Functional Insights of Salinity Stress-Related Pathways in Metagenome-Resolved
            <i>Methanothrix</i>
            Genomes

Gagliano, Maria Cristina; Sampara, Pranav; Plugge, Caroline M.; Temmink, Hardy; Sudmalis, Dainis; Ziels, Ryan M.

doi:10.1128/aem.02449-21

Cited by 15 publications

(4 citation statements)

References 117 publications

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“…We detected 26 viruses across 25 samples originating from 5 sites (Table 1). These viruses were found in ecosystems where biofilm formation has been evidenced (for example, anaerobic digester sludges 27 , petrochemical wastewater in a tailings pond 28 and a CO 2 -rich subsurface aquifer 29 ) and metabolic interdependencies have been highlighted using various methods such as co-occurrence networks 30 , metatrascriptomics 31 and lipidomics 29 . Additionally, many of the matching CRISPR spacers were found in known or hypothesized syntrophic taxa, such as Methanosarcinales 32 , Methanoculleus 33 , Smithella 34 and Thermotogales 35 (Supplementary Table 17).…”

Section: Global Distribution Of Microbial Domain-crossing Virusesmentioning

confidence: 99%

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats

et al. 2023

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Many microbes in nature reside in dense, metabolically interdependent communities. We investigated the nature and extent of microbe-virus interactions in relation to microbial density and syntrophy by examining microbe-virus interactions in a biomass dense, deep-sea hydrothermal mat. Using metagenomic sequencing, we find numerous instances where phylogenetically distant (up to domain level) microbes encode CRISPR-based immunity against the same viruses in the mat. Evidence of viral interactions with hosts cross-cutting microbial domains is particularly striking between known syntrophic partners, for example those engaged in anaerobic methanotrophy. These patterns are corroborated by proximity-ligation-based (Hi-C) inference. Surveys of public datasets reveal additional viruses interacting with hosts across domains in diverse ecosystems known to harbour syntrophic biofilms. We propose that the entry of viral particles and/or DNA to non-primary host cells may be a common phenomenon in densely populated ecosystems, with eco-evolutionary implications for syntrophic microbes and CRISPR-mediated inter-population augmentation of resilience against viruses.

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Section: Global Distribution Of Microbial Domain-crossing Virusesmentioning

confidence: 99%

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats

et al. 2023

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“…8F). Genome-centric metatranscriptomic data revealed that ectoine is used by Methanothrix_A_harundinacea_D (MAG_5_1) as an osmoprotectant, which potentially enhances cell granulation [84]. The benzoate degradation pathway, which requires elevated expression of enoyl-acyl carrier protein reductase can be linked to the novel mixotrophic methanogen Methanosarcina sp., which we found to be common in SZBP (no species-level representative was found in the GTDB and Biogas Microbiome databases; MAG_165_3).…”

Section: Resultsmentioning

confidence: 99%

Inter-kingdom microbial interactions revealed by a comparative machine-learning guided multi-omics analysis of industrial-scale biogas plants

Wirth

Bagi

Shetty

et al. 2023

Preprint

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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 16S 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 microbes as revealed by metagenome data were independent from corresponding metatranscriptome activity data. Interestingly, Archaea showed considerably higher activity than was expected from their abundance. We detected 53 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 H2/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. These findings highlight the importance of a combinatorial omics data framework to identify and characterise the activity of specific microbes in complex environments.

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“…MB108 (p < 0.05). The activity of ablB was only documented in Methanothrix species until now, 52 thus this is the first time that synthesis of Nε-acetyl-L-lysine was demonstrated also in hydrogenotrophic methanogens.…”

Section: Environmental Science and Technologymentioning

confidence: 88%

“…51 The reduction of acetate in Methanothrix spp. is catalyzed by the Acetyl-CoA synthetase (acs), 52 whose encoding gene showed no change in expression level after the two shocks in Methanothrix sp. MA6.…”

Section: Effect Of Ammonia On the Methanogenic Microcosmmentioning

confidence: 99%

Decoding Microbial Responses to Ammonia Shock Loads in Biogas Reactors through Metagenomics and Metatranscriptomics

Gaspari,

Ghiotto,

Centurion

et al. 2023

Environ. Sci. Technol.

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The presence of elevated ammonia levels is widely recognized as a significant contributor to process inhibition in biogas production, posing a common challenge for biogas plant operators. The present study employed a combination of biochemical, genome-centric metagenomic and metatranscriptomic data to investigate the response of the biogas microbiome to two shock loads induced by single pulses of elevated ammonia concentrations (i.e., 1.5 g NH 4 + /L R and 5 g NH 4 + /L R ). The analysis revealed a microbial community of high complexity consisting of 364 Metagenome Assembled Genomes (MAGs). The hydrogenotrophic pathway was the primary route for methane production during the entire experiment, confirming its efficiency even at high ammonia concentrations. Additionally, metatranscriptomic analysis uncovered a metabolic shift in the methanogens Methanothrix sp. MA6 and Methanosarcina f lavescens MX5, which switched their metabolism from the acetoclastic to the CO 2 reduction route during the second shock. Furthermore, multiple genes associated with mechanisms for maintaining osmotic balance in the cell were upregulated, emphasizing the critical role of osmoprotection in the rapid response to the presence of ammonia. Finally, this study offers insights into the transcriptional response of an anaerobic digestion community, specifically focusing on the mechanisms involved in recovering from ammonia-induced stress.

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Functional Insights of Salinity Stress-Related Pathways in Metagenome-Resolved Methanothrix Genomes

Cited by 15 publications

References 117 publications

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats

Inter-kingdom microbial interactions revealed by a comparative machine-learning guided multi-omics analysis of industrial-scale biogas plants

Decoding Microbial Responses to Ammonia Shock Loads in Biogas Reactors through Metagenomics and Metatranscriptomics

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