteolytic bacteria. The average ratio of volatile organic acid to total inorganic carbon increased to 0.52 ± 0.04, while the pH remained stable at an average of pH 8.1 ± 0.25 from day 32 to 98, spanning stable and flexible operation modes. This study contributes to the development of efficient flexible biological methanation systems for sustainable energy storage and management.

Tracing active members in microbial communities by BONCAT and click chemistry-based enrichment of newly synthesized proteins

A comprehensive understanding of microbial community dynamics is fundamental to the advancement of environmental microbiology, human health, and biotechnology. Metaproteomics, defined as the analysis of all proteins present within a microbial community, provides insights into these complex systems. Microbial adaptation and activity depend to an important extent on newly synthesized proteins (nP), however, the distinction between nP and bulk proteins is challenging. The application of BONCAT with click chemistry has demonstrated efficacy in the enrichment of nP in pure cultures for proteomics. However, the transfer of this technique to microbial communities and metaproteomics has proven challenging and thus it has not not been used on microbial communities before. To address this, a new workflow with efficient and specific nP enrichment was developed using a laboratory-scale mixture of labelled Escherichia coli and unlabeled yeast. This workflow was then successfully applied to an anaerobic microbial community with initially low bioorthogonal non-canonical amino acid tagging efficiency. A substrate shift from glucose to ethanol selectively enriched nP with minimal background. The identification of bifunctional alcohol dehydrogenase and a syntrophic interaction between an ethanol-utilizing bacterium and two methanogens (hydrogenotrophic and acetoclastic) demonstrates the potential of metaproteomics targeting nP to trace microbial activity in complex microbial communities.