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Metagenomic Analysis and Functional Characterization of the Biogas Microbiome Using High Throughput Shotgun Sequencing and a Novel Binning Strategy

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Metagenomic Analysis and Functional Characterization of the Biogas Microbiome Using High Throughput Shotgun Sequencing and a Novel Binning Strategy

Stefano Campanaro et al. Biotechnol Biofuels.

Abstract

Background: Biogas production is an economically attractive technology that has gained momentum worldwide over the past years. Biogas is produced by a biologically mediated process, widely known as "anaerobic digestion." This process is performed by a specialized and complex microbial community, in which different members have distinct roles in the establishment of a collective organization. Deciphering the complex microbial community engaged in this process is interesting both for unraveling the network of bacterial interactions and for applicability potential to the derived knowledge.

Results: In this study, we dissect the bioma involved in anaerobic digestion by means of high throughput Illumina sequencing (~51 gigabases of sequence data), disclosing nearly one million genes and extracting 106 microbial genomes by a novel strategy combining two binning processes. Microbial phylogeny and putative taxonomy performed using >400 proteins revealed that the biogas community is a trove of new species. A new approach based on functional properties as per network representation was developed to assign roles to the microbial species. The organization of the anaerobic digestion microbiome is resembled by a funnel concept, in which the microbial consortium presents a progressive functional specialization while reaching the final step of the process (i.e., methanogenesis). Key microbial genomes encoding enzymes involved in specific metabolic pathways, such as carbohydrates utilization, fatty acids degradation, amino acids fermentation, and syntrophic acetate oxidation, were identified. Additionally, the analysis identified a new uncultured archaeon that was putatively related to Methanomassiliicoccales but surprisingly having a methylotrophic methanogenic pathway.

Conclusion: This study is a pioneer research on the phylogenetic and functional characterization of the microbial community populating biogas reactors. By applying for the first time high-throughput sequencing and a novel binning strategy, the identified genes were anchored to single genomes providing a clear understanding of their metabolic pathways and highlighting their involvement in anaerobic digestion. The overall research established a reference catalog of biogas microbial genomes that will greatly simplify future genomic studies.

Keywords: Anaerobic digestion; Archaea; Bacteria; Binning; Biogas; Metagenomics; Methanogens; Microbial community structure; Next-generation sequencing.

Figures

Fig. 1
Fig. 1
Phylogenetic assignment of the 106 GBs. High-resolution microbial tree of life with taxonomic annotations, microbial phylogeny, and putative taxonomy, obtained with PhyloPhlAn using 400 broadly conserved proteins used to extract phylogenetic signal [66]. The tree was built using FigTree and contains a total of 3737 microbial genomes plus the 106 GBs identified (represented by small colored dots). Organisms are colored based on phyla, those in light grey color text, were absent
Fig. 2
Fig. 2
Network Representation of the Biogas Functional Organization (NRBFO). Nodes represent SEED functional categories. The size of each node is correlated to the number of GBs ranked among the top one-eighth of each functional category. Edges thickness is proportional to the number of GBs shared by two nodes; edge colors were used to simplify the visual observation of the connections. Thick edges connect nodes including GBs with high number of SEED feature counts in the two categories. Categories having thin edges are those comprising GBs that tend to have specialized functions
Fig. 3
Fig. 3
Functional roles of the GBs in the biogas production “food chain.” The main steps of the anaerobic degradation process are highlighted, together with the more relevant GBs involved. Functional roles were defined considering nearly complete KEGG pathways (Wood–Ljungdahl pathway, methanogenesis, propionate and butyrate metabolism), SEED categories (fatty acid degradation, carbohydrates utilization, denitrification, sulfate reduction), COG (amino acids fermentation) and Pfam (polysaccharides). Ovals refer to the compounds used by the microbial community (carbohydrates, fatty acids, proteins), intermediates (volatile fatty acids (VFA)-propionate, butyrate), and final products (carbon dioxide and methane)
Fig. 4
Fig. 4
Comparison of the KEGG methane pathways of the 5 archaeal GBs (Eu01–05). In the upper part of the figure the reference KEGG methane metabolism pathway is represented, in the lower part archaeal GBs’ genes present and absent in the pathway are highlighted. Genes identified in the archaeal GBs were labeled with a small colored dot. Genes absent in the GBs and present in the reference genomes are marked with a “X” (Eu01–Eu02—Methanoculleus marisnigri; Eu03—Candidatus Methanoplasma termitum; Eu04—Methanosarcina acetivorans; Eu05—Methanothermobacter thermoautotrophicus). Genes identified in the GBs and absent in the reference are labeled with a circled dot
Fig. 5
Fig. 5
Graphic representation of the GBs abundance in the biogas microbial community. The GBs coverages are represented as circles where the area is proportional to the coverage. GBs are grouped considering the taxonomic assignment at phylum level (Sp Spirochetes, Sy Synergistetes, Th Thermotogae, Pr Proteobacteria, Fi Firmicutes, Te Tenericutes, Ac Actinobacteria, Ba Bacteroidetes, Tm TM7 phylum, Eu Euryarchaeota). Outlines colors correspond to those reported in Fig. 1

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References

    1. Holm-Nielsen JB, Al Seadi T, Oleskowicz-Popiel P. The future of anaerobic digestion and biogas utilization. Bioresour Technol. 2009;100(22):5478–5484. doi: 10.1016/j.biortech.2008.12.046. - DOI - PubMed
    1. Batstone DJ, Keller J, Angelidaki I, Kalyuzhnyi S, Pavlostathis S, Rozzi A, Sanders W, Siegrist H, Vavilin V. The IWA Anaerobic Digestion Model No 1 (ADM 1) Water Sci Technol. 2002;45(10):65–73. - PubMed
    1. De Francisci D, Kougias PG, Treu L, Campanaro S, Angelidaki I. Microbial diversity and dynamicity of biogas reactors due to radical changes of feedstock composition. Bioresour Technol. 2015;176:56–64. doi: 10.1016/j.biortech.2014.10.126. - DOI - PubMed
    1. Eikmeyer FG, Rademacher A, Hanreich A, Hennig M, Jaenicke S, Maus I, Wibberg D, Zakrzewski M, Pühler A, Klocke M. Detailed analysis of metagenome datasets obtained from biogas-producing microbial communities residing in biogas reactors does not indicate the presence of putative pathogenic microorganisms. Biotechnol Biofuels. 2013;6(1):49. doi: 10.1186/1754-6834-6-49. - DOI - PMC - PubMed
    1. Schlüter A, Bekel T, Diaz NN, Dondrup M, Eichenlaub R, Gartemann K-H, Krahn I, Krause L, Krömeke H, Kruse O. The metagenome of a biogas-producing microbial community of a production-scale biogas plant fermenter analysed by the 454-pyrosequencing technology. J Biotechnol. 2008;136(1):77–90. doi: 10.1016/j.jbiotec.2008.05.008. - DOI - PubMed

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