Coal microbes are the predominant form of life in the subsurface ecosystem, which play a vital role in biogeochemical cycles. However, the systematic information about carbon–nitrogen–sulfur (C–N–S)-related microbial communities in coal seams is limited. In this study, 16S rRNA gene data from a total of 93 microbial communities in coals were collected for meta-analysis. The results showed that 718 functional genera were related to the C–N–S cycle, wherein N 2 fixation, denitrification, and C degradation groups dominated in relative abundance, Chao1 richness, Shannon diversity, and niche width. Genus Pseudomonas having the most C–N–S-related functions showed the highest relative abundance, and genus Herbaspirillum with a higher abundance participated in C degradation, CH 4 oxidation, N 2 fixation, ammoxidation, and denitrification. Such Herbaspirillum was a core genus in the co-occurrence network of microbial prokaryotes and showed higher levels in weight degree, betweenness centrality, and eigenvector centrality. In addition, most of the methanogens could fix N 2 and dominated in the N 2 fixation groups. Among them, genera Methanoculleus and Methanosaeta showed higher levels in the betweenness centrality index. In addition, the genus Clostridium was linked to the methanogenesis co-occurrence network module. In parallel, the S reduction gene was present in the highest total relative abundance of genes, followed by the C degradation and the denitrification genes, and S genes (especially cys genes) were the main genes linked to the co-occurrence network of the C–N–S-related genes. In summary, this study strengthened our knowledge regarding the C–N–S-related coal microbial communities, which is of great significance in understanding the microbial ecology and geochemical cycle of coals.
Microorganisms are the core drivers of coal biogeochemistry and are closely related to the formation of coalbed methane. However, it remains poorly understood about the network relationship and stability of microbial communities in coals with different ranks. In this study, a high-throughput sequencing data set was analyzed to understand the microbial co-occurrence network in coals with different ranks including anthracite, medium-volatile bituminous, and high-volatile bituminous. The results showed similar topological properties for the microbial networks among coals with different ranks, but a great difference was found in the microbial composition in different large modules among coals with different ranks, and these three networks had three, four, and four large modules with seven, nine, and nine phyla, respectively. Among these networks, a total of 46 keystone taxa were identified in large modules, and these keystone taxa were different in coals with different ranks. Bacteria dominated the keystone taxa in the microbial network, and these bacterial keystone taxa mainly belonged to phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Besides, the removal of the key microbial data could reduce the community stability of microbial communities in bituminous coals. A partial least-squares path model further showed that these bacterial keystone taxa indirectly affected methanogenic potential by maintaining the microbial community stability and bacterial diversity. In summary, these results showed that keystone taxa played an important role in determining the community diversity, maintaining the microbial community stability, and controlling the methanogenic potential, which is of great significance for understanding the microbial ecology and the geochemical cycle of coal seams.
Biogenic coalbed methane is produced by biological processes mediated by synergistic interactions of microbial complexes in coal seams. However, the ecological role of functional bacteria in biogenic coalbed methane remains poorly understood. Here, we studied the metagenome assembled genomes (MAGs) of Bacillales and Clostridiales from coal seams, revealing further expansion of hydrogen and acetogen producers involved in organic matter decomposition. In this study, Bacillales and Clostridiales were dominant orders (91.85 ± 0.94%) in cultured coal seams, and a total of 16 MAGs from 6 families, including Bacillus, Paenibacillus, Staphylococcus, Anaerosalibacter, Hungatella and Paeniclostridium, were reconstructed. These microbial groups possessed multiple metabolic pathways (glycolysis/gluconeogenesis, pentose phosphate, β-oxidation, TCA cycle, assimilatory sulfate reduction, nitrogen metabolism and encoding hydrogenase) that provided metabolic substrates (acetate and/or H2) for the methanogenic processes. Therein, the hydrogenase-encoding gene and hydrogenase maturation factors were merely found in all the Clostridiales MAGs. β-oxidation was the main metabolic pathway involved in short-chain fatty acid degradation and acetate production, and most of these pathways were detected and exhibited different operon structures in Bacillales MAGs. In addition, assimilatory sulfate reduction and nitrogen metabolism processes were also detected in some MAGs, and these processes were also closely related to acetate production and/or organic matter degradation according to their operon structures and metabolic pathways. In summary, this study enabled a better understanding of the ecological roles of Bacillales and Clostridiales in biogenic methane in coal seams based on a combination of bioinformatic techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.