Phage Genome Diversity in a Biogas-Producing Microbiome Analyzed by Illumina and Nanopore GridION Sequencing

Abstract

The microbial biogas network is complex and intertwined, and therefore relatively stable in its overall functionality. However, if key functional groups of microorganisms are affected by biotic or abiotic factors, the entire efficacy may be impaired. Bacteriophages are hypothesized to alter the steering process of the microbial network. In this study, an enriched fraction of virus-like particles was extracted from a mesophilic biogas reactor and sequenced on the Illumina MiSeq and Nanopore GridION sequencing platforms. Metagenome data analysis resulted in identifying 375 metagenome-assembled viral genomes (MAVGs). Two-thirds of the classified sequences were only assigned to the superkingdom Viruses and the remaining third to the family Siphoviridae, followed by Myoviridae, Podoviridae, Tectiviridae, and Inoviridae. The metavirome showed a close relationship to the phage genomes that infect members of the classes Clostridia and Bacilli. Using publicly available biogas metagenomic data, a fragment recruitment approach showed the widespread distribution of the MAVGs studied in other biogas microbiomes. In particular, phage sequences from mesophilic microbiomes were highly similar to the phage sequences of this study. Accordingly, the virus particle enrichment approach and metavirome sequencing provided additional genome sequence information for novel virome members, thus expanding the current knowledge of viral genetic diversity in biogas reactors.

Unraveling the viral dark matter of the rumen microbiome with a new global virome database

“…Recent virus-focused metagenomic studies of different habitats (ocean 1–3 , human gut 4–6 , soil 7 , and others 8,9,10 ) have generated growing catalogs of virus genomes 4,5,11 , identified numerous auxiliary metabolic genes (AMGs) 12 , and revealed the vast diversity, community structure, and ecological impact of viruses 13 . Further, model system-focused efforts are beginning to map out the specifics of how viruses can metabolically reprogram their prokaryotic hosts in ways that lead to distinct ‘virocell’ states that alter the ecological fitness and outputs of their hosts 14 .…”

A global virome of methanogenic archaea highlights novel diversity and adaptations to the gut environment

“…Methylarchaeales 18,19 ), in the Methanotecta (Methanonatronarchaeia 20 , Archaeoglobales 21 , Methanoliparales 16 , Metheno orentales 22 ), in the Diaforarchaea (Methanomassiliicoccales 23 ) and in the Acherontia (Nuwarchaeales_NM3 16 , Methanofastidiosa 24 ). Methanogenic archaea thrive in diverse arti cial and natural anoxic environments covering an extensive range of salinity and temperatures: freshwater and saline sediments 20,25,26 , peatlands 27 , terrestrial aquifers 28 , hydrothermal vents 29,30 , biogas reactors 31,32 , digesters [33][34][35][36][37] , wastewater treatment plants [38][39][40][41][42] , oil facilities 43 and coal seam 44 . Methanogens contribute to climate change through the production of a powerful greenhouse gas, participate in the complete degradation of organic matter in many anoxic environments through their interaction with fermentative bacteria, and are used in industry to transform biowaste into biogas.…”

Characterization of phage vB_EcoS-EE09 infecting E. coli DSM613 Isolated from Wastewater Treatment Plant Effluent and Comparative Proteomics of the Infected and Non-Infected Host

“…Thus far, bacteriophage research has benefited from developing cutting-edge technologies (e.g., all omics technologies). For instance, viral shotgun metagenomics unveiled the diversity and potential ecological function of bacteriophages in all kinds of environments like human and other animals' digestive tracts, biogas reactors, and marine and freshwater ecosystems [14,15]. However, more than 60% of viral sequences retrieved by viral metagenomics cannot be taxonomically or functionally classified (i.e., viral dark matter) due to the lack of fully characterized viral proteins in databases [16].…”