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

Microorganisms. 2023 Sep 27;11(10):2412. doi: 10.3390/microorganisms11102412.

Abstract

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.

Keywords: anaerobic digestion; biogas microbiome; biogas process chain; metagenome analyses; metagenomic binning; metaproteome analyses.

Grants and funding

J.H., R.H. and D.B. were funded by the German Federal Ministry of Food and Agriculture (BMEL) via the Fachagentur für Nachwachsende Rohstoffe e.V. (FNR) of the joint research project ‘Biogas measuring program III´ (FKZ 22404015, 22404115). I.M. and A.P. were funded by the BMBF funded project ‘Bielefeld-Gießen Center for Microbial Bioinformatics–BiGi´ (Grant numbers 031A533 and 031L0103) within the German Network for Bioinformatics Infrastructure (de.NBI). A.S. (Alexander Sczyrba) and A.S. (Andreas Schlüter) received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant agreement No. 818431 (SIMBA-Sustainable innovation of microbiome applications in food systems). B.O. was funded by the German Federal Ministry of Food and Agriculture (BMEL) via the Fachagentur für Nachwachsende Rohstoffe e.V. (FNR) of the joint research project ‘BIOGAS-GeneMining´ (FKZ 22031918). This work was supported by the BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) (031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A). We acknowledge support for the publication costs by the Open Access Publication Fund of Bielefeld University and the Deutsche Forschungsgemeinschaft (DFG).