Author dc.contributor.author | Wirth Roland | |
Author dc.contributor.author | Bagi Zoltán | |
Author dc.contributor.author | Shetty Prateek | |
Author dc.contributor.author | Szuhaj Márk | |
Author dc.contributor.author | Cheung Teur Teur Sally | |
Author dc.contributor.author | Kovács Kornél L. | |
Author dc.contributor.author | Maróti Gergely | |
Availability Date dc.date.accessioned | 2023-06-23T08:50:59Z | |
Availability Date dc.date.available | 2023-06-23T08:50:59Z | |
Release dc.date.issued | 2023 | |
Issn dc.identifier.issn | 1751-7370 | |
Issn dc.identifier.issn | 1751-7362 | |
uri dc.identifier.uri | http://hdl.handle.net/20.500.12944/20631 | |
Abstract dc.description.abstract | Multi-omics analysis is a powerful tool for the detection and study of inter-kingdom interactions, such as those between bacterial and archaeal members of complex biogas-producing microbial communities. In the present study, the microbiomes of three industrial-scale biogas digesters, each fed with different substrates, were analysed using a machine-learning guided genome-centric metagenomics framework complemented with metatranscriptome data. This data permitted us to elucidate the relationship between abundant core methanogenic communities and their syntrophic bacterial partners. In total, we detected 297 high-quality, non-redundant metagenome-assembled genomes (nrMAGs). Moreover, the assembled 16 S rRNA gene profiles of these nrMAGs showed that the phylum Firmicutes possessed the highest copy number, while the representatives of the archaeal domain had the lowest. Further investigation of the three anaerobic microbial communities showed characteristic alterations over time but remained specific to each industrial-scale biogas plant. The relative abundance of various microorganisms as revealed by metagenome data was independent from corresponding metatranscriptome activity data. Archaea showed considerably higher activity than was expected from their abundance. We detected 51 nrMAGs that were present in all three biogas plant microbiomes with different abundances. The core microbiome correlated with the main chemical fermentation parameters, and no individual parameter emerged as a predominant shaper of community composition. Various interspecies H 2 /electron transfer mechanisms were assigned to hydrogenotrophic methanogens in the biogas plants that ran on agricultural biomass and wastewater. Analysis of metatranscriptome data revealed that methanogenesis pathways were the most active of all main metabolic pathways. | |
Language dc.language | en | |
Keywords dc.subject | biogas | |
Keywords dc.subject | machine-learning | |
Keywords dc.subject | industrial | |
Title dc.title | Inter-kingdom interactions and stability of methanogens revealed by machine-learning guided multi-omics analysis of industrial-scale biogas plants | |
Type dc.type | folyóiratcikk | |
Date Change dc.date.updated | 2023-06-19T17:00:30Z | |
Version dc.description.version | kiadói | |
dc.rights.accessRights | nyílt hozzáférésű | |
Doi ID dc.identifier.doi | 10.1038/s41396-023-01448-3 | |
Discipline Discipline + dc.subject.discipline | Műszaki tudományok | |
dc.subject.sciencebranch | Bio-, környezet- és vegyészmérnöki tudományok | |
MTMT ID dc.identifier.mtmt | 34011308 | |
dc.identifier.journalTitle | ISME Journal | |
Scope dc.format.page | 1-14 | |
ID Scopus dc.identifier.scopus | 85161293447 | |
dc.identifier.journalAbbreviatedTitle | ISME J | |
Release Date dc.description.issuedate | 2023 | |
Author institution dc.contributor.department | Növénybiológiai Intézet | |
Author institution dc.contributor.department | Biotechnológiai Tanszék | |
Author institution dc.contributor.department | Vízellátási és Csatornázási Tanszék | |
Author institution dc.contributor.department | Biofizikai Intézet | |
Author institution dc.contributor.department | Biológia Doktori Iskola | |
Author institution dc.contributor.department | Biokémiai Intézet |